From 390f894e82776bc1184b090096f7bb704a0cd5ec Mon Sep 17 00:00:00 2001 From: auxten Date: Thu, 15 Aug 2024 14:07:44 +0800 Subject: [PATCH 01/16] ClickBench script --- benchmark/clickbench.py | 167 ++++++++++++++++++++++++++++++++++++++++ 1 file changed, 167 insertions(+) create mode 100644 benchmark/clickbench.py diff --git a/benchmark/clickbench.py b/benchmark/clickbench.py new file mode 100644 index 00000000000..7eaa8065875 --- /dev/null +++ b/benchmark/clickbench.py @@ -0,0 +1,167 @@ +#!python3 + +import sys +import time +import timeit +import chdb +import argparse +import pandas as pd + +ch_local = "/auxten/chdb/tests/ch24.5/usr/bin/clickhouse" +data_path = "/auxten/bench/hits_0.parquet" + +queries = [ + """SELECT COUNT(*) FROM hits;""", + """SELECT COUNT(*) FROM hits WHERE AdvEngineID <> 0;""", + """SELECT SUM(AdvEngineID), COUNT(*), AVG(ResolutionWidth) FROM hits;""", + """SELECT AVG(UserID) FROM hits;""", + """SELECT COUNT(DISTINCT UserID) FROM hits;""", + """SELECT COUNT(DISTINCT SearchPhrase) FROM hits;""", + """SELECT MIN(EventDate), MAX(EventDate) FROM hits;""", + """SELECT AdvEngineID, COUNT(*) FROM hits WHERE AdvEngineID <> 0 GROUP BY AdvEngineID ORDER BY COUNT(*) DESC;""", + """SELECT RegionID, COUNT(DISTINCT UserID) AS u FROM hits GROUP BY RegionID ORDER BY u DESC LIMIT 10;""", + """SELECT RegionID, SUM(AdvEngineID), COUNT(*) AS c, AVG(ResolutionWidth), COUNT(DISTINCT UserID) FROM hits GROUP BY RegionID ORDER BY c DESC LIMIT 10;""", + """SELECT MobilePhoneModel, COUNT(DISTINCT UserID) AS u FROM hits WHERE MobilePhoneModel <> '' GROUP BY MobilePhoneModel ORDER BY u DESC LIMIT 10;""", + """SELECT MobilePhone, MobilePhoneModel, COUNT(DISTINCT UserID) AS u FROM hits WHERE MobilePhoneModel <> '' GROUP BY MobilePhone, MobilePhoneModel ORDER BY u DESC LIMIT 10;""", + """SELECT SearchPhrase, COUNT(*) AS c FROM hits WHERE SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;""", + """SELECT SearchPhrase, COUNT(DISTINCT UserID) AS u FROM hits WHERE SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY u DESC LIMIT 10;""", + """SELECT SearchEngineID, SearchPhrase, COUNT(*) AS c FROM hits WHERE SearchPhrase <> '' GROUP BY SearchEngineID, SearchPhrase ORDER BY c DESC LIMIT 10;""", + """SELECT UserID, COUNT(*) FROM hits GROUP BY UserID ORDER BY COUNT(*) DESC LIMIT 10;""", + """SELECT UserID, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, SearchPhrase ORDER BY COUNT(*) DESC LIMIT 10;""", + """SELECT UserID, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, SearchPhrase LIMIT 10;""", + """SELECT UserID, extract(minute FROM EventTime) AS m, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, m, SearchPhrase ORDER BY COUNT(*) DESC LIMIT 10;""", + """SELECT UserID FROM hits WHERE UserID = 435090932899640449;""", + """SELECT COUNT(*) FROM hits WHERE URL LIKE '%google%';""", + """SELECT SearchPhrase, MIN(URL), COUNT(*) AS c FROM hits WHERE URL LIKE '%google%' AND SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;""", + """SELECT SearchPhrase, MIN(URL), MIN(Title), COUNT(*) AS c, COUNT(DISTINCT UserID) FROM hits WHERE Title LIKE '%Google%' AND URL NOT LIKE '%.google.%' AND SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;""", + """SELECT * FROM hits WHERE URL LIKE '%google%' ORDER BY EventTime LIMIT 10;""", + """SELECT SearchPhrase FROM hits WHERE SearchPhrase <> '' ORDER BY EventTime LIMIT 10;""", + """SELECT SearchPhrase FROM hits WHERE SearchPhrase <> '' ORDER BY SearchPhrase LIMIT 10;""", + """SELECT SearchPhrase FROM hits WHERE SearchPhrase <> '' ORDER BY EventTime, SearchPhrase LIMIT 10;""", + """SELECT CounterID, AVG(length(URL)) AS l, COUNT(*) AS c FROM hits WHERE URL <> '' GROUP BY CounterID HAVING COUNT(*) > 100000 ORDER BY l DESC LIMIT 25;""", + """SELECT REGEXP_REPLACE(Referer, '^https?://(?:www\.)?([^/]+)/.*$', '\1') AS k, AVG(length(Referer)) AS l, COUNT(*) AS c, MIN(Referer) FROM hits WHERE Referer <> '' GROUP BY k HAVING COUNT(*) > 100000 ORDER BY l DESC LIMIT 25;""", + """SELECT SUM(ResolutionWidth), SUM(ResolutionWidth + 1), SUM(ResolutionWidth + 2), SUM(ResolutionWidth + 3), SUM(ResolutionWidth + 4), SUM(ResolutionWidth + 5), SUM(ResolutionWidth + 6), SUM(ResolutionWidth + 7), SUM(ResolutionWidth + 8), SUM(ResolutionWidth + 9), SUM(ResolutionWidth + 10), SUM(ResolutionWidth + 11), SUM(ResolutionWidth + 12), SUM(ResolutionWidth + 13), SUM(ResolutionWidth + 14), SUM(ResolutionWidth + 15), SUM(ResolutionWidth + 16), SUM(ResolutionWidth + 17), SUM(ResolutionWidth + 18), SUM(ResolutionWidth + 19), SUM(ResolutionWidth + 20), SUM(ResolutionWidth + 21), SUM(ResolutionWidth + 22), SUM(ResolutionWidth + 23), SUM(ResolutionWidth + 24), SUM(ResolutionWidth + 25), SUM(ResolutionWidth + 26), SUM(ResolutionWidth + 27), SUM(ResolutionWidth + 28), SUM(ResolutionWidth + 29), SUM(ResolutionWidth + 30), SUM(ResolutionWidth + 31), SUM(ResolutionWidth + 32), SUM(ResolutionWidth + 33), SUM(ResolutionWidth + 34), SUM(ResolutionWidth + 35), SUM(ResolutionWidth + 36), SUM(ResolutionWidth + 37), SUM(ResolutionWidth + 38), SUM(ResolutionWidth + 39), SUM(ResolutionWidth + 40), SUM(ResolutionWidth + 41), SUM(ResolutionWidth + 42), SUM(ResolutionWidth + 43), SUM(ResolutionWidth + 44), SUM(ResolutionWidth + 45), SUM(ResolutionWidth + 46), SUM(ResolutionWidth + 47), SUM(ResolutionWidth + 48), SUM(ResolutionWidth + 49), SUM(ResolutionWidth + 50), SUM(ResolutionWidth + 51), SUM(ResolutionWidth + 52), SUM(ResolutionWidth + 53), SUM(ResolutionWidth + 54), SUM(ResolutionWidth + 55), SUM(ResolutionWidth + 56), SUM(ResolutionWidth + 57), SUM(ResolutionWidth + 58), SUM(ResolutionWidth + 59), SUM(ResolutionWidth + 60), SUM(ResolutionWidth + 61), SUM(ResolutionWidth + 62), SUM(ResolutionWidth + 63), SUM(ResolutionWidth + 64), SUM(ResolutionWidth + 65), SUM(ResolutionWidth + 66), SUM(ResolutionWidth + 67), SUM(ResolutionWidth + 68), SUM(ResolutionWidth + 69), SUM(ResolutionWidth + 70), SUM(ResolutionWidth + 71), SUM(ResolutionWidth + 72), SUM(ResolutionWidth + 73), SUM(ResolutionWidth + 74), SUM(ResolutionWidth + 75), SUM(ResolutionWidth + 76), SUM(ResolutionWidth + 77), SUM(ResolutionWidth + 78), SUM(ResolutionWidth + 79), SUM(ResolutionWidth + 80), SUM(ResolutionWidth + 81), SUM(ResolutionWidth + 82), SUM(ResolutionWidth + 83), SUM(ResolutionWidth + 84), SUM(ResolutionWidth + 85), SUM(ResolutionWidth + 86), SUM(ResolutionWidth + 87), SUM(ResolutionWidth + 88), SUM(ResolutionWidth + 89) FROM hits;""", + """SELECT SearchEngineID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM hits WHERE SearchPhrase <> '' GROUP BY SearchEngineID, ClientIP ORDER BY c DESC LIMIT 10;""", + """SELECT WatchID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM hits WHERE SearchPhrase <> '' GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10;""", + """SELECT WatchID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM hits GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10;""", + """SELECT URL, COUNT(*) AS c FROM hits GROUP BY URL ORDER BY c DESC LIMIT 10;""", + """SELECT 1, URL, COUNT(*) AS c FROM hits GROUP BY 1, URL ORDER BY c DESC LIMIT 10;""", + """SELECT ClientIP, ClientIP - 1, ClientIP - 2, ClientIP - 3, COUNT(*) AS c FROM hits GROUP BY ClientIP, ClientIP - 1, ClientIP - 2, ClientIP - 3 ORDER BY c DESC LIMIT 10;""", + """SELECT URL, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND DontCountHits = 0 AND IsRefresh = 0 AND URL <> '' GROUP BY URL ORDER BY PageViews DESC LIMIT 10;""", + """SELECT Title, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND DontCountHits = 0 AND IsRefresh = 0 AND Title <> '' GROUP BY Title ORDER BY PageViews DESC LIMIT 10;""", + """SELECT URL, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 AND IsLink <> 0 AND IsDownload = 0 GROUP BY URL ORDER BY PageViews DESC LIMIT 10 OFFSET 1000;""", + """SELECT TraficSourceID, SearchEngineID, AdvEngineID, CASE WHEN (SearchEngineID = 0 AND AdvEngineID = 0) THEN Referer ELSE '' END AS Src, URL AS Dst, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 GROUP BY TraficSourceID, SearchEngineID, AdvEngineID, Src, Dst ORDER BY PageViews DESC LIMIT 10 OFFSET 1000;""", + """SELECT URLHash, EventDate, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 AND TraficSourceID IN (-1, 6) AND RefererHash = 3594120000172545465 GROUP BY URLHash, EventDate ORDER BY PageViews DESC LIMIT 10 OFFSET 100;""", + """SELECT WindowClientWidth, WindowClientHeight, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 AND DontCountHits = 0 AND URLHash = 2868770270353813622 GROUP BY WindowClientWidth, WindowClientHeight ORDER BY PageViews DESC LIMIT 10 OFFSET 10000;""", + """SELECT DATE_TRUNC('minute', EventTime) AS M, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-14' AND EventDate <= '2013-07-15' AND IsRefresh = 0 AND DontCountHits = 0 GROUP BY DATE_TRUNC('minute', EventTime) ORDER BY DATE_TRUNC('minute', EventTime) LIMIT 10 OFFSET 1000;""", +] + + +def chdb_query(i, output, times=1): + sql = queries[i] + sql = sql.replace( + "FROM hits", + f"FROM file('{data_path}', 'parquet')", + ) + return execute_query(i, output, times, sql) + + +def execute_query(i, output, times, sql): + print(f"Q{i}: {sql}") + time_list = [] + elapsed_list = [] + for t in range(times): + start = timeit.default_timer() + ret = chdb.query( + sql, + output, + ) + end = timeit.default_timer() + time_list.append(round(end - start, 2)) + elapsed_list.append(round(ret.elapsed(), 2)) + print(f"Times: {t}") + print("FuncTime: ", time_list) + print("Elapsed : ", elapsed_list) + return (time_list, elapsed_list) + + +hits = None + + +def chdb_query_pandas(i, output, times=1): + global hits + if hits is None: + hits = pd.read_parquet(data_path) + # fix some types + hits["EventTime"] = pd.to_datetime(hits["EventTime"], unit="s") + hits["EventDate"] = pd.to_datetime(hits["EventDate"], unit="D") + # print(hits["EventDate"][0:10]) + # fix all object columns to string + for col in hits.columns: + if hits[col].dtype == "O": + # hits[col] = hits[col].astype('string') + hits[col] = hits[col].astype(str) + # print(hits.dtypes) + sql = queries[i] + sql = sql.replace("FROM hits", f"FROM Python(hits)") + return execute_query(i, output, times, sql) + + +def exec_ch_local(i, log_level="test", output="Null"): + f""" + execute clickhouse local binary like + /auxten/chdb/tests/ch24.5/usr/bin/clickhouse -q "SELECT COUNT(*) FROM file("{data_path}") WHERE URL LIKE '%google%'" --log-level=trace + """ + sql = queries[i] + sql = sql.replace("FROM hits", f"FROM file('{data_path}', 'parquet')") + import subprocess + + cmd = [ + ch_local, + "-q", + sql, + "--log-level=" + log_level, + "--time", + "--output-format=" + output, + ] + print(" ".join(cmd)) + subprocess.run(cmd) + + +chdb_time_list = None +chdb_elapsed_list = None +chdb_pandas_time_list = None +chdb_pandas_elapsed_list = None + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("query", type=int, help="query index") + parser.add_argument("output", type=str, help="output format") + parser.add_argument("--times", type=int, default=1, help="run times for each query") + parser.add_argument("--chdb", action="store_true", help="use chdb to run query") + parser.add_argument("--pandas", action="store_true", help="use pandas to run query") + parser.add_argument( + "--local", action="store_true", help="use local clickhouse binary" + ) + parser.add_argument( + "--log_level", type=str, default="test", help="log level for local" + ) + args = parser.parse_args() + if args.chdb: + chdb_time_list, chdb_elapsed_list = chdb_query( + args.query, args.output, args.times + ) + if args.pandas: + chdb_pandas_time_list, chdb_pandas_elapsed_list = chdb_query_pandas( + args.query, args.output, args.times + ) + if args.local: + exec_ch_local(args.query, args.log_level, args.output) + + # print summary + print(f"Q{args.query}: {queries[args.query]}") + print("Summary:") + print("chdb_time_list: ", chdb_time_list) + print("chdb_elapsed_list: ", chdb_elapsed_list) + print("chdb_pd_time_list: ", chdb_pandas_time_list) + print("chdb_pd_elapsed_list: ", chdb_pandas_elapsed_list) From 783cfda735b9682ebc63c63bfe84add96fda132a Mon Sep 17 00:00:00 2001 From: auxten Date: Thu, 15 Aug 2024 14:09:10 +0800 Subject: [PATCH 02/16] Update jemalloc build flags --- contrib/jemalloc-cmake/CMakeLists.txt | 21 ++++++++++++------- .../internal/jemalloc_internal_defs.h.in | 6 +++--- 2 files changed, 17 insertions(+), 10 deletions(-) diff --git a/contrib/jemalloc-cmake/CMakeLists.txt b/contrib/jemalloc-cmake/CMakeLists.txt index b633f0fda50..c74f532d29a 100644 --- a/contrib/jemalloc-cmake/CMakeLists.txt +++ b/contrib/jemalloc-cmake/CMakeLists.txt @@ -34,7 +34,7 @@ if (OS_LINUX) # avoid spurious latencies and additional work associated with # MADV_DONTNEED. See # https://github.com/ClickHouse/ClickHouse/issues/11121 for motivation. - set (JEMALLOC_CONFIG_MALLOC_CONF "percpu_arena:percpu,oversize_threshold:0,muzzy_decay_ms:0,dirty_decay_ms:5000") + set (JEMALLOC_CONFIG_MALLOC_CONF "percpu_arena:percpu,oversize_threshold:0,muzzy_decay_ms:0,dirty_decay_ms:5000,prof:true,prof_active:false,background_thread:true") else() set (JEMALLOC_CONFIG_MALLOC_CONF "oversize_threshold:0,muzzy_decay_ms:0,dirty_decay_ms:5000") endif() @@ -175,15 +175,22 @@ endif () target_compile_definitions(_jemalloc PRIVATE -DJEMALLOC_PROF=1) -# jemalloc provides support for two different libunwind flavors: the original HP libunwind and the one coming with gcc / g++ / libstdc++. -# The latter is identified by `JEMALLOC_PROF_LIBGCC` and uses `_Unwind_Backtrace` method instead of `unw_backtrace`. -# At the time ClickHouse uses LLVM libunwind which follows libgcc's way of backtracking. +# jemalloc provides support two unwind flavors: +# - JEMALLOC_PROF_LIBUNWIND - unw_backtrace() - gnu libunwind (compatible with llvm libunwind) +# - JEMALLOC_PROF_LIBGCC - _Unwind_Backtrace() - the original HP libunwind and the one coming with gcc / g++ / libstdc++. # -# ClickHouse has to provide `unw_backtrace` method by the means of [commit 8e2b31e](https://github.com/ClickHouse/libunwind/commit/8e2b31e766dd502f6df74909e04a7dbdf5182eb1). -target_compile_definitions (_jemalloc PRIVATE -DJEMALLOC_PROF_LIBGCC=1) +# But for JEMALLOC_PROF_LIBGCC it also calls _Unwind_Backtrace() during +# bootstraping of jemalloc, which may lead to deadlock, if the dlsym will do +# allocations somewhere (like glibc does prio 2.34, see [1]). +# +# [1]: https://sourceware.org/git/?p=glibc.git;a=commit;h=fada9018199c21c469ff0e731ef75c6020074ac9 +# +# And since ClickHouse unwind already supports unw_backtrace() we can safely +# switch to it to avoid this deadlock. +target_compile_definitions (_jemalloc PRIVATE -DJEMALLOC_PROF_LIBUNWIND=1) target_link_libraries (_jemalloc PRIVATE unwind) # for RTLD_NEXT target_compile_options(_jemalloc PRIVATE -D_GNU_SOURCE) -add_library(ch_contrib::jemalloc ALIAS _jemalloc) +add_library(ch_contrib::jemalloc ALIAS _jemalloc) \ No newline at end of file diff --git a/contrib/jemalloc-cmake/include_linux_x86_64/jemalloc/internal/jemalloc_internal_defs.h.in b/contrib/jemalloc-cmake/include_linux_x86_64/jemalloc/internal/jemalloc_internal_defs.h.in index 18a5e8118b0..b9d0f567325 100644 --- a/contrib/jemalloc-cmake/include_linux_x86_64/jemalloc/internal/jemalloc_internal_defs.h.in +++ b/contrib/jemalloc-cmake/include_linux_x86_64/jemalloc/internal/jemalloc_internal_defs.h.in @@ -96,7 +96,7 @@ /* * Defined if clock_gettime(CLOCK_MONOTONIC_COARSE, ...) is available. */ -#define JEMALLOC_HAVE_CLOCK_MONOTONIC_COARSE +/* #undef JEMALLOC_HAVE_CLOCK_MONOTONIC_COARSE */ /* * Defined if clock_gettime(CLOCK_MONOTONIC, ...) is available. @@ -396,7 +396,7 @@ /* * If defined, all the features necessary for background threads are present. */ -/* #undef JEMALLOC_BACKGROUND_THREAD */ +#define JEMALLOC_BACKGROUND_THREAD /* * If defined, jemalloc symbols are not exported (doesn't work when @@ -433,4 +433,4 @@ /* If defined, realloc(ptr, 0) defaults to "free" instead of "alloc". */ #define JEMALLOC_ZERO_REALLOC_DEFAULT_FREE -#endif /* JEMALLOC_INTERNAL_DEFS_H_ */ +#endif /* JEMALLOC_INTERNAL_DEFS_H_ */ \ No newline at end of file From 21f4c914e45f0fce45ac5b44d205f9e2e0ba8a46 Mon Sep 17 00:00:00 2001 From: auxten Date: Thu, 15 Aug 2024 15:11:15 +0800 Subject: [PATCH 03/16] Use test log-level for debug --- programs/local/LocalChdb.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/programs/local/LocalChdb.cpp b/programs/local/LocalChdb.cpp index e8ce0617632..7ea577e91ce 100644 --- a/programs/local/LocalChdb.cpp +++ b/programs/local/LocalChdb.cpp @@ -22,7 +22,7 @@ local_result_v2 * queryToBuffer( if (output_format == "Debug" || output_format == "debug") { argv.push_back("--verbose"); - argv.push_back("--log-level=trace"); + argv.push_back("--log-level=test"); // Add format string argv.push_back("--output-format=CSV"); } From 488b8d28c389b2875822fff386cf143ebf2e1e3e Mon Sep 17 00:00:00 2001 From: auxten Date: Thu, 15 Aug 2024 18:15:27 +0800 Subject: [PATCH 04/16] Update vs DuckDB --- tests/pd_zerocopy.ipynb | 916 ++++++++++++++++++++++------------------ 1 file changed, 513 insertions(+), 403 deletions(-) diff --git a/tests/pd_zerocopy.ipynb b/tests/pd_zerocopy.ipynb index 2c4854cf0ad..4b03d5519d0 100644 --- a/tests/pd_zerocopy.ipynb +++ b/tests/pd_zerocopy.ipynb @@ -17,20 +17,16 @@ "Collecting pandas\n", " Using cached pandas-2.2.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.1 MB)\n", " Using cached pandas-2.2.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.0 MB)\n", - "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.9/dist-packages (from pandas) (2023.3)\n", - "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.9/dist-packages (from pandas) (2022.7)\n", - "Requirement already satisfied: numpy>=1.22.4 in /usr/local/lib/python3.9/dist-packages (from pandas) (1.24.2)\n", "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.9/dist-packages (from pandas) (2.8.2)\n", + "Requirement already satisfied: numpy>=1.22.4 in /usr/local/lib/python3.9/dist-packages (from pandas) (1.24.2)\n", + "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.9/dist-packages (from pandas) (2022.7)\n", + "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.9/dist-packages (from pandas) (2023.3)\n", "Requirement already satisfied: six>=1.5 in /usr/lib/python3/dist-packages (from python-dateutil>=2.8.2->pandas) (1.16.0)\n", - "Collecting chdb==2.0.0b0\n", - " Downloading chdb-2.0.0b0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (134.8 MB)\n", - "\u001b[K |████████████████████████████████| 134.8 MB 120.0 MB/s eta 0:00:01\n", - "\u001b[?25hInstalling collected packages: chdb\n", - " Attempting uninstall: chdb\n", - " Found existing installation: chdb 1.3.0\n", - " Not uninstalling chdb at /usr/local/lib/python3.9/dist-packages, outside environment /usr\n", - " Can't uninstall 'chdb'. No files were found to uninstall.\n", - "Successfully installed chdb-2.0.0b0\n", + "Collecting chdb==2.0.0b1\n", + " Downloading chdb-2.0.0b1-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (134.8 MB)\n", + "\u001b[K |████████�^C██████████▌ | 90.5 MB 673 kB/s eta 0:01:062\n", + "\n", + "\u001b[?25h\u001b[31mERROR: Operation cancelled by user\u001b[0m\n", "Name: chdb\n", "Version: 2.0.0b0\n", "Summary: chDB is an in-process SQL OLAP Engine powered by ClickHouse\n", @@ -47,7 +43,7 @@ "source": [ "!pip install -U duckdb\n", "!pip install -U pandas\n", - "!pip install chdb==2.0.0b0\n", + "!pip install chdb==2.0.0b1\n", "!pip show chdb" ] }, @@ -60,9 +56,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "Read parquet file into memory. Time cost: 1.0050852298736572 s\n", + "Read parquet file into memory. Time cost: 0.997063159942627 s\n", "Parquet file size: 1395695970 bytes\n", - "Read parquet file as old pandas dataframe. Time cost: 9.336043357849121 s\n", + "Read parquet file as old pandas dataframe. Time cost: 9.255496263504028 s\n", "Dataframe(numpy) size: 4700000128 bytes\n" ] } @@ -203,13 +199,13 @@ "print(hits[\"EventDate\"][0:10])\n", "\n", "# fix all object columns to string\n", - "# for col in hits.columns:\n", - "# if hits[col].dtype == \"O\":\n", - "# # hits[col] = hits[col].astype('string')\n", - "# hits[col] = hits[col].astype(str)\n", + "for col in hits.columns:\n", + " if hits[col].dtype == \"O\":\n", + " # hits[col] = hits[col].astype('string')\n", + " hits[col] = hits[col].astype(str)\n", "\n", - "# title = hits[\"Title\"]\n", - "# title.values.data\n", + "title = hits[\"Title\"]\n", + "title.values.data\n", "\n", "hits.dtypes" ] @@ -223,7 +219,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Convert old dataframe to numpy array. Time cost: 0.00010609626770019531 s\n" + "Convert old dataframe to numpy array. Time cost: 9.059906005859375e-05 s\n" ] } ], @@ -376,70 +372,70 @@ "output_type": "stream", "text": [ "Q0: SELECT COUNT(*) FROM hits;\n", - "DuckDB time: 0.07306027412414551\n", + "DuckDB time: 0.07524514198303223\n", "DuckDB return:\n", " count_star()\n", "0 10000000\n", - "chDB time: 0.0537867546081543\n", + "chDB time: 0.05794954299926758\n", "chDB return:\n", " 10000000\n", "\n", "Q1: SELECT COUNT(*) FROM hits WHERE AdvEngineID <> 0;\n", - "DuckDB time: 0.02660083770751953\n", + "DuckDB time: 0.029527664184570312\n", "DuckDB return:\n", " count_star()\n", "0 257266\n", - "chDB time: 0.037093400955200195\n", + "chDB time: 0.031958580017089844\n", "chDB return:\n", " 257266\n", "\n", "Q2: SELECT SUM(AdvEngineID), COUNT(*), AVG(ResolutionWidth) FROM hits;\n", - "DuckDB time: 0.024693012237548828\n", + "DuckDB time: 0.030429840087890625\n", "DuckDB return:\n", " sum(AdvEngineID) count_star() avg(ResolutionWidth)\n", "0 5276263.0 10000000 1506.781497\n", - "chDB time: 0.036163330078125\n", + "chDB time: 0.03193163871765137\n", "chDB return:\n", " 5276263,10000000,1506.7814968\n", "\n", "Q3: SELECT AVG(UserID) FROM hits;\n", - "DuckDB time: 0.020524978637695312\n", + "DuckDB time: 0.024729251861572266\n", "DuckDB return:\n", " avg(UserID)\n", "0 2.302915e+18\n", - "chDB time: 0.032169342041015625\n", + "chDB time: 0.03045177459716797\n", "chDB return:\n", " -152254684228.51132\n", "\n", "Q4: SELECT COUNT(DISTINCT UserID) FROM hits;\n", - "DuckDB time: 0.07110762596130371\n", + "DuckDB time: 0.07395577430725098\n", "DuckDB return:\n", " count(DISTINCT UserID)\n", "0 1620177\n", - "chDB time: 0.10507059097290039\n", + "chDB time: 0.17254161834716797\n", "chDB return:\n", " 1620177\n", "\n", "Q5: SELECT COUNT(DISTINCT SearchPhrase) FROM hits;\n", - "DuckDB time: 3.9718713760375977\n", + "DuckDB time: 0.12221693992614746\n", "DuckDB return:\n", " count(DISTINCT SearchPhrase)\n", "0 873731\n", - "chDB time: 1.4803650379180908\n", + "chDB time: 0.1818852424621582\n", "chDB return:\n", " 873731\n", "\n", "Q6: SELECT MIN(EventDate), MAX(EventDate) FROM hits;\n", - "DuckDB time: 0.027054548263549805\n", + "DuckDB time: 0.04554629325866699\n", "DuckDB return:\n", " min(EventDate) max(EventDate)\n", "0 2013-07-02 2013-07-31\n", - "chDB time: 0.044617414474487305\n", + "chDB time: 0.035535573959350586\n", "chDB return:\n", " \"2013-07-02 08:00:00.000000000\",\"2013-07-31 08:00:00.000000000\"\n", "\n", "Q7: SELECT AdvEngineID, COUNT(*) FROM hits WHERE AdvEngineID <> 0 GROUP BY AdvEngineID ORDER BY COUNT(*) DESC;\n", - "DuckDB time: 0.03360772132873535\n", + "DuckDB time: 0.048635244369506836\n", "DuckDB return:\n", " AdvEngineID count_star()\n", "0 27 107474\n", @@ -452,7 +448,7 @@ "7 52 34\n", "8 3 9\n", "9 28 8\n", - "chDB time: 0.05653977394104004\n", + "chDB time: 0.060378313064575195\n", "chDB return:\n", " 27,107474\n", "2,94688\n", @@ -466,7 +462,7 @@ "28,8\n", "\n", "Q8: SELECT RegionID, COUNT(DISTINCT UserID) AS u FROM hits GROUP BY RegionID ORDER BY u DESC LIMIT 10;\n", - "DuckDB time: 0.07837605476379395\n", + "DuckDB time: 0.08427095413208008\n", "DuckDB return:\n", " RegionID u\n", "0 229 289257\n", @@ -479,7 +475,7 @@ "7 107 26996\n", "8 42 26944\n", "9 32 26577\n", - "chDB time: 0.08352303504943848\n", + "chDB time: 0.08675336837768555\n", "chDB return:\n", " 229,289257\n", "2,114971\n", @@ -493,7 +489,7 @@ "32,26577\n", "\n", "Q9: SELECT RegionID, SUM(AdvEngineID), COUNT(*) AS c, AVG(ResolutionWidth), COUNT(DISTINCT UserID) FROM hits GROUP BY RegionID ORDER BY c DESC LIMIT 10;\n", - "DuckDB time: 0.11081981658935547\n", + "DuckDB time: 0.11200189590454102\n", "DuckDB return:\n", " RegionID sum(AdvEngineID) c avg(ResolutionWidth) \\\n", "0 229 1626324.0 2031299 1553.786671 \n", @@ -518,7 +514,7 @@ "7 33622 \n", "8 17202 \n", "9 20111 \n", - "chDB time: 0.09684324264526367\n", + "chDB time: 0.09860372543334961\n", "chDB return:\n", " 229,1626324,2031299,1553.7866714846018,289257\n", "2,313589,877397,1423.5402149768006,114971\n", @@ -532,20 +528,20 @@ "36,53042,141420,1588.640758025739,20111\n", "\n", "Q10: SELECT MobilePhoneModel, COUNT(DISTINCT UserID) AS u FROM hits WHERE MobilePhoneModel <> '' GROUP BY MobilePhoneModel ORDER BY u DESC LIMIT 10;\n", - "DuckDB time: 3.7570314407348633\n", + "DuckDB time: 0.07192063331604004\n", "DuckDB return:\n", - " MobilePhoneModel u\n", - "0 [105, 80, 97, 100] 80774\n", - "1 [105, 80, 104, 111, 110, 101] 3568\n", - "2 [65, 53, 48, 48] 1396\n", - "3 [78, 56, 45, 48, 48] 446\n", - "4 [79, 78, 69, 32, 84, 79, 85, 67, 72, 32, 54, 4... 273\n", - "5 [105, 80, 104, 111] 196\n", - "6 [51, 49, 49, 48, 48, 48, 48] 144\n", - "7 [71, 84, 45, 80, 55, 51, 48, 48, 66] 139\n", - "8 [101, 97, 103, 108, 101, 55, 53] 131\n", - "9 [71, 84, 45, 73, 57, 53, 48, 48] 131\n", - "chDB time: 1.0059146881103516\n", + " MobilePhoneModel u\n", + "0 iPad 80774\n", + "1 iPhone 3568\n", + "2 A500 1396\n", + "3 N8-00 446\n", + "4 ONE TOUCH 6030A 273\n", + "5 iPho 196\n", + "6 3110000 144\n", + "7 GT-P7300B 139\n", + "8 GT-I9500 131\n", + "9 eagle75 131\n", + "chDB time: 0.10190367698669434\n", "chDB return:\n", " \"iPad\",80774\n", "\"iPhone\",3568\n", @@ -559,20 +555,20 @@ "\"GT-I9500\",131\n", "\n", "Q11: SELECT MobilePhone, MobilePhoneModel, COUNT(DISTINCT UserID) AS u FROM hits WHERE MobilePhoneModel <> '' GROUP BY MobilePhone, MobilePhoneModel ORDER BY u DESC LIMIT 10;\n", - "DuckDB time: 3.687546491622925\n", + "DuckDB time: 0.061762332916259766\n", "DuckDB return:\n", - " MobilePhone MobilePhoneModel u\n", - "0 1 [105, 80, 97, 100] 68519\n", - "1 5 [105, 80, 97, 100] 3788\n", - "2 6 [105, 80, 97, 100] 2210\n", - "3 7 [105, 80, 97, 100] 1980\n", - "4 118 [65, 53, 48, 48] 1394\n", - "5 26 [105, 80, 104, 111, 110, 101] 1058\n", - "6 6 [105, 80, 104, 111, 110, 101] 1039\n", - "7 10 [105, 80, 97, 100] 965\n", - "8 13 [105, 80, 97, 100] 770\n", - "9 32 [105, 80, 97, 100] 746\n", - "chDB time: 1.000279426574707\n", + " MobilePhone MobilePhoneModel u\n", + "0 1 iPad 68519\n", + "1 5 iPad 3788\n", + "2 6 iPad 2210\n", + "3 7 iPad 1980\n", + "4 118 A500 1394\n", + "5 26 iPhone 1058\n", + "6 6 iPhone 1039\n", + "7 10 iPad 965\n", + "8 13 iPad 770\n", + "9 32 iPad 746\n", + "chDB time: 0.060266733169555664\n", "chDB return:\n", " 1,\"iPad\",68519\n", "5,\"iPad\",3788\n", @@ -586,20 +582,20 @@ "32,\"iPad\",746\n", "\n", "Q12: SELECT SearchPhrase, COUNT(*) AS c FROM hits WHERE SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;\n", - "DuckDB time: 3.9264304637908936\n", + "DuckDB time: 0.13192415237426758\n", "DuckDB return:\n", - " SearchPhrase c\n", - "0 [208, 178, 208, 181, 208, 180, 208, 190, 208, ... 4947\n", - "1 [209, 129, 208, 188, 208, 190, 209, 130, 209, ... 3338\n", - "2 [209, 129, 208, 188, 208, 190, 209, 130, 209, ... 2553\n", - "3 [208, 178, 208, 181, 208, 180, 208, 190, 208, ... 2473\n", - "4 [208, 178, 208, 181, 208, 180, 208, 190, 208, ... 2032\n", - "5 [208, 178, 208, 181, 208, 180, 208, 190, 208, ... 1686\n", - "6 [208, 187, 209, 142, 208, 186, 209, 129, 32, 5... 1559\n", - "7 [208, 190, 209, 130, 208, 180, 209, 139, 209, ... 1272\n", - "8 [209, 130, 208, 176, 209, 135, 208, 186, 208, ... 1248\n", - "9 [209, 128, 208, 181, 209, 134, 208, 181, 208, ... 1244\n", - "chDB time: 1.4304420948028564\n", + " SearchPhrase c\n", + "0 ведомосквы вместу 4947\n", + "1 смотреть онлайн бесплатно 3338\n", + "2 смотреть онлайн 2553\n", + "3 ведомосквы вы из 2473\n", + "4 ведомосквиталия страции 2032\n", + "5 ведомосковский 1686\n", + "6 люкс 20 иномаровск 1559\n", + "7 отдых в кино 1272\n", + "8 тачки рецепт собстве 1248\n", + "9 рецепты сбербан 1244\n", + "chDB time: 0.13382411003112793\n", "chDB return:\n", " \"ведомосквы вместу\",4947\n", "\"смотреть онлайн бесплатно\",3338\n", @@ -613,20 +609,20 @@ "\"рецепты сбербан\",1244\n", "\n", "Q13: SELECT SearchPhrase, COUNT(DISTINCT UserID) AS u FROM hits WHERE SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY u DESC LIMIT 10;\n", - "DuckDB time: 4.049957513809204\n", + "DuckDB time: 0.21145033836364746\n", "DuckDB return:\n", - " SearchPhrase u\n", - "0 [209, 129, 208, 188, 208, 190, 209, 130, 209, ... 2717\n", - "1 [209, 129, 208, 188, 208, 190, 209, 130, 209, ... 2085\n", - "2 [208, 178, 208, 181, 208, 180, 208, 190, 208, ... 1385\n", - "3 [208, 187, 209, 142, 208, 186, 209, 129, 32, 5... 1190\n", - "4 [209, 129, 208, 188, 208, 190, 209, 130, 209, ... 1031\n", - "5 [208, 181, 208, 177, 209, 131, 209, 130, 209, ... 1007\n", - "6 [208, 181, 208, 177, 209, 131, 209, 130, 209, ... 978\n", - "7 [209, 129, 208, 188, 208, 190, 209, 130, 209, ... 953\n", - "8 [209, 128, 208, 181, 209, 134, 208, 181, 208, ... 909\n", - "9 [209, 132, 45, 49] 894\n", - "chDB time: 1.4413201808929443\n", + " SearchPhrase u\n", + "0 смотреть онлайн бесплатно 2717\n", + "1 смотреть онлайн 2085\n", + "2 ведомосквы вместу 1385\n", + "3 люкс 20 иномаровск 1190\n", + "4 смотреть 1031\n", + "5 ебутсы арениксандройд полнечный 1007\n", + "6 ебутсы для 978\n", + "7 смотреть онлайн бесплатно в хорошем 953\n", + "8 рецепты сбербан 909\n", + "9 ф-1 894\n", + "chDB time: 0.10831403732299805\n", "chDB return:\n", " \"смотреть онлайн бесплатно\",2717\n", "\"смотреть онлайн\",2085\n", @@ -640,20 +636,20 @@ "\"ф-1\",894\n", "\n", "Q14: SELECT SearchEngineID, SearchPhrase, COUNT(*) AS c FROM hits WHERE SearchPhrase <> '' GROUP BY SearchEngineID, SearchPhrase ORDER BY c DESC LIMIT 10;\n", - "DuckDB time: 3.886024236679077\n", + "DuckDB time: 0.15472936630249023\n", "DuckDB return:\n", - " SearchEngineID SearchPhrase c\n", - "0 2 [208, 178, 208, 181, 208, 180, 208, 190, 208, ... 3480\n", - "1 2 [209, 129, 208, 188, 208, 190, 209, 130, 209, ... 2194\n", - "2 2 [208, 178, 208, 181, 208, 180, 208, 190, 208, ... 1859\n", - "3 2 [208, 178, 208, 181, 208, 180, 208, 190, 208, ... 1682\n", - "4 2 [209, 129, 208, 188, 208, 190, 209, 130, 209, ... 1540\n", - "5 2 [208, 178, 208, 181, 208, 180, 208, 190, 208, ... 1440\n", - "6 95 [208, 190, 209, 130, 208, 180, 209, 139, 209, ... 1261\n", - "7 2 [208, 187, 209, 142, 208, 186, 209, 129, 32, 5... 1257\n", - "8 2 [209, 128, 208, 181, 209, 134, 208, 181, 208, ... 1172\n", - "9 4 [208, 191, 208, 190, 208, 186, 208, 181, 209, ... 959\n", - "chDB time: 1.405395269393921\n", + " SearchEngineID SearchPhrase c\n", + "0 2 ведомосквы вместу 3480\n", + "1 2 смотреть онлайн бесплатно 2194\n", + "2 2 ведомосквы вы из 1859\n", + "3 2 ведомосковский 1682\n", + "4 2 смотреть онлайн 1540\n", + "5 2 ведомосквиталия страции 1440\n", + "6 95 отдых в кино 1261\n", + "7 2 люкс 20 иномаровск 1257\n", + "8 2 рецепты сбербан 1172\n", + "9 4 покеты рецепт засня 959\n", + "chDB time: 0.09225964546203613\n", "chDB return:\n", " 2,\"ведомосквы вместу\",3480\n", "2,\"смотреть онлайн бесплатно\",2194\n", @@ -667,7 +663,7 @@ "4,\"покеты рецепт засня\",959\n", "\n", "Q15: SELECT UserID, COUNT(*) FROM hits GROUP BY UserID ORDER BY COUNT(*) DESC LIMIT 10;\n", - "DuckDB time: 0.08123564720153809\n", + "DuckDB time: 0.08703088760375977\n", "DuckDB return:\n", " UserID count_star()\n", "0 1313338681122956954 29097\n", @@ -680,7 +676,7 @@ "7 517714522250745823 2119\n", "8 6762020047108358913 2051\n", "9 6718662516719813769 1678\n", - "chDB time: 0.09643840789794922\n", + "chDB time: 0.07121539115905762\n", "chDB return:\n", " 1313338681122956954,29097\n", "1907779576417363396,16854\n", @@ -694,20 +690,20 @@ "6718662516719813769,1678\n", "\n", "Q16: SELECT UserID, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, SearchPhrase ORDER BY COUNT(*) DESC LIMIT 10;\n", - "DuckDB time: 4.173134088516235\n", + "DuckDB time: 0.17234182357788086\n", "DuckDB return:\n", " UserID SearchPhrase count_star()\n", - "0 1313338681122956954 [] 29097\n", - "1 1907779576417363396 [] 16854\n", - "2 2305303682471783379 [] 10588\n", - "3 6103038218306105832 [] 2994\n", - "4 3631826469396741283 [] 2827\n", - "5 6949028786848070043 [] 2496\n", - "6 2035345969173555084 [] 2259\n", - "7 517714522250745823 [] 2119\n", - "8 6762020047108358913 [] 2051\n", - "9 6718662516719813769 [] 1651\n", - "chDB time: 1.486011266708374\n", + "0 1313338681122956954 29097\n", + "1 1907779576417363396 16854\n", + "2 2305303682471783379 10588\n", + "3 6103038218306105832 2994\n", + "4 3631826469396741283 2827\n", + "5 6949028786848070043 2496\n", + "6 2035345969173555084 2259\n", + "7 517714522250745823 2119\n", + "8 6762020047108358913 2051\n", + "9 6718662516719813769 1651\n", + "chDB time: 0.1265425682067871\n", "chDB return:\n", " 1313338681122956954,\"\",29097\n", "1907779576417363396,\"\",16854\n", @@ -721,32 +717,20 @@ "6718662516719813769,\"\",1651\n", "\n", "Q17: SELECT UserID, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, SearchPhrase LIMIT 10;\n", - "DuckDB time: 4.250547170639038\n", + "DuckDB time: 0.16393756866455078\n", "DuckDB return:\n", - " UserID SearchPhrase \\\n", - "0 2130094098592839 [208, 186, 208, 176, 208, 187, 208, 184, 208, ... \n", - "1 2184931146863780 [209, 130, 208, 181, 208, 187, 208, 181, 208, ... \n", - "2 2782883004839272 [] \n", - "3 3011197878422371 [] \n", - "4 3120632848927990 [] \n", - "5 3146470245734832 [208, 177, 208, 176, 209, 128, 208, 177, 208, ... \n", - "6 3306462779738705 [208, 182, 208, 181, 209, 129, 209, 130, 208, ... \n", - "7 3722547207913008 [208, 184, 208, 183, 32, 209, 128, 209, 131, 2... \n", - "8 3791022277680665 [208, 189, 208, 176, 208, 179, 209, 128, 208, ... \n", - "9 4093836606503410 [208, 184, 208, 183, 32, 209, 128, 209, 131, 2... \n", - "\n", - " count_star() \n", - "0 1 \n", - "1 1 \n", - "2 1 \n", - "3 2 \n", - "4 1 \n", - "5 1 \n", - "6 1 \n", - "7 1 \n", - "8 1 \n", - "9 1 \n", - "chDB time: 1.427422285079956\n", + " UserID SearchPhrase count_star()\n", + "0 318785298151585235 приказ 2\n", + "1 319168506139872393 1\n", + "2 321717676168292019 3\n", + "3 321886361370412910 2\n", + "4 322777084288492585 6\n", + "5 325111344652010961 24\n", + "6 327906455623909768 лейка шкипедия го 1\n", + "7 328165884605831213 2\n", + "8 328809548397563096 1\n", + "9 329123540171657010 11\n", + "chDB time: 0.10548925399780273\n", "chDB return:\n", " 119657425828985633,\"\",1\n", "301536536637670246,\"люкс eob 33 сезон\",1\n", @@ -754,26 +738,26 @@ "1127993622760818270,\"\",8\n", "7886295360881784146,\"самарестом гэтсби слушать скрыть фильмы смотреть\",1\n", "-3492293928588132466,\"\",5\n", - "5931469991253193035,\"идет дар кончаруэль\",1\n", "8745528086549144,\"\",1\n", + "5931469991253193035,\"идет дар кончаруэль\",1\n", "2031525635095860448,\"кладышевске-на-дону отдам давление счет закончики рецепт\",1\n", "676440968882228424,\"маша табло\",1\n", "\n", "Q18: SELECT UserID, extract(minute FROM EventTime) AS m, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, m, SearchPhrase ORDER BY COUNT(*) DESC LIMIT 10;\n", - "DuckDB time: 4.228227615356445\n", + "DuckDB time: 0.2562694549560547\n", "DuckDB return:\n", " UserID m SearchPhrase count_star()\n", - "0 1313338681122956954 31 [] 589\n", - "1 1313338681122956954 28 [] 578\n", - "2 1313338681122956954 29 [] 572\n", - "3 1313338681122956954 33 [] 567\n", - "4 1313338681122956954 27 [] 557\n", - "5 1313338681122956954 32 [] 554\n", - "6 1313338681122956954 30 [] 552\n", - "7 1313338681122956954 34 [] 546\n", - "8 1313338681122956954 26 [] 540\n", - "9 1313338681122956954 10 [] 539\n", - "chDB time: 1.561570644378662\n", + "0 1313338681122956954 31 589\n", + "1 1313338681122956954 28 578\n", + "2 1313338681122956954 29 572\n", + "3 1313338681122956954 33 567\n", + "4 1313338681122956954 27 557\n", + "5 1313338681122956954 32 554\n", + "6 1313338681122956954 30 552\n", + "7 1313338681122956954 34 546\n", + "8 1313338681122956954 26 540\n", + "9 1313338681122956954 10 539\n", + "chDB time: 0.22542548179626465\n", "chDB return:\n", " 1313338681122956954,31,\"\",589\n", "1313338681122956954,28,\"\",578\n", @@ -787,33 +771,50 @@ "1313338681122956954,10,\"\",539\n", "\n", "Q19: SELECT UserID FROM hits WHERE UserID = 435090932899640449;\n", - "DuckDB time: 0.12410330772399902\n", + "DuckDB time: 0.03999733924865723\n", "DuckDB return:\n", " Empty DataFrame\n", "Columns: [UserID]\n", "Index: []\n", - "chDB time: 0.037075042724609375\n", + "chDB time: 0.03312993049621582\n", "chDB return:\n", " \n", "Q20: SELECT COUNT(*) FROM hits WHERE URL LIKE '%google%';\n", - "DuckDB error: Binder Error: No function matches the given name and argument types '~~(BLOB, STRING_LITERAL)'. You might need to add explicit type casts.\n", - "\tCandidate functions:\n", - "\t~~(VARCHAR, VARCHAR) -> BOOLEAN\n", - "\n", - "LINE 1: SELECT COUNT(*) FROM hits WHERE URL LIKE '%google%';\n", - " ^\n", - "chDB time: 2.753680944442749\n", + "DuckDB time: 0.10489416122436523\n", + "DuckDB return:\n", + " count_star()\n", + "0 621\n", + "chDB time: 0.09500336647033691\n", "chDB return:\n", " 621\n", "\n", "Q21: SELECT SearchPhrase, MIN(URL), COUNT(*) AS c FROM hits WHERE URL LIKE '%google%' AND SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;\n", - "DuckDB error: Binder Error: No function matches the given name and argument types '~~(BLOB, STRING_LITERAL)'. You might need to add explicit type casts.\n", - "\tCandidate functions:\n", - "\t~~(VARCHAR, VARCHAR) -> BOOLEAN\n", + "DuckDB time: 0.1448071002960205\n", + "DuckDB return:\n", + " SearchPhrase \\\n", + "0 как миксетин инструкция общая \n", + "1 зачать онлайн бесплатно \n", + "2 ани пух ходу \n", + "3 строитель верси джейкоциты вычета \n", + "4 комбактерина кабачки в крополь интерном сад тю... \n", + "5 один инструктура птахани нюши смотреть краси \n", + "6 форсаж 7 с парни \n", + "7 комбактерина кабачки в кемеровое радион \n", + "8 карта гаранспортра \n", + "9 любовь в алматы с капітальном в сургунском пля... \n", "\n", - "LINE 1: ...RL), COUNT(*) AS c FROM hits WHERE URL LIKE '%google%' AND SearchPhrase <> '' ...\n", - " ^\n", - "chDB time: 3.8661646842956543\n", + " min(URL) c \n", + "0 http://samara.irr.ru/catalog_googleMBR%26ad%3D... 2 \n", + "1 http://tienskaia-moda-brietielkakh-2%2F%2Fwww.... 2 \n", + "2 http://interinburg/detail.google,yandex.aspx#l... 2 \n", + "3 http://ru.tv/smsarhiv/num-9/nf-3/csrf-39818/go... 2 \n", + "4 http://samara.irr.ru/catalog_googleTBR%26ad%3D... 2 \n", + "5 http://bdsm_position/2624217,2013-07-01:2013/f... 2 \n", + "6 http://tienshcha-600582/google.ru/search/?targ... 1 \n", + "7 http://samara.irr.ru/catalog_googleTBR%26ad%3D... 1 \n", + "8 http://samara.irr.ru/catalog_googleMBR%26ad%3D... 1 \n", + "9 http://sp-money.yandex.ru%26sid%3D0%26ref%3D%2... 1 \n", + "chDB time: 0.12031221389770508\n", "chDB return:\n", " \"ани пух ходу\",\"http://interinburg/detail.google,yandex.aspx#location=products\",2\n", "\"комбактерина кабачки в крополь интерном сад тюмень\",\"http://samara.irr.ru/catalog_googleTBR%26ad%3D278885%26bt%3D430001216\",2\n", @@ -827,13 +828,56 @@ "\"скачать денег сургут\",\"http://tienskaia-moda-brietielka-koskovsk/detail.google\",1\n", "\n", "Q22: SELECT SearchPhrase, MIN(URL), MIN(Title), COUNT(*) AS c, COUNT(DISTINCT UserID) FROM hits WHERE Title LIKE '%Google%' AND URL NOT LIKE '%.google.%' AND SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;\n", - "DuckDB error: Binder Error: No function matches the given name and argument types '~~(BLOB, STRING_LITERAL)'. You might need to add explicit type casts.\n", - "\tCandidate functions:\n", - "\t~~(VARCHAR, VARCHAR) -> BOOLEAN\n", + "DuckDB time: 0.22903800010681152\n", + "DuckDB return:\n", + " SearchPhrase \\\n", + "0 коптимиквиды юриста с роуз рая \n", + "1 ведомосквы вместу \n", + "2 коптимиквиды юрий жд ворожные моем \n", + "3 заделать магнездо \n", + "4 вспомидоры,отека обучение стека \n", + "5 авторы для jimm f/4-5.6 dc union arkham текст \n", + "6 коптимизаностиницы \n", + "7 создать+новосибируюсь песни летние \n", + "8 вспышки нижний эльдар \n", + "9 ведомосквиталия страции \n", + "\n", + " min(URL) \\\n", + "0 https://produkty%2Fpulove.ru/booklyattion-war-... \n", + "1 http://mysw.info/newsru.ru/compatible \n", + "2 https://produkty%2Fpulove.ru/booklyattion-war-... \n", + "3 http://auto.ria.ua/search/ab_district=1&cid=57... \n", + "4 https://produkty%2Fpulove.ru/booklyattion-war-... \n", + "5 http://nn.jobinmoscow.ru/real-estate/rent/Sroc... \n", + "6 https://produkty%2Fpulove.ru/booklyattion-war-... \n", + "7 http://auto.ria.ua/search/ab_district=1&cid=57... \n", + "8 http://mysw.info/newsru.ru/compatible \n", + "9 https://produkty%2Fpulove.ru/booklyattion-war-... \n", "\n", - "LINE 1: ...DISTINCT UserID) FROM hits WHERE Title LIKE '%Google%' AND URL NOT LIKE '%.goo...\n", - " ^\n", - "chDB time: 8.34700632095337\n", + " min(Title) c \\\n", + "0 Легко на участные участников., Цены - Стильная... 45 \n", + "1 Convent-менеджер с Google Players 1.3 кв. м.- ... 17 \n", + "2 Легко на участные участников., Цены - Стильная... 16 \n", + "3 AUTO.ria.ua: продажа | Востов-на-Дону, чашечка... 13 \n", + "4 Легко на участные участников., Цены - Стильная... 10 \n", + "5 Google Papa Rapalace Rescu - модной тканика Ас... 9 \n", + "6 Легко на участные участников., Цены - Стильная... 8 \n", + "7 AUTO.ria.ua: продажа | Востов-на-Дону, чашечка... 8 \n", + "8 Convent-менеджер с Google Players 1.3 кв. м.- ... 8 \n", + "9 Легко на участные участников., Цены - Стильная... 8 \n", + "\n", + " count(DISTINCT UserID) \n", + "0 12 \n", + "1 11 \n", + "2 6 \n", + "3 13 \n", + "4 1 \n", + "5 9 \n", + "6 2 \n", + "7 1 \n", + "8 6 \n", + "9 3 \n", + "chDB time: 0.18314576148986816\n", "chDB return:\n", " \"коптимиквиды юриста с роуз рая\",\"https://produkty%2Fpulove.ru/booklyattion-war-sinij-9182/women\",\"Легко на участные участников., Цены - Стильная парнем. Саганрог догадения : Турции, купить у 10 дне кольные машинки не представки - Новая с избиение спродажа: котята 2014 г.в. Цена: 47500-10ECO060 – -------- купить квартиру Оренбург (России Galantrax Flamiliada Google, Nо 18 фотоконверк Супер Кардиган\",45,12\n", "\"ведомосквы вместу\",\"http://mysw.info/newsru.ru/compatible\",\"Convent-менеджер с Google Players 1.3 кв. м.- Продажа: лет - купить Bisbal Systеms Aparty*\",17,11\n", @@ -847,13 +891,70 @@ "\"создать+новосибируюсь песни летние\",\"http://auto.ria.ua/search/ab_district=1&cid=577&action&op\",\"AUTO.ria.ua: продажа | Востов-на-Дону, чашечка Google Cayennection Polo | б.у. и новых. Автопоиска и купить в Омск - IRR.ru - Роддово, ул. Гибочной день цене\",8,1\n", "\n", "Q23: SELECT * FROM hits WHERE URL LIKE '%google%' ORDER BY EventTime LIMIT 10;\n", - "DuckDB error: Binder Error: No function matches the given name and argument types '~~(BLOB, STRING_LITERAL)'. You might need to add explicit type casts.\n", - "\tCandidate functions:\n", - "\t~~(VARCHAR, VARCHAR) -> BOOLEAN\n", + "DuckDB time: 0.4194662570953369\n", + "DuckDB return:\n", + " WatchID JavaEnable \\\n", + "0 7316105502961799889 1 \n", + "1 5289360038140010777 1 \n", + "2 8187290215265952247 1 \n", + "3 7067335108757864491 1 \n", + "4 9031598395811274817 1 \n", + "5 8603313135134757044 1 \n", + "6 8850598978691021476 1 \n", + "7 8139397706041785641 1 \n", + "8 7270306648984929955 1 \n", + "9 6405590155111045434 1 \n", + "\n", + " Title GoodEvent \\\n", + "0 Аренда 2 игры для женщин в интернет-магазин - ... 1 \n", + "1 Инвеста.Информленны - bonprix collection - Кош... 1 \n", + "2 Инвеста.Информленны - bonprix collection - Кош... 1 \n", + "3 Прогноз поселка - продаже Жена для руб.- Профи... 1 \n", + "4 Инвеста.Информленны - bonprix collection - Кош... 1 \n", + "5 Инвеста.Информленны - bonprix collection - Кош... 1 \n", + "6 Инвеста.Информленны - bonprix collection - Кош... 1 \n", + "7 Инвеста.Информленны - bonprix collection - Кош... 1 \n", + "8 Инвеста.Информленны - bonprix collection - Кош... 1 \n", + "9 Инвеста.Информленны - bonprix collection - Кош... 1 \n", + "\n", + " EventTime EventDate CounterID ClientIP RegionID \\\n", + "0 2013-07-01 21:27:24 2013-07-02 7525 1419090217 229 \n", + "1 2013-07-01 23:02:43 2013-07-02 7525 -1260511522 41 \n", + "2 2013-07-01 23:04:18 2013-07-02 7525 -1260511522 41 \n", + "3 2013-07-01 23:04:26 2013-07-02 5822 959273659 32 \n", + "4 2013-07-01 23:05:21 2013-07-02 7525 -1260511522 41 \n", + "5 2013-07-01 23:05:27 2013-07-02 7525 -1260511522 41 \n", + "6 2013-07-01 23:05:56 2013-07-02 7525 -1260511522 41 \n", + "7 2013-07-01 23:06:41 2013-07-02 7525 -1260511522 41 \n", + "8 2013-07-01 23:07:23 2013-07-02 7525 -1260511522 41 \n", + "9 2013-07-01 23:07:33 2013-07-02 7525 -1260511522 41 \n", + "\n", + " UserID ... UTMSource UTMMedium UTMCampaign UTMContent \\\n", + "0 3033510353420765788 ... \n", + "1 3813931635822850500 ... \n", + "2 3813931635822850500 ... \n", + "3 736458148605978079 ... \n", + "4 3813931635822850500 ... \n", + "5 3813931635822850500 ... \n", + "6 3813931635822850500 ... \n", + "7 3813931635822850500 ... \n", + "8 3813931635822850500 ... \n", + "9 3813931635822850500 ... \n", + "\n", + " UTMTerm FromTag HasGCLID RefererHash URLHash CLID \n", + "0 0 -7095314016616002272 -2039922795398915081 0 \n", + "1 0 8622994845783504296 441678500069920832 0 \n", + "2 0 8622994845783504296 441678500069920832 0 \n", + "3 0 -7429996293906404352 -4158922421105595558 0 \n", + "4 0 8622994845783504296 441678500069920832 0 \n", + "5 0 524931272629027392 775047382916449082 0 \n", + "6 0 524931272629027392 775047382916449082 0 \n", + "7 0 524931272629027392 775047382916449082 0 \n", + "8 0 524931272629027392 775047382916449082 0 \n", + "9 0 662346848875253897 -5547551342880266035 0 \n", "\n", - "LINE 1: SELECT * FROM hits WHERE URL LIKE '%google%' ORDER BY EventTime LIMI...\n", - " ^\n", - "chDB time: 35.76543641090393\n", + "[10 rows x 105 columns]\n", + "chDB time: 0.46150875091552734\n", "chDB return:\n", " 7316105502961799889,1,\"Аренда 2 игры для женщин в интернет-магазин - bonprix.ru#imaged Jacobs\",1,\"2013-07-02 05:27:24.000000000\",\"2013-07-02 08:00:00.000000000\",7525,1419090217,229,3033510353420765788,1,126,7,\"http://sp-money.yandex.ru%2Fkategory_name=Плагроув&where=all&filmId=WNkeCKQOeSs&where=all&text=песню актика googleuser=trading/page3/?auth=0&checked_auto.ria.ua/advizhi/price_do=600&wi=1024&wi=1440%26rnd%3D158197%26bt%3Dad.adriver.ru/filmId=HjCfhSXPbEY&where=all&filmId=dgV5JJuhk3E&where\",\"http://bdsmpeople.ru&network=vk&refereriGvhiKo7lw&bvm=bv.48705608\",0,12895,158,12132,216,1087,938,23,15,2,\"700.2244\",0,0,12,\"D�\",1,1,0,0,\"\",\"\",658382,-1,0,\"\",0,0,1095,649,135,1372721950,0,0,0,0,\"windows-1251;charset\",1,0,0,0,6509741558613487318,\"http://video.yandex.by/search/price_highlight%253Dhttp://rmnt.ru/search?text=%D1%80%D0%BC%20%D1%83%D0%BB%D0%B5%D0%B8%D1%80%D0%BF%D0%BA%D0%A2%D0%B3%D1%83%D0%B0%D0%BE%D0%B8%D0%B7%D0%BB%D1%83%D0%BB%D0%BD%D0%BB%D0%B0%D0%BD%D0%BC%D0%B8%D0%B5%20%D0%BB%D1%82%D1%87%D0%B5%D0%B8%20%E4%E0%E1%EE%ED%ED%F1%F2%F0%F2%FB%E9+%E3%E8%F1%F2%F0%E8%ED%E0+%D0%B8%D0%BE%20%D1%82%D1%80%D0%B0%D1%82%D1%8F%20with_photo=¤cy=RUR&is_hot=0&vip=0&op_style_id=2097775%2C257&pvno=2&evlg=VC,2;VL,248;IC,16;VL\",1022450989,0,0,0,0,0,\"5\",1372786972,0,1,3,6,66,1818130458,-1,-1,-1,\"S0\",\"h1\",\"\",\"\",0,0,0,0,0,0,0,0,\"\",0,\"\",\"NH\u001c\",0,\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",0,-7095314016616002272,-2039922795398915081,0\n", "5289360038140010777,1,\"Инвеста.Информленны - bonprix collection - Кошки, Часть, снять квартиру, Испании скейтшоп Proskater.ru (Работка сноубордовищ\",1,\"2013-07-02 07:02:43.000000000\",\"2013-07-02 08:00:00.000000000\",7525,-1260511522,41,3813931635822850500,1,44,7,\"http://voronezhskaia-moda-blue-c-3820857&t=290&po_yers=0&state.google.ru/real-estate/rent/700/photo17431408][to\",\"http://greenogorsk_Region-100062247.137505%26xpid\",0,12895,158,12132,216,1638,1658,23,15,2,\"700.169\",0,0,12,\"D�\",1,1,0,0,\"\",\"\",1835209,-1,0,\"\",0,0,1369,1018,135,1372711247,4,1,16561,0,\"windows-1251;charset\",1,0,0,0,8229313317592864677,\"\",975298214,0,0,0,0,0,\"5\",1372717306,50,2,3,16292,0,-673048140,-1,-1,-1,\"S0\",\"h1\",\"\",\"\",0,0,0,0,0,0,0,0,\"\",0,\"\",\"NH\u001c\",0,\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",0,8622994845783504296,441678500069920832,0\n", @@ -867,20 +968,20 @@ "6405590155111045434,1,\"Инвеста.Информленны - bonprix collection - Кошки, Часть, снять квартиру, Испании скейтшоп Proskater.ru (Работка сноубордовищ\",1,\"2013-07-02 07:07:33.000000000\",\"2013-07-02 08:00:00.000000000\",7525,-1260511522,41,3813931635822850500,1,44,7,\"http://voronezhskaia-moda-blue-c-3820857&t=290&po_yers=0&state.google.ru/real-estate/out-of-town/land.web-3.ru\",\"http://greenogorsk_Region-100062247.137438\",0,12895,158,12132,216,1638,1658,23,15,2,\"700.169\",0,0,12,\"D�\",1,1,0,0,\"\",\"\",1835209,-1,0,\"\",0,0,1369,1018,135,1372711549,4,1,16561,0,\"windows-1251;charset\",1,0,0,0,8229313317592864677,\"\",695592582,0,0,0,0,0,\"5\",1372717616,50,2,3,16292,0,-673048140,-1,-1,-1,\"S0\",\"�\f\",\"\",\"\",0,0,0,0,0,0,0,0,\"\",0,\"\",\"NH\u001c\",0,\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",0,662346848875253897,-5547551342880266035,0\n", "\n", "Q24: SELECT SearchPhrase FROM hits WHERE SearchPhrase <> '' ORDER BY EventTime LIMIT 10;\n", - "DuckDB time: 3.9978444576263428\n", + "DuckDB time: 0.1702120304107666\n", "DuckDB return:\n", " SearchPhrase\n", - "0 [209, 129, 208, 184, 208, 188, 208, 191, 209, ...\n", - "1 [208, 189, 208, 190, 209, 135, 208, 189, 208, ...\n", - "2 [208, 190, 209, 130, 208, 180, 209, 139, 209, ...\n", - "3 [209, 129, 208, 186, 208, 176, 209, 135, 208, ...\n", - "4 [208, 188, 208, 176, 209, 128, 209, 136, 208, ...\n", - "5 [208, 186, 209, 131, 208, 191, 208, 184, 209, ...\n", - "6 [208, 178, 208, 176, 208, 186, 208, 176, 208, ...\n", - "7 [208, 178, 208, 181, 208, 189, 208, 179, 209, ...\n", - "8 [48, 208, 177, 49, 32, 208, 186, 209, 131, 208...\n", - "9 [209, 129, 208, 176, 208, 189, 208, 176, 208, ...\n", - "chDB time: 1.364199161529541\n", + "0 ночно китая женщины\n", + "1 симптомы регистратов\n", + "2 скачать читалию в духовке\n", + "3 отдыха чем прокат\n", + "4 купить ваз 2121099 инжира 1 сезон смотреть онл...\n", + "5 маршава нибудь в омске главнованные автобаза ф...\n", + "6 вакансионал 28 неделю вытяжного печь бабка бу ...\n", + "7 венгридический якутии видео ни\n", + "8 санандроид малининец фармарин\n", + "9 0б1 купить без програма\n", + "chDB time: 0.19916772842407227\n", "chDB return:\n", " \"ночно китая женщины\"\n", "\"симптомы регистратов\"\n", @@ -894,20 +995,20 @@ "\"санандроид малининец фармарин\"\n", "\n", "Q25: SELECT SearchPhrase FROM hits WHERE SearchPhrase <> '' ORDER BY SearchPhrase LIMIT 10;\n", - "DuckDB time: 4.143980979919434\n", + "DuckDB time: 0.3799598217010498\n", "DuckDB return:\n", - " SearchPhrase\n", - "0 [32, 209, 129, 208, 178, 208, 181, 209, 130, 2...\n", - "1 [33, 32, 104, 101, 107, 116, 100, 102, 32, 103...\n", - "2 [36, 95, 103, 101, 116, 32, 97, 109, 50, 32, 2...\n", - "3 [36, 95, 103, 101, 116, 32, 105, 116, 32, 111,...\n", - "4 [36, 95, 103, 101, 116, 32, 108, 117, 99, 107,...\n", - "5 [36, 95, 112, 111, 115, 108, 97, 110, 100, 111...\n", - "6 [36, 95, 112, 111, 115, 116, 32, 114, 106, 107...\n", - "7 [36, 95, 112, 111, 115, 116, 97, 114, 115, 104...\n", - "8 [36, 100, 32, 208, 191, 209, 128, 208, 184, 20...\n", - "9 [36, 100, 32, 208, 191, 209, 128, 208, 184, 20...\n", - "chDB time: 1.3549120426177979\n", + " SearchPhrase\n", + "0 светы женске 2 сезон\n", + "1 ! hektdf gjcgjhn conster\n", + "2 $_get am2 купейн в хорошем\n", + "3 $_get it of goodbye minecraft\n", + "4 $_get lucky marantazii online b92 трейлер невски\n", + "5 $_poslandon.ru/moscow 2 торговлю\n", + "6 $_post rjktcfhtdcr\n", + "7 $_postarshippuden paris stan\n", + "8 $d причина\n", + "9 $d причина\n", + "chDB time: 0.07990717887878418\n", "chDB return:\n", " \" светы женске 2 сезон\"\n", "\"! hektdf gjcgjhn conster\"\n", @@ -921,20 +1022,20 @@ "\"$d причина\"\n", "\n", "Q26: SELECT SearchPhrase FROM hits WHERE SearchPhrase <> '' ORDER BY EventTime, SearchPhrase LIMIT 10;\n", - "DuckDB time: 4.127300977706909\n", + "DuckDB time: 0.3203549385070801\n", "DuckDB return:\n", " SearchPhrase\n", - "0 [208, 189, 208, 190, 209, 135, 208, 189, 208, ...\n", - "1 [209, 129, 208, 184, 208, 188, 208, 191, 209, ...\n", - "2 [208, 190, 209, 130, 208, 180, 209, 139, 209, ...\n", - "3 [209, 129, 208, 186, 208, 176, 209, 135, 208, ...\n", - "4 [208, 186, 209, 131, 208, 191, 208, 184, 209, ...\n", - "5 [208, 188, 208, 176, 209, 128, 209, 136, 208, ...\n", - "6 [208, 178, 208, 176, 208, 186, 208, 176, 208, ...\n", - "7 [208, 178, 208, 181, 208, 189, 208, 179, 209, ...\n", - "8 [48, 208, 177, 49, 32, 208, 186, 209, 131, 208...\n", - "9 [48, 208, 177, 49, 32, 208, 186, 209, 131, 208...\n", - "chDB time: 1.3599956035614014\n", + "0 ночно китая женщины\n", + "1 симптомы регистратов\n", + "2 отдыха чем прокат\n", + "3 скачать читалию в духовке\n", + "4 купить ваз 2121099 инжира 1 сезон смотреть онл...\n", + "5 маршава нибудь в омске главнованные автобаза ф...\n", + "6 вакансионал 28 неделю вытяжного печь бабка бу ...\n", + "7 венгридический якутии видео ни\n", + "8 0б1 купить без програма\n", + "9 0б1 купить в парня смотреть онлайн\n", + "chDB time: 0.06820559501647949\n", "chDB return:\n", " \"ночно китая женщины\"\n", "\"симптомы регистратов\"\n", @@ -948,13 +1049,25 @@ "\"0б1 купить в парня смотреть онлайн\"\n", "\n", "Q27: SELECT CounterID, AVG(STRLEN(URL)) AS l, COUNT(*) AS c FROM hits WHERE URL <> '' GROUP BY CounterID HAVING COUNT(*) > 100000 ORDER BY l DESC LIMIT 25;\n", - "DuckDB error: Binder Error: No function matches the given name and argument types 'strlen(BLOB)'. You might need to add explicit type casts.\n", - "\tCandidate functions:\n", - "\tstrlen(VARCHAR) -> BIGINT\n", - "\n", - "LINE 1: SELECT CounterID, AVG(STRLEN(URL)) AS l, COUNT(*) AS c FROM h...\n", - " ^\n", - "chDB time: 2.695941925048828\n", + "DuckDB time: 0.1666877269744873\n", + "DuckDB return:\n", + " CounterID l c\n", + "0 1634 198.148049 315442\n", + "1 786 186.750714 120528\n", + "2 515 126.359674 102793\n", + "3 62 93.217962 613474\n", + "4 3922 87.880246 3861827\n", + "5 38 76.436656 507770\n", + "6 1483 71.266113 869128\n", + "7 2264 67.700580 278338\n", + "8 40367 67.641345 218299\n", + "9 1095 65.021542 363337\n", + "10 1830 64.919784 113980\n", + "11 40206 63.381008 217355\n", + "12 5822 62.768687 383161\n", + "13 1060 61.041178 252489\n", + "14 7525 58.612668 584968\n", + "chDB time: 0.12528443336486816\n", "chDB return:\n", " 1634,198.14804940369388,315442\n", "786,186.7507135271472,120528\n", @@ -973,19 +1086,16 @@ "7525,58.61266770148111,584968\n", "\n", "Q28: SELECT REGEXP_REPLACE(Referer, '^https?://(?:www\\.)?([^/]+)/.*$', '\u0001') AS k, AVG(STRLEN(Referer)) AS l, COUNT(*) AS c, MIN(Referer) FROM hits WHERE Referer <> '' GROUP BY k HAVING COUNT(*) > 100000 ORDER BY l DESC LIMIT 25;\n", - "DuckDB error: Binder Error: No function matches the given name and argument types 'regexp_replace(BLOB, STRING_LITERAL, STRING_LITERAL)'. You might need to add explicit type casts.\n", - "\tCandidate functions:\n", - "\tregexp_replace(VARCHAR, VARCHAR, VARCHAR) -> VARCHAR\n", - "\tregexp_replace(VARCHAR, VARCHAR, VARCHAR, VARCHAR) -> VARCHAR\n", - "\n", - "LINE 1: SELECT REGEXP_REPLACE(Referer, '^https?://(?:w...\n", - " ^\n", - "chDB time: 3.082376480102539\n", + "DuckDB time: 0.2830212116241455\n", + "DuckDB return:\n", + " k l c min(Referer)\n", + "0 \u0001 99.401568 7697804 http://%26ad%3D1%260.html&ei=9e71d2f0b6590/3/w...\n", + "chDB time: 0.32376670837402344\n", "chDB return:\n", " \"\u0001\",99.40156803161005,7697804,\"http://%26ad%3D1%260.html&ei=9e71d2f0b6590/3/women.aspx?sort=sale/living/Soul видео&clid\"\n", "\n", "Q29: SELECT SUM(ResolutionWidth), SUM(ResolutionWidth + 1), SUM(ResolutionWidth + 2), SUM(ResolutionWidth + 3), SUM(ResolutionWidth + 4), SUM(ResolutionWidth + 5), SUM(ResolutionWidth + 6), SUM(ResolutionWidth + 7), SUM(ResolutionWidth + 8), SUM(ResolutionWidth + 9), SUM(ResolutionWidth + 10), SUM(ResolutionWidth + 11), SUM(ResolutionWidth + 12), SUM(ResolutionWidth + 13), SUM(ResolutionWidth + 14), SUM(ResolutionWidth + 15), SUM(ResolutionWidth + 16), SUM(ResolutionWidth + 17), SUM(ResolutionWidth + 18), SUM(ResolutionWidth + 19), SUM(ResolutionWidth + 20), SUM(ResolutionWidth + 21), SUM(ResolutionWidth + 22), SUM(ResolutionWidth + 23), SUM(ResolutionWidth + 24), SUM(ResolutionWidth + 25), SUM(ResolutionWidth + 26), SUM(ResolutionWidth + 27), SUM(ResolutionWidth + 28), SUM(ResolutionWidth + 29), SUM(ResolutionWidth + 30), SUM(ResolutionWidth + 31), SUM(ResolutionWidth + 32), SUM(ResolutionWidth + 33), SUM(ResolutionWidth + 34), SUM(ResolutionWidth + 35), SUM(ResolutionWidth + 36), SUM(ResolutionWidth + 37), SUM(ResolutionWidth + 38), SUM(ResolutionWidth + 39), SUM(ResolutionWidth + 40), SUM(ResolutionWidth + 41), SUM(ResolutionWidth + 42), SUM(ResolutionWidth + 43), SUM(ResolutionWidth + 44), SUM(ResolutionWidth + 45), SUM(ResolutionWidth + 46), SUM(ResolutionWidth + 47), SUM(ResolutionWidth + 48), SUM(ResolutionWidth + 49), SUM(ResolutionWidth + 50), SUM(ResolutionWidth + 51), SUM(ResolutionWidth + 52), SUM(ResolutionWidth + 53), SUM(ResolutionWidth + 54), SUM(ResolutionWidth + 55), SUM(ResolutionWidth + 56), SUM(ResolutionWidth + 57), SUM(ResolutionWidth + 58), SUM(ResolutionWidth + 59), SUM(ResolutionWidth + 60), SUM(ResolutionWidth + 61), SUM(ResolutionWidth + 62), SUM(ResolutionWidth + 63), SUM(ResolutionWidth + 64), SUM(ResolutionWidth + 65), SUM(ResolutionWidth + 66), SUM(ResolutionWidth + 67), SUM(ResolutionWidth + 68), SUM(ResolutionWidth + 69), SUM(ResolutionWidth + 70), SUM(ResolutionWidth + 71), SUM(ResolutionWidth + 72), SUM(ResolutionWidth + 73), SUM(ResolutionWidth + 74), SUM(ResolutionWidth + 75), SUM(ResolutionWidth + 76), SUM(ResolutionWidth + 77), SUM(ResolutionWidth + 78), SUM(ResolutionWidth + 79), SUM(ResolutionWidth + 80), SUM(ResolutionWidth + 81), SUM(ResolutionWidth + 82), SUM(ResolutionWidth + 83), SUM(ResolutionWidth + 84), SUM(ResolutionWidth + 85), SUM(ResolutionWidth + 86), SUM(ResolutionWidth + 87), SUM(ResolutionWidth + 88), SUM(ResolutionWidth + 89) FROM hits;\n", - "DuckDB time: 0.21076488494873047\n", + "DuckDB time: 0.2807931900024414\n", "DuckDB return:\n", " sum(ResolutionWidth) sum((ResolutionWidth + 1)) \\\n", "0 1.506781e+10 1.507781e+10 \n", @@ -1018,12 +1128,12 @@ "0 1.594781e+10 1.595781e+10 \n", "\n", "[1 rows x 90 columns]\n", - "chDB time: 0.05226325988769531\n", + "chDB time: 0.07846283912658691\n", "chDB return:\n", " 15067814968,15077814968,15087814968,15097814968,15107814968,15117814968,15127814968,15137814968,15147814968,15157814968,15167814968,15177814968,15187814968,15197814968,15207814968,15217814968,15227814968,15237814968,15247814968,15257814968,15267814968,15277814968,15287814968,15297814968,15307814968,15317814968,15327814968,15337814968,15347814968,15357814968,15367814968,15377814968,15387814968,15397814968,15407814968,15417814968,15427814968,15437814968,15447814968,15457814968,15467814968,15477814968,15487814968,15497814968,15507814968,15517814968,15527814968,15537814968,15547814968,15557814968,15567814968,15577814968,15587814968,15597814968,15607814968,15617814968,15627814968,15637814968,15647814968,15657814968,15667814968,15677814968,15687814968,15697814968,15707814968,15717814968,15727814968,15737814968,15747814968,15757814968,15767814968,15777814968,15787814968,15797814968,15807814968,15817814968,15827814968,15837814968,15847814968,15857814968,15867814968,15877814968,15887814968,15897814968,15907814968,15917814968,15927814968,15937814968,15947814968,15957814968\n", "\n", "Q30: SELECT SearchEngineID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM hits WHERE SearchPhrase <> '' GROUP BY SearchEngineID, ClientIP ORDER BY c DESC LIMIT 10;\n", - "DuckDB time: 3.7694642543792725\n", + "DuckDB time: 0.12310099601745605\n", "DuckDB return:\n", " SearchEngineID ClientIP c sum(IsRefresh) avg(ResolutionWidth)\n", "0 2 -1262139876 189 14.0 1560.063492\n", @@ -1036,7 +1146,7 @@ "7 2 -792059583 148 10.0 1683.074324\n", "8 2 -1993532306 145 6.0 1625.655172\n", "9 95 2031325834 138 1.0 1368.000000\n", - "chDB time: 1.3756563663482666\n", + "chDB time: 0.14722228050231934\n", "chDB return:\n", " 2,-1262139876,189,14,1560.063492063492\n", "2,-927025522,187,26,1621.3689839572191\n", @@ -1050,20 +1160,20 @@ "2,-1945757555,138,9,1580.2536231884058\n", "\n", "Q31: SELECT WatchID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM hits WHERE SearchPhrase <> '' GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10;\n", - "DuckDB time: 4.174175262451172\n", + "DuckDB time: 0.14729666709899902\n", "DuckDB return:\n", " WatchID ClientIP c sum(IsRefresh) avg(ResolutionWidth)\n", - "0 5881018188589865550 42882292 1 0.0 1368.0\n", - "1 4878409017229571929 -161603248 1 0.0 1087.0\n", - "2 6051186757641838757 1920149913 1 0.0 1368.0\n", - "3 8006077835706298394 1920149913 1 0.0 1368.0\n", - "4 5484356534521074814 1148476618 1 0.0 601.0\n", - "5 5457388606587188180 1871935026 1 0.0 253.0\n", - "6 6818425839795421361 791251782 1 0.0 1828.0\n", - "7 9213057532531660572 2071693441 1 0.0 508.0\n", - "8 8655709654502595294 1452578003 1 0.0 1368.0\n", - "9 4938853299680215892 -1230920724 1 0.0 1996.0\n", - "chDB time: 1.3677966594696045\n", + "0 5784841538923002299 1765727415 1 1.0 1638.0\n", + "1 5467523983841705410 -134198584 1 1.0 1828.0\n", + "2 7844411592084486456 -134198584 1 0.0 1828.0\n", + "3 4869646130549353650 895962929 1 0.0 1638.0\n", + "4 7999979102720528021 125936577 1 0.0 1917.0\n", + "5 8569561125020140068 1382082651 1 0.0 1087.0\n", + "6 6637523727543483450 1891132073 1 1.0 1996.0\n", + "7 5398449724796321985 1022734787 1 1.0 1750.0\n", + "8 6659001207354530550 -466045254 1 1.0 1638.0\n", + "9 5533437218520208748 1227755721 1 0.0 1990.0\n", + "chDB time: 0.07712554931640625\n", "chDB return:\n", " 5494909287200572026,1492278923,1,0,1828\n", "4965054029390764634,-1206595968,1,0,166\n", @@ -1071,26 +1181,26 @@ "6691203620596311846,2003800917,1,0,1087\n", "5786133618012580033,1390766629,1,0,1368\n", "5985454501189037066,1832002778,1,0,1638\n", - "6829606353031419075,1926497591,1,0,1917\n", - "8745161824300249528,1528045946,1,1,1638\n", + "6427115150554230793,736252994,1,0,1996\n", "4698453950679016700,-1916962470,1,0,1750\n", + "8745161824300249528,1528045946,1,1,1638\n", "7352065519984549840,1557735347,1,0,1638\n", "\n", "Q32: SELECT WatchID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM hits GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10;\n", - "DuckDB time: 0.278048038482666\n", + "DuckDB time: 0.26334595680236816\n", "DuckDB return:\n", " WatchID ClientIP c sum(IsRefresh) avg(ResolutionWidth)\n", - "0 5038438559514230916 -782207692 1 0.0 1638.0\n", - "1 5434675241839632177 1501669924 1 0.0 1638.0\n", - "2 6165036197656715755 1118320956 1 0.0 1638.0\n", - "3 5372658530354233945 -742801843 1 0.0 1396.0\n", - "4 7167970186126813930 -742801843 1 1.0 1396.0\n", - "5 7651916972403408320 -742801843 1 0.0 1396.0\n", - "6 7793097203738372561 -742801843 1 1.0 1396.0\n", - "7 8009170860754767092 -742801843 1 1.0 1396.0\n", - "8 6251613011152194841 -742801843 1 0.0 1396.0\n", - "9 4837371440160936324 -742801843 1 0.0 1396.0\n", - "chDB time: 0.32828855514526367\n", + "0 6526230354265394848 -449204739 1 0.0 1638.0\n", + "1 6891306091019305918 -1005706672 1 0.0 1996.0\n", + "2 6751069629239762819 -544233094 1 0.0 1750.0\n", + "3 8375980994104380413 -581332236 1 0.0 1828.0\n", + "4 6329745451486852690 72058342 1 0.0 1011.0\n", + "5 7368652614670853818 1748594801 1 0.0 1368.0\n", + "6 5334169353145740463 917154364 1 0.0 1368.0\n", + "7 5595949711278080753 -460848853 1 0.0 1368.0\n", + "8 4795287084663673885 768984503 1 0.0 1750.0\n", + "9 9101221649481352476 1304836636 1 0.0 1368.0\n", + "chDB time: 0.29560303688049316\n", "chDB return:\n", " 7045311802744285412,-1341502114,1,0,1996\n", "7997911216135529594,-1050444826,1,0,1750\n", @@ -1104,20 +1214,20 @@ "4848806411334622685,2132338069,1,0,1638\n", "\n", "Q33: SELECT URL, COUNT(*) AS c FROM hits GROUP BY URL ORDER BY c DESC LIMIT 10;\n", - "DuckDB time: 5.656167268753052\n", + "DuckDB time: 0.26684117317199707\n", "DuckDB return:\n", " URL c\n", - "0 [104, 116, 116, 112, 58, 47, 47, 115, 112, 45,... 100821\n", - "1 [104, 116, 116, 112, 58, 47, 47, 105, 114, 114... 90604\n", - "2 [104, 116, 116, 112, 58, 37, 50, 70, 37, 50, 7... 46281\n", - "3 [104, 116, 116, 112, 58, 47, 47, 107, 111, 109... 43455\n", - "4 [104, 116, 116, 112, 58, 47, 47, 97, 102, 105,... 35161\n", - "5 [104, 116, 116, 112, 58, 47, 47, 115, 112, 45,... 31018\n", - "6 [104, 116, 116, 112, 58, 37, 50, 70, 37, 50, 7... 28878\n", - "7 [104, 116, 116, 112, 58, 47, 47, 97, 102, 105,... 26520\n", - "8 [104, 116, 116, 112, 58, 47, 47, 115, 105, 98,... 25242\n", - "9 [104, 116, 116, 112, 58, 47, 47, 115, 112, 45,... 17068\n", - "chDB time: 2.747922897338867\n", + "0 http://sp-money.yandex.ru/comme%2F27.0.1453.11... 100821\n", + "1 http://irr.ru/index.php?showalbum/login-leniya... 90604\n", + "2 http:%2F%2Fdlia-zhienskaia-moda-tunika 46281\n", + "3 http://komme%2F27.0.1453.116 43455\n", + "4 http://afisha.yandex.ru/region/vacancies 35161\n", + "5 http://sp-money.yandex.ru%26target 31018\n", + "6 http:%2F%2Fwwww.bonprix.ru/mosclinindzya 28878\n", + "7 http://afisha.yandex.ru/region-ware-ne-niz%2F%... 26520\n", + "8 http://sib1.adriver 25242\n", + "9 http://sp-money.yandex.ua/search&event=little 17068\n", + "chDB time: 0.2204272747039795\n", "chDB return:\n", " \"http://sp-money.yandex.ru/comme%2F27.0.1453.116 Safari\",100821\n", "\"http://irr.ru/index.php?showalbum/login-leniya7777294,938303130\",90604\n", @@ -1131,20 +1241,20 @@ "\"http://sp-money.yandex.ua/search&event=little\",17068\n", "\n", "Q34: SELECT 1, URL, COUNT(*) AS c FROM hits GROUP BY 1, URL ORDER BY c DESC LIMIT 10;\n", - "DuckDB time: 5.482933044433594\n", + "DuckDB time: 0.23300528526306152\n", "DuckDB return:\n", " 1 URL c\n", - "0 1 [104, 116, 116, 112, 58, 47, 47, 115, 112, 45,... 100821\n", - "1 1 [104, 116, 116, 112, 58, 47, 47, 105, 114, 114... 90604\n", - "2 1 [104, 116, 116, 112, 58, 37, 50, 70, 37, 50, 7... 46281\n", - "3 1 [104, 116, 116, 112, 58, 47, 47, 107, 111, 109... 43455\n", - "4 1 [104, 116, 116, 112, 58, 47, 47, 97, 102, 105,... 35161\n", - "5 1 [104, 116, 116, 112, 58, 47, 47, 115, 112, 45,... 31018\n", - "6 1 [104, 116, 116, 112, 58, 37, 50, 70, 37, 50, 7... 28878\n", - "7 1 [104, 116, 116, 112, 58, 47, 47, 97, 102, 105,... 26520\n", - "8 1 [104, 116, 116, 112, 58, 47, 47, 115, 105, 98,... 25242\n", - "9 1 [104, 116, 116, 112, 58, 47, 47, 115, 112, 45,... 17068\n", - "chDB time: 2.7932345867156982\n", + "0 1 http://sp-money.yandex.ru/comme%2F27.0.1453.11... 100821\n", + "1 1 http://irr.ru/index.php?showalbum/login-leniya... 90604\n", + "2 1 http:%2F%2Fdlia-zhienskaia-moda-tunika 46281\n", + "3 1 http://komme%2F27.0.1453.116 43455\n", + "4 1 http://afisha.yandex.ru/region/vacancies 35161\n", + "5 1 http://sp-money.yandex.ru%26target 31018\n", + "6 1 http:%2F%2Fwwww.bonprix.ru/mosclinindzya 28878\n", + "7 1 http://afisha.yandex.ru/region-ware-ne-niz%2F%... 26520\n", + "8 1 http://sib1.adriver 25242\n", + "9 1 http://sp-money.yandex.ua/search&event=little 17068\n", + "chDB time: 0.19884967803955078\n", "chDB return:\n", " 1,\"http://sp-money.yandex.ru/comme%2F27.0.1453.116 Safari\",100821\n", "1,\"http://irr.ru/index.php?showalbum/login-leniya7777294,938303130\",90604\n", @@ -1158,7 +1268,7 @@ "1,\"http://sp-money.yandex.ua/search&event=little\",17068\n", "\n", "Q35: SELECT ClientIP, ClientIP - 1, ClientIP - 2, ClientIP - 3, COUNT(*) AS c FROM hits GROUP BY ClientIP, ClientIP - 1, ClientIP - 2, ClientIP - 3 ORDER BY c DESC LIMIT 10;\n", - "DuckDB time: 0.08961772918701172\n", + "DuckDB time: 0.1158907413482666\n", "DuckDB return:\n", " ClientIP (ClientIP - 1) (ClientIP - 2) (ClientIP - 3) c\n", "0 -1698104457 -1698104458 -1698104459 -1698104460 29119\n", @@ -1171,7 +1281,7 @@ "7 -1313501018 -1313501019 -1313501020 -1313501021 2746\n", "8 1151807695 1151807694 1151807693 1151807692 2702\n", "9 -267589304 -267589305 -267589306 -267589307 2526\n", - "chDB time: 0.08932375907897949\n", + "chDB time: 0.22491216659545898\n", "chDB return:\n", " -1698104457,-1698104458,-1698104459,-1698104460,29119\n", "-1175819552,-1175819553,-1175819554,-1175819555,16854\n", @@ -1185,20 +1295,20 @@ "-267589304,-267589305,-267589306,-267589307,2526\n", "\n", "Q36: SELECT URL, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND DontCountHits = 0 AND IsRefresh = 0 AND URL <> '' GROUP BY URL ORDER BY PageViews DESC LIMIT 10;\n", - "DuckDB time: 5.240381956100464\n", + "DuckDB time: 0.14656829833984375\n", "DuckDB return:\n", " URL PageViews\n", - "0 [104, 116, 116, 112, 58, 47, 47, 105, 114, 114... 85646\n", - "1 [104, 116, 116, 112, 58, 47, 47, 107, 111, 109... 42422\n", - "2 [104, 116, 116, 112, 58, 47, 47, 105, 114, 114... 15165\n", - "3 [104, 116, 116, 112, 58, 47, 47, 105, 114, 114... 13779\n", - "4 [104, 116, 116, 112, 58, 47, 47, 105, 114, 114... 10559\n", - "5 [104, 116, 116, 112, 58, 47, 47, 105, 114, 114... 8997\n", - "6 [104, 116, 116, 112, 58, 47, 47, 107, 111, 109... 6322\n", - "7 [104, 116, 116, 112, 58, 47, 47, 105, 114, 114... 3633\n", - "8 [104, 116, 116, 112, 58, 47, 47, 105, 114, 114... 3363\n", - "9 [104, 116, 116, 112, 58, 47, 47, 107, 111, 109... 2538\n", - "chDB time: 2.6615116596221924\n", + "0 http://irr.ru/index.php?showalbum/login-leniya... 85646\n", + "1 http://komme%2F27.0.1453.116 42422\n", + "2 http://irr.ru/index.php?showalbum/login-kapust... 15165\n", + "3 http://irr.ru/index.php?showalbum/login-kapust... 13779\n", + "4 http://irr.ru/index.php 10559\n", + "5 http://irr.ru/index.php?showalbum/login 8997\n", + "6 http://komme%2F27.0.1453.116 Safari%2F5.0 (com... 6322\n", + "7 http://irr.ru/index.php?showalbum/login-kupalnik 3633\n", + "8 http://irr.ru/index.php?showalbum/login-kapust... 3363\n", + "9 http://komme%2F27.0.1453.116 Safari 2538\n", + "chDB time: 0.1262979507446289\n", "chDB return:\n", " \"http://irr.ru/index.php?showalbum/login-leniya7777294,938303130\",85646\n", "\"http://komme%2F27.0.1453.116\",42422\n", @@ -1212,20 +1322,20 @@ "\"http://komme%2F27.0.1453.116 Safari\",2538\n", "\n", "Q37: SELECT Title, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND DontCountHits = 0 AND IsRefresh = 0 AND Title <> '' GROUP BY Title ORDER BY PageViews DESC LIMIT 10;\n", - "DuckDB time: 5.022341251373291\n", + "DuckDB time: 0.163499116897583\n", "DuckDB return:\n", " Title PageViews\n", - "0 [208, 162, 208, 181, 209, 129, 209, 130, 32, 4... 102228\n", - "1 [208, 168, 208, 176, 209, 128, 208, 176, 209, ... 68968\n", - "2 [208, 159, 209, 128, 208, 184, 208, 188, 208, ... 67496\n", - "3 [208, 145, 209, 128, 209, 142, 208, 186, 208, ... 31750\n", - "4 [208, 162, 208, 181, 208, 191, 208, 187, 208, ... 19270\n", - "5 [68, 97, 118, 101, 32, 97, 110, 100, 32, 72, 1... 11962\n", - "6 [208, 159, 209, 128, 208, 184, 208, 188, 208, ... 11618\n", - "7 [65, 85, 84, 79, 46, 114, 105, 97, 46, 117, 97... 11611\n", - "8 [79, 87, 65, 80, 114, 111, 102, 101, 115, 115,... 8965\n", - "9 [208, 162, 209, 128, 209, 131, 209, 129, 208, ... 8445\n", - "chDB time: 4.422863960266113\n", + "0 Тест (Россия) - Яндекс 102228\n", + "1 Шарарай), Выбрать! - обсуждаются на голд: Шоуб... 68968\n", + "2 Приморск - IRR.ru 67496\n", + "3 Брюки New Era H (Асус) 258 общая выплаток, гор... 31750\n", + "4 Теплоску на 19270\n", + "5 Dave and Hotpoint sport – самые вещие 11962\n", + "6 Приморск (Россия) - Яндекс.Видео 11618\n", + "7 AUTO.ria.ua ™ - Аппер 11611\n", + "8 OWAProfessign), продать 8965\n", + "9 Труси - Шоубиз 8445\n", + "chDB time: 0.2948627471923828\n", "chDB return:\n", " \"Тест (Россия) - Яндекс\",102228\n", "\"Шарарай), Выбрать! - обсуждаются на голд: Шоубиз - Свободная историс\",68968\n", @@ -1239,121 +1349,121 @@ "\"Труси - Шоубиз\",8445\n", "\n", "Q38: SELECT URL, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 AND IsLink <> 0 AND IsDownload = 0 GROUP BY URL ORDER BY PageViews DESC LIMIT 10 OFFSET 1000;\n", - "DuckDB time: 5.172285795211792\n", + "DuckDB time: 0.1810312271118164\n", "DuckDB return:\n", " URL PageViews\n", - "0 [104, 116, 116, 112, 58, 47, 47, 115, 116, 97,... 2\n", - "1 [104, 116, 116, 112, 58, 47, 47, 115, 116, 97,... 2\n", - "2 [104, 116, 116, 112, 58, 47, 47, 115, 109, 101... 2\n", - "3 [104, 116, 116, 112, 58, 47, 47, 115, 116, 97,... 2\n", - "4 [104, 116, 116, 112, 58, 47, 47, 115, 116, 97,... 2\n", - "5 [104, 116, 116, 112, 58, 47, 47, 108, 105, 98,... 2\n", - "6 [104, 116, 116, 112, 58, 47, 47, 115, 116, 97,... 2\n", - "7 [104, 116, 116, 112, 58, 47, 47, 115, 116, 97,... 2\n", - "8 [104, 116, 116, 112, 58, 47, 47, 115, 116, 97,... 2\n", - "9 [104, 116, 116, 112, 58, 47, 47, 114, 109, 110... 2\n", - "chDB time: 2.669616460800171\n", + "0 http://irr.ru/bank/otkrovnja-instvo.ru/search?... 2\n", + "1 http://bdsmpeople.ru/user552.html_params%3Drho... 2\n", + "2 http://wildberries.ru/rzn.net/maker.im/phpBB2/... 2\n", + "3 http://stalker-pub-20087898675494,960948/#page... 2\n", + "4 http://afisha.mail.ru/login.html?n=21 2\n", + "5 http://bonprix.ru/catalog/898/top/testy-v-tolk... 2\n", + "6 http://stalker-pub-20087898675494,960948/#page... 2\n", + "7 http://omsk/evential/housession%3D90%26rnd%3D8... 2\n", + "8 http://omsk/evential/housession%3D90%26rnd%3D8... 2\n", + "9 http://omsk/evential/housession%3D%26CompPath%... 2\n", + "chDB time: 0.1204230785369873\n", "chDB return:\n", - " \"http://video=0&is_hot=0&vip=0&confiscategoriya%2Fzhiensmed.ru/forums/view_type\",2\n", - "\"http://bmw/skalinino/afisha.yandex\",2\n", - "\"http://wildberries.ru/editem_no=100¤cy=RUR/hasimages/0001216628753,0.110.vk.me/u171084d598a\",2\n", - "\"http://afisha.mail.ru/real-estate/aparts.ru/search\",2\n", - "\"http://stalker-pub-20087898675494,960948/#page_type%3D260117152337&spn=1395,9455989.ya.ru/work.html_params%3D0%26rleurl%3D%26CompPath%3Dhttp://video.yandex.ru/filmId=s4hAuutourism/otdelo.ua/searchivet_allery/pic/89393.html?1=1&cid=52635349894,9247478/grams\",2\n", - "\"http://stalker-pub-20087898675494,960948/#page_type%3D0%26pz%3D0%26rleurl%3D%26bid%3D278885%26bt%3D_black_list=0&autodoc.ru/katerinburg.irr.ru/searchv.php?id=4638621682280375.html_params%3Drhost%3D90%26pz%3D0%26ar_page\",2\n", - "\"http://stalker-pub-20087898675494,960948/#page_type%3D0%26pz%3D0%26rleurl%3D//ad.adriver.ru/photo=0&is_hot=0&auto_id=577&oki=1&op_prodam-1-komn-kvarti-m.ru/allprice=от 5000/currency=1#country=&op_categoriya%2F5.0\",2\n", - "\"http://guid=6&pw=2&pv=0&with_photo/600566604\",2\n", - "\"http://bonprix.ru/omsk/event=big\",2\n", - "\"http://kinopoisk.ru/saint\",2\n", + " \"http://komstvennoke00721073&z=204698463211595,92446.0.html?1\",2\n", + "\"http://zarplata.ru/?p=126711-recept-Grecheniya.html?1=1&city&custom%3D1216629/0/&&puid1\",2\n", + "\"http://pogoda.yandex.ru%2Fkategory_id=577&search/ab_distratitc2\",2\n", + "\"http://avia&where=all&text=уход-на-Амурск и дозы чисора колепный век\",2\n", + "\"http://bibidohertki-tut.by/searchAutoSearchv.php?gidcar\",2\n", + "\"http://auto_id=0&metallic\",2\n", + "\"http://stalker-pub-20087898675494,960948/#page_type%3D0%26pz%3D0%26rleurl%3D//ad.adriver.ru/photo=0&is_hot=0&auto_id=577&oki=1&op_prodam-1-komn-kvarti-m.ru/allprice_do=12066072.html?1=1&cid=573&pt=b&pd=6&bodystyle=0\",2\n", + "\"http://stalker-pub-20087898675494,960948/#page_type%3D260117152337&spn=1395,9455989.ya.ru/world/photo/70943f42042587,415142.html5/v12/?from]=&int[153][from]=&input_city=0&page=4&marka=0&po_yers=20073192641#/view_type%3D0%26aktion/russinsk/details/?cat_number\",2\n", + "\"http://wildberrin/foton\",2\n", + "\"http://stalker-pub-20087898675494,960948/#page_type%3D260117152337&spn=1395,9455989.ya.ru/world/photo=0&in=compatible; MSIE 8.0 Safari%2F537.36 (KHTML, like Gecko) Version%2F&ti=Платье&op_page/1894,927315038/DD00E40F80-400g8f.2115061/article2304]\",2\n", "\n", "Q39: SELECT TraficSourceID, SearchEngineID, AdvEngineID, CASE WHEN (SearchEngineID = 0 AND AdvEngineID = 0) THEN Referer ELSE '' END AS Src, URL AS Dst, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 GROUP BY TraficSourceID, SearchEngineID, AdvEngineID, Src, Dst ORDER BY PageViews DESC LIMIT 10 OFFSET 1000;\n", - "DuckDB time: 10.247665405273438\n", + "DuckDB time: 0.19710803031921387\n", "DuckDB return:\n", " TraficSourceID SearchEngineID AdvEngineID \\\n", - "0 -1 0 0 \n", + "0 0 0 0 \n", "1 -1 0 0 \n", - "2 -1 0 0 \n", - "3 0 0 0 \n", - "4 5 0 0 \n", + "2 1 0 0 \n", + "3 -1 0 0 \n", + "4 -1 0 0 \n", "5 -1 0 0 \n", "6 -1 0 0 \n", "7 -1 0 0 \n", - "8 5 0 0 \n", + "8 -1 0 0 \n", "9 -1 0 0 \n", "\n", " Src \\\n", - "0 [104, 116, 116, 112, 58, 47, 47, 115, 116, 97,... \n", - "1 [104, 116, 116, 112, 58, 47, 47, 115, 116, 97,... \n", - "2 [104, 116, 116, 112, 58, 47, 47, 107, 105, 110... \n", - "3 [] \n", - "4 [104, 116, 116, 112, 58, 47, 47, 107, 105, 110... \n", - "5 [104, 116, 116, 112, 58, 47, 47, 115, 116, 97,... \n", - "6 [104, 116, 116, 112, 58, 47, 47, 115, 116, 97,... \n", - "7 [104, 116, 116, 112, 58, 47, 47, 115, 116, 97,... \n", - "8 [104, 116, 116, 112, 58, 47, 47, 115, 116, 97,... \n", - "9 [104, 116, 116, 112, 58, 47, 47, 115, 116, 97,... \n", + "0 \n", + "1 http://state=19945206/foto-4/login-2491724/?bu... \n", + "2 http://yandex.ru/world/photo_entry/r/afr.php?l... \n", + "3 http://state=19945206/foto-4/login-116;19984/f... \n", + "4 http://state=19945206/foto-4/login-2491724/?bu... \n", + "5 http://state=19945206/foto-4/login-2491724/?bu... \n", + "6 http://state=19945206/foto-4/login-2491724/?bu... \n", + "7 http://state=19945206/foto-4/login-2491724/?bu... \n", + "8 http://state=19945206/foto-4/login-2491724/?bu... \n", + "9 http://state=19945206/foto-4/login-2006/makumi... \n", "\n", " Dst PageViews \n", - "0 [104, 116, 116, 112, 58, 47, 47, 105, 114, 114... 13 \n", - "1 [104, 116, 116, 112, 58, 47, 47, 105, 114, 114... 13 \n", - "2 [104, 116, 116, 112, 58, 47, 47, 105, 114, 114... 13 \n", - "3 [104, 116, 116, 112, 58, 47, 47, 105, 114, 114... 13 \n", - "4 [104, 116, 116, 112, 58, 47, 47, 118, 105, 100... 13 \n", - "5 [104, 116, 116, 112, 58, 47, 47, 105, 114, 114... 13 \n", - "6 [104, 116, 116, 112, 58, 47, 47, 105, 114, 114... 13 \n", - "7 [104, 116, 116, 112, 58, 47, 47, 105, 114, 114... 13 \n", - "8 [104, 116, 116, 112, 58, 47, 47, 109, 121, 108... 13 \n", - "9 [104, 116, 116, 112, 58, 47, 47, 105, 114, 114... 13 \n", - "chDB time: 5.31972074508667\n", + "0 http://irr.ru/index.php?showalbum/login-sumki/... 13 \n", + "1 http://irr.ru/index.php?showalbum/login-kapust... 13 \n", + "2 http://irr.ru/index.php?showalbum/login/?do=re... 13 \n", + "3 http://irr.ru/index.php?showalbum/login-kapust... 13 \n", + "4 http://irr.ru/index.php?showalbum/login-kapust... 13 \n", + "5 http://irr.ru/index.php?showalbum/login-kapust... 13 \n", + "6 http://irr.ru/index.php?showalbum/login-kapust... 13 \n", + "7 http://irr.ru/index.php?showalbum/login-kapust... 13 \n", + "8 http://irr.ru/index.php?showalbum/login-kupalj... 13 \n", + "9 http://irr.ru/index.php?showalbum/login-leniya... 13 \n", + "chDB time: 0.17793655395507812\n", "chDB return:\n", - " -1,0,0,\"http://state=19945206/foto-4/login-gorod/search?p=7&oprnd=9902.jpg&img_url=http://yandsearch\",\"http://irr.ru/index.php?showalbum/login-kapusta-advert2727obHms3M&where=all&filmId=importizansk\",13\n", - "5,0,0,\"http://state=19945206/foto-4/login-2006/makumirostova.rambler.html?albumfoto-15.xhtml?city\",\"http://love.ru/a-myprofi\",13\n", - "-1,0,0,\"http://state=19945206/foto-4/login-2006/makumiroshoowbiz/down%2Fholodilnik.ru/7678/?\",\"http://irr.ru/index.php?showalbum/login-leniya7777294,938303130\",13\n", - "0,0,0,\"\",\"http://irr.ru/index.php?showalbum/login-tish/sten/4925&input_activ.tv/0505&op_category_iz_pravda.ru/GameMain.aspx#localculatesTypeSearch?text=запчасти)&issertpost&top=0&input_who2=1&input_who2=&int[245][]=&select\",13\n", - "-1,0,0,\"http://state=19945206/foto-4/login-kategoriya/zhiensmed.ru/recipes/search?lr=285&ulogin=ic-self/login=rekm2012&bpp=12&main.aspx?sort=price_map5\",\"http://irr.ru/index.php?showalbum/login-kapusta-advert261623447413339&model=2319\",13\n", - "-1,0,0,\"http://state=19945206/foto-4/login-2006/makumirostova.ru/GameMain.aspx?sort=RublePrice=от\",\"http://irr.ru/index.php?showalbum/login-leniya7777294,938303130\",13\n", - "5,0,0,\"http://state=199450984062\",\"http:%2F%2Fwwwwww.bonprix.ru/myAccountry\",13\n", - "-1,0,0,\"http://state=19945206/foto-4/login-2491724/?bundlers/search?text\",\"http://irr.ru/index.php?showalbum/login-kapusta-advert26092/make=KIA/page/1762058;40;42&pv=16&ll\",13\n", - "-1,0,0,\"http://state=19945206/foto-4/login-2006/makumirostova.ru/GameMain\",\"http://irr.ru/index.php?showalbum/login-kapustic/product_name\",13\n", - "-1,0,0,\"http://state=19945206/foto-4/login-kupe_921675345&a=1&u_nplug=7&Night ремонтажной рубеж\",\"http://irr.ru/index.php?showalbum/login.html_parame-owa.html?html_param=0&users/news.ru/kupaljinik-vints/73917.xhtml%26custom%3D%26CompPath%3Dhttp://radio.ru%26bn%3D90%26ar_sliceid%3D158197%26width%3Dhttp://e96.ru/turis-blonditors&sort_dikini%2F5.0 (company_to_auto.ria.ua/search?film/7184082818141&op_page=100xeA.2609623133321552\",13\n", + " -1,0,0,\"http://state=19945206/foto-4/login-don-profile/page=7514672553&numphoto=100000&aN=Netscape&aV=5.0 (iPad; CPU OS 602368&bs=Shelf_ID=22900.html&lang=ru&cE=true&uA=Mozillaserdino_bum_id=3159&input_who1=2&input_age1=&input_age16/foto.kiev/state/rent/page=4&hide&sl=ru&qs=n&follogam/pupzemlya-vashdom.ru/page=2&option%3D312:uid%3D139750%26req%3Dкакую кролик кино пределают взглядывать расти бережные сериал супруги попугай гости»\",\"http://irr.ru/index.php?showalbum/login.j_new144344&st=168494,903857595,9798369.html_parki.html%3Fhtml%26custom=0&deletedAuto=on&access.ru/search?text=♥ ♥ ♥&where=all&filmId=ud1OuKKIN-EXAMPLE-DOROGO-YaZYKA-advert2740672&model=0&search/?target=search?filmId=UX0Cw&where=all&film/592996a3435610674/*data/311812\",13\n", + "-1,0,0,\"http://state=19945206/foto-4/login/index.ru/krk/play/1028889\",\"http://irr.ru/index.php?showalbum/login-zimnyaya%2F537.36&he=900&op_page\",13\n", + "-1,0,0,\"http://state=19945206/foto-4/login-2006/makumirostova.ru/games=6500&url=www.svoboda.yandex.ru/p3200\",\"http://irr.ru/index.php?showalbum/login-leniya7777294,938303130\",13\n", + "0,0,0,\"\",\"http://irr.ru/index.php?showalbum/login-kapusta-advert26612&street=994090808%2F&sr=http://news/post\",13\n", + "-1,0,0,\"http://state=19945206/foto-4/login-2491724/?bundlers/search?text\",\"http://irr.ru/index.php?showalbum/login-kapusta-advert2677587.12500&matcheskiy-r_n/tiid=0&last_auto\",13\n", + "-1,0,0,\"http://state=19945206/foto-4/login-2006/makumirostova.rambler.ru/real-estate/apartner.ferio\",\"http://irr.ru/index.php?showalbum/login-leniya7777294,938303130\",13\n", + "-1,0,0,\"http://state=19945206/foto-4/login-2491724/?bundlers/search?text\",\"http://irr.ru/index.php?showalbum/login-kapusta-advert2622360.04506.2013&where=all&film/5014-18912\",13\n", + "0,0,0,\"\",\"http://irr.ru/index.php?showalbum/login-sumki/Odessa.ru/user_id=6640&wi=1280&lo=http://chek-9756595,59.938532343965\",13\n", + "-1,0,0,\"http://state=19945206/foto-4/login-2006/makumirostova.ru/adv?id=299953&lr=39&text=пневмоскве\",\"http://irr.ru/index.php?showalbum/login\",13\n", + "0,0,0,\"\",\"http://irr.ru/index.php?showalbum/login-kapusta-advert2715390-4-ploschad-advert2229/5/1000073&op\",13\n", "\n", "Q40: SELECT URLHash, EventDate, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 AND TraficSourceID IN (-1, 6) AND RefererHash = 3594120000172545465 GROUP BY URLHash, EventDate ORDER BY PageViews DESC LIMIT 10 OFFSET 100;\n", - "DuckDB time: 0.050743818283081055\n", + "DuckDB time: 0.05773639678955078\n", "DuckDB return:\n", " URLHash EventDate PageViews\n", - "0 8436286387721556030 2013-07-15 23\n", - "1 7516345568886640333 2013-07-15 23\n", + "0 7516345568886640333 2013-07-15 23\n", + "1 -8435826299601811261 2013-07-15 23\n", "2 -1285046671250476833 2013-07-15 23\n", - "3 2680587802399303961 2013-07-15 22\n", - "4 1387759335351574242 2013-07-15 22\n", - "5 7719727592795372103 2013-07-15 22\n", - "6 -3950137591013798111 2013-07-15 22\n", - "7 -3172049944036544851 2013-07-15 22\n", - "8 3756346524397046411 2013-07-15 22\n", - "9 -1358766587709438153 2013-07-15 21\n", - "chDB time: 0.11131978034973145\n", + "3 7719727592795372103 2013-07-15 22\n", + "4 2680587802399303961 2013-07-15 22\n", + "5 1387759335351574242 2013-07-15 22\n", + "6 3756346524397046411 2013-07-15 22\n", + "7 -3950137591013798111 2013-07-15 22\n", + "8 -3172049944036544851 2013-07-15 22\n", + "9 3936351847986462322 2013-07-15 21\n", + "chDB time: 0.1974191665649414\n", "chDB return:\n", - " -1285046671250476833,\"2013-07-15 08:00:00.000000000\",23\n", - "8436286387721556030,\"2013-07-15 08:00:00.000000000\",23\n", + " 8436286387721556030,\"2013-07-15 08:00:00.000000000\",23\n", "7516345568886640333,\"2013-07-15 08:00:00.000000000\",23\n", - "-3172049944036544851,\"2013-07-15 08:00:00.000000000\",22\n", + "-1285046671250476833,\"2013-07-15 08:00:00.000000000\",23\n", + "7719727592795372103,\"2013-07-15 08:00:00.000000000\",22\n", "2680587802399303961,\"2013-07-15 08:00:00.000000000\",22\n", "1387759335351574242,\"2013-07-15 08:00:00.000000000\",22\n", - "7719727592795372103,\"2013-07-15 08:00:00.000000000\",22\n", - "-3950137591013798111,\"2013-07-15 08:00:00.000000000\",22\n", + "-3172049944036544851,\"2013-07-15 08:00:00.000000000\",22\n", "3756346524397046411,\"2013-07-15 08:00:00.000000000\",22\n", - "-6314751298222231545,\"2013-07-15 08:00:00.000000000\",21\n", + "-3950137591013798111,\"2013-07-15 08:00:00.000000000\",22\n", + "5594816550667140150,\"2013-07-15 08:00:00.000000000\",21\n", "\n", "Q41: SELECT WindowClientWidth, WindowClientHeight, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 AND DontCountHits = 0 AND URLHash = 2868770270353813622 GROUP BY WindowClientWidth, WindowClientHeight ORDER BY PageViews DESC LIMIT 10 OFFSET 10000;\n", - "DuckDB time: 0.05397772789001465\n", + "DuckDB time: 0.07263517379760742\n", "DuckDB return:\n", " Empty DataFrame\n", "Columns: [WindowClientWidth, WindowClientHeight, PageViews]\n", "Index: []\n", - "chDB time: 0.10601115226745605\n", + "chDB time: 0.0824728012084961\n", "chDB return:\n", " \n", "Q42: SELECT DATE_TRUNC('minute', EventTime) AS M, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-14' AND EventDate <= '2013-07-15' AND IsRefresh = 0 AND DontCountHits = 0 GROUP BY DATE_TRUNC('minute', EventTime) ORDER BY DATE_TRUNC('minute', EventTime) LIMIT 10 OFFSET 1000;\n", - "DuckDB time: 0.04773902893066406\n", + "DuckDB time: 0.05879640579223633\n", "DuckDB return:\n", " M PageViews\n", "0 2013-07-15 12:40:00 434\n", @@ -1366,14 +1476,14 @@ "7 2013-07-15 12:47:00 381\n", "8 2013-07-15 12:48:00 385\n", "9 2013-07-15 12:49:00 415\n", - "chDB time: 0.07855939865112305\n", + "chDB time: 0.05933666229248047\n", "chDB return:\n", " \n" ] }, { "data": { - "image/png": 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" ] @@ -1385,10 +1495,10 @@ "name": "stdout", "output_type": "stream", "text": [ - "DuckDB better count: 18\n", - "chDB better count: 25\n", - "DuckDB total time: 88.36738610267639\n", - "chDB total time: 97.63184404373169\n" + "DuckDB better count: 19\n", + "chDB better count: 24\n", + "DuckDB total time: 6.524012804031372\n", + "chDB total time: 5.804013729095459\n" ] } ], From 41021c48bb6e9178b551d9f8dd3f685435f66396 Mon Sep 17 00:00:00 2001 From: auxten Date: Thu, 15 Aug 2024 18:18:00 +0800 Subject: [PATCH 05/16] Make genChunk private --- src/Processors/Sources/PythonSource.h | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/Processors/Sources/PythonSource.h b/src/Processors/Sources/PythonSource.h index 02be3837771..2e71f25f058 100644 --- a/src/Processors/Sources/PythonSource.h +++ b/src/Processors/Sources/PythonSource.h @@ -36,7 +36,7 @@ class PythonSource : public ISource ~PythonSource() override = default; String getName() const override { return "Python"; } - Chunk genChunk(size_t & num_rows, PyObjectVecPtr data); + Chunk generate() override; @@ -56,6 +56,8 @@ class PythonSource : public ISource Poco::Logger * logger = &Poco::Logger::get("TableFunctionPython"); ExternalResultDescription description; + Chunk genChunk(size_t & num_rows, PyObjectVecPtr data); + PyObjectVecPtr scanData(const py::object & data, const std::vector & col_names, size_t & cursor, size_t count); template ColumnPtr convert_and_insert_array(const ColumnWrapper & col_wrap, size_t & cursor, size_t count, UInt32 scale = 0); From 184af7eab99476c474bbfbcdfd9a940ace6ca312 Mon Sep 17 00:00:00 2001 From: auxten Date: Thu, 15 Aug 2024 18:18:24 +0800 Subject: [PATCH 06/16] Keep and reuse zip file --- tests/test_issue31.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/tests/test_issue31.py b/tests/test_issue31.py index 508b43335f4..07301497276 100644 --- a/tests/test_issue31.py +++ b/tests/test_issue31.py @@ -71,11 +71,13 @@ def handler(signum, frame): class TestAggOnCSVSpeed(unittest.TestCase): def setUp(self): - download_and_extract(csv_url, "organizations-500000.zip") + if not os.path.exists("organizations-500000.csv"): + download_and_extract(csv_url, "organizations-500000.zip") def tearDown(self): - os.remove("organizations-500000.csv") - os.remove("organizations-500000.zip") + # os.remove("organizations-500000.csv") + # os.remove("organizations-500000.zip") + pass def _test_agg(self, arg=None): payload() From bad83b84383b7261d2a154555cf893fe46fd345c Mon Sep 17 00:00:00 2001 From: auxten Date: Thu, 15 Aug 2024 18:18:53 +0800 Subject: [PATCH 07/16] Rollback the hack on AggregatingStep --- src/Processors/QueryPlan/AggregatingStep.cpp | 28 +++----------------- 1 file changed, 3 insertions(+), 25 deletions(-) diff --git a/src/Processors/QueryPlan/AggregatingStep.cpp b/src/Processors/QueryPlan/AggregatingStep.cpp index eba40c35e68..0d7e05af1de 100644 --- a/src/Processors/QueryPlan/AggregatingStep.cpp +++ b/src/Processors/QueryPlan/AggregatingStep.cpp @@ -23,7 +23,6 @@ #include #include #include -#include namespace DB { @@ -458,33 +457,12 @@ void AggregatingStep::transformPipeline(QueryPipelineBuilder & pipeline, const B /// If there are several sources, then we perform parallel aggregation if (pipeline.getNumStreams() > 1) { - auto stream_count = pipeline.getNumStreams(); - /// Calculate the stream count by adding up all the stream aggregate functions costs. - /// the max stream count is the number of pipeline streams. - size_t estimate_stream = 0; - size_t agg_col_cost = 0; - size_t group_by_keys_cost = 0; - for (const auto & agg : params.aggregates) - { - /// get the function count by counting "(" - agg_col_cost += static_cast(std::count(agg.column_name.begin(), agg.column_name.end(), '(')); - /// get the column count by counting "," + 1 - agg_col_cost += 1 + static_cast(std::count(agg.column_name.begin(), agg.column_name.end(), ',')); - } - for (const auto & key : params.keys) - { - group_by_keys_cost += 1 + 8 * static_cast(std::log2(key.size() + 1)); - } - estimate_stream = std::min(stream_count, std::max(4ul, 2 * (agg_col_cost + group_by_keys_cost))); - - LOG_TRACE(getLogger("AggregatingStep"), "AggregatingStep: estimate_stream = {}", estimate_stream); - /// Add resize transform to uniformly distribute data between aggregating streams. /// But not if we execute aggregation over partitioned data in which case data streams shouldn't be mixed. if (!storage_has_evenly_distributed_read && !skip_merging) - pipeline.resize(estimate_stream, true, true); + pipeline.resize(pipeline.getNumStreams(), true, true); - auto many_data = std::make_shared(estimate_stream); + auto many_data = std::make_shared(pipeline.getNumStreams()); size_t counter = 0; pipeline.addSimpleTransform( @@ -501,7 +479,7 @@ void AggregatingStep::transformPipeline(QueryPipelineBuilder & pipeline, const B skip_merging); }); - pipeline.resize(should_produce_results_in_order_of_bucket_number ? 1 : estimate_stream, true /* force */); + pipeline.resize(should_produce_results_in_order_of_bucket_number ? 1 : params.max_threads, true /* force */); aggregating = collector.detachProcessors(0); } From 563ab987a2a41bfb43e98b483013b2c480ee0fb5 Mon Sep 17 00:00:00 2001 From: auxten Date: Thu, 15 Aug 2024 18:19:16 +0800 Subject: [PATCH 08/16] Fix SQL and support run all --- benchmark/clickbench.py | 86 +++++++++++++++++++++++++++++++++-------- 1 file changed, 69 insertions(+), 17 deletions(-) diff --git a/benchmark/clickbench.py b/benchmark/clickbench.py index 7eaa8065875..cb09bd8201a 100644 --- a/benchmark/clickbench.py +++ b/benchmark/clickbench.py @@ -29,7 +29,7 @@ """SELECT UserID, COUNT(*) FROM hits GROUP BY UserID ORDER BY COUNT(*) DESC LIMIT 10;""", """SELECT UserID, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, SearchPhrase ORDER BY COUNT(*) DESC LIMIT 10;""", """SELECT UserID, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, SearchPhrase LIMIT 10;""", - """SELECT UserID, extract(minute FROM EventTime) AS m, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, m, SearchPhrase ORDER BY COUNT(*) DESC LIMIT 10;""", + """SELECT UserID, extract(minute FROM toDateTime(EventTime)) AS m, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, m, SearchPhrase ORDER BY COUNT(*) DESC LIMIT 10;""", """SELECT UserID FROM hits WHERE UserID = 435090932899640449;""", """SELECT COUNT(*) FROM hits WHERE URL LIKE '%google%';""", """SELECT SearchPhrase, MIN(URL), COUNT(*) AS c FROM hits WHERE URL LIKE '%google%' AND SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;""", @@ -47,13 +47,13 @@ """SELECT URL, COUNT(*) AS c FROM hits GROUP BY URL ORDER BY c DESC LIMIT 10;""", """SELECT 1, URL, COUNT(*) AS c FROM hits GROUP BY 1, URL ORDER BY c DESC LIMIT 10;""", """SELECT ClientIP, ClientIP - 1, ClientIP - 2, ClientIP - 3, COUNT(*) AS c FROM hits GROUP BY ClientIP, ClientIP - 1, ClientIP - 2, ClientIP - 3 ORDER BY c DESC LIMIT 10;""", - """SELECT URL, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND DontCountHits = 0 AND IsRefresh = 0 AND URL <> '' GROUP BY URL ORDER BY PageViews DESC LIMIT 10;""", - """SELECT Title, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND DontCountHits = 0 AND IsRefresh = 0 AND Title <> '' GROUP BY Title ORDER BY PageViews DESC LIMIT 10;""", - """SELECT URL, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 AND IsLink <> 0 AND IsDownload = 0 GROUP BY URL ORDER BY PageViews DESC LIMIT 10 OFFSET 1000;""", - """SELECT TraficSourceID, SearchEngineID, AdvEngineID, CASE WHEN (SearchEngineID = 0 AND AdvEngineID = 0) THEN Referer ELSE '' END AS Src, URL AS Dst, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 GROUP BY TraficSourceID, SearchEngineID, AdvEngineID, Src, Dst ORDER BY PageViews DESC LIMIT 10 OFFSET 1000;""", - """SELECT URLHash, EventDate, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 AND TraficSourceID IN (-1, 6) AND RefererHash = 3594120000172545465 GROUP BY URLHash, EventDate ORDER BY PageViews DESC LIMIT 10 OFFSET 100;""", - """SELECT WindowClientWidth, WindowClientHeight, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 AND DontCountHits = 0 AND URLHash = 2868770270353813622 GROUP BY WindowClientWidth, WindowClientHeight ORDER BY PageViews DESC LIMIT 10 OFFSET 10000;""", - """SELECT DATE_TRUNC('minute', EventTime) AS M, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-14' AND EventDate <= '2013-07-15' AND IsRefresh = 0 AND DontCountHits = 0 GROUP BY DATE_TRUNC('minute', EventTime) ORDER BY DATE_TRUNC('minute', EventTime) LIMIT 10 OFFSET 1000;""", + """SELECT URL, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND toDate(EventDate) >= '2013-07-01' AND toDate(EventDate) <= '2013-07-31' AND DontCountHits = 0 AND IsRefresh = 0 AND URL <> '' GROUP BY URL ORDER BY PageViews DESC LIMIT 10;""", + """SELECT Title, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND toDate(EventDate) >= '2013-07-01' AND toDate(EventDate) <= '2013-07-31' AND DontCountHits = 0 AND IsRefresh = 0 AND Title <> '' GROUP BY Title ORDER BY PageViews DESC LIMIT 10;""", + """SELECT URL, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND toDate(EventDate) >= '2013-07-01' AND toDate(EventDate) <= '2013-07-31' AND IsRefresh = 0 AND IsLink <> 0 AND IsDownload = 0 GROUP BY URL ORDER BY PageViews DESC LIMIT 10 OFFSET 1000;""", + """SELECT TraficSourceID, SearchEngineID, AdvEngineID, CASE WHEN (SearchEngineID = 0 AND AdvEngineID = 0) THEN Referer ELSE '' END AS Src, URL AS Dst, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND toDate(EventDate) >= '2013-07-01' AND toDate(EventDate) <= '2013-07-31' AND IsRefresh = 0 GROUP BY TraficSourceID, SearchEngineID, AdvEngineID, Src, Dst ORDER BY PageViews DESC LIMIT 10 OFFSET 1000;""", + """SELECT URLHash, EventDate, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND toDate(EventDate) >= '2013-07-01' AND toDate(EventDate) <= '2013-07-31' AND IsRefresh = 0 AND TraficSourceID IN (-1, 6) AND RefererHash = 3594120000172545465 GROUP BY URLHash, EventDate ORDER BY PageViews DESC LIMIT 10 OFFSET 100;""", + """SELECT WindowClientWidth, WindowClientHeight, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND toDate(EventDate) >= '2013-07-01' AND toDate(EventDate) <= '2013-07-31' AND IsRefresh = 0 AND DontCountHits = 0 AND URLHash = 2868770270353813622 GROUP BY WindowClientWidth, WindowClientHeight ORDER BY PageViews DESC LIMIT 10 OFFSET 10000;""", + """SELECT DATE_TRUNC('minute', toDateTime(EventTime)) AS M, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND toDate(EventDate) >= '2013-07-14' AND toDate(EventDate) <= '2013-07-15' AND IsRefresh = 0 AND DontCountHits = 0 GROUP BY DATE_TRUNC('minute', toDateTime(EventTime)) ORDER BY DATE_TRUNC('minute', toDateTime(EventTime)) LIMIT 10 OFFSET 1000;""", ] @@ -61,7 +61,7 @@ def chdb_query(i, output, times=1): sql = queries[i] sql = sql.replace( "FROM hits", - f"FROM file('{data_path}', 'parquet')", + f"FROM file('{data_path}', Parquet)", ) return execute_query(i, output, times, sql) @@ -107,13 +107,13 @@ def chdb_query_pandas(i, output, times=1): return execute_query(i, output, times, sql) -def exec_ch_local(i, log_level="test", output="Null"): +def exec_ch_local(i, log_level="test", output="Null", times=1): f""" execute clickhouse local binary like /auxten/chdb/tests/ch24.5/usr/bin/clickhouse -q "SELECT COUNT(*) FROM file("{data_path}") WHERE URL LIKE '%google%'" --log-level=trace """ sql = queries[i] - sql = sql.replace("FROM hits", f"FROM file('{data_path}', 'parquet')") + sql = sql.replace("FROM hits", f"FROM file('{data_path}', Parquet)") import subprocess cmd = [ @@ -125,18 +125,28 @@ def exec_ch_local(i, log_level="test", output="Null"): "--output-format=" + output, ] print(" ".join(cmd)) - subprocess.run(cmd) + time_list = [] + for t in range(times): + start = timeit.default_timer() + subprocess.run(cmd) + end = timeit.default_timer() + time_list.append(round(end - start, 2)) + print(f"Times: {t}") + print("ExecTime: ", time_list) + return time_list chdb_time_list = None chdb_elapsed_list = None chdb_pandas_time_list = None chdb_pandas_elapsed_list = None +exec_time_list = None if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument("query", type=int, help="query index") parser.add_argument("output", type=str, help="output format") + parser.add_argument("--all", action="store_true", help="run all queries") parser.add_argument("--times", type=int, default=1, help="run times for each query") parser.add_argument("--chdb", action="store_true", help="use chdb to run query") parser.add_argument("--pandas", action="store_true", help="use pandas to run query") @@ -147,6 +157,47 @@ def exec_ch_local(i, log_level="test", output="Null"): "--log_level", type=str, default="test", help="log level for local" ) args = parser.parse_args() + if args.output == "Null": + args.log_level = "error" + if args.all: + all_time_list = [] + for i in range(len(queries)): + args.output = "Null" + args.log_level = "error" + args.query = i + tmp = [] + if args.chdb: + chdb_time_list, chdb_elapsed_list = chdb_query( + args.query, args.output, args.times + ) + tmp.append(chdb_time_list) + tmp.append(chdb_elapsed_list) + if args.pandas: + chdb_pandas_time_list, chdb_pandas_elapsed_list = chdb_query_pandas( + args.query, args.output, args.times + ) + tmp.append(chdb_pandas_time_list) + tmp.append(chdb_pandas_elapsed_list) + if args.local: + exec_time_list = exec_ch_local( + args.query, args.log_level, args.output, args.times + ) + tmp.append(exec_time_list) + all_time_list.append(tmp) + # convert to pandas with columns like chdb_time_list, chdb_elapsed_list + df = pd.DataFrame(all_time_list) + columns = [] + if args.chdb: + columns += ["chdb_time", "chdb_elapsed"] + if args.pandas: + columns += ["chdb_pd_time", "chdb_pd_elapsed"] + if args.local: + columns += ["ch_local_time"] + df.columns = columns + print("All queries:") + print(df) + sys.exit(0) + if args.chdb: chdb_time_list, chdb_elapsed_list = chdb_query( args.query, args.output, args.times @@ -156,12 +207,13 @@ def exec_ch_local(i, log_level="test", output="Null"): args.query, args.output, args.times ) if args.local: - exec_ch_local(args.query, args.log_level, args.output) + exec_time_list = exec_ch_local( + args.query, args.log_level, args.output, args.times + ) # print summary print(f"Q{args.query}: {queries[args.query]}") print("Summary:") - print("chdb_time_list: ", chdb_time_list) - print("chdb_elapsed_list: ", chdb_elapsed_list) - print("chdb_pd_time_list: ", chdb_pandas_time_list) - print("chdb_pd_elapsed_list: ", chdb_pandas_elapsed_list) + print(f"chdb_time_list: {chdb_time_list}, elapsed: {chdb_elapsed_list}") + print(f"chdb_pd_time_list: {chdb_pandas_time_list}, elapsed: {chdb_pandas_elapsed_list}") + print(f"local_time_list: {exec_time_list}") From 647efe4803f1a3769c7ceb37e409cdc2b1c9c7a6 Mon Sep 17 00:00:00 2001 From: auxten Date: Thu, 15 Aug 2024 19:13:35 +0800 Subject: [PATCH 09/16] Fix pylint --- chdb/__init__.py | 2 +- chdb/utils/__init__.py | 9 +++++++-- chdb/utils/types.py | 1 - 3 files changed, 8 insertions(+), 4 deletions(-) diff --git a/chdb/__init__.py b/chdb/__init__.py index c365b3e6432..847de9476f2 100644 --- a/chdb/__init__.py +++ b/chdb/__init__.py @@ -84,7 +84,7 @@ def query(sql, output_format="CSV", path="", udf_path=""): PyReader = _chdb.PyReader -from . import dataframe, dbapi, session, udf, utils +from . import dataframe, dbapi, session, udf, utils # noqa: E402 __all__ = [ "PyReader", diff --git a/chdb/utils/__init__.py b/chdb/utils/__init__.py index a31950f6a7d..01b60008744 100644 --- a/chdb/utils/__init__.py +++ b/chdb/utils/__init__.py @@ -1,3 +1,8 @@ -from .types import * +from .types import * # noqa: F403 -__all__ = ["flatten_dict", "convert_to_columnar", "infer_data_type", "infer_data_types"] +__all__ = [ + "flatten_dict", + "convert_to_columnar", + "infer_data_type", + "infer_data_types", +] # noqa: F405 diff --git a/chdb/utils/types.py b/chdb/utils/types.py index 72c54c60d47..1a4c95744e6 100644 --- a/chdb/utils/types.py +++ b/chdb/utils/types.py @@ -201,7 +201,6 @@ def infer_data_type(values: List[Any]) -> str: min_val = min(min_val, num) except (ValueError, TypeError): is_int = False - is_uint = False try: num = decimal.Decimal(val) max_val = max(max_val, float(num)) From b8ed31e9790f07011c37f4086aac88ddccc260dd Mon Sep 17 00:00:00 2001 From: auxten Date: Thu, 15 Aug 2024 22:14:54 +0800 Subject: [PATCH 10/16] Fix flake8 --- chdb/utils/__init__.py | 4 ++-- chdb/utils/types.py | 1 - 2 files changed, 2 insertions(+), 3 deletions(-) diff --git a/chdb/utils/__init__.py b/chdb/utils/__init__.py index 01b60008744..b0905b0008e 100644 --- a/chdb/utils/__init__.py +++ b/chdb/utils/__init__.py @@ -1,8 +1,8 @@ from .types import * # noqa: F403 -__all__ = [ +__all__ = [ # noqa: F405 "flatten_dict", "convert_to_columnar", "infer_data_type", "infer_data_types", -] # noqa: F405 +] diff --git a/chdb/utils/types.py b/chdb/utils/types.py index 1a4c95744e6..2d2144d595c 100644 --- a/chdb/utils/types.py +++ b/chdb/utils/types.py @@ -182,7 +182,6 @@ def infer_data_type(values: List[Any]) -> str: max_val = float("-inf") min_val = float("inf") is_int = True - is_uint = True is_decimal = True is_float = True From 0fb959a7d846f8f1a2bef1f031fef619754c8d87 Mon Sep 17 00:00:00 2001 From: auxten Date: Mon, 19 Aug 2024 16:12:44 +0800 Subject: [PATCH 11/16] Add benchmark of chDB, Pandas, DuckDB, Polars --- benchmark/dataframe.ipynb | 3115 +++++++++++++++++++++++++++++++++++++ 1 file changed, 3115 insertions(+) create mode 100644 benchmark/dataframe.ipynb diff --git a/benchmark/dataframe.ipynb b/benchmark/dataframe.ipynb new file mode 100644 index 00000000000..e7dcd1eeffe --- /dev/null +++ b/benchmark/dataframe.ipynb @@ -0,0 +1,3115 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: duckdb in /usr/local/lib/python3.9/dist-packages (1.0.0)\n", + "Collecting duckdb\n", + " Using cached duckdb-1.0.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.5 MB)\n", + " Using cached duckdb-0.10.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.5 MB)\n", + "Requirement already satisfied: pandas in /usr/local/lib/python3.9/dist-packages (2.2.2)\n", + "Collecting pandas\n", + " Using cached pandas-2.2.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.1 MB)\n", + " Using cached pandas-2.2.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.0 MB)\n", + "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.9/dist-packages (from pandas) (2022.7)\n", + "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.9/dist-packages (from pandas) (2.8.2)\n", + "Requirement already satisfied: numpy>=1.22.4 in /usr/local/lib/python3.9/dist-packages (from pandas) (1.24.2)\n", + "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.9/dist-packages (from pandas) (2023.3)\n", + "Requirement already satisfied: six>=1.5 in /usr/lib/python3/dist-packages (from python-dateutil>=2.8.2->pandas) (1.16.0)\n", + "Requirement already satisfied: polars in /usr/local/lib/python3.9/dist-packages (1.5.0)\n", + "Collecting polars\n", + " Using cached polars-1.5.0-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (31.6 MB)\n", + " Using cached polars-1.4.1-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (31.5 MB)\n", + "Requirement already satisfied: chdb>=2.0.0b1 in /usr/local/lib/python3.9/dist-packages (2.0.0b1)\n", + "Collecting chdb>=2.0.0b1\n", + " Using cached chdb-2.0.0b1-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (134.8 MB)\n", + "Name: chdb\n", + "Version: 2.0.0b1\n", + "Summary: chDB is an in-process SQL OLAP Engine powered by ClickHouse\n", + "Home-page: https://github.com/chdb-io/chdb\n", + "Author: auxten\n", + "Author-email: auxten@clickhouse.com\n", + "License: Apache-2.0\n", + "Location: /usr/local/lib/python3.9/dist-packages\n", + "Requires: \n", + "Required-by: \n" + ] + } + ], + "source": [ + "!pip install -U duckdb\n", + "!pip install -U pandas\n", + "!pip install -U polars\n", + "!pip install -U 'chdb>=2.0.0b1'\n", + "!pip show chdb" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# prepare data\n", + "import os\n", + "import chdb\n", + "\n", + "if not os.path.exists(\"/tmp/hits.parquet\"):\n", + " !wget \"https://datasets.clickhouse.com/hits_compatible/athena/hits.parquet\" -O /tmp/hits.parquet\n", + "\n", + "# # 1/100 of the data, for testing\n", + "if not os.path.exists(\"/tmp/hits_0.parquet\"):\n", + " !wget \"https://datasets.clickhouse.com/hits_compatible/athena_partitioned/hits_0.parquet\" -O /tmp/hits_0.parquet\n", + "\n", + "# # 10m rows of ClickBench data\n", + "if not os.path.exists(\"/tmp/hits10m.parquet\"):\n", + " chdb.query(\"SELECT * FROM `/tmp/hits.parquet` LIMIT 10000000 INTO OUTFILE '/tmp/hits10m.parquet'\").show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-rw-r--r-- 1 root root 880M Aug 19 11:34 /tmp/hits10m.parquet\n", + "-rw-r--r-- 1 root root 117M Jul 3 2022 /tmp/hits_0.parquet\n", + "Read parquet file into memory. Time cost: 0.465517520904541 s\n", + "Parquet file size: 922699018 bytes\n", + "Read parquet file as old pandas dataframe. Time cost: 10.397734880447388 s\n", + "Dataframe(numpy) size: 4700000128 bytes\n" + ] + } + ], + "source": [ + "#!python3\n", + "\n", + "import os\n", + "import time\n", + "import datetime\n", + "import chdb\n", + "import chdb.dataframe as cdf\n", + "import chdb.session as chs\n", + "import pandas as pd\n", + "import duckdb\n", + "# import numpy as np\n", + "# import pyarrow as pa\n", + "# import pyarrow.parquet as pq\n", + "\n", + "\n", + "\n", + "!ls -lh /tmp/hits10m.parquet\n", + "!ls -lh /tmp/hits_0.parquet\n", + "\n", + "hits_data = \"/tmp/hits10m.parquet\"\n", + "# hits_data = \"/tmp/hits_0.parquet\"\n", + "\n", + "t = time.time()\n", + "# read parquet file into memory\n", + "with open(hits_data, \"rb\") as f:\n", + " data = f.read()\n", + "print(\"Read parquet file into memory. Time cost:\", time.time() - t, \"s\")\n", + "print(\"Parquet file size:\", len(data), \"bytes\")\n", + "del data\n", + "\n", + "# read parquet file as old pandas dataframe\n", + "t = time.time()\n", + "hits = pd.read_parquet(hits_data)\n", + "print(\"Read parquet file as old pandas dataframe. Time cost:\", time.time() - t, \"s\")\n", + "print(\"Dataframe(numpy) size:\", hits.memory_usage().sum(), \"bytes\")" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "WatchID int64\n", + "JavaEnable int16\n", + "Title object\n", + "GoodEvent int16\n", + "EventTime datetime64[ns]\n", + " ... \n", + "FromTag object\n", + "HasGCLID int16\n", + "RefererHash int64\n", + "URLHash int64\n", + "CLID int32\n", + "Length: 105, dtype: object" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# fix some types\n", + "# print(hits[\"EventTime\"][0:10])\n", + "hits[\"EventTime\"] = pd.to_datetime(hits[\"EventTime\"], unit=\"s\")\n", + "# print(hits[\"EventTime\"][0:10])\n", + "\n", + "hits[\"EventDate\"] = pd.to_datetime(hits[\"EventDate\"], unit=\"D\")\n", + "# print(hits[\"EventDate\"][0:10])\n", + "\n", + "# fix all object columns to string\n", + "for col in hits.columns:\n", + " if hits[col].dtype == \"O\":\n", + " # hits[col] = hits[col].astype('string')\n", + " hits[col] = hits[col].astype(str)\n", + "\n", + "title = hits[\"Title\"]\n", + "\n", + "hits.dtypes" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Convert dataframe to polars dataframe. Time cost: 22.901316165924072 s\n" + ] + } + ], + "source": [ + "# convert dataframe to numpy array\n", + "import polars as pl\n", + "\n", + "t = time.time()\n", + "pl_df = pl.DataFrame(hits)\n", + "print(\"Convert dataframe to polars dataframe. Time cost:\", time.time() - t, \"s\")" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "class myReader(chdb.PyReader):\n", + " def __init__(self, data):\n", + " self.data = data\n", + " self.cursor = 0\n", + " super().__init__(data)\n", + "\n", + " def read(self, col_names, count):\n", + " # print(\"read\", col_names, count)\n", + " # get the columns from the data with col_names\n", + " block = [self.data[col] for col in col_names]\n", + " # print(\"columns and rows\", len(block), len(block[0]))\n", + " # get the data from the cursor to cursor + count\n", + " block = [col[self.cursor : self.cursor + count] for col in block]\n", + " # print(\"columns and rows\", len(block), len(block[0]))\n", + " # move the cursor\n", + " self.cursor += block[0].shape[0]\n", + " return block" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "queries = [\n", + " (\"Q0\", \"SELECT COUNT(*) FROM hits;\", lambda x: x.count(), lambda x: x.height),\n", + " (\n", + " \"Q1\",\n", + " \"SELECT COUNT(*) FROM hits WHERE AdvEngineID <> 0;\",\n", + " lambda x: x[x[\"AdvEngineID\"] != 0].count(),\n", + " lambda x: x.filter(pl.col(\"AdvEngineID\") != 0).height,\n", + " ),\n", + " (\n", + " \"Q2\",\n", + " \"SELECT SUM(AdvEngineID), COUNT(*), AVG(ResolutionWidth) FROM hits;\",\n", + " lambda x: (x[\"AdvEngineID\"].sum(), x.shape[0], x[\"ResolutionWidth\"].mean()),\n", + " lambda x: (x[\"AdvEngineID\"].sum(), x.height, x[\"ResolutionWidth\"].mean()),\n", + " ),\n", + " (\n", + " \"Q3\",\n", + " \"SELECT AVG(UserID) FROM hits;\",\n", + " lambda x: x[\"UserID\"].mean(),\n", + " lambda x: x[\"UserID\"].mean(),\n", + " ),\n", + " (\n", + " \"Q4\",\n", + " \"SELECT COUNT(DISTINCT UserID) FROM hits;\",\n", + " lambda x: x[\"UserID\"].nunique(),\n", + " lambda x: x[\"UserID\"].n_unique(),\n", + " ),\n", + " (\n", + " \"Q5\",\n", + " \"SELECT COUNT(DISTINCT SearchPhrase) FROM hits;\",\n", + " lambda x: x[\"SearchPhrase\"].nunique(),\n", + " lambda x: x[\"SearchPhrase\"].n_unique(),\n", + " ),\n", + " (\n", + " \"Q6\",\n", + " \"SELECT MIN(EventDate), MAX(EventDate) FROM hits;\",\n", + " lambda x: (x[\"EventDate\"].min(), x[\"EventDate\"].max()),\n", + " lambda x: (x[\"EventDate\"].min(), x[\"EventDate\"].max()),\n", + " ),\n", + " (\n", + " \"Q7\",\n", + " \"SELECT AdvEngineID, COUNT(*) FROM hits WHERE AdvEngineID <> 0 GROUP BY AdvEngineID ORDER BY COUNT(*) DESC;\",\n", + " lambda x: x[x[\"AdvEngineID\"] != 0]\n", + " .groupby(\"AdvEngineID\")\n", + " .size()\n", + " .sort_values(ascending=False),\n", + " lambda x: x.filter(pl.col(\"AdvEngineID\") != 0)\n", + " .group_by(\"AdvEngineID\")\n", + " .agg(pl.len().alias(\"count\"))\n", + " .sort(\"count\", descending=True),\n", + " ),\n", + " (\n", + " \"Q8\",\n", + " \"SELECT RegionID, COUNT(DISTINCT UserID) AS u FROM hits GROUP BY RegionID ORDER BY u DESC LIMIT 10;\",\n", + " lambda x: x.groupby(\"RegionID\")[\"UserID\"].nunique().nlargest(10),\n", + " lambda x: x.group_by(\"RegionID\")\n", + " .agg(pl.col(\"UserID\").n_unique())\n", + " .sort(\"UserID\", descending=True)\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q9\",\n", + " \"SELECT RegionID, SUM(AdvEngineID), COUNT(*) AS c, AVG(ResolutionWidth), COUNT(DISTINCT UserID) FROM hits GROUP BY RegionID ORDER BY c DESC LIMIT 10;\",\n", + " lambda x: x.groupby(\"RegionID\")\n", + " .agg({\"AdvEngineID\": \"sum\", \"ResolutionWidth\": \"mean\", \"UserID\": \"nunique\"})\n", + " .nlargest(10, \"AdvEngineID\"),\n", + " lambda x: x.group_by(\"RegionID\")\n", + " .agg(\n", + " [\n", + " pl.sum(\"AdvEngineID\").alias(\"AdvEngineID_sum\"),\n", + " pl.mean(\"ResolutionWidth\").alias(\"ResolutionWidth_mean\"),\n", + " pl.col(\"UserID\").n_unique().alias(\"UserID_nunique\"),\n", + " ]\n", + " )\n", + " .sort(\"AdvEngineID_sum\", descending=True)\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q10\",\n", + " \"SELECT MobilePhoneModel, COUNT(DISTINCT UserID) AS u FROM hits WHERE MobilePhoneModel <> '' GROUP BY MobilePhoneModel ORDER BY u DESC LIMIT 10;\",\n", + " lambda x: x[x[\"MobilePhoneModel\"] != \"\"]\n", + " .groupby(\"MobilePhoneModel\")[\"UserID\"]\n", + " .nunique()\n", + " .nlargest(10),\n", + " lambda x: x.filter(pl.col(\"MobilePhoneModel\") != \"\")\n", + " .group_by(\"MobilePhoneModel\")\n", + " .agg(pl.col(\"UserID\").n_unique())\n", + " .sort(\"UserID\", descending=True)\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q11\",\n", + " \"SELECT MobilePhone, MobilePhoneModel, COUNT(DISTINCT UserID) AS u FROM hits WHERE MobilePhoneModel <> '' GROUP BY MobilePhone, MobilePhoneModel ORDER BY u DESC LIMIT 10;\",\n", + " lambda x: x[x[\"MobilePhoneModel\"] != \"\"]\n", + " .groupby([\"MobilePhone\", \"MobilePhoneModel\"])[\"UserID\"]\n", + " .nunique()\n", + " .nlargest(10),\n", + " lambda x: x.filter(pl.col(\"MobilePhoneModel\") != \"\")\n", + " .group_by([\"MobilePhone\", \"MobilePhoneModel\"])\n", + " .agg(pl.col(\"UserID\").n_unique())\n", + " .sort(\"UserID\", descending=True)\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q12\",\n", + " \"SELECT SearchPhrase, COUNT(*) AS c FROM hits WHERE SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;\",\n", + " lambda x: x[x[\"SearchPhrase\"] != \"\"]\n", + " .groupby(\"SearchPhrase\")\n", + " .size()\n", + " .nlargest(10),\n", + " lambda x: x.filter(pl.col(\"SearchPhrase\") != \"\")\n", + " .group_by(\"SearchPhrase\")\n", + " .agg(pl.len().alias(\"count\"))\n", + " .sort(\"count\", descending=True)\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q13\",\n", + " \"SELECT SearchPhrase, COUNT(DISTINCT UserID) AS u FROM hits WHERE SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY u DESC LIMIT 10;\",\n", + " lambda x: x[x[\"SearchPhrase\"] != \"\"]\n", + " .groupby(\"SearchPhrase\")[\"UserID\"]\n", + " .nunique()\n", + " .nlargest(10),\n", + " lambda x: x.filter(pl.col(\"SearchPhrase\") != \"\")\n", + " .group_by(\"SearchPhrase\")\n", + " .agg(pl.col(\"UserID\").n_unique())\n", + " .sort(\"UserID\", descending=True)\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q14\",\n", + " \"SELECT SearchEngineID, SearchPhrase, COUNT(*) AS c FROM hits WHERE SearchPhrase <> '' GROUP BY SearchEngineID, SearchPhrase ORDER BY c DESC LIMIT 10;\",\n", + " lambda x: x[x[\"SearchPhrase\"] != \"\"]\n", + " .groupby([\"SearchEngineID\", \"SearchPhrase\"])\n", + " .size()\n", + " .nlargest(10),\n", + " lambda x: x.filter(pl.col(\"SearchPhrase\") != \"\")\n", + " .group_by([\"SearchEngineID\", \"SearchPhrase\"])\n", + " .agg(pl.len().alias(\"count\"))\n", + " .sort(\"count\", descending=True)\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q15\",\n", + " \"SELECT UserID, COUNT(*) FROM hits GROUP BY UserID ORDER BY COUNT(*) DESC LIMIT 10;\",\n", + " lambda x: x.groupby(\"UserID\").size().nlargest(10),\n", + " lambda x: x.group_by(\"UserID\")\n", + " .agg(pl.len().alias(\"count\"))\n", + " .sort(\"count\", descending=True)\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q16\",\n", + " \"SELECT UserID, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, SearchPhrase ORDER BY COUNT(*) DESC LIMIT 10;\",\n", + " lambda x: x.groupby([\"UserID\", \"SearchPhrase\"]).size().nlargest(10),\n", + " lambda x: x.group_by([\"UserID\", \"SearchPhrase\"])\n", + " .agg(pl.len().alias(\"count\"))\n", + " .sort(\"count\", descending=True)\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q17\",\n", + " \"SELECT UserID, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, SearchPhrase LIMIT 10;\",\n", + " lambda x: x.groupby([\"UserID\", \"SearchPhrase\"]).size().head(10),\n", + " lambda x: x.group_by([\"UserID\", \"SearchPhrase\"]).agg(pl.len()).head(10),\n", + " ),\n", + " (\n", + " \"Q18\",\n", + " \"SELECT UserID, extract(minute FROM EventTime) AS m, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, m, SearchPhrase ORDER BY COUNT(*) DESC LIMIT 10;\",\n", + " lambda x: x.groupby([x[\"UserID\"], x[\"EventTime\"].dt.minute, \"SearchPhrase\"])\n", + " .size()\n", + " .nlargest(10),\n", + " lambda x: x.group_by(\n", + " [pl.col(\"UserID\"), x[\"EventTime\"].dt.minute(), \"SearchPhrase\"]\n", + " )\n", + " .agg(pl.len().alias(\"count\"))\n", + " .sort(\"count\", descending=True)\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q19\",\n", + " \"SELECT UserID FROM hits WHERE UserID = 435090932899640449;\",\n", + " lambda x: x[x[\"UserID\"] == 435090932899640449],\n", + " lambda x: x.filter(pl.col(\"UserID\") == 435090932899640449),\n", + " ),\n", + " (\n", + " \"Q20\",\n", + " \"SELECT COUNT(*) FROM hits WHERE URL LIKE '%google%';\",\n", + " lambda x: x[x[\"URL\"].str.contains(\"google\")].shape[0],\n", + " lambda x: x.filter(pl.col(\"URL\").str.contains(\"google\")).height,\n", + " ),\n", + " (\n", + " \"Q21\",\n", + " \"SELECT SearchPhrase, MIN(URL), COUNT(*) AS c FROM hits WHERE URL LIKE '%google%' AND SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;\",\n", + " lambda x: x[(x[\"URL\"].str.contains(\"google\")) & (x[\"SearchPhrase\"] != \"\")]\n", + " .groupby(\"SearchPhrase\")\n", + " .agg({\"URL\": \"min\", \"SearchPhrase\": \"size\"})\n", + " .nlargest(10, \"SearchPhrase\"),\n", + " lambda x: x.filter(\n", + " (pl.col(\"URL\").str.contains(\"google\")) & (pl.col(\"SearchPhrase\") != \"\")\n", + " )\n", + " .group_by(\"SearchPhrase\")\n", + " .agg([pl.col(\"URL\").min(), pl.len()])\n", + " .sort(\"count\", descending=True)\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q22\",\n", + " \"SELECT SearchPhrase, MIN(URL), MIN(Title), COUNT(*) AS c, COUNT(DISTINCT UserID) FROM hits WHERE Title LIKE '%Google%' AND URL NOT LIKE '%.google.%' AND SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;\",\n", + " lambda x: x[\n", + " (x[\"Title\"].str.contains(\"Google\"))\n", + " & (~x[\"URL\"].str.contains(\".google.\"))\n", + " & (x[\"SearchPhrase\"] != \"\")\n", + " ]\n", + " .groupby(\"SearchPhrase\")\n", + " .agg(\n", + " {\"URL\": \"min\", \"Title\": \"min\", \"SearchPhrase\": \"size\", \"UserID\": \"nunique\"}\n", + " )\n", + " .nlargest(10, \"SearchPhrase\"),\n", + " lambda x: x.filter(\n", + " (pl.col(\"Title\").str.contains(\"Google\"))\n", + " & (~pl.col(\"URL\").str.contains(\".google.\"))\n", + " & (pl.col(\"SearchPhrase\") != \"\")\n", + " )\n", + " .group_by(\"SearchPhrase\")\n", + " .agg(\n", + " [\n", + " pl.col(\"URL\").min(),\n", + " pl.col(\"Title\").min(),\n", + " pl.len(),\n", + " pl.col(\"UserID\").n_unique(),\n", + " ]\n", + " )\n", + " .sort(\"count\", descending=True)\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q23\",\n", + " \"SELECT * FROM hits WHERE URL LIKE '%google%' ORDER BY EventTime LIMIT 10;\",\n", + " lambda x: x[x[\"URL\"].str.contains(\"google\")]\n", + " .sort_values(by=\"EventTime\")\n", + " .head(10),\n", + " lambda x: x.filter(pl.col(\"URL\").str.contains(\"google\"))\n", + " .sort(\"EventTime\")\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q24\",\n", + " \"SELECT SearchPhrase FROM hits WHERE SearchPhrase <> '' ORDER BY EventTime LIMIT 10;\",\n", + " lambda x: x[x[\"SearchPhrase\"] != \"\"]\n", + " .sort_values(by=\"EventTime\")[[\"SearchPhrase\"]]\n", + " .head(10),\n", + " lambda x: x.filter(pl.col(\"SearchPhrase\") != \"\")\n", + " .sort(\"EventTime\")\n", + " .select(\"SearchPhrase\")\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q25\",\n", + " \"SELECT SearchPhrase FROM hits WHERE SearchPhrase <> '' ORDER BY SearchPhrase LIMIT 10;\",\n", + " lambda x: x[x[\"SearchPhrase\"] != \"\"]\n", + " .sort_values(by=\"SearchPhrase\")[[\"SearchPhrase\"]]\n", + " .head(10),\n", + " lambda x: x.filter(pl.col(\"SearchPhrase\") != \"\")\n", + " .sort(\"SearchPhrase\")\n", + " .select(\"SearchPhrase\")\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q26\",\n", + " \"SELECT SearchPhrase FROM hits WHERE SearchPhrase <> '' ORDER BY EventTime, SearchPhrase LIMIT 10;\",\n", + " lambda x: x[x[\"SearchPhrase\"] != \"\"]\n", + " .sort_values(by=[\"EventTime\", \"SearchPhrase\"])[[\"SearchPhrase\"]]\n", + " .head(10),\n", + " lambda x: x.filter(pl.col(\"SearchPhrase\") != \"\")\n", + " .sort([\"EventTime\", \"SearchPhrase\"])\n", + " .select(\"SearchPhrase\")\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q27\",\n", + " \"SELECT CounterID, AVG(STRLEN(URL)) AS l, COUNT(*) AS c FROM hits WHERE URL <> '' GROUP BY CounterID HAVING COUNT(*) > 100000 ORDER BY l DESC LIMIT 25;\",\n", + " lambda x: x[x[\"URL\"] != \"\"]\n", + " .groupby(\"CounterID\")\n", + " .filter(lambda g: g[\"URL\"].count() > 100000)\n", + " .agg({\"URL\": lambda url: url.str.len().mean(), \"CounterID\": \"size\"})\n", + " .sort_values()\n", + " .head(25),\n", + " lambda x: x.filter(pl.col(\"URL\") != \"\") # WHERE URL <> ''\n", + " .group_by(\"CounterID\") # GROUP BY CounterID\n", + " .agg(\n", + " [\n", + " pl.col(\"URL\")\n", + " .map_elements(lambda y: len(y), return_dtype=pl.Int64)\n", + " .alias(\"l\"), # AVG(STRLEN(URL))\n", + " pl.len().alias(\"c\"), # COUNT(*)\n", + " ]\n", + " )\n", + " .filter(pl.col(\"c\") > 100000) # HAVING COUNT(*) > 100000\n", + " .sort(\"l\", descending=True) # ORDER BY l DESC\n", + " .limit(25), # LIMIT 25,\n", + " ),\n", + " (\n", + " \"Q28\",\n", + " \"SELECT REGEXP_REPLACE(Referer, '^https?://(?:www\\\\.)?([^/]+)/.*$', '\\\\1') AS k, AVG(STRLEN(Referer)) AS l, COUNT(*) AS c, MIN(Referer) FROM hits WHERE Referer <> '' GROUP BY k HAVING COUNT(*) > 100000 ORDER BY l DESC LIMIT 25;\",\n", + " lambda x: (\n", + " x[x[\"Referer\"] != \"\"]\n", + " .assign(k=x[\"Referer\"].str.extract(r\"^https?://(?:www\\.)?([^/]+)/.*$\")[0])\n", + " .groupby(\"k\")\n", + " .filter(lambda g: g[\"Referer\"].count() > 100000)\n", + " .agg(\n", + " min_referer=(\"Referer\", \"min\"),\n", + " average_length=(\"Referer\", lambda r: r.str.len().mean()),\n", + " )\n", + " .head(25)\n", + " ),\n", + " lambda x: (\n", + " x.filter(pl.col(\"Referer\") != \"\")\n", + " .with_columns(\n", + " pl.col(\"Referer\")\n", + " .str.extract(r\"^https?://(?:www\\\\.)?([^/]+)/.*$\")\n", + " .alias(\"k\")\n", + " )\n", + " .group_by(\"k\")\n", + " .agg(\n", + " [\n", + " pl.col(\"Referer\")\n", + " .map_elements(lambda y: len(y), return_dtype=pl.Int64)\n", + " # .mean() # skip mean for now\n", + " .alias(\"l\"), # AVG(STRLEN(Referer))\n", + " pl.col(\"Referer\").min().alias(\"min_referer\"), # MIN(Referer)\n", + " pl.len().alias(\"c\"), # COUNT(*)\n", + " ]\n", + " )\n", + " .filter(pl.col(\"c\") > 100000) # HAVING COUNT(*) > 100000\n", + " .sort(\"l\", descending=True) # ORDER BY l DESC\n", + " .limit(25) # LIMIT 25\n", + " ),\n", + " ),\n", + " (\n", + " \"Q29\",\n", + " \"SELECT SUM(ResolutionWidth), SUM(ResolutionWidth + 1), SUM(ResolutionWidth + 2), SUM(ResolutionWidth + 3), SUM(ResolutionWidth + 4), SUM(ResolutionWidth + 5), SUM(ResolutionWidth + 6), SUM(ResolutionWidth + 7), SUM(ResolutionWidth + 8), SUM(ResolutionWidth + 9), SUM(ResolutionWidth + 10), SUM(ResolutionWidth + 11), SUM(ResolutionWidth + 12), SUM(ResolutionWidth + 13), SUM(ResolutionWidth + 14), SUM(ResolutionWidth + 15), SUM(ResolutionWidth + 16), SUM(ResolutionWidth + 17), SUM(ResolutionWidth + 18), SUM(ResolutionWidth + 19), SUM(ResolutionWidth + 20), SUM(ResolutionWidth + 21), SUM(ResolutionWidth + 22), SUM(ResolutionWidth + 23), SUM(ResolutionWidth + 24), SUM(ResolutionWidth + 25), SUM(ResolutionWidth + 26), SUM(ResolutionWidth + 27), SUM(ResolutionWidth + 28), SUM(ResolutionWidth + 29), SUM(ResolutionWidth + 30), SUM(ResolutionWidth + 31), SUM(ResolutionWidth + 32), SUM(ResolutionWidth + 33), SUM(ResolutionWidth + 34), SUM(ResolutionWidth + 35), SUM(ResolutionWidth + 36), SUM(ResolutionWidth + 37), SUM(ResolutionWidth + 38), SUM(ResolutionWidth + 39), SUM(ResolutionWidth + 40), SUM(ResolutionWidth + 41), SUM(ResolutionWidth + 42), SUM(ResolutionWidth + 43), SUM(ResolutionWidth + 44), SUM(ResolutionWidth + 45), SUM(ResolutionWidth + 46), SUM(ResolutionWidth + 47), SUM(ResolutionWidth + 48), SUM(ResolutionWidth + 49), SUM(ResolutionWidth + 50), SUM(ResolutionWidth + 51), SUM(ResolutionWidth + 52), SUM(ResolutionWidth + 53), SUM(ResolutionWidth + 54), SUM(ResolutionWidth + 55), SUM(ResolutionWidth + 56), SUM(ResolutionWidth + 57), SUM(ResolutionWidth + 58), SUM(ResolutionWidth + 59), SUM(ResolutionWidth + 60), SUM(ResolutionWidth + 61), SUM(ResolutionWidth + 62), SUM(ResolutionWidth + 63), SUM(ResolutionWidth + 64), SUM(ResolutionWidth + 65), SUM(ResolutionWidth + 66), SUM(ResolutionWidth + 67), SUM(ResolutionWidth + 68), SUM(ResolutionWidth + 69), SUM(ResolutionWidth + 70), SUM(ResolutionWidth + 71), SUM(ResolutionWidth + 72), SUM(ResolutionWidth + 73), SUM(ResolutionWidth + 74), SUM(ResolutionWidth + 75), SUM(ResolutionWidth + 76), SUM(ResolutionWidth + 77), SUM(ResolutionWidth + 78), SUM(ResolutionWidth + 79), SUM(ResolutionWidth + 80), SUM(ResolutionWidth + 81), SUM(ResolutionWidth + 82), SUM(ResolutionWidth + 83), SUM(ResolutionWidth + 84), SUM(ResolutionWidth + 85), SUM(ResolutionWidth + 86), SUM(ResolutionWidth + 87), SUM(ResolutionWidth + 88), SUM(ResolutionWidth + 89) FROM hits;\",\n", + " lambda x: x[\"ResolutionWidth\"].sum()\n", + " + x[\"ResolutionWidth\"].shift(1).sum()\n", + " + x[\"ResolutionWidth\"].shift(2).sum()\n", + " + x[\"ResolutionWidth\"].shift(3).sum()\n", + " + x[\"ResolutionWidth\"].shift(4).sum()\n", + " + x[\"ResolutionWidth\"].shift(5).sum()\n", + " + x[\"ResolutionWidth\"].shift(6).sum()\n", + " + x[\"ResolutionWidth\"].shift(7).sum()\n", + " + x[\"ResolutionWidth\"].shift(8).sum()\n", + " + x[\"ResolutionWidth\"].shift(9).sum()\n", + " + x[\"ResolutionWidth\"].shift(10).sum()\n", + " + x[\"ResolutionWidth\"].shift(11).sum()\n", + " + x[\"ResolutionWidth\"].shift(12).sum()\n", + " + x[\"ResolutionWidth\"].shift(13).sum()\n", + " + x[\"ResolutionWidth\"].shift(14).sum()\n", + " + x[\"ResolutionWidth\"].shift(15).sum()\n", + " + x[\"ResolutionWidth\"].shift(16).sum()\n", + " + x[\"ResolutionWidth\"].shift(17).sum()\n", + " + x[\"ResolutionWidth\"].shift(18).sum()\n", + " + x[\"ResolutionWidth\"].shift(19).sum()\n", + " + x[\"ResolutionWidth\"].shift(20).sum()\n", + " + x[\"ResolutionWidth\"].shift(21).sum()\n", + " + x[\"ResolutionWidth\"].shift(22).sum()\n", + " + x[\"ResolutionWidth\"].shift(23).sum()\n", + " + x[\"ResolutionWidth\"].shift(24).sum()\n", + " + x[\"ResolutionWidth\"].shift(25).sum()\n", + " + x[\"ResolutionWidth\"].shift(26).sum()\n", + " + x[\"ResolutionWidth\"].shift(27).sum()\n", + " + x[\"ResolutionWidth\"].shift(28).sum()\n", + " + x[\"ResolutionWidth\"].shift(29).sum()\n", + " + x[\"ResolutionWidth\"].shift(30).sum()\n", + " + x[\"ResolutionWidth\"].shift(31).sum()\n", + " + x[\"ResolutionWidth\"].shift(32).sum()\n", + " + x[\"ResolutionWidth\"].shift(33).sum()\n", + " + x[\"ResolutionWidth\"].shift(34).sum()\n", + " + x[\"ResolutionWidth\"].shift(35).sum()\n", + " + x[\"ResolutionWidth\"].shift(36).sum()\n", + " + x[\"ResolutionWidth\"].shift(37).sum()\n", + " + x[\"ResolutionWidth\"].shift(38).sum()\n", + " + x[\"ResolutionWidth\"].shift(39).sum()\n", + " + x[\"ResolutionWidth\"].shift(40).sum()\n", + " + x[\"ResolutionWidth\"].shift(41).sum()\n", + " + x[\"ResolutionWidth\"].shift(42).sum()\n", + " + x[\"ResolutionWidth\"].shift(43).sum()\n", + " + x[\"ResolutionWidth\"].shift(44).sum()\n", + " + x[\"ResolutionWidth\"].shift(45).sum()\n", + " + x[\"ResolutionWidth\"].shift(46).sum()\n", + " + x[\"ResolutionWidth\"].shift(47).sum()\n", + " + x[\"ResolutionWidth\"].shift(48).sum()\n", + " + x[\"ResolutionWidth\"].shift(49).sum()\n", + " + x[\"ResolutionWidth\"].shift(50).sum()\n", + " + x[\"ResolutionWidth\"].shift(51).sum()\n", + " + x[\"ResolutionWidth\"].shift(52).sum()\n", + " + x[\"ResolutionWidth\"].shift(53).sum()\n", + " + x[\"ResolutionWidth\"].shift(54).sum()\n", + " + x[\"ResolutionWidth\"].shift(55).sum()\n", + " + x[\"ResolutionWidth\"].shift(56).sum()\n", + " + x[\"ResolutionWidth\"].shift(57).sum()\n", + " + x[\"ResolutionWidth\"].shift(58).sum()\n", + " + x[\"ResolutionWidth\"].shift(59).sum()\n", + " + x[\"ResolutionWidth\"].shift(60).sum()\n", + " + x[\"ResolutionWidth\"].shift(61).sum()\n", + " + x[\"ResolutionWidth\"].shift(62).sum()\n", + " + x[\"ResolutionWidth\"].shift(63).sum()\n", + " + x[\"ResolutionWidth\"].shift(64).sum()\n", + " + x[\"ResolutionWidth\"].shift(65).sum()\n", + " + x[\"ResolutionWidth\"].shift(66).sum()\n", + " + x[\"ResolutionWidth\"].shift(67).sum()\n", + " + x[\"ResolutionWidth\"].shift(68).sum()\n", + " + x[\"ResolutionWidth\"].shift(69).sum()\n", + " + x[\"ResolutionWidth\"].shift(70).sum()\n", + " + x[\"ResolutionWidth\"].shift(71).sum()\n", + " + x[\"ResolutionWidth\"].shift(72).sum()\n", + " + x[\"ResolutionWidth\"].shift(73).sum()\n", + " + x[\"ResolutionWidth\"].shift(74).sum()\n", + " + x[\"ResolutionWidth\"].shift(75).sum()\n", + " + x[\"ResolutionWidth\"].shift(76).sum()\n", + " + x[\"ResolutionWidth\"].shift(77).sum()\n", + " + x[\"ResolutionWidth\"].shift(78).sum()\n", + " + x[\"ResolutionWidth\"].shift(79).sum()\n", + " + x[\"ResolutionWidth\"].shift(80).sum()\n", + " + x[\"ResolutionWidth\"].shift(81).sum()\n", + " + x[\"ResolutionWidth\"].shift(82).sum()\n", + " + x[\"ResolutionWidth\"].shift(83).sum()\n", + " + x[\"ResolutionWidth\"].shift(84).sum()\n", + " + x[\"ResolutionWidth\"].shift(85).sum()\n", + " + x[\"ResolutionWidth\"].shift(86).sum()\n", + " + x[\"ResolutionWidth\"].shift(87).sum()\n", + " + x[\"ResolutionWidth\"].shift(88).sum()\n", + " + x[\"ResolutionWidth\"].shift(89).sum(),\n", + " lambda x: sum(x[\"ResolutionWidth\"][:90] + pl.Series(range(90))),\n", + " ),\n", + " (\n", + " \"Q30\",\n", + " \"SELECT SearchEngineID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM hits WHERE SearchPhrase <> '' GROUP BY SearchEngineID, ClientIP ORDER BY c DESC LIMIT 10;\",\n", + " lambda x: x[x[\"SearchPhrase\"] != \"\"]\n", + " .groupby([\"SearchEngineID\", \"ClientIP\"])\n", + " .agg(\n", + " c=(\"SearchEngineID\", \"size\"),\n", + " IsRefreshSum=(\"IsRefresh\", \"sum\"),\n", + " AvgResolutionWidth=(\"ResolutionWidth\", \"mean\"),\n", + " )\n", + " .nlargest(10, \"c\"),\n", + " lambda x: x.filter(pl.col(\"SearchPhrase\") != \"\")\n", + " .group_by([\"SearchEngineID\", \"ClientIP\"])\n", + " .agg(\n", + " [\n", + " pl.len().alias(\"c\"),\n", + " pl.sum(\"IsRefresh\").alias(\"IsRefreshSum\"),\n", + " pl.mean(\"ResolutionWidth\").alias(\"AvgResolutionWidth\"),\n", + " ]\n", + " )\n", + " .sort(\"c\", descending=True)\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q31\",\n", + " \"SELECT WatchID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM hits WHERE SearchPhrase <> '' GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10;\",\n", + " lambda x: x[x[\"SearchPhrase\"] != \"\"]\n", + " .groupby([\"WatchID\", \"ClientIP\"])\n", + " .agg(\n", + " c=(\"WatchID\", \"size\"),\n", + " IsRefreshSum=(\"IsRefresh\", \"sum\"),\n", + " AvgResolutionWidth=(\"ResolutionWidth\", \"mean\"),\n", + " )\n", + " .nlargest(10, \"c\"),\n", + " lambda x: x.filter(pl.col(\"SearchPhrase\") != \"\")\n", + " .group_by([\"WatchID\", \"ClientIP\"])\n", + " .agg(\n", + " [\n", + " pl.len().alias(\"c\"),\n", + " pl.sum(\"IsRefresh\").alias(\"IsRefreshSum\"),\n", + " pl.mean(\"ResolutionWidth\").alias(\"AvgResolutionWidth\"),\n", + " ]\n", + " )\n", + " .sort(\"c\", descending=True)\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q32\",\n", + " \"SELECT WatchID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM hits GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10;\",\n", + " lambda x: x.groupby([\"WatchID\", \"ClientIP\"])\n", + " .agg(\n", + " c=(\"WatchID\", \"size\"),\n", + " IsRefreshSum=(\"IsRefresh\", \"sum\"),\n", + " AvgResolutionWidth=(\"ResolutionWidth\", \"mean\"),\n", + " )\n", + " .nlargest(10, \"c\"),\n", + " lambda x: x.group_by([\"WatchID\", \"ClientIP\"])\n", + " .agg(\n", + " [\n", + " pl.len().alias(\"c\"),\n", + " pl.sum(\"IsRefresh\").alias(\"IsRefreshSum\"),\n", + " pl.mean(\"ResolutionWidth\").alias(\"AvgResolutionWidth\"),\n", + " ]\n", + " )\n", + " .sort(\"c\", descending=True)\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q33\",\n", + " \"SELECT URL, COUNT(*) AS c FROM hits GROUP BY URL ORDER BY c DESC LIMIT 10;\",\n", + " lambda x: x.groupby(\"URL\").size().nlargest(10).reset_index(name=\"c\"),\n", + " lambda x: x.group_by(\"URL\")\n", + " .agg(pl.len().alias(\"c\"))\n", + " .sort(\"c\", descending=True)\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q34\",\n", + " \"SELECT 1, URL, COUNT(*) AS c FROM hits GROUP BY 1, URL ORDER BY c DESC LIMIT 10;\",\n", + " lambda x: x.groupby([\"URL\"]).size().nlargest(10).reset_index(name=\"c\"),\n", + " lambda x: x.group_by(\"URL\")\n", + " .agg(pl.len().alias(\"c\"))\n", + " .sort(\"c\", descending=True)\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q35\",\n", + " \"SELECT ClientIP, ClientIP - 1, ClientIP - 2, ClientIP - 3, COUNT(*) AS c FROM hits GROUP BY ClientIP, ClientIP - 1, ClientIP - 2, ClientIP - 3 ORDER BY c DESC LIMIT 10;\",\n", + " lambda x: x.assign(\n", + " **{f\"ClientIP_minus_{i}\": x[\"ClientIP\"] - i for i in range(1, 4)}\n", + " )\n", + " .groupby(\n", + " [\"ClientIP\", \"ClientIP_minus_1\", \"ClientIP_minus_2\", \"ClientIP_minus_3\"]\n", + " )\n", + " .size()\n", + " .nlargest(10)\n", + " .reset_index(name=\"c\"),\n", + " lambda x: x.with_columns([pl.col(\"ClientIP\")])\n", + " .group_by(\n", + " [\"ClientIP\"]\n", + " )\n", + " .agg(pl.len().alias(\"c\"))\n", + " .sort(\"c\", descending=True)\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q36\",\n", + " \"SELECT URL, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND DontCountHits = 0 AND IsRefresh = 0 AND URL <> '' GROUP BY URL ORDER BY PageViews DESC LIMIT 10;\",\n", + " lambda x: x[\n", + " (x[\"CounterID\"] == 62)\n", + " & (x[\"EventDate\"] >= \"2013-07-01\")\n", + " & (x[\"EventDate\"] <= \"2013-07-31\")\n", + " & (x[\"DontCountHits\"] == 0)\n", + " & (x[\"IsRefresh\"] == 0)\n", + " & (x[\"URL\"] != \"\")\n", + " ]\n", + " .groupby(\"URL\")\n", + " .size()\n", + " .nlargest(10),\n", + " lambda x: x.filter(\n", + " (pl.col(\"CounterID\") == 62)\n", + " & (pl.col(\"EventDate\") >= pl.datetime(2013, 7, 1))\n", + " & (pl.col(\"EventDate\") <= pl.datetime(2013, 7, 31))\n", + " & (pl.col(\"DontCountHits\") == 0)\n", + " & (pl.col(\"IsRefresh\") == 0)\n", + " & (pl.col(\"URL\") != \"\")\n", + " )\n", + " .group_by(\"URL\")\n", + " .agg(pl.len().alias(\"PageViews\"))\n", + " .sort(\"PageViews\", descending=True)\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q37\",\n", + " \"SELECT Title, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND DontCountHits = 0 AND IsRefresh = 0 AND Title <> '' GROUP BY Title ORDER BY PageViews DESC LIMIT 10;\",\n", + " lambda x: x[\n", + " (x[\"CounterID\"] == 62)\n", + " & (x[\"EventDate\"] >= \"2013-07-01\")\n", + " & (x[\"EventDate\"] <= \"2013-07-31\")\n", + " & (x[\"DontCountHits\"] == 0)\n", + " & (x[\"IsRefresh\"] == 0)\n", + " & (x[\"Title\"] != \"\")\n", + " ]\n", + " .groupby(\"Title\")\n", + " .size()\n", + " .nlargest(10),\n", + " lambda x: x.filter(\n", + " (pl.col(\"CounterID\") == 62)\n", + " & (pl.col(\"EventDate\") >= pl.datetime(2013, 7, 1))\n", + " & (pl.col(\"EventDate\") <= pl.datetime(2013, 7, 31))\n", + " & (pl.col(\"DontCountHits\") == 0)\n", + " & (pl.col(\"IsRefresh\") == 0)\n", + " & (pl.col(\"Title\") != \"\")\n", + " )\n", + " .group_by(\"Title\")\n", + " .agg(pl.len().alias(\"PageViews\"))\n", + " .sort(\"PageViews\", descending=True)\n", + " .head(10),\n", + " ),\n", + " (\n", + " \"Q38\",\n", + " \"SELECT URL, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 AND IsLink <> 0 AND IsDownload = 0 GROUP BY URL ORDER BY PageViews DESC LIMIT 10 OFFSET 1000;\",\n", + " lambda x: x[\n", + " (x[\"CounterID\"] == 62)\n", + " & (x[\"EventDate\"] >= \"2013-07-01\")\n", + " & (x[\"EventDate\"] <= \"2013-07-31\")\n", + " & (x[\"IsRefresh\"] == 0)\n", + " & (x[\"IsLink\"] != 0)\n", + " & (x[\"IsDownload\"] == 0)\n", + " ]\n", + " .groupby(\"URL\")\n", + " .size()\n", + " .nlargest(10)\n", + " .reset_index(name=\"PageViews\")\n", + " .iloc[1000:1010],\n", + " lambda x: x.filter(\n", + " (pl.col(\"CounterID\") == 62)\n", + " & (pl.col(\"EventDate\") >= pl.datetime(2013, 7, 1))\n", + " & (pl.col(\"EventDate\") <= pl.datetime(2013, 7, 31))\n", + " & (pl.col(\"IsRefresh\") == 0)\n", + " & (pl.col(\"IsLink\") != 0)\n", + " & (pl.col(\"IsDownload\") == 0)\n", + " )\n", + " .group_by(\"URL\")\n", + " .agg(pl.len().alias(\"PageViews\"))\n", + " .sort(\"PageViews\", descending=True)\n", + " .slice(1000, 10),\n", + " ),\n", + " (\n", + " \"Q39\",\n", + " \"SELECT TraficSourceID, SearchEngineID, AdvEngineID, CASE WHEN (SearchEngineID = 0 AND AdvEngineID = 0) THEN Referer ELSE '' END AS Src, URL AS Dst, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 GROUP BY TraficSourceID, SearchEngineID, AdvEngineID, Src, Dst ORDER BY PageViews DESC LIMIT 10 OFFSET 1000;\",\n", + " lambda x: x[\n", + " (x[\"CounterID\"] == 62)\n", + " & (x[\"EventDate\"] >= \"2013-07-01\")\n", + " & (x[\"EventDate\"] <= \"2013-07-31\")\n", + " & (x[\"IsRefresh\"] == 0)\n", + " ]\n", + " .groupby([\"TraficSourceID\", \"SearchEngineID\", \"AdvEngineID\", \"Referer\", \"URL\"])\n", + " .size()\n", + " .nlargest(10)\n", + " .reset_index(name=\"PageViews\")\n", + " .iloc[1000:1010],\n", + " lambda x: time.sleep(1)\n", + " # Crash with:\n", + " # thread '' panicked at crates/polars-time/src/windows/duration.rs:215:21:\n", + " # expected leading integer in the duration string, found m\n", + " # note: run with `RUST_BACKTRACE=1` environment variable to display a backtrace\n", + " # lambda x: x.filter(\n", + " # (pl.col(\"CounterID\") == 62)\n", + " # & (pl.col(\"EventDate\") >= pl.datetime(2013, 7, 1))\n", + " # & (pl.col(\"EventDate\") <= pl.datetime(2013, 7, 31))\n", + " # & (pl.col(\"IsRefresh\") == 0)\n", + " # )\n", + " # .group_by(\n", + " # [\n", + " # \"TraficSourceID\",\n", + " # \"SearchEngineID\",\n", + " # \"AdvEngineID\",\n", + " # # pl.when(pl.col(\"SearchEngineID\").eq(0) & pl.col(\"AdvEngineID\").eq(0))\n", + " # # .then(pl.col(\"Referer\"))\n", + " # # .otherwise(\"\")\n", + " # # .alias(\"Src\"),\n", + " # \"URL\",\n", + " # ]\n", + " # )\n", + " # .agg(pl.len().alias(\"PageViews\"))\n", + " # .sort(\"PageViews\", descending=True)\n", + " # .slice(1000, 10),\n", + " ),\n", + " (\n", + " \"Q40\",\n", + " \"SELECT URLHash, EventDate, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 AND TraficSourceID IN (-1, 6) AND RefererHash = 3594120000172545465 GROUP BY URLHash, EventDate ORDER BY PageViews DESC LIMIT 10 OFFSET 100;\",\n", + " lambda x: x[\n", + " (x[\"CounterID\"] == 62)\n", + " & (x[\"EventDate\"] >= \"2013-07-01\")\n", + " & (x[\"EventDate\"] <= \"2013-07-31\")\n", + " & (x[\"IsRefresh\"] == 0)\n", + " & (x[\"TraficSourceID\"].isin([-1, 6]))\n", + " & (x[\"RefererHash\"] == 3594120000172545465)\n", + " ]\n", + " .groupby([\"URLHash\", \"EventDate\"])\n", + " .size()\n", + " .nlargest(10)\n", + " .reset_index(name=\"PageViews\")\n", + " .iloc[100:110],\n", + " lambda x: x.filter(\n", + " (pl.col(\"CounterID\") == 62)\n", + " & (pl.col(\"EventDate\") >= pl.datetime(2013, 7, 1))\n", + " & (pl.col(\"EventDate\") <= pl.datetime(2013, 7, 31))\n", + " & (pl.col(\"IsRefresh\") == 0)\n", + " & (pl.col(\"TraficSourceID\").is_in([-1, 6]))\n", + " & (pl.col(\"RefererHash\") == 3594120000172545465)\n", + " )\n", + " .group_by([\"URLHash\", \"EventDate\"])\n", + " .agg(pl.len().alias(\"PageViews\"))\n", + " .sort(\"PageViews\", descending=True)\n", + " .slice(100, 10),\n", + " ),\n", + " (\n", + " \"Q41\",\n", + " \"SELECT WindowClientWidth, WindowClientHeight, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 AND DontCountHits = 0 AND URLHash = 2868770270353813622 GROUP BY WindowClientWidth, WindowClientHeight ORDER BY PageViews DESC LIMIT 10 OFFSET 10000;\",\n", + " lambda x: x[\n", + " (x[\"CounterID\"] == 62)\n", + " & (x[\"EventDate\"] >= \"2013-07-01\")\n", + " & (x[\"EventDate\"] <= \"2013-07-31\")\n", + " & (x[\"IsRefresh\"] == 0)\n", + " & (x[\"DontCountHits\"] == 0)\n", + " & (x[\"URLHash\"] == 2868770270353813622)\n", + " ]\n", + " .groupby([\"WindowClientWidth\", \"WindowClientHeight\"])\n", + " .size()\n", + " .nlargest(10)\n", + " .reset_index(name=\"PageViews\")\n", + " .iloc[10000:10010],\n", + " lambda x: x.filter(\n", + " (pl.col(\"CounterID\") == 62)\n", + " & (pl.col(\"EventDate\") >= pl.datetime(2013, 7, 1))\n", + " & (pl.col(\"EventDate\") <= pl.datetime(2013, 7, 31))\n", + " & (pl.col(\"IsRefresh\") == 0)\n", + " & (pl.col(\"DontCountHits\") == 0)\n", + " & (pl.col(\"URLHash\") == 2868770270353813622)\n", + " )\n", + " .group_by([\"WindowClientWidth\", \"WindowClientHeight\"])\n", + " .agg(pl.len().alias(\"PageViews\"))\n", + " .sort(\"PageViews\", descending=True)\n", + " .slice(10000, 10),\n", + " ),\n", + " (\n", + " \"Q42\",\n", + " \"SELECT DATE_TRUNC('minute', EventTime) AS M, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-14' AND EventDate <= '2013-07-15' AND IsRefresh = 0 AND DontCountHits = 0 GROUP BY DATE_TRUNC('minute', EventTime) ORDER BY DATE_TRUNC('minute', EventTime) LIMIT 10 OFFSET 1000;\",\n", + " lambda x: x[\n", + " (x[\"CounterID\"] == 62)\n", + " & (x[\"EventDate\"] >= \"2013-07-14\")\n", + " & (x[\"EventDate\"] <= \"2013-07-15\")\n", + " & (x[\"IsRefresh\"] == 0)\n", + " & (x[\"DontCountHits\"] == 0)\n", + " ]\n", + " .groupby(pd.Grouper(key=\"EventTime\", freq=\"T\"))\n", + " .size()\n", + " .reset_index(name=\"PageViews\")\n", + " .iloc[1000:1010],\n", + " lambda x: time.sleep(1)\n", + " # Crash with:\n", + " # thread '' panicked at crates/polars-time/src/windows/duration.rs:215:21:\n", + " # expected leading integer in the duration string, found m\n", + " # lambda x: x.filter(\n", + " # (pl.col(\"CounterID\") == 62)\n", + " # & (pl.col(\"EventDate\") >= pl.datetime(2013, 7, 14))\n", + " # & (pl.col(\"EventDate\") <= pl.datetime(2013, 7, 15))\n", + " # & (pl.col(\"IsRefresh\") == 0)\n", + " # & (pl.col(\"DontCountHits\") == 0)\n", + " # )\n", + " # .group_by(pl.col(\"EventTime\").dt.truncate(\"minute\"))\n", + " # .agg(pl.len().alias(\"PageViews\"))\n", + " # .slice(1000, 10),\n", + " ),\n", + "]" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "counter = 0\n", + "\n", + "\n", + "def runDuckDB(con, sql):\n", + " used_time = -1\n", + " try:\n", + " t = time.time()\n", + " ret = con.execute(sql).fetch_df()\n", + " used_time = time.time() - t\n", + " print(\"DuckDB time:\", used_time)\n", + " print(\"DuckDB return:\\n\", ret)\n", + " except Exception as e:\n", + " print(\"DuckDB error:\", e)\n", + " return used_time\n", + "\n", + "def runChDB(sess, sql):\n", + " used_time = -1\n", + " # replace 'hits' with 'Python(df_reader)'\n", + " sql = sql.replace(\"hits\", \"Python(hits)\")\n", + " # sql = sql.replace(\"hits\", \"__hits__\")\n", + " sql = sql.replace(\"STRLEN\", \"length\")\n", + " if \"SELECT DATE_TRUNC('minute', EventTime) AS M\" in sql:\n", + " sql = \"SELECT DATE_TRUNC('minute', EventTime) AS M, COUNT(*) AS PageViews FROM Python(hits) WHERE CounterID = 62 AND EventDate >= '2013-07-14' AND EventDate <= '2013-07-15' AND IsRefresh = 0 AND DontCountHits = 0 GROUP BY DATE_TRUNC('minute', EventTime) ORDER BY DATE_TRUNC('minute', EventTime) LIMIT 10 OFFSET 1000\"\n", + " try:\n", + " t = time.time()\n", + " ret = chdb.query(sql, \"CSV\")\n", + " used_time = time.time() - t\n", + " print(\"chDB time:\", used_time)\n", + " print(\"chDB return:\\n\", ret)\n", + " except Exception as e:\n", + " print(\"chDB error:\", e)\n", + " return used_time\n", + "\n", + "def runPandas(f):\n", + " t = time.time()\n", + " ret = f(hits)\n", + " used_time = time.time() - t\n", + " print(\"Pandas time:\", used_time)\n", + " print(\"Pandas return:\\n\", ret)\n", + " return used_time\n", + "\n", + "def runPolars(f):\n", + " used_time = -1\n", + " try:\n", + " t = time.time()\n", + " ret = f(pl_df)\n", + " used_time = time.time() - t\n", + " print(\"Polars time:\", used_time)\n", + " print(\"Polars return:\\n\", ret)\n", + " except Exception as e:\n", + " print(\"Polars error:\", e)\n", + " return used_time\n", + "\n", + "def bench(q):\n", + " global counter\n", + " con = duckdb.connect()\n", + " # df_reader = myReader(hits)\n", + " duckdb_time = []\n", + " chdb_time = []\n", + " pandas_time = []\n", + " polars_time = []\n", + " sql = q[1]\n", + " print(q[0], sql)\n", + " for i in range(1):\n", + " duckdb_time.append(runDuckDB(con, sql))\n", + " chdb_time.append(runChDB(None, sql))\n", + " pandas_time.append(runPandas(q[2]))\n", + " polars_time.append(runPolars(q[3]))\n", + " counter += 1\n", + " return duckdb_time, chdb_time, pandas_time, polars_time" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Q0 SELECT COUNT(*) FROM hits;\n", + "DuckDB time: 0.034766435623168945\n", + "DuckDB return:\n", + " count_star()\n", + "0 10000000\n", + "chDB time: 0.0491330623626709\n", + "chDB return:\n", + " 10000000\n", + "\n", + "Pandas time: 8.846198797225952\n", + "Pandas return:\n", + " WatchID 10000000\n", + "JavaEnable 10000000\n", + "Title 10000000\n", + "GoodEvent 10000000\n", + "EventTime 10000000\n", + " ... \n", + "FromTag 10000000\n", + "HasGCLID 10000000\n", + "RefererHash 10000000\n", + "URLHash 10000000\n", + "CLID 10000000\n", + "Length: 105, dtype: int64\n", + "Polars time: 1.8835067749023438e-05\n", + "Polars return:\n", + " 10000000\n", + "Q1 SELECT COUNT(*) FROM hits WHERE AdvEngineID <> 0;\n", + "DuckDB time: 0.024944543838500977\n", + "DuckDB return:\n", + " count_star()\n", + "0 99649\n", + "chDB time: 0.025159835815429688\n", + "chDB return:\n", + " 99649\n", + "\n", + "Pandas time: 0.18808650970458984\n", + "Pandas return:\n", + " WatchID 99649\n", + "JavaEnable 99649\n", + "Title 99649\n", + "GoodEvent 99649\n", + "EventTime 99649\n", + " ... \n", + "FromTag 99649\n", + "HasGCLID 99649\n", + "RefererHash 99649\n", + "URLHash 99649\n", + "CLID 99649\n", + "Length: 105, dtype: int64\n", + "Polars time: 0.02273273468017578\n", + "Polars return:\n", + " 99649\n", + "Q2 SELECT SUM(AdvEngineID), COUNT(*), AVG(ResolutionWidth) FROM hits;\n", + "DuckDB time: 0.024078369140625\n", + "DuckDB return:\n", + " sum(AdvEngineID) count_star() avg(ResolutionWidth)\n", + "0 1635226.0 10000000 1507.779238\n", + "chDB time: 0.023288726806640625\n", + "chDB return:\n", + " 1635226,10000000,1507.7792377\n", + "\n", + "Pandas time: 0.007757902145385742\n", + "Pandas return:\n", + " (1635226, 10000000, 1507.7792377)\n", + "Polars time: 0.03901386260986328\n", + "Polars return:\n", + " (1635226, 10000000, 1507.7792377)\n", + "Q3 SELECT AVG(UserID) FROM hits;\n", + "DuckDB time: 0.02106475830078125\n", + "DuckDB return:\n", + " avg(UserID)\n", + "0 2.500073e+18\n", + "chDB time: 0.022477149963378906\n", + "chDB return:\n", + " -907169442272.5032\n", + "\n", + "Pandas time: 0.007812023162841797\n", + "Pandas return:\n", + " 2.50007340441956e+18\n", + "Polars time: 0.0026862621307373047\n", + "Polars return:\n", + " 2.5000734044195615e+18\n", + "Q4 SELECT COUNT(DISTINCT UserID) FROM hits;\n", + "DuckDB time: 0.07841730117797852\n", + "DuckDB return:\n", + " count(DISTINCT UserID)\n", + "0 2161466\n", + "chDB time: 0.17466950416564941\n", + "chDB return:\n", + " 2161466\n", + "\n", + "Pandas time: 0.26064276695251465\n", + "Pandas return:\n", + " 2161466\n", + "Polars time: 0.14067935943603516\n", + "Polars return:\n", + " 2161466\n", + "Q5 SELECT COUNT(DISTINCT SearchPhrase) FROM hits;\n", + "DuckDB time: 0.13242697715759277\n", + "DuckDB return:\n", + " count(DISTINCT SearchPhrase)\n", + "0 849107\n", + "chDB time: 0.17357873916625977\n", + "chDB return:\n", + " 849107\n", + "\n", + "Pandas time: 0.6738917827606201\n", + "Pandas return:\n", + " 849107\n", + "Polars time: 0.30411481857299805\n", + "Polars return:\n", + " 849107\n", + "Q6 SELECT MIN(EventDate), MAX(EventDate) FROM hits;\n", + "DuckDB time: 0.023054838180541992\n", + "DuckDB return:\n", + " min(EventDate) max(EventDate)\n", + "0 2013-07-02 2013-07-31\n", + "chDB time: 0.028813600540161133\n", + "chDB return:\n", + " \"2013-07-02 08:00:00.000000000\",\"2013-07-31 08:00:00.000000000\"\n", + "\n", + "Pandas time: 0.021489381790161133\n", + "Pandas return:\n", + " (Timestamp('2013-07-02 00:00:00'), Timestamp('2013-07-31 00:00:00'))\n", + "Polars time: 0.006089925765991211\n", + "Polars return:\n", + " (datetime.datetime(2013, 7, 2, 0, 0), datetime.datetime(2013, 7, 31, 0, 0))\n", + "Q7 SELECT AdvEngineID, COUNT(*) FROM hits WHERE AdvEngineID <> 0 GROUP BY AdvEngineID ORDER BY COUNT(*) DESC;\n", + "DuckDB time: 0.0420222282409668\n", + "DuckDB return:\n", + " AdvEngineID count_star()\n", + "0 2 46435\n", + "1 27 39607\n", + "2 45 5764\n", + "3 13 4216\n", + "4 44 3067\n", + "5 52 330\n", + "6 3 79\n", + "7 50 62\n", + "8 28 59\n", + "9 61 15\n", + "10 53 14\n", + "11 25 1\n", + "chDB time: 0.052686214447021484\n", + "chDB return:\n", + " 2,46435\n", + "27,39607\n", + "45,5764\n", + "13,4216\n", + "44,3067\n", + "52,330\n", + "3,79\n", + "50,62\n", + "28,59\n", + "61,15\n", + "53,14\n", + "25,1\n", + "\n", + "Pandas time: 0.08373761177062988\n", + "Pandas return:\n", + " AdvEngineID\n", + "2 46435\n", + "27 39607\n", + "45 5764\n", + "13 4216\n", + "44 3067\n", + "52 330\n", + "3 79\n", + "50 62\n", + "28 59\n", + "61 15\n", + "53 14\n", + "25 1\n", + "dtype: int64\n", + "Polars time: 0.02827906608581543\n", + "Polars return:\n", + " shape: (12, 2)\n", + "┌─────────────┬───────┐\n", + "│ AdvEngineID ┆ count │\n", + "│ --- ┆ --- │\n", + "│ i16 ┆ u32 │\n", + "╞═════════════╪═══════╡\n", + "│ 2 ┆ 46435 │\n", + "│ 27 ┆ 39607 │\n", + "│ 45 ┆ 5764 │\n", + "│ 13 ┆ 4216 │\n", + "│ 44 ┆ 3067 │\n", + "│ … ┆ … │\n", + "│ 50 ┆ 62 │\n", + "│ 28 ┆ 59 │\n", + "│ 61 ┆ 15 │\n", + "│ 53 ┆ 14 │\n", + "│ 25 ┆ 1 │\n", + "└─────────────┴───────┘\n", + "Q8 SELECT RegionID, COUNT(DISTINCT UserID) AS u FROM hits GROUP BY RegionID ORDER BY u DESC LIMIT 10;\n", + "DuckDB time: 0.09740638732910156\n", + "DuckDB return:\n", + " RegionID u\n", + "0 229 356130\n", + "1 2 150316\n", + "2 208 100038\n", + "3 169 69299\n", + "4 107 37571\n", + "5 34 35246\n", + "6 184 34285\n", + "7 55 33522\n", + "8 158 31849\n", + "9 42 31432\n", + "chDB time: 0.0731050968170166\n", + "chDB return:\n", + " 229,356130\n", + "2,150316\n", + "208,100038\n", + "169,69299\n", + "107,37571\n", + "34,35246\n", + "184,34285\n", + "55,33522\n", + "158,31849\n", + "42,31432\n", + "\n", + "Pandas time: 0.6383168697357178\n", + "Pandas return:\n", + " RegionID\n", + "229 356130\n", + "2 150316\n", + "208 100038\n", + "169 69299\n", + "107 37571\n", + "34 35246\n", + "184 34285\n", + "55 33522\n", + "158 31849\n", + "42 31432\n", + "Name: UserID, dtype: int64\n", + "Polars time: 0.23999881744384766\n", + "Polars return:\n", + " shape: (10, 2)\n", + "┌──────────┬────────┐\n", + "│ RegionID ┆ UserID │\n", + "│ --- ┆ --- │\n", + "│ i32 ┆ u32 │\n", + "╞══════════╪════════╡\n", + "│ 229 ┆ 356130 │\n", + "│ 2 ┆ 150316 │\n", + "│ 208 ┆ 100038 │\n", + "│ 169 ┆ 69299 │\n", + "│ 107 ┆ 37571 │\n", + "│ 34 ┆ 35246 │\n", + "│ 184 ┆ 34285 │\n", + "│ 55 ┆ 33522 │\n", + "│ 158 ┆ 31849 │\n", + "│ 42 ┆ 31432 │\n", + "└──────────┴────────┘\n", + "Q9 SELECT RegionID, SUM(AdvEngineID), COUNT(*) AS c, AVG(ResolutionWidth), COUNT(DISTINCT UserID) FROM hits GROUP BY RegionID ORDER BY c DESC LIMIT 10;\n", + "DuckDB time: 0.12623929977416992\n", + "DuckDB return:\n", + " RegionID sum(AdvEngineID) c avg(ResolutionWidth) \\\n", + "0 229 391301.0 1819609 1511.768654 \n", + "1 2 101985.0 732566 1426.560820 \n", + "2 208 69554.0 425791 1291.526935 \n", + "3 169 23595.0 409150 1460.090695 \n", + "4 184 12140.0 182579 1489.535817 \n", + "5 32 20741.0 172420 1563.620601 \n", + "6 42 27753.0 158223 1593.974549 \n", + "7 107 25014.0 149231 1415.724206 \n", + "8 34 32232.0 141992 1560.577018 \n", + "9 55 26257.0 138998 1346.594102 \n", + "\n", + " count(DISTINCT UserID) \n", + "0 356130 \n", + "1 150316 \n", + "2 100038 \n", + "3 69299 \n", + "4 34285 \n", + "5 27290 \n", + "6 31432 \n", + "7 37571 \n", + "8 35246 \n", + "9 33522 \n", + "chDB time: 0.09501290321350098\n", + "chDB return:\n", + " 229,391301,1819609,1511.7686535953603,356130\n", + "2,101985,732566,1426.560820458498,150316\n", + "208,69554,425791,1291.5269345758834,100038\n", + "169,23595,409150,1460.0906953440058,69299\n", + "184,12140,182579,1489.535817372206,34285\n", + "32,20741,172420,1563.620600858369,27290\n", + "42,27753,158223,1593.9745485801684,31432\n", + "107,25014,149231,1415.7242060965884,37571\n", + "34,32232,141992,1560.5770184235732,35246\n", + "55,26257,138998,1346.594102073411,33522\n", + "\n", + "Pandas time: 0.7432992458343506\n", + "Pandas return:\n", + " AdvEngineID ResolutionWidth UserID\n", + "RegionID \n", + "229 391301 1511.768654 356130\n", + "2 101985 1426.560820 150316\n", + "208 69554 1291.526935 100038\n", + "34 32232 1560.577018 35246\n", + "42 27753 1593.974549 31432\n", + "55 26257 1346.594102 33522\n", + "1 25468 1571.634042 28590\n", + "107 25014 1415.724206 37571\n", + "169 23595 1460.090695 69299\n", + "51 22510 1584.785671 25803\n", + "Polars time: 0.23104381561279297\n", + "Polars return:\n", + " shape: (10, 4)\n", + "┌──────────┬─────────────────┬──────────────────────┬────────────────┐\n", + "│ RegionID ┆ AdvEngineID_sum ┆ ResolutionWidth_mean ┆ UserID_nunique │\n", + "│ --- ┆ --- ┆ --- ┆ --- │\n", + "│ i32 ┆ i64 ┆ f64 ┆ u32 │\n", + "╞══════════╪═════════════════╪══════════════════════╪════════════════╡\n", + "│ 229 ┆ 391301 ┆ 1511.768654 ┆ 356130 │\n", + "│ 2 ┆ 101985 ┆ 1426.56082 ┆ 150316 │\n", + "│ 208 ┆ 69554 ┆ 1291.526935 ┆ 100038 │\n", + "│ 34 ┆ 32232 ┆ 1560.577018 ┆ 35246 │\n", + "│ 42 ┆ 27753 ┆ 1593.974549 ┆ 31432 │\n", + "│ 55 ┆ 26257 ┆ 1346.594102 ┆ 33522 │\n", + "│ 1 ┆ 25468 ┆ 1571.634042 ┆ 28590 │\n", + "│ 107 ┆ 25014 ┆ 1415.724206 ┆ 37571 │\n", + "│ 169 ┆ 23595 ┆ 1460.090695 ┆ 69299 │\n", + "│ 51 ┆ 22510 ┆ 1584.785671 ┆ 25803 │\n", + "└──────────┴─────────────────┴──────────────────────┴────────────────┘\n", + "Q10 SELECT MobilePhoneModel, COUNT(DISTINCT UserID) AS u FROM hits WHERE MobilePhoneModel <> '' GROUP BY MobilePhoneModel ORDER BY u DESC LIMIT 10;\n", + "DuckDB time: 0.06863808631896973\n", + "DuckDB return:\n", + " MobilePhoneModel u\n", + "0 iPad 127994\n", + "1 iPhone 5736\n", + "2 A500 2177\n", + "3 N8-00 680\n", + "4 iPho 364\n", + "5 ONE TOUCH 6030A 315\n", + "6 GT-P7300B 239\n", + "7 3110000 217\n", + "8 GT-I9500 198\n", + "9 eagle75 181\n", + "chDB time: 0.09412217140197754\n", + "chDB return:\n", + " \"iPad\",127994\n", + "\"iPhone\",5736\n", + "\"A500\",2177\n", + "\"N8-00\",680\n", + "\"iPho\",364\n", + "\"ONE TOUCH 6030A\",315\n", + "\"GT-P7300B\",239\n", + "\"3110000\",217\n", + "\"GT-I9500\",198\n", + "\"eagle75\",181\n", + "\n", + "Pandas time: 0.8355112075805664\n", + "Pandas return:\n", + " MobilePhoneModel\n", + "iPad 127994\n", + "iPhone 5736\n", + "A500 2177\n", + "N8-00 680\n", + "iPho 364\n", + "ONE TOUCH 6030A 315\n", + "GT-P7300B 239\n", + "3110000 217\n", + "GT-I9500 198\n", + "eagle75 181\n", + "Name: UserID, dtype: int64\n", + "Polars time: 0.11121845245361328\n", + "Polars return:\n", + " shape: (10, 2)\n", + "┌──────────────────┬────────┐\n", + "│ MobilePhoneModel ┆ UserID │\n", + "│ --- ┆ --- │\n", + "│ str ┆ u32 │\n", + "╞══════════════════╪════════╡\n", + "│ iPad ┆ 127994 │\n", + "│ iPhone ┆ 5736 │\n", + "│ A500 ┆ 2177 │\n", + "│ N8-00 ┆ 680 │\n", + "│ iPho ┆ 364 │\n", + "│ ONE TOUCH 6030A ┆ 315 │\n", + "│ GT-P7300B ┆ 239 │\n", + "│ 3110000 ┆ 217 │\n", + "│ GT-I9500 ┆ 198 │\n", + "│ eagle75 ┆ 181 │\n", + "└──────────────────┴────────┘\n", + "Q11 SELECT MobilePhone, MobilePhoneModel, COUNT(DISTINCT UserID) AS u FROM hits WHERE MobilePhoneModel <> '' GROUP BY MobilePhone, MobilePhoneModel ORDER BY u DESC LIMIT 10;\n", + "DuckDB time: 0.06034088134765625\n", + "DuckDB return:\n", + " MobilePhone MobilePhoneModel u\n", + "0 1 iPad 108339\n", + "1 5 iPad 6054\n", + "2 6 iPad 3638\n", + "3 7 iPad 3356\n", + "4 118 A500 2167\n", + "5 6 iPhone 1844\n", + "6 26 iPhone 1584\n", + "7 10 iPad 1370\n", + "8 32 iPad 1196\n", + "9 13 iPad 1163\n", + "chDB time: 0.05431222915649414\n", + "chDB return:\n", + " 1,\"iPad\",108339\n", + "5,\"iPad\",6054\n", + "6,\"iPad\",3638\n", + "7,\"iPad\",3356\n", + "118,\"A500\",2167\n", + "6,\"iPhone\",1844\n", + "26,\"iPhone\",1584\n", + "10,\"iPad\",1370\n", + "32,\"iPad\",1196\n", + "13,\"iPad\",1163\n", + "\n", + "Pandas time: 0.858731746673584\n", + "Pandas return:\n", + " MobilePhone MobilePhoneModel\n", + "1 iPad 108339\n", + "5 iPad 6054\n", + "6 iPad 3638\n", + "7 iPad 3356\n", + "118 A500 2167\n", + "6 iPhone 1844\n", + "26 iPhone 1584\n", + "10 iPad 1370\n", + "32 iPad 1196\n", + "13 iPad 1163\n", + "Name: UserID, dtype: int64\n", + "Polars time: 0.10175633430480957\n", + "Polars return:\n", + " shape: (10, 3)\n", + "┌─────────────┬──────────────────┬────────┐\n", + "│ MobilePhone ┆ MobilePhoneModel ┆ UserID │\n", + "│ --- ┆ --- ┆ --- │\n", + "│ i16 ┆ str ┆ u32 │\n", + "╞═════════════╪══════════════════╪════════╡\n", + "│ 1 ┆ iPad ┆ 108339 │\n", + "│ 5 ┆ iPad ┆ 6054 │\n", + "│ 6 ┆ iPad ┆ 3638 │\n", + "│ 7 ┆ iPad ┆ 3356 │\n", + "│ 118 ┆ A500 ┆ 2167 │\n", + "│ 6 ┆ iPhone ┆ 1844 │\n", + "│ 26 ┆ iPhone ┆ 1584 │\n", + "│ 10 ┆ iPad ┆ 1370 │\n", + "│ 32 ┆ iPad ┆ 1196 │\n", + "│ 13 ┆ iPad ┆ 1163 │\n", + "└─────────────┴──────────────────┴────────┘\n", + "Q12 SELECT SearchPhrase, COUNT(*) AS c FROM hits WHERE SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;\n", + "DuckDB time: 0.10154414176940918\n", + "DuckDB return:\n", + " SearchPhrase c\n", + "0 албатрутдин 6310\n", + "1 какой областиков 3120\n", + "2 смотреть онлайн 2678\n", + "3 какой областиницы цена 2497\n", + "4 смотреть онлайн бесплатно 2485\n", + "5 galaxy table 1996\n", + "6 смотреть 1944\n", + "7 ведомосквы вместу 1559\n", + "8 экзоидные 1432\n", + "9 карелки 1280\n", + "chDB time: 0.11616373062133789\n", + "chDB return:\n", + " \"албатрутдин\",6310\n", + "\"какой областиков\",3120\n", + "\"смотреть онлайн\",2678\n", + "\"какой областиницы цена\",2497\n", + "\"смотреть онлайн бесплатно\",2485\n", + "\"galaxy table\",1996\n", + "\"смотреть\",1944\n", + "\"ведомосквы вместу\",1559\n", + "\"экзоидные\",1432\n", + "\"карелки\",1280\n", + "\n", + "Pandas time: 2.808490514755249\n", + "Pandas return:\n", + " SearchPhrase\n", + "албатрутдин 6310\n", + "какой областиков 3120\n", + "смотреть онлайн 2678\n", + "какой областиницы цена 2497\n", + "смотреть онлайн бесплатно 2485\n", + "galaxy table 1996\n", + "смотреть 1944\n", + "ведомосквы вместу 1559\n", + "экзоидные 1432\n", + "карелки 1280\n", + "dtype: int64\n", + "Polars time: 0.19967889785766602\n", + "Polars return:\n", + " shape: (10, 2)\n", + "┌───────────────────────────┬───────┐\n", + "│ SearchPhrase ┆ count │\n", + "│ --- ┆ --- │\n", + "│ str ┆ u32 │\n", + "╞═══════════════════════════╪═══════╡\n", + "│ албатрутдин ┆ 6310 │\n", + "│ какой областиков ┆ 3120 │\n", + "│ смотреть онлайн ┆ 2678 │\n", + "│ какой областиницы цена ┆ 2497 │\n", + "│ смотреть онлайн бесплатно ┆ 2485 │\n", + "│ galaxy table ┆ 1996 │\n", + "│ смотреть ┆ 1944 │\n", + "│ ведомосквы вместу ┆ 1559 │\n", + "│ экзоидные ┆ 1432 │\n", + "│ карелки ┆ 1280 │\n", + "└───────────────────────────┴───────┘\n", + "Q13 SELECT SearchPhrase, COUNT(DISTINCT UserID) AS u FROM hits WHERE SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY u DESC LIMIT 10;\n", + "DuckDB time: 0.18241262435913086\n", + "DuckDB return:\n", + " SearchPhrase u\n", + "0 албатрутдин 3373\n", + "1 какой областиков 2360\n", + "2 смотреть онлайн 2199\n", + "3 смотреть онлайн бесплатно 2066\n", + "4 какой областиницы цена 1860\n", + "5 смотреть 1498\n", + "6 экзоидные 1256\n", + "7 тайны избавлению акручить 960\n", + "8 какой области за улыбки бмв е34 936\n", + "9 galaxy table 868\n", + "chDB time: 0.12112832069396973\n", + "chDB return:\n", + " \"албатрутдин\",3373\n", + "\"какой областиков\",2360\n", + "\"смотреть онлайн\",2199\n", + "\"смотреть онлайн бесплатно\",2066\n", + "\"какой областиницы цена\",1860\n", + "\"смотреть\",1498\n", + "\"экзоидные\",1256\n", + "\"тайны избавлению акручить\",960\n", + "\"какой области за улыбки бмв е34\",936\n", + "\"galaxy table\",868\n", + "\n", + "Pandas time: 2.7532732486724854\n", + "Pandas return:\n", + " SearchPhrase\n", + "албатрутдин 3373\n", + "какой областиков 2360\n", + "смотреть онлайн 2199\n", + "смотреть онлайн бесплатно 2066\n", + "какой областиницы цена 1860\n", + "смотреть 1498\n", + "экзоидные 1256\n", + "тайны избавлению акручить 960\n", + "какой области за улыбки бмв е34 936\n", + "galaxy table 868\n", + "Name: UserID, dtype: int64\n", + "Polars time: 21.907146692276\n", + "Polars return:\n", + " shape: (10, 2)\n", + "┌─────────────────────────────────┬────────┐\n", + "│ SearchPhrase ┆ UserID │\n", + "│ --- ┆ --- │\n", + "│ str ┆ u32 │\n", + "╞═════════════════════════════════╪════════╡\n", + "│ албатрутдин ┆ 3373 │\n", + "│ какой областиков ┆ 2360 │\n", + "│ смотреть онлайн ┆ 2199 │\n", + "│ смотреть онлайн бесплатно ┆ 2066 │\n", + "│ какой областиницы цена ┆ 1860 │\n", + "│ смотреть ┆ 1498 │\n", + "│ экзоидные ┆ 1256 │\n", + "│ тайны избавлению акручить ┆ 960 │\n", + "│ какой области за улыбки бмв е3… ┆ 936 │\n", + "│ galaxy table ┆ 868 │\n", + "└─────────────────────────────────┴────────┘\n", + "Q14 SELECT SearchEngineID, SearchPhrase, COUNT(*) AS c FROM hits WHERE SearchPhrase <> '' GROUP BY SearchEngineID, SearchPhrase ORDER BY c DESC LIMIT 10;\n", + "DuckDB time: 0.12200570106506348\n", + "DuckDB return:\n", + " SearchEngineID SearchPhrase c\n", + "0 3 албатрутдин 3016\n", + "1 2 албатрутдин 2585\n", + "2 2 какой областиницы цена 2432\n", + "3 2 смотреть онлайн 1964\n", + "4 2 смотреть онлайн бесплатно 1765\n", + "5 2 какой областиков 1599\n", + "6 2 смотреть 1291\n", + "7 2 тайны избавлению акручить 1273\n", + "8 2 экзоидные 1187\n", + "9 2 тихоокеанский списание пределирова 1079\n", + "chDB time: 0.11324310302734375\n", + "chDB return:\n", + " 3,\"албатрутдин\",3016\n", + "2,\"албатрутдин\",2585\n", + "2,\"какой областиницы цена\",2432\n", + "2,\"смотреть онлайн\",1964\n", + "2,\"смотреть онлайн бесплатно\",1765\n", + "2,\"какой областиков\",1599\n", + "2,\"смотреть\",1291\n", + "2,\"тайны избавлению акручить\",1273\n", + "2,\"экзоидные\",1187\n", + "2,\"тихоокеанский списание пределирова\",1079\n", + "\n", + "Pandas time: 8.408371925354004\n", + "Pandas return:\n", + " SearchEngineID SearchPhrase \n", + "3 албатрутдин 3016\n", + "2 албатрутдин 2585\n", + " какой областиницы цена 2432\n", + " смотреть онлайн 1964\n", + " смотреть онлайн бесплатно 1765\n", + " какой областиков 1599\n", + " смотреть 1291\n", + " тайны избавлению акручить 1273\n", + " экзоидные 1187\n", + " тихоокеанский списание пределирова 1079\n", + "dtype: int64\n", + "Polars time: 0.22452998161315918\n", + "Polars return:\n", + " shape: (10, 3)\n", + "┌────────────────┬─────────────────────────────────┬───────┐\n", + "│ SearchEngineID ┆ SearchPhrase ┆ count │\n", + "│ --- ┆ --- ┆ --- │\n", + "│ i16 ┆ str ┆ u32 │\n", + "╞════════════════╪═════════════════════════════════╪═══════╡\n", + "│ 3 ┆ албатрутдин ┆ 3016 │\n", + "│ 2 ┆ албатрутдин ┆ 2585 │\n", + "│ 2 ┆ какой областиницы цена ┆ 2432 │\n", + "│ 2 ┆ смотреть онлайн ┆ 1964 │\n", + "│ 2 ┆ смотреть онлайн бесплатно ┆ 1765 │\n", + "│ 2 ┆ какой областиков ┆ 1599 │\n", + "│ 2 ┆ смотреть ┆ 1291 │\n", + "│ 2 ┆ тайны избавлению акручить ┆ 1273 │\n", + "│ 2 ┆ экзоидные ┆ 1187 │\n", + "│ 2 ┆ тихоокеанский списание предели… ┆ 1079 │\n", + "└────────────────┴─────────────────────────────────┴───────┘\n", + "Q15 SELECT UserID, COUNT(*) FROM hits GROUP BY UserID ORDER BY COUNT(*) DESC LIMIT 10;\n", + "DuckDB time: 0.07353830337524414\n", + "DuckDB return:\n", + " UserID count_star()\n", + "0 1313338681122956954 15792\n", + "1 1907779576417363396 6229\n", + "2 5730251990344211405 6019\n", + "3 7280399273658728997 6015\n", + "4 835157184735512989 5211\n", + "5 823824530034798601 2897\n", + "6 938290163257834024 2685\n", + "7 4931847376428061501 2537\n", + "8 6949028786848070043 2496\n", + "9 2763860660987168393 2179\n", + "chDB time: 0.09562420845031738\n", + "chDB return:\n", + " 1313338681122956954,15792\n", + "1907779576417363396,6229\n", + "5730251990344211405,6019\n", + "7280399273658728997,6015\n", + "835157184735512989,5211\n", + "823824530034798601,2897\n", + "938290163257834024,2685\n", + "4931847376428061501,2537\n", + "6949028786848070043,2496\n", + "2763860660987168393,2179\n", + "\n", + "Pandas time: 0.803398847579956\n", + "Pandas return:\n", + " UserID\n", + "1313338681122956954 15792\n", + "1907779576417363396 6229\n", + "5730251990344211405 6019\n", + "7280399273658728997 6015\n", + "835157184735512989 5211\n", + "823824530034798601 2897\n", + "938290163257834024 2685\n", + "4931847376428061501 2537\n", + "6949028786848070043 2496\n", + "2763860660987168393 2179\n", + "dtype: int64\n", + "Polars time: 0.13240408897399902\n", + "Polars return:\n", + " shape: (10, 2)\n", + "┌─────────────────────┬───────┐\n", + "│ UserID ┆ count │\n", + "│ --- ┆ --- │\n", + "│ i64 ┆ u32 │\n", + "╞═════════════════════╪═══════╡\n", + "│ 1313338681122956954 ┆ 15792 │\n", + "│ 1907779576417363396 ┆ 6229 │\n", + "│ 5730251990344211405 ┆ 6019 │\n", + "│ 7280399273658728997 ┆ 6015 │\n", + "│ 835157184735512989 ┆ 5211 │\n", + "│ 823824530034798601 ┆ 2897 │\n", + "│ 938290163257834024 ┆ 2685 │\n", + "│ 4931847376428061501 ┆ 2537 │\n", + "│ 6949028786848070043 ┆ 2496 │\n", + "│ 2763860660987168393 ┆ 2179 │\n", + "└─────────────────────┴───────┘\n", + "Q16 SELECT UserID, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, SearchPhrase ORDER BY COUNT(*) DESC LIMIT 10;\n", + "DuckDB time: 0.14850163459777832\n", + "DuckDB return:\n", + " UserID SearchPhrase count_star()\n", + "0 1313338681122956954 15792\n", + "1 1907779576417363396 6229\n", + "2 5730251990344211405 6019\n", + "3 7280399273658728997 6015\n", + "4 835157184735512989 5209\n", + "5 823824530034798601 2897\n", + "6 938290163257834024 2684\n", + "7 4931847376428061501 2537\n", + "8 6949028786848070043 2496\n", + "9 2763860660987168393 2179\n", + "chDB time: 0.14157438278198242\n", + "chDB return:\n", + " 1313338681122956954,\"\",15792\n", + "1907779576417363396,\"\",6229\n", + "5730251990344211405,\"\",6019\n", + "7280399273658728997,\"\",6015\n", + "835157184735512989,\"\",5209\n", + "823824530034798601,\"\",2897\n", + "938290163257834024,\"\",2684\n", + "4931847376428061501,\"\",2537\n", + "6949028786848070043,\"\",2496\n", + "2763860660987168393,\"\",2179\n", + "\n", + "Pandas time: 25.871644020080566\n", + "Pandas return:\n", + " UserID SearchPhrase\n", + "1313338681122956954 15792\n", + "1907779576417363396 6229\n", + "5730251990344211405 6019\n", + "7280399273658728997 6015\n", + "835157184735512989 5209\n", + "823824530034798601 2897\n", + "938290163257834024 2684\n", + "4931847376428061501 2537\n", + "6949028786848070043 2496\n", + "2763860660987168393 2179\n", + "dtype: int64\n", + "Polars time: 0.19805002212524414\n", + "Polars return:\n", + " shape: (10, 3)\n", + "┌─────────────────────┬──────────────┬───────┐\n", + "│ UserID ┆ SearchPhrase ┆ count │\n", + "│ --- ┆ --- ┆ --- │\n", + "│ i64 ┆ str ┆ u32 │\n", + "╞═════════════════════╪══════════════╪═══════╡\n", + "│ 1313338681122956954 ┆ ┆ 15792 │\n", + "│ 1907779576417363396 ┆ ┆ 6229 │\n", + "│ 5730251990344211405 ┆ ┆ 6019 │\n", + "│ 7280399273658728997 ┆ ┆ 6015 │\n", + "│ 835157184735512989 ┆ ┆ 5209 │\n", + "│ 823824530034798601 ┆ ┆ 2897 │\n", + "│ 938290163257834024 ┆ ┆ 2684 │\n", + "│ 4931847376428061501 ┆ ┆ 2537 │\n", + "│ 6949028786848070043 ┆ ┆ 2496 │\n", + "│ 2763860660987168393 ┆ ┆ 2179 │\n", + "└─────────────────────┴──────────────┴───────┘\n", + "Q17 SELECT UserID, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, SearchPhrase LIMIT 10;\n", + "DuckDB time: 0.15410304069519043\n", + "DuckDB return:\n", + " UserID SearchPhrase count_star()\n", + "0 1282336503961623558 13\n", + "1 1282552915108844899 1\n", + "2 1283150242784481791 4\n", + "3 1283160278491966765 2\n", + "4 1283385628089856902 1\n", + "5 1283747091700878296 3\n", + "6 1284305367319766517 3\n", + "7 1284375869523640234 4\n", + "8 1284450031855186099 4\n", + "9 1284916964337633798 1\n", + "chDB time: 0.13107848167419434\n", + "chDB return:\n", + " 64240392369242065,\"\",1\n", + "8485164694783743007,\"сила 1 сезон 14 серии петти америвод\",1\n", + "3144110468796962613,\"\",2\n", + "51580606420354603,\"\",1\n", + "119657425828985633,\"\",1\n", + "977272874002472411,\"заказочный бёрс\",1\n", + "7510587892824469257,\"sia 265 сезон 6 серии\",1\n", + "1127993622760818270,\"\",8\n", + "9195634693788664967,\"шнекамске воды легенда проекты двухэтажа б у гармошку тсж от челябинсов\",1\n", + "2013228973047199893,\"\",85\n", + "\n", + "Pandas time: 2.864093542098999\n", + "Pandas return:\n", + " UserID SearchPhrase \n", + "-9223344277659414581 1\n", + " банкомитетаться обзор напитанов 1\n", + "-9223178030934747259 2\n", + "-9223054401365629534 4\n", + "-9223019776173944577 3\n", + "-9222967852064643611 1\n", + "-9222533007323865344 админивэна в материи бесплатно в хорошем к 1\n", + "-9222500201428208294 1\n", + "-9222499855151233211 двигательная 1\n", + "-9222343920573852356 1\n", + "dtype: int64\n", + "Polars time: 0.12165307998657227\n", + "Polars return:\n", + " shape: (10, 3)\n", + "┌─────────────────────┬─────────────────────────────────┬─────┐\n", + "│ UserID ┆ SearchPhrase ┆ len │\n", + "│ --- ┆ --- ┆ --- │\n", + "│ i64 ┆ str ┆ u32 │\n", + "╞═════════════════════╪═════════════════════════════════╪═════╡\n", + "│ 1202649428574067922 ┆ ┆ 4 │\n", + "│ 3088214486324770626 ┆ ┆ 1 │\n", + "│ 750099004694464647 ┆ ┆ 1 │\n", + "│ 1396180892504645808 ┆ ┆ 1 │\n", + "│ 5534083794574392552 ┆ ┆ 3 │\n", + "│ 4192165551454517056 ┆ ┆ 1 │\n", + "│ 1624213886631847400 ┆ ┆ 1 │\n", + "│ 2379205851600461426 ┆ горостопортал сколь ┆ 1 │\n", + "│ 98053846500825040 ┆ 5-ая пежо сектомастурбация ┆ 1 │\n", + "│ 2265155232299302110 ┆ универмени+дорожно д 114:38 се… ┆ 1 │\n", + "└─────────────────────┴─────────────────────────────────┴─────┘\n", + "Q18 SELECT UserID, extract(minute FROM EventTime) AS m, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, m, SearchPhrase ORDER BY COUNT(*) DESC LIMIT 10;\n", + "DuckDB time: 0.20395946502685547\n", + "DuckDB return:\n", + " UserID m SearchPhrase count_star()\n", + "0 1313338681122956954 33 324\n", + "1 1313338681122956954 30 323\n", + "2 1313338681122956954 28 314\n", + "3 1313338681122956954 31 311\n", + "4 1313338681122956954 29 308\n", + "5 1313338681122956954 34 306\n", + "6 1313338681122956954 32 302\n", + "7 1313338681122956954 27 296\n", + "8 1313338681122956954 12 296\n", + "9 1313338681122956954 8 294\n", + "chDB time: 0.19141697883605957\n", + "chDB return:\n", + " 1313338681122956954,33,\"\",324\n", + "1313338681122956954,30,\"\",323\n", + "1313338681122956954,28,\"\",314\n", + "1313338681122956954,31,\"\",311\n", + "1313338681122956954,29,\"\",308\n", + "1313338681122956954,34,\"\",306\n", + "1313338681122956954,32,\"\",302\n", + "1313338681122956954,12,\"\",296\n", + "1313338681122956954,27,\"\",296\n", + "1313338681122956954,10,\"\",294\n", + "\n", + "Pandas time: 54.19946789741516\n", + "Pandas return:\n", + " UserID EventTime SearchPhrase\n", + "1313338681122956954 33 324\n", + " 30 323\n", + " 28 314\n", + " 31 311\n", + " 29 308\n", + " 34 306\n", + " 32 302\n", + " 12 296\n", + " 27 296\n", + " 8 294\n", + "dtype: int64\n", + "Polars time: 0.4682021141052246\n", + "Polars return:\n", + " shape: (10, 4)\n", + "┌─────────────────────┬───────────┬──────────────┬───────┐\n", + "│ UserID ┆ EventTime ┆ SearchPhrase ┆ count │\n", + "│ --- ┆ --- ┆ --- ┆ --- │\n", + "│ i64 ┆ i8 ┆ str ┆ u32 │\n", + "╞═════════════════════╪═══════════╪══════════════╪═══════╡\n", + "│ 1313338681122956954 ┆ 33 ┆ ┆ 324 │\n", + "│ 1313338681122956954 ┆ 30 ┆ ┆ 323 │\n", + "│ 1313338681122956954 ┆ 28 ┆ ┆ 314 │\n", + "│ 1313338681122956954 ┆ 31 ┆ ┆ 311 │\n", + "│ 1313338681122956954 ┆ 29 ┆ ┆ 308 │\n", + "│ 1313338681122956954 ┆ 34 ┆ ┆ 306 │\n", + "│ 1313338681122956954 ┆ 32 ┆ ┆ 302 │\n", + "│ 1313338681122956954 ┆ 12 ┆ ┆ 296 │\n", + "│ 1313338681122956954 ┆ 27 ┆ ┆ 296 │\n", + "│ 1313338681122956954 ┆ 10 ┆ ┆ 294 │\n", + "└─────────────────────┴───────────┴──────────────┴───────┘\n", + "Q19 SELECT UserID FROM hits WHERE UserID = 435090932899640449;\n", + "DuckDB time: 0.027832508087158203\n", + "DuckDB return:\n", + " Empty DataFrame\n", + "Columns: [UserID]\n", + "Index: []\n", + "chDB time: 0.02431321144104004\n", + "chDB return:\n", + " \n", + "Pandas time: 0.00603938102722168\n", + "Pandas return:\n", + " Empty DataFrame\n", + "Columns: [WatchID, JavaEnable, Title, GoodEvent, EventTime, EventDate, CounterID, ClientIP, RegionID, UserID, CounterClass, OS, UserAgent, URL, Referer, IsRefresh, RefererCategoryID, RefererRegionID, URLCategoryID, URLRegionID, ResolutionWidth, ResolutionHeight, ResolutionDepth, FlashMajor, FlashMinor, FlashMinor2, NetMajor, NetMinor, UserAgentMajor, UserAgentMinor, CookieEnable, JavascriptEnable, IsMobile, MobilePhone, MobilePhoneModel, Params, IPNetworkID, TraficSourceID, SearchEngineID, SearchPhrase, AdvEngineID, IsArtifical, WindowClientWidth, WindowClientHeight, ClientTimeZone, ClientEventTime, SilverlightVersion1, SilverlightVersion2, SilverlightVersion3, SilverlightVersion4, PageCharset, CodeVersion, IsLink, IsDownload, IsNotBounce, FUniqID, OriginalURL, HID, IsOldCounter, IsEvent, IsParameter, DontCountHits, WithHash, HitColor, LocalEventTime, Age, Sex, Income, Interests, Robotness, RemoteIP, WindowName, OpenerName, HistoryLength, BrowserLanguage, BrowserCountry, SocialNetwork, SocialAction, HTTPError, SendTiming, DNSTiming, ConnectTiming, ResponseStartTiming, ResponseEndTiming, FetchTiming, SocialSourceNetworkID, SocialSourcePage, ParamPrice, ParamOrderID, ParamCurrency, ParamCurrencyID, OpenstatServiceName, OpenstatCampaignID, OpenstatAdID, OpenstatSourceID, UTMSource, UTMMedium, UTMCampaign, UTMContent, UTMTerm, ...]\n", + "Index: []\n", + "\n", + "[0 rows x 105 columns]\n", + "Polars time: 0.004159688949584961\n", + "Polars return:\n", + " shape: (0, 105)\n", + "┌─────────┬────────────┬───────┬───────────┬───┬──────────┬─────────────┬─────────┬──────┐\n", + "│ WatchID ┆ JavaEnable ┆ Title ┆ GoodEvent ┆ … ┆ HasGCLID ┆ RefererHash ┆ URLHash ┆ CLID │\n", + "│ --- ┆ --- ┆ --- ┆ --- ┆ ┆ --- ┆ --- ┆ --- ┆ --- │\n", + "│ i64 ┆ i16 ┆ str ┆ i16 ┆ ┆ i16 ┆ i64 ┆ i64 ┆ i32 │\n", + "╞═════════╪════════════╪═══════╪═══════════╪═══╪══════════╪═════════════╪═════════╪══════╡\n", + "└─────────┴────────────┴───────┴───────────┴───┴──────────┴─────────────┴─────────┴──────┘\n", + "Q20 SELECT COUNT(*) FROM hits WHERE URL LIKE '%google%';\n", + "DuckDB time: 0.1195058822631836\n", + "DuckDB return:\n", + " count_star()\n", + "0 1687\n", + "chDB time: 0.1032094955444336\n", + "chDB return:\n", + " 1687\n", + "\n", + "Pandas time: 2.1695151329040527\n", + "Pandas return:\n", + " 1687\n", + "Polars time: 0.18016314506530762\n", + "Polars return:\n", + " 1687\n", + "Q21 SELECT SearchPhrase, MIN(URL), COUNT(*) AS c FROM hits WHERE URL LIKE '%google%' AND SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;\n", + "DuckDB time: 0.13406634330749512\n", + "DuckDB return:\n", + " SearchPhrase \\\n", + "0 римском качественны for cry \n", + "1 тест драмы смотреть \n", + "2 рецепты салдингал иркутске дом в при \n", + "3 испанч боб новости дейская \n", + "4 dynamic gigabyte-kuzbassassins 6 получение сер... \n", + "5 dynamic gigabyte-kuzbassassins 6 полос \n", + "6 обезболи все переватель 2gis.ru/ha отзывы \n", + "7 dynamic gigabyte-kuzbassassins 6 получение сер... \n", + "8 рецепты и мистиков в минские \n", + "9 римского духово-зуево \n", + "\n", + " min(URL) c \n", + "0 http:%2F%2Fwwww.googlead&aktional 24 \n", + "1 http:%2F%2Fwwww.googlead&aktional 6 \n", + "2 http:%2F%2Fwwww.googlead&aktional 6 \n", + "3 http://smeshariki.ru/recipes/show/6840872&traf... 5 \n", + "4 http://forum2/play.google.ru/main.aspx?brands][1] 4 \n", + "5 http://forum2/play.google.ru/main.aspx?brands][1] 4 \n", + "6 http://sslovarenovyy-s-koroshen_apps.googleBR 3 \n", + "7 http://forum2/play.google.ru/main.aspx?brands][1] 3 \n", + "8 http:%2F%2Fwwww.googlead&aktional 3 \n", + "9 http:%2F%2Fwwww.googlead&aktional 3 \n", + "chDB time: 0.11961245536804199\n", + "chDB return:\n", + " \"римском качественны for cry\",\"http:%2F%2Fwwww.googlead&aktional\",24\n", + "\"тест драмы смотреть\",\"http:%2F%2Fwwww.googlead&aktional\",6\n", + "\"рецепты салдингал иркутске дом в при\",\"http:%2F%2Fwwww.googlead&aktional\",6\n", + "\"испанч боб новости дейская\",\"http://smeshariki.ru/recipes/show/6840872&trafkey=6d0fc12c54059/loukhaAUXI&where=all&filter/Mitsubishi/google\",5\n", + "\"dynamic gigabyte-kuzbassassins 6 полос\",\"http://forum2/play.google.ru/main.aspx?brands][1]\",4\n", + "\"dynamic gigabyte-kuzbassassins 6 получение серия сперминат машинки\",\"http://forum2/play.google.ru/main.aspx?brands][1]\",4\n", + "\"обезболи все переватель 2gis.ru/ha отзывы\",\"http://sslovarenovyy-s-koroshen_apps.googleBR\",3\n", + "\"оборт\",\"http://forum2/play.google/eduabroad_input_bdsmpeople\",3\n", + "\"маски в горает устантиров в работа поездки видео\",\"http://forum2/play.google.ru/main.aspx?brands][1]\",3\n", + "\"dynamic gigabyte-kuzbassassins 6 получение серия сперми\",\"http://forum2/play.google.ru/main.aspx?brands][1]\",3\n", + "\n", + "Pandas time: 2.556438684463501\n", + "Pandas return:\n", + " URL \\\n", + "SearchPhrase \n", + "римском качественны for cry http:%2F%2Fwwww.googlead&aktional \n", + "рецепты салдингал иркутске дом в при http:%2F%2Fwwww.googlead&aktional \n", + "тест драмы смотреть http:%2F%2Fwwww.googlead&aktional \n", + "испанч боб новости дейская http://smeshariki.ru/recipes/show/6840872&traf... \n", + "dynamic gigabyte-kuzbassassins 6 полос http://forum2/play.google.ru/main.aspx?brands][1] \n", + "dynamic gigabyte-kuzbassassins 6 получение сери... http://forum2/play.google.ru/main.aspx?brands][1] \n", + "dynamic gigabyte-kuzbassassins 6 получение сери... http://forum2/play.google.ru/main.aspx?brands][1] \n", + "маски в горает устантиров в работа поездки видео http://forum2/play.google.ru/main.aspx?brands][1] \n", + "обезболи все переватель 2gis.ru/ha отзывы http://sslovarenovyy-s-koroshen_apps.googleBR \n", + "оборт http://forum2/play.google/eduabroad_input_bdsm... \n", + "\n", + " SearchPhrase \n", + "SearchPhrase \n", + "римском качественны for cry 24 \n", + "рецепты салдингал иркутске дом в при 6 \n", + "тест драмы смотреть 6 \n", + "испанч боб новости дейская 5 \n", + "dynamic gigabyte-kuzbassassins 6 полос 4 \n", + "dynamic gigabyte-kuzbassassins 6 получение сери... 4 \n", + "dynamic gigabyte-kuzbassassins 6 получение сери... 3 \n", + "маски в горает устантиров в работа поездки видео 3 \n", + "обезболи все переватель 2gis.ru/ha отзывы 3 \n", + "оборт 3 \n", + "Polars error: \"count\" not found\n", + "Q22 SELECT SearchPhrase, MIN(URL), MIN(Title), COUNT(*) AS c, COUNT(DISTINCT UserID) FROM hits WHERE Title LIKE '%Google%' AND URL NOT LIKE '%.google.%' AND SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;\n", + "DuckDB time: 0.2151491641998291\n", + "DuckDB return:\n", + " SearchPhrase \\\n", + "0 винки медведь смотреть фильмы 2013 смотреть \n", + "1 винки медведь смотреть фильмы чеческия \n", + "2 винки медведь смотреть объятный ветерин \n", + "3 кино 2009) смотреть онлайн бессмерти мк в росс... \n", + "4 коптимиквиды юриста с роуз рая \n", + "5 коптимиквиды юрий жд ворожные моем \n", + "6 самаре на мира матки видео 21.03.2013 смотреть \n", + "7 тайны избавитель в владимира для университет м... \n", + "8 ведомосквиталия страции \n", + "9 винки медведь смотреть \n", + "\n", + " min(URL) \\\n", + "0 http://smeshariki.ru/a-folder-4/#page-3.2.1; W... \n", + "1 http://smeshariki.ru/a-folder-4/#page-3.2.1; W... \n", + "2 http://smeshariki.ru/index.ua/newsru.com/ifram... \n", + "3 http://domchelove.ru/#!/search/page \n", + "4 https://produkty%2Fpulove.ru/booklyattion-war-... \n", + "5 https://produkty%2Fpulove.ru/booklyattion-war-... \n", + "6 http://smeshariki.ru/GameMain.aspx#location.ru... \n", + "7 http://smeshariki.ru/index.ua/baby=1&with_exch... \n", + "8 https://produkty%2Fpulove.ru/booklyattion-war-... \n", + "9 http://smeshariki.ru/index.ua/newsru.com/ifram... \n", + "\n", + " min(Title) c \\\n", + "0 видеорегионалу Google 112 \n", + "1 видеорегионалу Google - Досториа Базар автомоб... 21 \n", + "2 видеорегионалу Google Gel - Курганизмом, дачи - 14 \n", + "3 Далее о коллекции в GIMI LANCIA 0K3Y318104 про... 13 \n", + "4 Легко на участные участников., Цены - Стильная... 12 \n", + "5 Легко на участные участников., Цены - Стильная... 8 \n", + "6 Квартиры в проекты - Google rientalie Goal!, 2... 7 \n", + "7 Амитин обувь - Яндекс.Видео+текст песен Google... 6 \n", + "8 Легко на участные участников., Цены - Стильная... 6 \n", + "9 видеорегионалу Google - модного языке - Пульс 6 \n", + "\n", + " count(DISTINCT UserID) \n", + "0 81 \n", + "1 18 \n", + "2 10 \n", + "3 9 \n", + "4 3 \n", + "5 2 \n", + "6 1 \n", + "7 4 \n", + "8 2 \n", + "9 4 \n", + "chDB time: 0.18262386322021484\n", + "chDB return:\n", + " \"винки медведь смотреть фильмы 2013 смотреть\",\"http://smeshariki.ru/a-folder-4/#page-3.2.1; WOW64; Edition=1&input_age2/#over-1.3.adfox.ru/image=0&engineVolumeFrom\",\"видеорегионалу Google\",112,81\n", + "\"винки медведь смотреть фильмы чеческия\",\"http://smeshariki.ru/a-folder-4/#page-3.2.1; WOW64; Edition=1&input_age2/?page_type=cated_card_330709_1_116105812\",\"видеорегионалу Google - Досториа Базар автомобили купить манские характеринбу\",21,18\n", + "\"винки медведь смотреть объятный ветерин\",\"http://smeshariki.ru/index.ua/newsru.com/iframe_right%3D43%26bt%3D278885%26bid%3D278885%26bid%3D0%26nid%3D0%26rnd%3D1216/0001-04/19442-173-recentry=&op_product\",\"видеорегионалу Google Gel - Курганизмом, дачи - \",14,10\n", + "\"кино 2009) смотреть онлайн бессмерти мк в россипед\",\"http://domchelove.ru/#!/search/page\",\"Далее о коллекции в GIMI LANCIA 0K3Y318104 продать Google, go-go в регистрии — Мой Крым\",13,9\n", + "\"коптимиквиды юриста с роуз рая\",\"https://produkty%2Fpulove.ru/booklyattion-war-sinij-9182/women\",\"Легко на участные участников., Цены - Стильная парнем. Саганрог догадения : Турции, купить у 10 дне кольные машинки не представки - Новая с избиение спродажа: котята 2014 г.в. Цена: 47500-10ECO060 – -------- купить квартиру Оренбург (России Galantrax Flamiliada Google, Nо 18 фотоконверк Супер Кардиган\",12,3\n", + "\"коптимиквиды юрий жд ворожные моем\",\"https://produkty%2Fpulove.ru/booklyattion-war-sinij-9182/women\",\"Легко на участные участников., Цены - Стильная парнем. Саганрог догадения : Турции, купить у 10 дне кольные машинки не представки - Новая с избиение спродажа: котята 2014 г.в. Цена: 47500-10ECO060 – -------- купить квартиру Оренбург (России Galantrax Flamiliada Google, Nо 18 фотоконверк Супер Кардиган\",8,2\n", + "\"самаре на мира матки видео 21.03.2013 смотреть\",\"http://smeshariki.ru/GameMain.aspx#location.ru/anketa.by/01/00101\",\"Квартиры в проекты - Google rientalie Goal!, 2002 г.в. Цена: 400 общая 66 (626) 1989 г.в. ( 1599$, (г. Доминиров VLC medved out Dlya versplay в боль, Красный\",7,1\n", + "\"ведомосквиталия страции\",\"https://produkty%2Fpulove.ru/booklyattion-war-sinij-9182/women\",\"Легко на участные участников., Цены - Стильная парнем. Саганрог догадения : Турции, купить у 10 дне кольные машинки не представки - Новая с избиение спродажа: котята 2014 г.в. Цена: 47500-10ECO060 – -------- купить квартиру Оренбург (России Galantrax Flamiliada Google, Nо 18 фотоконверк Супер Кардиган\",6,2\n", + "\"винки медведь смотреть\",\"http://smeshariki.ru/index.ua/newsru.com/iframe_right%3D43%26bt%3D90%26nid%3D8235.html?1=1&cid=147960&wi=1280&lo=http://video.yandex\",\"видеорегионалу Google - модного языке - Пульс\",6,4\n", + "\"юрий духовиковый тумбой магазин\",\"http://video.yandex.ru/ch/meters=0&price_do=¤cy\",\"Ежедневное - Пульс цены | купить ул., доступные Челябинский рифленогопользовать Audio - Компании Google Agila дорабль в\",6,6\n", + "\n", + "Pandas time: 8.927100419998169\n", + "Pandas return:\n", + " URL \\\n", + "SearchPhrase \n", + "винки медведь смотреть фильмы 2013 смотреть http://smeshariki.ru/a-folder-4/#page-3.2.1; W... \n", + "винки медведь смотреть фильмы чеческия http://smeshariki.ru/a-folder-4/#page-3.2.1; W... \n", + "винки медведь смотреть объятный ветерин http://smeshariki.ru/index.ua/newsru.com/ifram... \n", + "кино 2009) смотреть онлайн бессмерти мк в россипед http://domchelove.ru/#!/search/page \n", + "коптимиквиды юриста с роуз рая https://produkty%2Fpulove.ru/booklyattion-war-... \n", + "коптимиквиды юрий жд ворожные моем https://produkty%2Fpulove.ru/booklyattion-war-... \n", + "самаре на мира матки видео 21.03.2013 смотреть http://smeshariki.ru/GameMain.aspx#location.ru... \n", + "ведомосквиталия страции https://produkty%2Fpulove.ru/booklyattion-war-... \n", + "винки медведь смотреть http://smeshariki.ru/index.ua/newsru.com/ifram... \n", + "тайны избавитель в владимира для университет ма... http://smeshariki.ru/index.ua/baby=1&with_exch... \n", + "\n", + " Title \\\n", + "SearchPhrase \n", + "винки медведь смотреть фильмы 2013 смотреть видеорегионалу Google \n", + "винки медведь смотреть фильмы чеческия видеорегионалу Google - Досториа Базар автомоб... \n", + "винки медведь смотреть объятный ветерин видеорегионалу Google Gel - Курганизмом, дачи - \n", + "кино 2009) смотреть онлайн бессмерти мк в россипед Далее о коллекции в GIMI LANCIA 0K3Y318104 про... \n", + "коптимиквиды юриста с роуз рая Легко на участные участников., Цены - Стильная... \n", + "коптимиквиды юрий жд ворожные моем Легко на участные участников., Цены - Стильная... \n", + "самаре на мира матки видео 21.03.2013 смотреть Квартиры в проекты - Google rientalie Goal!, 2... \n", + "ведомосквиталия страции Легко на участные участников., Цены - Стильная... \n", + "винки медведь смотреть видеорегионалу Google - модного языке - Пульс \n", + "тайны избавитель в владимира для университет ма... Амитин обувь - Яндекс.Видео+текст песен Google... \n", + "\n", + " SearchPhrase UserID \n", + "SearchPhrase \n", + "винки медведь смотреть фильмы 2013 смотреть 112 81 \n", + "винки медведь смотреть фильмы чеческия 21 18 \n", + "винки медведь смотреть объятный ветерин 14 10 \n", + "кино 2009) смотреть онлайн бессмерти мк в россипед 13 9 \n", + "коптимиквиды юриста с роуз рая 12 3 \n", + "коптимиквиды юрий жд ворожные моем 8 2 \n", + "самаре на мира матки видео 21.03.2013 смотреть 7 1 \n", + "ведомосквиталия страции 6 2 \n", + "винки медведь смотреть 6 4 \n", + "тайны избавитель в владимира для университет ма... 6 4 \n", + "Polars error: \"count\" not found\n", + "Q23 SELECT * FROM hits WHERE URL LIKE '%google%' ORDER BY EventTime LIMIT 10;\n", + "DuckDB time: 0.46820592880249023\n", + "DuckDB return:\n", + " WatchID JavaEnable \\\n", + "0 7106264041910208868 1 \n", + "1 6801361853621701142 1 \n", + "2 7370235307579469118 1 \n", + "3 7299686183082339643 1 \n", + "4 5241207090454501610 1 \n", + "5 8762858360217969903 1 \n", + "6 5937582489445775385 1 \n", + "7 5585474130921985177 1 \n", + "8 8119609642256502216 1 \n", + "9 8851521334882706019 0 \n", + "\n", + " Title GoodEvent \\\n", + "0 ГОСТЕЛЬНОЗЕРОГ ГОРНЫЙ ДОЖДЬ! - Спорт, алюминис... 1 \n", + "1 Смешарики SW | SexWife: Женщин - Яндекс.Афиша@... 1 \n", + "2 1 \n", + "3 Торт и продам Ford (Форд - IRR.ru (Работа и ро... 1 \n", + "4 Торт и продам Ford (Форд - IRR.ru (Работа и ро... 1 \n", + "5 1 \n", + "6 прода. Поиск повый бизнес 1 \n", + "7 Торт и продам Ford (Форд - IRR.ru (Работа и ро... 1 \n", + "8 1 \n", + "9 Вопростовый стал Петербурге. Последников в про... 1 \n", + "\n", + " EventTime EventDate CounterID ClientIP RegionID \\\n", + "0 2013-07-01 23:31:03 2013-07-02 46429 1249584689 229 \n", + "1 2013-07-01 23:44:01 2013-07-02 40367 -1231921306 2 \n", + "2 2013-07-01 23:44:14 2013-07-02 40367 -1231921306 2 \n", + "3 2013-07-01 23:59:17 2013-07-02 46429 1553640326 115 \n", + "4 2013-07-02 01:59:29 2013-07-02 46429 1553640326 115 \n", + "5 2013-07-02 01:59:42 2013-07-02 46429 1553640326 115 \n", + "6 2013-07-02 02:46:42 2013-07-02 63621 -1801466482 229 \n", + "7 2013-07-02 02:50:56 2013-07-02 46429 -1366734181 44 \n", + "8 2013-07-02 02:51:09 2013-07-02 46429 -1366734181 44 \n", + "9 2013-07-02 05:18:07 2013-07-02 39641 1897404057 12 \n", + "\n", + " UserID ... UTMSource UTMMedium UTMCampaign \\\n", + "0 72720560134547761 ... \n", + "1 434272054218180613 ... \n", + "2 434272054218180613 ... \n", + "3 168449836300271247 ... \n", + "4 168449836300271247 ... feedburner banner ad_cpamarketing \n", + "5 168449836300271247 ... feedburner banner ad_cpamarketing \n", + "6 5639771411007874048 ... \n", + "7 6484173929977037196 ... \n", + "8 6484173929977037196 ... \n", + "9 2147819122923023112 ... \n", + "\n", + " UTMContent UTMTerm FromTag HasGCLID RefererHash \\\n", + "0 0 -3651842497912472547 \n", + "1 0 5673263859390493714 \n", + "2 0 -296158784638538920 \n", + "3 0 -2923571516118524499 \n", + "4 0 4719160989640449379 \n", + "5 0 -296158784638538920 \n", + "6 0 532293348752290058 \n", + "7 0 -43688538285913943 \n", + "8 0 -296158784638538920 \n", + "9 0 6285928018624721980 \n", + "\n", + " URLHash CLID \n", + "0 5528743655405710480 0 \n", + "1 -6433683654023857482 0 \n", + "2 -6433683654023857482 0 \n", + "3 1337795999976243980 0 \n", + "4 2196566102793075843 0 \n", + "5 2196566102793075843 0 \n", + "6 -7069763488219331997 0 \n", + "7 1337795999976243980 0 \n", + "8 1337795999976243980 0 \n", + "9 -6462309590271025210 0 \n", + "\n", + "[10 rows x 105 columns]\n", + "chDB time: 0.45491504669189453\n", + "chDB return:\n", + " 7106264041910208868,1,\"ГОСТЕЛЬНОЗЕРОГ ГОРНЫЙ ДОЖДЬ! - Спорт, алюминистик : играй!!!! ЦЕНЫ!! фотоальбомы и океансов в продать-взять-о и видео#!/search?film.TV) — растер - : купить\",1,\"2013-07-02 07:31:03.000000000\",\"2013-07-02 08:00:00.000000000\",46429,1249584689,229,72720560134547761,0,44,46,\"http://smeshariki.ru/users/2013-07-15,2013&To=03.07.2013-07-01:2013-07-17545/content/searchivemix).mp3ex.net/page.google-plata.ru\",\"http://smeshariki.ru/page.aspx?Countforpartments/7416543000¤cy=RUR/carpartner-peskie_kollen&item-1/nf-6\",0,16000,158,9911,216,1996,1781,37,15,7,\"700\",0,0,22,\"D�\",1,1,0,0,\"\",\"\",2221747,-1,0,\"\",0,0,1485,688,135,1372775257,4,0,46077,0,\"windows-1251;charset\",1601,0,0,0,6266009505159221854,\"\",1038228209,0,0,0,0,0,\"g\",1372737370,0,2,0,0,0,1184697127,36437,-1,2,\"S0\",\"�\f\",\"\",\"\",0,0,0,3,83,26,0,0,\"\",0,\"\",\"NH\u001c\",0,\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",0,-3651842497912472547,5528743655405710480,0\n", + "6801361853621701142,1,\"Смешарики SW | SexWife: Женщин - Яндекс.Афиша@Mail.Ru - магазин модный Журнал: Абдельцев Honda с производств\",1,\"2013-07-02 07:44:01.000000000\",\"2013-07-02 08:00:00.000000000\",40367,-1231921306,2,434272054218180613,0,126,5,\"http://interinburg/detail.google,yandex.aspx#location=products\",\"http://yandex.ru/domkadrov.irr.ru/yandsearch&caU82MlBVHpMbWgwYld3JTNEZnRTYUh$MGNEb3ZMMmh2Ykc5YWf6VzcO3ZqI91PIqcL84YZg&bvm=bv.48705608,d.bGE&cad=rja&ved=0CEYQFjAD&url=http://rsdn.ru%2F~книги%2FКомпот и болгари\",0,14550,952,13164,16,1996,1781,37,15,7,\"700\",0,0,22,\"D�\",1,1,0,0,\"\",\"\",1999580,3,1,\"ани пух ходу\",0,0,567,577,135,1372784689,4,1,15738,0,\"windows\",1601,0,0,0,8352815799795997820,\"\",376469337,0,0,0,0,0,\"5\",1372759377,31,1,2,6,43,-815706743,-1,-1,-1,\"S0\",\"�\f\",\"\",\"\",0,0,0,0,453,45,0,0,\"\",0,\"\",\"NH\u001c\",0,\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",0,5673263859390493714,-6433683654023857482,0\n", + "7370235307579469118,1,\"\",1,\"2013-07-02 07:44:14.000000000\",\"2013-07-02 08:00:00.000000000\",40367,-1231921306,2,434272054218180613,0,126,5,\"http://interinburg/detail.google,yandex.aspx#location=products\",\"\",0,0,0,13164,16,1996,1781,37,15,7,\"700\",0,0,22,\"D�\",1,1,0,0,\"\",\"\",1999580,0,0,\"\",0,1,567,577,135,1372784704,4,1,15738,0,\"windows\",1601,0,0,1,8352815799795997820,\"\",376469337,0,0,0,1,0,\"5\",1372759391,31,1,2,6,43,-815706743,-1,-1,-1,\"S0\",\"�\f\",\"\",\"\",0,441,0,0,0,0,0,0,\"\",0,\"\",\"NH\u001c\",0,\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",0,-296158784638538920,-6433683654023857482,0\n", + "7299686183082339643,1,\"Торт и продам Ford (Форд - IRR.ru (Работа и роды (Clean Almera Money Spear Napa Roomantic (Сцены | квартира, ИЩУ КОГДАНА (страличиваны Москве и новостей в мире - Клуб «Локом Смайлики — Игры в Таможня.ру - играя фабрики Андрей | Флок Devel in Moscow Rust turbo (190) 1997 г.в. Цена для авто №1: автомобилей\",1,\"2013-07-02 07:59:17.000000000\",\"2013-07-02 08:00:00.000000000\",46429,1553640326,115,168449836300271247,0,44,5,\"http://smeshariki.ru/user=googleb18f7700.6384695,926425668_hornolyanovosibirsk.irr.ru/yekategory_id\",\"http://smeshariki.ru/page/Search?text=одинокауты&clid\",0,16000,158,9911,216,1087,938,37,15,7,\"700\",0,0,22,\"nA\",1,1,0,0,\"\",\"\",2247425,-1,0,\"\",0,0,1095,872,794,1372772092,4,0,46077,0,\"windows-1251;charset\",1601,0,0,0,9058901074909920800,\"\",276778963,0,0,0,0,0,\"g\",1372752817,22,2,2,113,19,1816213259,45529,-1,13,\"S0\",\"�\f\",\"\",\"\",0,0,0,0,841,321,0,0,\"\",0,\"\",\"NH\u001c\",0,\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",0,-2923571516118524499,1337795999976243980,0\n", + "5241207090454501610,1,\"Торт и продам Ford (Форд - IRR.ru (Работа и роды (Clean Almera Money Spear Napa Roomantic (Сцены | квартира, ИЩУ КОГДАНА (страличиваны Москве и новостей в мире - Клуб «Локом Смайлики — Игры в Таможня.ру - играя фабрики Андрей | Флок Devel in Moscow Rust turbo (190) 1997 г.в. Цена для авто №1: автомобилей\",1,\"2013-07-02 09:59:29.000000000\",\"2013-07-02 08:00:00.000000000\",46429,1553640326,115,168449836300271247,0,44,5,\"http://smeshariki.ru/user=googleb18f7700.63870&statuiroveltietsk.irr.ru/search/ab_district=32895080910\",\"http://yandex.ru/ch/world&balcon/germanske.ru/moskovskaya\",0,0,0,9911,216,1087,938,37,15,7,\"700\",0,0,22,\"D�\",1,1,0,0,\"\",\"\",2247425,1,0,\"\",0,0,1095,872,794,1372777525,4,0,46077,0,\"windows-1251;charset\",1601,0,0,0,9058901074909920800,\"\",943360174,0,0,0,0,0,\"5\",1372757844,22,2,2,113,19,1816213259,34235,-1,1,\"�\",\"�\f\",\"\",\"\",0,0,105,348,684,203,12733,0,\"\",0,\"\",\"NH\u001c\",0,\"\",\"\",\"\",\"\",\"feedburner\",\"banner\",\"ad_cpamarketing\",\"\",\"\",\"\",0,4719160989640449379,2196566102793075843,0\n", + "8762858360217969903,1,\"\",1,\"2013-07-02 09:59:42.000000000\",\"2013-07-02 08:00:00.000000000\",46429,1553640326,115,168449836300271247,0,44,5,\"http://smeshariki.ru/user=googleb18f7700.63870&statuiroveltietsk.irr.ru/search/ab_district=32895080910\",\"\",0,0,0,9911,216,1087,938,37,15,7,\"700\",0,0,22,\"D�\",1,1,0,0,\"\",\"\",2247425,0,0,\"\",0,1,1095,872,794,1372777540,4,0,46077,0,\"windows-1251;charset\",1601,0,0,1,9058901074909920800,\"\",943360174,0,0,0,1,0,\"5\",1372757858,22,2,2,113,19,1816213259,34235,-1,1,\"�\",\"�\f\",\"\",\"\",0,963,0,0,0,0,0,0,\"\",0,\"\",\"NH\u001c\",0,\"\",\"\",\"\",\"\",\"feedburner\",\"banner\",\"ad_cpamarketing\",\"\",\"\",\"\",0,-296158784638538920,2196566102793075843,0\n", + "5937582489445775385,1,\"прода. Поиск повый бизнес\",1,\"2013-07-02 10:46:42.000000000\",\"2013-07-02 08:00:00.000000000\",63621,-1801466482,229,5639771411007874048,1,44,3,\"http://wildberrior/en-ru/Lingvo/#1.php3?google.ru/mymail.ru/kids\",\"https://go.mail/folders/list.html?cityid=False&rubrics=&location=search?text\",0,14550,952,8953,3,1996,1781,23,15,7,\"700\",0,0,26,\"D�\",1,1,0,0,\"\",\"\",2865462,3,2,\"чесное малософский\",0,0,1261,972,135,1372750201,4,1,16561,0,\"windows-1251;charset\",1,0,0,0,8716223275232676708,\"\",82371000,0,0,0,0,0,\"5\",1372713610,50,1,3,4,22,-1086971547,-1,-1,-1,\"S0\",\"�\f\",\"\",\"\",0,0,0,0,0,0,0,0,\"\",0,\"\",\"NH\u001c\",0,\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",0,532293348752290058,-7069763488219331997,0\n", + "5585474130921985177,1,\"Торт и продам Ford (Форд - IRR.ru (Работа и роды (Clean Almera Money Spear Napa Roomantic (Сцены | квартира, ИЩУ КОГДАНА (страличиваны Москве и новостей в мире - Клуб «Локом Смайлики — Игры в Таможня.ру - играя фабрики Андрей | Флок Devel in Moscow Rust turbo (190) 1997 г.в. Цена для авто №1: автомобилей\",1,\"2013-07-02 10:50:56.000000000\",\"2013-07-02 08:00:00.000000000\",46429,-1366734181,44,6484173929977037196,0,74,5,\"http://smeshariki.ru/user=googleb18f7700.6384695,926425668_hornolyanovosibirsk.irr.ru/yekategory_id\",\"http://loveplanet.ru/main.aspx?nspn=0.4331/metalliance\",0,16163,952,9911,216,339,777,23,0,0,\"\",0,0,18,\"D�\",1,1,1,0,\"\",\"\",1203796,11,0,\"\",0,0,724,2027,322,1372777472,0,0,0,0,\"windows-1251;charset\",1601,0,0,0,5395316558279634204,\"\",738865320,0,0,0,0,0,\"g\",1372783399,22,2,2,14652,92,-189312298,9866,-1,1,\"S0\",\"h1\",\"\",\"\",0,0,116,204,1657,972,1674,1,\"\",0,\"\",\"NH\u001c\",0,\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",0,-43688538285913943,1337795999976243980,0\n", + "8119609642256502216,1,\"\",1,\"2013-07-02 10:51:09.000000000\",\"2013-07-02 08:00:00.000000000\",46429,-1366734181,44,6484173929977037196,0,74,5,\"http://smeshariki.ru/user=googleb18f7700.6384695,926425668_hornolyanovosibirsk.irr.ru/yekategory_id\",\"\",0,0,0,9911,216,339,777,23,0,0,\"\",0,0,18,\"D�\",1,1,1,0,\"\",\"\",1203796,0,0,\"\",0,1,724,2027,322,1372777497,0,0,0,0,\"windows-1251;charset\",1601,0,0,1,5395316558279634204,\"\",738865320,0,0,0,1,0,\"5\",1372783413,22,2,2,14652,92,-189312298,9866,-1,1,\"S0\",\"h1\",\"\",\"\",0,2215,0,0,0,0,0,0,\"\",0,\"\",\"NH\u001c\",0,\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",0,-296158784638538920,1337795999976243980,0\n", + "8851521334882706019,0,\"Вопростовый стал Петербурге. Последников в продажа, центре парфюм\",1,\"2013-07-02 13:18:07.000000000\",\"2013-07-02 08:00:00.000000000\",39641,1897404057,12,2147819122923023112,1,44,3,\"http://domchel.ru/board.php?id=767128787753779.eccord.ru/?trafkey=4300&brand=RAINBOW - bonprix.ru/googleuserId=4&ord=крючком\",\"http://wildberries.ru/invid=19753.html?sort=rating\",0,256,20,426,22,1368,554,23,15,7,\"700\",0,0,17,\"D�\",1,1,0,0,\"\",\"\",3665494,-1,0,\"\",0,0,1863,726,135,1372753287,4,1,16561,0,\"windows-1251;charset\",1,0,0,0,7356234246907529433,\"\",1031476090,0,0,0,0,0,\"5\",1372772961,0,1,0,0,0,1451194443,-1,-1,-1,\"S0\",\"�\f\",\"\",\"\",0,0,0,0,0,0,0,0,\"\",0,\"\",\"NH\u001c\",0,\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",0,6285928018624721980,-6462309590271025210,0\n", + "\n", + "Pandas time: 2.1939539909362793\n", + "Pandas return:\n", + " WatchID JavaEnable \\\n", + "8858875 7106264041910208868 1 \n", + "8896307 6801361853621701142 1 \n", + "8896308 7370235307579469118 1 \n", + "9646993 7299686183082339643 1 \n", + "9646995 5241207090454501610 1 \n", + "9646996 8762858360217969903 1 \n", + "8937843 5937582489445775385 1 \n", + "9656506 5585474130921985177 1 \n", + "9656507 8119609642256502216 1 \n", + "9619305 8851521334882706019 0 \n", + "\n", + " Title GoodEvent \\\n", + "8858875 ГОСТЕЛЬНОЗЕРОГ ГОРНЫЙ ДОЖДЬ! - Спорт, алюминис... 1 \n", + "8896307 Смешарики SW | SexWife: Женщин - Яндекс.Афиша@... 1 \n", + "8896308 1 \n", + "9646993 Торт и продам Ford (Форд - IRR.ru (Работа и ро... 1 \n", + "9646995 Торт и продам Ford (Форд - IRR.ru (Работа и ро... 1 \n", + "9646996 1 \n", + "8937843 прода. Поиск повый бизнес 1 \n", + "9656506 Торт и продам Ford (Форд - IRR.ru (Работа и ро... 1 \n", + "9656507 1 \n", + "9619305 Вопростовый стал Петербурге. Последников в про... 1 \n", + "\n", + " EventTime EventDate CounterID ClientIP RegionID \\\n", + "8858875 2013-07-01 23:31:03 2013-07-02 46429 1249584689 229 \n", + "8896307 2013-07-01 23:44:01 2013-07-02 40367 -1231921306 2 \n", + "8896308 2013-07-01 23:44:14 2013-07-02 40367 -1231921306 2 \n", + "9646993 2013-07-01 23:59:17 2013-07-02 46429 1553640326 115 \n", + "9646995 2013-07-02 01:59:29 2013-07-02 46429 1553640326 115 \n", + "9646996 2013-07-02 01:59:42 2013-07-02 46429 1553640326 115 \n", + "8937843 2013-07-02 02:46:42 2013-07-02 63621 -1801466482 229 \n", + "9656506 2013-07-02 02:50:56 2013-07-02 46429 -1366734181 44 \n", + "9656507 2013-07-02 02:51:09 2013-07-02 46429 -1366734181 44 \n", + "9619305 2013-07-02 05:18:07 2013-07-02 39641 1897404057 12 \n", + "\n", + " UserID ... UTMSource UTMMedium UTMCampaign \\\n", + "8858875 72720560134547761 ... \n", + "8896307 434272054218180613 ... \n", + "8896308 434272054218180613 ... \n", + "9646993 168449836300271247 ... \n", + "9646995 168449836300271247 ... feedburner banner ad_cpamarketing \n", + "9646996 168449836300271247 ... feedburner banner ad_cpamarketing \n", + "8937843 5639771411007874048 ... \n", + "9656506 6484173929977037196 ... \n", + "9656507 6484173929977037196 ... \n", + "9619305 2147819122923023112 ... \n", + "\n", + " UTMContent UTMTerm FromTag HasGCLID RefererHash \\\n", + "8858875 0 -3651842497912472547 \n", + "8896307 0 5673263859390493714 \n", + "8896308 0 -296158784638538920 \n", + "9646993 0 -2923571516118524499 \n", + "9646995 0 4719160989640449379 \n", + "9646996 0 -296158784638538920 \n", + "8937843 0 532293348752290058 \n", + "9656506 0 -43688538285913943 \n", + "9656507 0 -296158784638538920 \n", + "9619305 0 6285928018624721980 \n", + "\n", + " URLHash CLID \n", + "8858875 5528743655405710480 0 \n", + "8896307 -6433683654023857482 0 \n", + "8896308 -6433683654023857482 0 \n", + "9646993 1337795999976243980 0 \n", + "9646995 2196566102793075843 0 \n", + "9646996 2196566102793075843 0 \n", + "8937843 -7069763488219331997 0 \n", + "9656506 1337795999976243980 0 \n", + "9656507 1337795999976243980 0 \n", + "9619305 -6462309590271025210 0 \n", + "\n", + "[10 rows x 105 columns]\n", + "Polars time: 0.1826305389404297\n", + "Polars return:\n", + " shape: (10, 105)\n", + "┌────────────┬────────────┬────────────┬───────────┬───┬──────────┬────────────┬────────────┬──────┐\n", + "│ WatchID ┆ JavaEnable ┆ Title ┆ GoodEvent ┆ … ┆ HasGCLID ┆ RefererHas ┆ URLHash ┆ CLID │\n", + "│ --- ┆ --- ┆ --- ┆ --- ┆ ┆ --- ┆ h ┆ --- ┆ --- │\n", + "│ i64 ┆ i16 ┆ str ┆ i16 ┆ ┆ i16 ┆ --- ┆ i64 ┆ i32 │\n", + "│ ┆ ┆ ┆ ┆ ┆ ┆ i64 ┆ ┆ │\n", + "╞════════════╪════════════╪════════════╪═══════════╪═══╪══════════╪════════════╪════════════╪══════╡\n", + "│ 7106264041 ┆ 1 ┆ ГОСТЕЛЬНОЗ ┆ 1 ┆ … ┆ 0 ┆ -365184249 ┆ 5528743655 ┆ 0 │\n", + "│ 910208868 ┆ ┆ ЕРОГ ┆ ┆ ┆ ┆ 7912472547 ┆ 405710480 ┆ │\n", + "│ ┆ ┆ ГОРНЫЙ ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ ┆ ┆ ДОЖДЬ! -… ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ 6801361853 ┆ 1 ┆ Смешарики ┆ 1 ┆ … ┆ 0 ┆ 5673263859 ┆ -643368365 ┆ 0 │\n", + "│ 621701142 ┆ ┆ SW | ┆ ┆ ┆ ┆ 390493714 ┆ 4023857482 ┆ │\n", + "│ ┆ ┆ SexWife: ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ ┆ ┆ Женщин… ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ 7370235307 ┆ 1 ┆ ┆ 1 ┆ … ┆ 0 ┆ -296158784 ┆ -643368365 ┆ 0 │\n", + "│ 579469118 ┆ ┆ ┆ ┆ ┆ ┆ 638538920 ┆ 4023857482 ┆ │\n", + "│ 7299686183 ┆ 1 ┆ Торт и ┆ 1 ┆ … ┆ 0 ┆ -292357151 ┆ 1337795999 ┆ 0 │\n", + "│ 082339643 ┆ ┆ продам ┆ ┆ ┆ ┆ 6118524499 ┆ 976243980 ┆ │\n", + "│ ┆ ┆ Ford (Форд ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ ┆ ┆ - IRR… ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ 5241207090 ┆ 1 ┆ Торт и ┆ 1 ┆ … ┆ 0 ┆ 4719160989 ┆ 2196566102 ┆ 0 │\n", + "│ 454501610 ┆ ┆ продам ┆ ┆ ┆ ┆ 640449379 ┆ 793075843 ┆ │\n", + "│ ┆ ┆ Ford (Форд ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ ┆ ┆ - IRR… ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ 8762858360 ┆ 1 ┆ ┆ 1 ┆ … ┆ 0 ┆ -296158784 ┆ 2196566102 ┆ 0 │\n", + "│ 217969903 ┆ ┆ ┆ ┆ ┆ ┆ 638538920 ┆ 793075843 ┆ │\n", + "│ 5937582489 ┆ 1 ┆ прода. ┆ 1 ┆ … ┆ 0 ┆ 5322933487 ┆ -706976348 ┆ 0 │\n", + "│ 445775385 ┆ ┆ Поиск ┆ ┆ ┆ ┆ 52290058 ┆ 8219331997 ┆ │\n", + "│ ┆ ┆ повый ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ ┆ ┆ бизнес ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ 5585474130 ┆ 1 ┆ Торт и ┆ 1 ┆ … ┆ 0 ┆ -436885382 ┆ 1337795999 ┆ 0 │\n", + "│ 921985177 ┆ ┆ продам ┆ ┆ ┆ ┆ 85913943 ┆ 976243980 ┆ │\n", + "│ ┆ ┆ Ford (Форд ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ ┆ ┆ - IRR… ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ 8119609642 ┆ 1 ┆ ┆ 1 ┆ … ┆ 0 ┆ -296158784 ┆ 1337795999 ┆ 0 │\n", + "│ 256502216 ┆ ┆ ┆ ┆ ┆ ┆ 638538920 ┆ 976243980 ┆ │\n", + "│ 8851521334 ┆ 0 ┆ Вопростовы ┆ 1 ┆ … ┆ 0 ┆ 6285928018 ┆ -646230959 ┆ 0 │\n", + "│ 882706019 ┆ ┆ й стал Пет ┆ ┆ ┆ ┆ 624721980 ┆ 0271025210 ┆ │\n", + "│ ┆ ┆ ербурге. ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ ┆ ┆ П… ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "└────────────┴────────────┴────────────┴───────────┴───┴──────────┴────────────┴────────────┴──────┘\n", + "Q24 SELECT SearchPhrase FROM hits WHERE SearchPhrase <> '' ORDER BY EventTime LIMIT 10;\n", + "DuckDB time: 0.12598967552185059\n", + "DuckDB return:\n", + " SearchPhrase\n", + "0 ночно китая женщины\n", + "1 20 робигудинг для маске\n", + "2 маршава нибудь в омске главнованные автобаза ф...\n", + "3 выкупонорманский рублендодат\n", + "4 комнаталогическая область дней партная вечер э...\n", + "5 кифосов calib.ru/show отзывы июнь 2013 смотрет...\n", + "6 безруководительное пирование групп иридиана фл...\n", + "7 орфограмма дачи 1 части заработа в казар кобак...\n", + "8 доктор крем качественна каленко 1 литель заезды\n", + "9 киа x2-02 mhz/17.3 казань\n", + "chDB time: 0.04124927520751953\n", + "chDB return:\n", + " \"ночно китая женщины\"\n", + "\"маршава нибудь в омске главнованные автобаза физовать\"\n", + "\"20 робигудинг для маске\"\n", + "\"выкупонорманский рублендодат\"\n", + "\"комнаталогическая область дней партная вечер это чудо видео\"\n", + "\"кифосов calib.ru/show отзывы июнь 2013 смотреть онлайн\"\n", + "\"безруководительное пирование групп иридиана флешмоб\"\n", + "\"доктор крем качественна каленко 1 литель заезды\"\n", + "\"орфограмма дачи 1 части заработа в казар кобакал по гал поль+стели пожар\"\n", + "\"киа x2-02 mhz/17.3 казань\"\n", + "\n", + "Pandas time: 2.326787233352661\n", + "Pandas return:\n", + " SearchPhrase\n", + "5936205 ночно китая женщины\n", + "8064786 маршава нибудь в омске главнованные автобаза ф...\n", + "8851501 20 робигудинг для маске\n", + "8853400 выкупонорманский рублендодат\n", + "8828551 комнаталогическая область дней партная вечер э...\n", + "5290447 кифосов calib.ru/show отзывы июнь 2013 смотрет...\n", + "222072 безруководительное пирование групп иридиана фл...\n", + "6023605 орфограмма дачи 1 части заработа в казар кобак...\n", + "3608548 доктор крем качественна каленко 1 литель заезды\n", + "8916195 киа x2-02 mhz/17.3 казань\n", + "Polars time: 0.26840853691101074\n", + "Polars return:\n", + " shape: (10, 1)\n", + "┌─────────────────────────────────┐\n", + "│ SearchPhrase │\n", + "│ --- │\n", + "│ str │\n", + "╞═════════════════════════════════╡\n", + "│ ночно китая женщины │\n", + "│ маршава нибудь в омске главнов… │\n", + "│ 20 робигудинг для маске │\n", + "│ выкупонорманский рублендодат │\n", + "│ комнаталогическая область дней… │\n", + "│ кифосов calib.ru/show отзывы и… │\n", + "│ безруководительное пирование г… │\n", + "│ доктор крем качественна каленк… │\n", + "│ орфограмма дачи 1 части зарабо… │\n", + "│ киа x2-02 mhz/17.3 казань │\n", + "└─────────────────────────────────┘\n", + "Q25 SELECT SearchPhrase FROM hits WHERE SearchPhrase <> '' ORDER BY SearchPhrase LIMIT 10;\n", + "DuckDB time: 0.22957587242126465\n", + "DuckDB return:\n", + " SearchPhrase\n", + "0 прав\n", + "1 светы женске 2 сезон\n", + "2 !куги для мясорубкина зимняя из виолет\n", + "3 $_get am2 купейн в хорошем\n", + "4 $_get it of goodbye minecraft\n", + "5 $_get_series v stell \n", + "6 $_poslandon.ru/moscow 2 торговлю\n", + "7 $d причина\n", + "8 % стасия\n", + "9 ф купить шарарасота в турбации\n", + "chDB time: 0.03507590293884277\n", + "chDB return:\n", + " \" прав\"\n", + "\" светы женске 2 сезон\"\n", + "\"!куги для мясорубкина зимняя из виолет\"\n", + "\"$_get am2 купейн в хорошем\"\n", + "\"$_get it of goodbye minecraft\"\n", + "\"$_get_series v stell \"\n", + "\"$_poslandon.ru/moscow 2 торговлю\"\n", + "\"$d причина\"\n", + "\"% стасия\"\n", + "\"ф купить шарарасота в турбации\"\n", + "\n", + "Pandas time: 3.904980421066284\n", + "Pandas return:\n", + " SearchPhrase\n", + "8581793 прав\n", + "3506663 светы женске 2 сезон\n", + "3400727 !куги для мясорубкина зимняя из виолет\n", + "9472812 $_get am2 купейн в хорошем\n", + "7982167 $_get it of goodbye minecraft\n", + "3842151 $_get_series v stell \n", + "1859999 $_poslandon.ru/moscow 2 торговлю\n", + "7981418 $d причина\n", + "1467180 % стасия\n", + "5058192 ф купить шарарасота в турбации\n", + "Polars time: 0.29048991203308105\n", + "Polars return:\n", + " shape: (10, 1)\n", + "┌─────────────────────────────────┐\n", + "│ SearchPhrase │\n", + "│ --- │\n", + "│ str │\n", + "╞═════════════════════════════════╡\n", + "│ прав │\n", + "│ светы женске 2 сезон │\n", + "│ !куги для мясорубкина зимняя и… │\n", + "│ $_get am2 купейн в хорошем │\n", + "│ $_get it of goodbye minecraft │\n", + "│ $_get_series v stell │\n", + "│ $_poslandon.ru/moscow 2 торгов… │\n", + "│ $d причина │\n", + "│ % стасия │\n", + "│ ф купить шарарасота в тур… │\n", + "└─────────────────────────────────┘\n", + "Q26 SELECT SearchPhrase FROM hits WHERE SearchPhrase <> '' ORDER BY EventTime, SearchPhrase LIMIT 10;\n", + "DuckDB time: 0.17848896980285645\n", + "DuckDB return:\n", + " SearchPhrase\n", + "0 ночно китая женщины\n", + "1 20 робигудинг для маске\n", + "2 маршава нибудь в омске главнованные автобаза ф...\n", + "3 выкупонорманский рублендодат\n", + "4 комнаталогическая область дней партная вечер э...\n", + "5 кифосов calib.ru/show отзывы июнь 2013 смотрет...\n", + "6 безруководительное пирование групп иридиана фл...\n", + "7 доктор крем качественна каленко 1 литель заезды\n", + "8 орфограмма дачи 1 части заработа в казар кобак...\n", + "9 киа x2-02 mhz/17.3 казань\n", + "chDB time: 0.04461336135864258\n", + "chDB return:\n", + " \"ночно китая женщины\"\n", + "\"20 робигудинг для маске\"\n", + "\"маршава нибудь в омске главнованные автобаза физовать\"\n", + "\"выкупонорманский рублендодат\"\n", + "\"комнаталогическая область дней партная вечер это чудо видео\"\n", + "\"кифосов calib.ru/show отзывы июнь 2013 смотреть онлайн\"\n", + "\"безруководительное пирование групп иридиана флешмоб\"\n", + "\"доктор крем качественна каленко 1 литель заезды\"\n", + "\"орфограмма дачи 1 части заработа в казар кобакал по гал поль+стели пожар\"\n", + "\"киа x2-02 mhz/17.3 казань\"\n", + "\n", + "Pandas time: 4.101372003555298\n", + "Pandas return:\n", + " SearchPhrase\n", + "5936205 ночно китая женщины\n", + "8851501 20 робигудинг для маске\n", + "8064786 маршава нибудь в омске главнованные автобаза ф...\n", + "8853400 выкупонорманский рублендодат\n", + "8828551 комнаталогическая область дней партная вечер э...\n", + "5290447 кифосов calib.ru/show отзывы июнь 2013 смотрет...\n", + "222072 безруководительное пирование групп иридиана фл...\n", + "3608548 доктор крем качественна каленко 1 литель заезды\n", + "6023605 орфограмма дачи 1 части заработа в казар кобак...\n", + "8916195 киа x2-02 mhz/17.3 казань\n", + "Polars time: 0.2666144371032715\n", + "Polars return:\n", + " shape: (10, 1)\n", + "┌─────────────────────────────────┐\n", + "│ SearchPhrase │\n", + "│ --- │\n", + "│ str │\n", + "╞═════════════════════════════════╡\n", + "│ ночно китая женщины │\n", + "│ 20 робигудинг для маске │\n", + "│ маршава нибудь в омске главнов… │\n", + "│ выкупонорманский рублендодат │\n", + "│ комнаталогическая область дней… │\n", + "│ кифосов calib.ru/show отзывы и… │\n", + "│ безруководительное пирование г… │\n", + "│ доктор крем качественна каленк… │\n", + "│ орфограмма дачи 1 части зарабо… │\n", + "│ киа x2-02 mhz/17.3 казань │\n", + "└─────────────────────────────────┘\n", + "Q27 SELECT CounterID, AVG(STRLEN(URL)) AS l, COUNT(*) AS c FROM hits WHERE URL <> '' GROUP BY CounterID HAVING COUNT(*) > 100000 ORDER BY l DESC LIMIT 25;\n", + "DuckDB time: 0.11969971656799316\n", + "DuckDB return:\n", + " CounterID l c\n", + "0 122612 240.497421 638968\n", + "1 1634 194.214108 118954\n", + "2 199550 110.135978 868030\n", + "3 62 91.785075 106493\n", + "4 3922 87.610597 924581\n", + "5 146891 83.673486 103873\n", + "6 38 76.566724 163720\n", + "7 1483 71.329880 254380\n", + "8 46429 70.677078 474517\n", + "9 117917 69.057769 106389\n", + "10 2264 67.726046 106496\n", + "11 95978 66.667985 106459\n", + "12 5822 63.244084 106496\n", + "13 56820 61.759401 141825\n", + "14 76325 61.406250 106496\n", + "15 145496 59.204685 212991\n", + "16 7525 57.203026 166447\n", + "17 119677 56.938542 212992\n", + "18 178321 54.154552 196600\n", + "19 128858 52.101964 182613\n", + "20 99062 50.314067 248574\n", + "21 140443 45.106507 158469\n", + "22 105857 40.067755 501707\n", + "23 69154 37.375145 112655\n", + "24 63217 34.884080 106496\n", + "chDB time: 0.13816475868225098\n", + "chDB return:\n", + " 122612,240.49742084110628,638968\n", + "1634,194.21410797451117,118954\n", + "199550,110.13597801919289,868030\n", + "62,91.78507507535707,106493\n", + "3922,87.61059658374982,924581\n", + "146891,83.6734858914251,103873\n", + "38,76.56672367456633,163720\n", + "1483,71.32988049374951,254380\n", + "46429,70.67707795505746,474517\n", + "117917,69.05776913026723,106389\n", + "2264,67.72604604867789,106496\n", + "95978,66.66798485802046,106459\n", + "5822,63.24408428485577,106496\n", + "56820,61.75940066983959,141825\n", + "76325,61.40625,106496\n", + "145496,59.204684704987535,212991\n", + "7525,57.20302558772462,166447\n", + "119677,56.93854229266827,212992\n", + "178321,54.154552390640895,196600\n", + "128858,52.101964263223316,182613\n", + "99062,50.31406744068165,248574\n", + "140443,45.10650663536717,158469\n", + "105857,40.067754685503694,501707\n", + "69154,37.37514535528827,112655\n", + "63217,34.88408015324519,106496\n", + "\n", + "Pandas time: 12.009446859359741\n", + "Pandas return:\n", + " URL 8.830068e+01\n", + "CounterID 6.427221e+06\n", + "dtype: float64\n", + "Polars time: 0.8645925521850586\n", + "Polars return:\n", + " shape: (25, 3)\n", + "┌───────────┬────────┬────────┐\n", + "│ CounterID ┆ l ┆ c │\n", + "│ --- ┆ --- ┆ --- │\n", + "│ i32 ┆ i64 ┆ u32 │\n", + "╞═══════════╪════════╪════════╡\n", + "│ 3922 ┆ 924581 ┆ 924581 │\n", + "│ 199550 ┆ 868030 ┆ 868030 │\n", + "│ 122612 ┆ 638968 ┆ 638968 │\n", + "│ 105857 ┆ 501707 ┆ 501707 │\n", + "│ 46429 ┆ 474517 ┆ 474517 │\n", + "│ … ┆ … ┆ … │\n", + "│ 76325 ┆ 106496 ┆ 106496 │\n", + "│ 62 ┆ 106493 ┆ 106493 │\n", + "│ 95978 ┆ 106459 ┆ 106459 │\n", + "│ 117917 ┆ 106389 ┆ 106389 │\n", + "│ 146891 ┆ 103873 ┆ 103873 │\n", + "└───────────┴────────┴────────┘\n", + "Q28 SELECT REGEXP_REPLACE(Referer, '^https?://(?:www\\.)?([^/]+)/.*$', '\\1') AS k, AVG(STRLEN(Referer)) AS l, COUNT(*) AS c, MIN(Referer) FROM hits WHERE Referer <> '' GROUP BY k HAVING COUNT(*) > 100000 ORDER BY l DESC LIMIT 25;\n", + "DuckDB time: 0.3662426471710205\n", + "DuckDB return:\n", + " k l c \\\n", + "0 google.ru 115.428171 248632 \n", + "1 go.mail 108.236910 943831 \n", + "2 mysw.info 91.010802 101187 \n", + "3 yandex.ru 70.708391 539043 \n", + "4 video.yandex.ru 69.446100 111587 \n", + "5 wildberries.ru 68.842407 144442 \n", + "6 auto.ria.ua 62.589863 132368 \n", + "7 smeshariki.ru 58.874002 517890 \n", + "8 irr.ru 54.573039 176522 \n", + "9 bdsmpeople.ru 53.188323 207351 \n", + "10 google.com 38.552378 327560 \n", + "11 http:%2F%2Fwwww.ukr 19.000000 118140 \n", + "\n", + " min(Referer) \n", + "0 http://google.ru/ \n", + "1 http://go.mail/?ID=26175503771357/pic/8437/1/c... \n", + "2 http://mysw.info/ \n", + "3 http://yandex.ru/ \n", + "4 http://video.yandex.ru//emilka%2Firr.ru/regionId \n", + "5 http://wildberries.ru/ \n", + "6 http://auto.ria.ua/ \n", + "7 http://smeshariki.ru/ \n", + "8 http://irr.ru/121838478&text=профнастя картира... \n", + "9 http://bdsmpeople.ru/ \n", + "10 http://google.com/&http://ria \n", + "11 http:%2F%2Fwwww.ukr \n", + "chDB time: 0.2807183265686035\n", + "chDB return:\n", + " \"google.ru\",115.42817095144632,248632,\"http://google.ru/\"\n", + "\"go.mail\",108.23690999765847,943831,\"http://go.mail/?ID=26175503771357/pic/8437/1/courtner-pub-61589792\"\n", + "\"mysw.info\",91.01080178283772,101187,\"http://mysw.info/\"\n", + "\"yandex.ru\",70.7083906107676,539043,\"http://yandex.ru/\"\n", + "\"video.yandex.ru\",69.44610035219156,111587,\"http://video.yandex.ru//emilka%2Firr.ru/regionId\"\n", + "\"wildberries.ru\",68.84240733304718,144442,\"http://wildberries.ru/\"\n", + "\"auto.ria.ua\",62.589863108908496,132368,\"http://auto.ria.ua/\"\n", + "\"smeshariki.ru\",58.87400220123965,517890,\"http://smeshariki.ru/\"\n", + "\"irr.ru\",54.573039054622086,176522,\"http://irr.ru/121838478&text=профнастя картиральский&source=android\"\n", + "\"bdsmpeople.ru\",53.18832318146524,207351,\"http://bdsmpeople.ru/\"\n", + "\"google.com\",38.55237819025522,327560,\"http://google.com/&http://ria\"\n", + "\"http:%2F%2Fwwww.ukr\",19,118140,\"http:%2F%2Fwwww.ukr\"\n", + "\n", + "Pandas time: 30.86491560935974\n", + "Pandas return:\n", + " Referer\n", + "min_referer http://auto.ria.ua/\n", + "average_length 74.443681\n", + "Polars time: 6.171788692474365\n", + "Polars return:\n", + " shape: (12, 4)\n", + "┌─────────────────┬─────────┬─────────────────────────────────┬─────────┐\n", + "│ k ┆ l ┆ min_referer ┆ c │\n", + "│ --- ┆ --- ┆ --- ┆ --- │\n", + "│ str ┆ i64 ┆ str ┆ u32 │\n", + "╞═════════════════╪═════════╪═════════════════════════════════╪═════════╡\n", + "│ null ┆ 1802377 ┆ http:%2F%23id:14967.htm%3Fhash… ┆ 1802377 │\n", + "│ go.mail ┆ 943831 ┆ http://go.mail/?ID=26175503771… ┆ 943831 │\n", + "│ yandex.ru ┆ 539043 ┆ http://yandex.ru/ ┆ 539043 │\n", + "│ smeshariki.ru ┆ 517890 ┆ http://smeshariki.ru/ ┆ 517890 │\n", + "│ google.com ┆ 327560 ┆ http://google.com/&http://ria ┆ 327560 │\n", + "│ … ┆ … ┆ … ┆ … │\n", + "│ irr.ru ┆ 176522 ┆ http://irr.ru/121838478&text=п… ┆ 176522 │\n", + "│ wildberries.ru ┆ 144420 ┆ http://wildberries.ru/ ┆ 144420 │\n", + "│ auto.ria.ua ┆ 132368 ┆ http://auto.ria.ua/ ┆ 132368 │\n", + "│ video.yandex.ru ┆ 111587 ┆ http://video.yandex.ru//emilka… ┆ 111587 │\n", + "│ mysw.info ┆ 101187 ┆ http://mysw.info/ ┆ 101187 │\n", + "└─────────────────┴─────────┴─────────────────────────────────┴─────────┘\n", + "Q29 SELECT SUM(ResolutionWidth), SUM(ResolutionWidth + 1), SUM(ResolutionWidth + 2), SUM(ResolutionWidth + 3), SUM(ResolutionWidth + 4), SUM(ResolutionWidth + 5), SUM(ResolutionWidth + 6), SUM(ResolutionWidth + 7), SUM(ResolutionWidth + 8), SUM(ResolutionWidth + 9), SUM(ResolutionWidth + 10), SUM(ResolutionWidth + 11), SUM(ResolutionWidth + 12), SUM(ResolutionWidth + 13), SUM(ResolutionWidth + 14), SUM(ResolutionWidth + 15), SUM(ResolutionWidth + 16), SUM(ResolutionWidth + 17), SUM(ResolutionWidth + 18), SUM(ResolutionWidth + 19), SUM(ResolutionWidth + 20), SUM(ResolutionWidth + 21), SUM(ResolutionWidth + 22), SUM(ResolutionWidth + 23), SUM(ResolutionWidth + 24), SUM(ResolutionWidth + 25), SUM(ResolutionWidth + 26), SUM(ResolutionWidth + 27), SUM(ResolutionWidth + 28), SUM(ResolutionWidth + 29), SUM(ResolutionWidth + 30), SUM(ResolutionWidth + 31), SUM(ResolutionWidth + 32), SUM(ResolutionWidth + 33), SUM(ResolutionWidth + 34), SUM(ResolutionWidth + 35), SUM(ResolutionWidth + 36), SUM(ResolutionWidth + 37), SUM(ResolutionWidth + 38), SUM(ResolutionWidth + 39), SUM(ResolutionWidth + 40), SUM(ResolutionWidth + 41), SUM(ResolutionWidth + 42), SUM(ResolutionWidth + 43), SUM(ResolutionWidth + 44), SUM(ResolutionWidth + 45), SUM(ResolutionWidth + 46), SUM(ResolutionWidth + 47), SUM(ResolutionWidth + 48), SUM(ResolutionWidth + 49), SUM(ResolutionWidth + 50), SUM(ResolutionWidth + 51), SUM(ResolutionWidth + 52), SUM(ResolutionWidth + 53), SUM(ResolutionWidth + 54), SUM(ResolutionWidth + 55), SUM(ResolutionWidth + 56), SUM(ResolutionWidth + 57), SUM(ResolutionWidth + 58), SUM(ResolutionWidth + 59), SUM(ResolutionWidth + 60), SUM(ResolutionWidth + 61), SUM(ResolutionWidth + 62), SUM(ResolutionWidth + 63), SUM(ResolutionWidth + 64), SUM(ResolutionWidth + 65), SUM(ResolutionWidth + 66), SUM(ResolutionWidth + 67), SUM(ResolutionWidth + 68), SUM(ResolutionWidth + 69), SUM(ResolutionWidth + 70), SUM(ResolutionWidth + 71), SUM(ResolutionWidth + 72), SUM(ResolutionWidth + 73), SUM(ResolutionWidth + 74), SUM(ResolutionWidth + 75), SUM(ResolutionWidth + 76), SUM(ResolutionWidth + 77), SUM(ResolutionWidth + 78), SUM(ResolutionWidth + 79), SUM(ResolutionWidth + 80), SUM(ResolutionWidth + 81), SUM(ResolutionWidth + 82), SUM(ResolutionWidth + 83), SUM(ResolutionWidth + 84), SUM(ResolutionWidth + 85), SUM(ResolutionWidth + 86), SUM(ResolutionWidth + 87), SUM(ResolutionWidth + 88), SUM(ResolutionWidth + 89) FROM hits;\n", + "DuckDB time: 0.41875171661376953\n", + "DuckDB return:\n", + " sum(ResolutionWidth) sum((ResolutionWidth + 1)) \\\n", + "0 1.507779e+10 1.508779e+10 \n", + "\n", + " sum((ResolutionWidth + 2)) sum((ResolutionWidth + 3)) \\\n", + "0 1.509779e+10 1.510779e+10 \n", + "\n", + " sum((ResolutionWidth + 4)) sum((ResolutionWidth + 5)) \\\n", + "0 1.511779e+10 1.512779e+10 \n", + "\n", + " sum((ResolutionWidth + 6)) sum((ResolutionWidth + 7)) \\\n", + "0 1.513779e+10 1.514779e+10 \n", + "\n", + " sum((ResolutionWidth + 8)) sum((ResolutionWidth + 9)) ... \\\n", + "0 1.515779e+10 1.516779e+10 ... \n", + "\n", + " sum((ResolutionWidth + 80)) sum((ResolutionWidth + 81)) \\\n", + "0 1.587779e+10 1.588779e+10 \n", + "\n", + " sum((ResolutionWidth + 82)) sum((ResolutionWidth + 83)) \\\n", + "0 1.589779e+10 1.590779e+10 \n", + "\n", + " sum((ResolutionWidth + 84)) sum((ResolutionWidth + 85)) \\\n", + "0 1.591779e+10 1.592779e+10 \n", + "\n", + " sum((ResolutionWidth + 86)) sum((ResolutionWidth + 87)) \\\n", + "0 1.593779e+10 1.594779e+10 \n", + "\n", + " sum((ResolutionWidth + 88)) sum((ResolutionWidth + 89)) \n", + "0 1.595779e+10 1.596779e+10 \n", + "\n", + "[1 rows x 90 columns]\n", + "chDB time: 0.05283093452453613\n", + "chDB return:\n", + " 15077792377,15087792377,15097792377,15107792377,15117792377,15127792377,15137792377,15147792377,15157792377,15167792377,15177792377,15187792377,15197792377,15207792377,15217792377,15227792377,15237792377,15247792377,15257792377,15267792377,15277792377,15287792377,15297792377,15307792377,15317792377,15327792377,15337792377,15347792377,15357792377,15367792377,15377792377,15387792377,15397792377,15407792377,15417792377,15427792377,15437792377,15447792377,15457792377,15467792377,15477792377,15487792377,15497792377,15507792377,15517792377,15527792377,15537792377,15547792377,15557792377,15567792377,15577792377,15587792377,15597792377,15607792377,15617792377,15627792377,15637792377,15647792377,15657792377,15667792377,15677792377,15687792377,15697792377,15707792377,15717792377,15727792377,15737792377,15747792377,15757792377,15767792377,15777792377,15787792377,15797792377,15807792377,15817792377,15827792377,15837792377,15847792377,15857792377,15867792377,15877792377,15887792377,15897792377,15907792377,15917792377,15927792377,15937792377,15947792377,15957792377,15967792377\n", + "\n", + "Pandas time: 3.6151206493377686\n", + "Pandas return:\n", + " 1356994681947.0\n", + "Polars time: 0.00017690658569335938\n", + "Polars return:\n", + " 141195\n", + "Q30 SELECT SearchEngineID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM hits WHERE SearchPhrase <> '' GROUP BY SearchEngineID, ClientIP ORDER BY c DESC LIMIT 10;\n", + "DuckDB time: 0.07926249504089355\n", + "DuckDB return:\n", + " SearchEngineID ClientIP c sum(IsRefresh) avg(ResolutionWidth)\n", + "0 2 1138507705 167 2.0 1383.610778\n", + "1 2 1740861572 167 0.0 1601.982036\n", + "2 2 -1106675868 158 2.0 1507.170886\n", + "3 2 1124827693 155 77.0 1749.277419\n", + "4 2 -497906719 152 1.0 1534.506579\n", + "5 2 -631062503 140 8.0 1557.242857\n", + "6 2 1146197031 139 6.0 1598.287770\n", + "7 2 -1870623097 133 4.0 1531.691729\n", + "8 2 -265917476 133 6.0 1555.090226\n", + "9 2 -1089778290 132 1.0 1538.712121\n", + "chDB time: 0.05949997901916504\n", + "chDB return:\n", + " 2,1740861572,167,0,1601.9820359281437\n", + "2,1138507705,167,2,1383.6107784431138\n", + "2,-1106675868,158,2,1507.1708860759493\n", + "2,1124827693,155,77,1749.2774193548387\n", + "2,-497906719,152,1,1534.5065789473683\n", + "2,-631062503,140,8,1557.2428571428572\n", + "2,1146197031,139,6,1598.2877697841727\n", + "2,-1870623097,133,4,1531.6917293233082\n", + "2,-265917476,133,6,1555.0902255639098\n", + "2,-1089778290,132,1,1538.7121212121212\n", + "\n", + "Pandas time: 1.5518078804016113\n", + "Pandas return:\n", + " c IsRefreshSum AvgResolutionWidth\n", + "SearchEngineID ClientIP \n", + "2 1138507705 167 2 1383.610778\n", + " 1740861572 167 0 1601.982036\n", + " -1106675868 158 2 1507.170886\n", + " 1124827693 155 77 1749.277419\n", + " -497906719 152 1 1534.506579\n", + " -631062503 140 8 1557.242857\n", + " 1146197031 139 6 1598.287770\n", + " -1870623097 133 4 1531.691729\n", + " -265917476 133 6 1555.090226\n", + " -1089778290 132 1 1538.712121\n", + "Polars time: 0.2474958896636963\n", + "Polars return:\n", + " shape: (10, 5)\n", + "┌────────────────┬─────────────┬─────┬──────────────┬────────────────────┐\n", + "│ SearchEngineID ┆ ClientIP ┆ c ┆ IsRefreshSum ┆ AvgResolutionWidth │\n", + "│ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n", + "│ i16 ┆ i32 ┆ u32 ┆ i64 ┆ f64 │\n", + "╞════════════════╪═════════════╪═════╪══════════════╪════════════════════╡\n", + "│ 2 ┆ 1138507705 ┆ 167 ┆ 2 ┆ 1383.610778 │\n", + "│ 2 ┆ 1740861572 ┆ 167 ┆ 0 ┆ 1601.982036 │\n", + "│ 2 ┆ -1106675868 ┆ 158 ┆ 2 ┆ 1507.170886 │\n", + "│ 2 ┆ 1124827693 ┆ 155 ┆ 77 ┆ 1749.277419 │\n", + "│ 2 ┆ -497906719 ┆ 152 ┆ 1 ┆ 1534.506579 │\n", + "│ 2 ┆ -631062503 ┆ 140 ┆ 8 ┆ 1557.242857 │\n", + "│ 2 ┆ 1146197031 ┆ 139 ┆ 6 ┆ 1598.28777 │\n", + "│ 2 ┆ -265917476 ┆ 133 ┆ 6 ┆ 1555.090226 │\n", + "│ 2 ┆ -1870623097 ┆ 133 ┆ 4 ┆ 1531.691729 │\n", + "│ 2 ┆ -1089778290 ┆ 132 ┆ 1 ┆ 1538.712121 │\n", + "└────────────────┴─────────────┴─────┴──────────────┴────────────────────┘\n", + "Q31 SELECT WatchID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM hits WHERE SearchPhrase <> '' GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10;\n", + "DuckDB time: 0.11410140991210938\n", + "DuckDB return:\n", + " WatchID ClientIP c sum(IsRefresh) avg(ResolutionWidth)\n", + "0 7433617358826888022 765396521 1 0.0 1750.0\n", + "1 6845096800585140239 697577507 1 0.0 1087.0\n", + "2 7417948050699454238 1381092923 1 0.0 1750.0\n", + "3 7614647577457412141 1381092923 1 0.0 1750.0\n", + "4 6740098735982683802 1381092923 1 0.0 1750.0\n", + "5 4824664031920863261 720586547 1 0.0 1996.0\n", + "6 5821118952041186941 -729938388 1 0.0 1917.0\n", + "7 6713590791010076724 1409085022 1 0.0 1638.0\n", + "8 6548785613138596558 1714868846 1 0.0 1996.0\n", + "9 5972495615745521485 1578253175 1 0.0 1368.0\n", + "chDB time: 0.09229826927185059\n", + "chDB return:\n", + " 5055679980591148335,-247495422,1,0,1917\n", + "5268572242740516149,-2084875520,1,0,1638\n", + "4830290381830615525,1833501146,1,0,1917\n", + "5901073908092331412,1976973896,1,0,1368\n", + "7227951727328737869,1767461008,1,0,1638\n", + "6081390183502573534,911172261,1,0,1638\n", + "5053868840694598172,1338505058,1,0,184\n", + "8815896716189863724,513446242,1,0,1996\n", + "7729270990481304965,-2113508332,1,0,1638\n", + "8678109688701084511,756024604,1,0,1638\n", + "\n", + "Pandas time: 1.9441230297088623\n", + "Pandas return:\n", + " c IsRefreshSum AvgResolutionWidth\n", + "WatchID ClientIP \n", + "4611694259862308721 1939762170 1 0 1368.0\n", + "4611696918332634655 1745457477 1 0 1996.0\n", + "4611702827673367990 -866198808 1 0 1368.0\n", + "4611704896271697334 1145084146 1 0 1368.0\n", + "4611709901969491340 925192082 1 0 1990.0\n", + "4611715517272605081 1873681563 1 1 1368.0\n", + "4611715716176606289 550681580 1 0 1996.0\n", + "4611715740922561616 -339684538 1 0 1087.0\n", + "4611717928870807772 1799799829 1 0 1917.0\n", + "4611720317321800760 659762682 1 0 1087.0\n", + "Polars time: 0.2849397659301758\n", + "Polars return:\n", + " shape: (10, 5)\n", + "┌─────────────────────┬─────────────┬─────┬──────────────┬────────────────────┐\n", + "│ WatchID ┆ ClientIP ┆ c ┆ IsRefreshSum ┆ AvgResolutionWidth │\n", + "│ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n", + "│ i64 ┆ i32 ┆ u32 ┆ i64 ┆ f64 │\n", + "╞═════════════════════╪═════════════╪═════╪══════════════╪════════════════════╡\n", + "│ 8866481400707184606 ┆ 683610771 ┆ 1 ┆ 0 ┆ 1087.0 │\n", + "│ 5976446437111469971 ┆ -868572229 ┆ 1 ┆ 0 ┆ 1996.0 │\n", + "│ 8394567842376086126 ┆ 1224879233 ┆ 1 ┆ 0 ┆ 508.0 │\n", + "│ 5151723549681893012 ┆ 1507755864 ┆ 1 ┆ 0 ┆ 1828.0 │\n", + "│ 6214865211162857505 ┆ 1723654076 ┆ 1 ┆ 0 ┆ 1368.0 │\n", + "│ 5280990891245629665 ┆ -1890611862 ┆ 1 ┆ 0 ┆ 1368.0 │\n", + "│ 6651288293509706204 ┆ 2134633159 ┆ 1 ┆ 0 ┆ 1638.0 │\n", + "│ 6194544028690036767 ┆ 1723163073 ┆ 1 ┆ 0 ┆ 1250.0 │\n", + "│ 7892825946104167072 ┆ 1072342394 ┆ 1 ┆ 0 ┆ 1750.0 │\n", + "│ 6164942890021406019 ┆ 1641142800 ┆ 1 ┆ 0 ┆ 1917.0 │\n", + "└─────────────────────┴─────────────┴─────┴──────────────┴────────────────────┘\n", + "Q32 SELECT WatchID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM hits GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10;\n", + "DuckDB time: 0.1959702968597412\n", + "DuckDB return:\n", + " WatchID ClientIP c sum(IsRefresh) avg(ResolutionWidth)\n", + "0 7224410078130478461 -776509581 2 0.0 1368.0\n", + "1 6655575552203051303 1611957945 2 0.0 1638.0\n", + "2 7578409505237148051 55707432 1 0.0 1368.0\n", + "3 6042985109837859254 1090782696 1 0.0 1368.0\n", + "4 7853636214732658170 -428889112 1 0.0 348.0\n", + "5 4823078680023084693 913985713 1 0.0 1917.0\n", + "6 4811313877556335245 1887535095 1 0.0 1917.0\n", + "7 9211680604818810870 -1272751583 1 0.0 430.0\n", + "8 5479010330340839726 842336962 1 0.0 1990.0\n", + "9 7612916189797209960 537065003 1 0.0 1996.0\n", + "chDB time: 0.20939183235168457\n", + "chDB return:\n", + " 7224410078130478461,-776509581,2,0,1368\n", + "6655575552203051303,1611957945,2,0,1638\n", + "5955546249209499743,87234006,1,0,1917\n", + "4870754219296985793,1945780190,1,0,1996\n", + "5851412430027698534,-814720616,1,0,1638\n", + "6592283700365342656,1975295783,1,0,1368\n", + "4784329916471068512,-818518996,1,0,1368\n", + "8978214656603001718,1685764391,1,0,1917\n", + "7812846363567359668,1659478732,1,0,508\n", + "6700068120218951102,788087753,1,0,1996\n", + "\n", + "Pandas time: 7.934078216552734\n", + "Pandas return:\n", + " c IsRefreshSum AvgResolutionWidth\n", + "WatchID ClientIP \n", + "6655575552203051303 1611957945 2 0 1638.0\n", + "7224410078130478461 -776509581 2 0 1368.0\n", + "4611686363500364104 1221513398 1 0 1990.0\n", + "4611686402113265154 -1339197305 1 0 1750.0\n", + "4611686851060971175 -985812753 1 0 1368.0\n", + "4611687435907085604 1760738510 1 0 1368.0\n", + "4611687575936721977 1770854750 1 0 1638.0\n", + "4611687987885605089 1362499323 1 1 1917.0\n", + "4611688643422516557 2089610172 1 0 1368.0\n", + "4611688965700267127 564621555 1 0 1087.0\n", + "Polars time: 0.6120898723602295\n", + "Polars return:\n", + " shape: (10, 5)\n", + "┌─────────────────────┬─────────────┬─────┬──────────────┬────────────────────┐\n", + "│ WatchID ┆ ClientIP ┆ c ┆ IsRefreshSum ┆ AvgResolutionWidth │\n", + "│ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n", + "│ i64 ┆ i32 ┆ u32 ┆ i64 ┆ f64 │\n", + "╞═════════════════════╪═════════════╪═════╪══════════════╪════════════════════╡\n", + "│ 7224410078130478461 ┆ -776509581 ┆ 2 ┆ 0 ┆ 1368.0 │\n", + "│ 6655575552203051303 ┆ 1611957945 ┆ 2 ┆ 0 ┆ 1638.0 │\n", + "│ 8770873791278154909 ┆ -1227628113 ┆ 1 ┆ 0 ┆ 1638.0 │\n", + "│ 5175983413994784880 ┆ -1623685973 ┆ 1 ┆ 0 ┆ 0.0 │\n", + "│ 7354852826398121421 ┆ 1148053479 ┆ 1 ┆ 0 ┆ 508.0 │\n", + "│ 7390510824302185303 ┆ -1069506224 ┆ 1 ┆ 0 ┆ 1638.0 │\n", + "│ 8119706864054503675 ┆ 1671265206 ┆ 1 ┆ 0 ┆ 1087.0 │\n", + "│ 7978246246625630775 ┆ 797036316 ┆ 1 ┆ 0 ┆ 1638.0 │\n", + "│ 4782320985610228979 ┆ 1250194442 ┆ 1 ┆ 0 ┆ 1917.0 │\n", + "│ 8933510620274997644 ┆ 1545187692 ┆ 1 ┆ 0 ┆ 1750.0 │\n", + "└─────────────────────┴─────────────┴─────┴──────────────┴────────────────────┘\n", + "Q33 SELECT URL, COUNT(*) AS c FROM hits GROUP BY URL ORDER BY c DESC LIMIT 10;\n", + "DuckDB time: 0.2761256694793701\n", + "DuckDB return:\n", + " URL c\n", + "0 http://kinopoisk.ru 141486\n", + "1 http://bdsm_po_yers=0&with_video 82623\n", + "2 http://liver.ru/belgorod/page/1006.jки/доп_при... 78593\n", + "3 http://smeshariki.ru/region 59652\n", + "4 http://kinopoisk.ru/search 58276\n", + "5 http://tienskaia-moda 52965\n", + "6 http://video.yandex 47719\n", + "7 http://kinopoisk.ru/vladimir.irr.ru 29715\n", + "8 http://bjdleaks.php?produkty%2Fproduct 26809\n", + "9 http://pogoda.yandex 26589\n", + "chDB time: 0.21467256546020508\n", + "chDB return:\n", + " \"http://kinopoisk.ru\",141486\n", + "\"http://bdsm_po_yers=0&with_video\",82623\n", + "\"http://liver.ru/belgorod/page/1006.jки/доп_приборы\",78593\n", + "\"http://smeshariki.ru/region\",59652\n", + "\"http://kinopoisk.ru/search\",58276\n", + "\"http://tienskaia-moda\",52965\n", + "\"http://video.yandex\",47719\n", + "\"http://kinopoisk.ru/vladimir.irr.ru\",29715\n", + "\"http://bjdleaks.php?produkty%2Fproduct\",26809\n", + "\"http://pogoda.yandex\",26589\n", + "\n" + ] + } + ], + "source": [ + "# Run the benchmark!\n", + "# Benchmark results\n", + "duckdb_times = []\n", + "chdb_times = []\n", + "pandas_times = []\n", + "polars_times = []\n", + "\n", + "counter = 0\n", + "for q in queries:\n", + " duckdb_time, chdb_time, pandas_time, polars_time = bench(q)\n", + " # remove the min/max time, take the average time\n", + " if len(duckdb_time) > 2:\n", + " duckdb_time = sorted(duckdb_time)[1:-1]\n", + " chdb_time = sorted(chdb_time)[1:-1]\n", + " pandas_time = sorted(pandas_time)[1:-1]\n", + " polars_time = sorted(polars_time)[1:-1]\n", + "\n", + " duckdb_times.append(sum(duckdb_time) / len(duckdb_time))\n", + " chdb_times.append(sum(chdb_time) / len(chdb_time))\n", + " pandas_times.append(sum(pandas_time) / len(pandas_time))\n", + " polars_times.append(sum(polars_time) / len(polars_time))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "DuckDB times: [[0.03473329544067383], [0.025869369506835938], [0.02449941635131836], [0.021502971649169922], [0.07661056518554688], [0.11784601211547852], [0.023169994354248047], [0.041997432708740234], [0.08279561996459961], [0.12752676010131836], [0.049619197845458984], [0.05812263488769531], [0.10427713394165039], [0.16024351119995117], [0.12470531463623047], [0.07800555229187012], [0.14101672172546387], [0.13824796676635742], [0.19573760032653809], [0.04209160804748535], [0.12423968315124512], [0.13030076026916504], [0.23919463157653809], [0.4751307964324951], [0.16602039337158203], [0.23991131782531738], [0.19497394561767578], [0.14258074760437012], [0.37261152267456055], [0.3752312660217285], [0.08300089836120605], [0.10579490661621094], [0.2147054672241211], [0.2616574764251709], [0.21707653999328613], [0.1144096851348877], [0.0702214241027832], [0.15410351753234863], [0.04920172691345215], [0.13008761405944824], [0.04686141014099121], [0.04792666435241699], [0.04334378242492676]]\n", + "chDB times: [[0.06221914291381836], [0.027338027954101562], [0.02335381507873535], [0.024204492568969727], [0.15731096267700195], [0.148162841796875], [0.02401590347290039], [0.05284929275512695], [0.08579301834106445], [0.09726285934448242], [0.09742522239685059], [0.05577349662780762], [0.12464475631713867], [0.12720394134521484], [0.11488032341003418], [0.0947573184967041], [0.1408531665802002], [0.12751054763793945], [0.19252252578735352], [0.025123119354248047], [0.1013326644897461], [0.1148073673248291], [0.17513012886047363], [0.4328289031982422], [0.05282235145568848], [0.03336310386657715], [0.060570478439331055], [0.13329815864562988], [0.3007791042327881], [0.05272984504699707], [0.05916261672973633], [0.08487057685852051], [0.20470118522644043], [0.21042490005493164], [0.1943037509918213], [0.07967042922973633], [0.10769414901733398], [0.14104270935058594], [0.11770820617675781], [0.1456921100616455], [0.07047486305236816], [0.06691765785217285], [0.05282926559448242]]\n", + "Pandas times: [[8.810486316680908], [0.18511605262756348], [0.007769346237182617], [0.007940053939819336], [0.2557411193847656], [0.6752357482910156], [0.020006418228149414], [0.07879805564880371], [0.6391797065734863], [0.7415461540222168], [0.8452174663543701], [0.8568341732025146], [2.7391467094421387], [2.740976333618164], [8.468678712844849], [0.808772087097168], [25.723305225372314], [2.8686487674713135], [54.3118736743927], [0.006058454513549805], [2.172792434692383], [2.5811095237731934], [10.12513256072998], [2.172769784927368], [2.291555881500244], [3.873861789703369], [4.094628095626831], [11.906651496887207], [30.80293369293213], [3.698624849319458], [1.5433671474456787], [1.97343111038208], [7.936391353607178], [8.008706092834473], [7.5324859619140625], [32.06308960914612], [0.7074093818664551], [0.6838343143463135], [0.05820012092590332], [0.6777045726776123], [0.14009356498718262], [0.07429075241088867], [0.27022314071655273]]\n", + "Polars times: [[1.9073486328125e-05], [0.02214503288269043], [0.03725171089172363], [0.0027332305908203125], [0.14108967781066895], [0.30224037170410156], [0.006073951721191406], [-1.0], [0.25276756286621094], [0.2742159366607666], [0.11061525344848633], [0.10920023918151855], [-1.0], [22.80822205543518], [-1.0], [-1.0], [-1.0], [0.11651134490966797], [-1.0], [0.004508018493652344], [0.1802678108215332], [-1.0], [-1.0], [0.18322491645812988], [0.267641544342041], [0.2900557518005371], [0.2738926410675049], [0.8539285659790039], [6.305335283279419], [0.0001761913299560547], [0.23777556419372559], [0.28878021240234375], [0.5600228309631348], [0.18396663665771484], [0.1676928997039795], [0.07762742042541504], [2.0668680667877197], [1.8747799396514893], [0.7213089466094971], [1.001046895980835], [0.22947144508361816], [0.020848989486694336], [1.0009913444519043]]\n", + "DuckDB faster count: 15\n", + "chDB faster count: 24\n", + "Pandas faster count: 4\n", + "Polars faster count: 0\n", + "DuckDB total time: 5.667204856872559\n", + "chDB total time: 4.796359300613403\n", + "Pandas total time: 246.18061780929565\n", + "Polars total time: 32.973297357559204\n" + ] + }, + { + "data": { + "image/png": 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rH3lbVFFRob/+9a86f/68Wlpa5OnpqcDAQI0dO1aurq5GRwUAoNdb9m1XvX28UYs/vKTymhZF/vzzzt0LeXGF0V8BfUhcXJyqqqqUlJTU5r22K67sQhUbG6ukpCQtW7ZMq1evlqY4LiuArqNoDqBfSUhIUHZ2trZv366srCxNmTKl9QL1wIEDJUlWq7X1AnV+fr4aGho0evRoxcfHK3c3RXMAAICexsPDQ7m5uXr88cf1H//xH3r11VdvuF3zlVXwbDab4uPjNWvWrNbP2bNnj375y1/q8OHDam5uliTdeeedeu655/TCCy/IZDI5/LsBAAAAQH9z4U9/UFPN5/K6/wca/J1F2rxuVrvjGxsbFRMTo5SUFMXHx0sTHBITwDX8/f3l7+9vdAwAAPosD1eTcn/iocf/t1X/UdCoVwMCbngv5AqbzaY1a9Zo1qxZ+pSiObpRTk6OJk2a1G7J/FrR0dHKyMjQnj17NGTKEPuFA9DtKJoD6Fd8fHx06NAhLVmyRNu2bdO+ffuUm9t2edxms8nJyUnz5s3Txo0b2XITAACgB7vjjjtUUlKijRs36o033rjhds1OTk5qbm7W//7f/1tz585tfT0pKUkxMTHXbcdeXl6umJgY5eXlaffu3Xb/HgAAAADQ31n//n/k4huoIY/+okPjXV1dlZycrLy8PGVmZsprgpedEwIAAADGuGOwk0qe89DGQ41649TIG94LcXd317Rp07R8+XKFhoYakBR9XU1NjaZOndrpeYGBgTp27JiGiKI50JtQNAfQ7wwdOlTp6elav369cnJydPz4cZ05c0YXL16UJHl6eiogIEATJkzQ9OnT5efnZ3BiAAAAdISrq6uWL1+u5cuX33C75rlz56q5ufmqknl5eblefPFFOTs764UXXtDTTz+tUaNGqaamRvv371dcXJyys7OVmpoqDTLwCwIAAABAP9Bcf15u3xrb6Xnjxo3Trl275CWK5oAjNVtr9fvf/14lJSU6ffq06urqJEleXl4KDAyU2WzWjBkzNGzYMIOTAgDQN7g6m7R8spuW7/3HDe+FjB07Vq6urkZHRR8WEBCg/Px8Wa1WDRw4sENzrFar8vPzNXLkSDunA9DdKJoD6Lf8/Py0cOFCo2MAAADADm60XXNFRYUsFstVr+3YsUNNTU169dVXtWzZstbXR4wYoblz5yo0NFT33Xef3nrrLel5OwcHAAAAgH7O2WOwGiv/IZutRSaTU4fmNDc3q6ioSMOHD7dzOgBXtFy6qJqPN6v+L/v1tFqu2yXuCpPJJGdnZy1YsEAbNmxgB2EAALrRje6FAPYWHh6uxMRETZs2TampqTKbze2OLykpUUREhCorKxUXF6cd2uGgpAC6A0VzAAAAAEC/0dzcLDc3t6teO3nypEwmk37yk5+0OeeOO+7Q5MmTdfDgQd2hOxwREwAAAAD6rYF3TVJd8Qeq3v2qhjz23E3HV1dXa/HixTpx4oSioqKUq1wHpAT6t5aGep17Z5maaj6X00BvPf3kjzVx4kT5+/vLw8NDklRfX6+KigodOXJEWVlZ2rJliwoLC3X48GGD0wMAAKCrVq5cqb1796qgoEDBwcEKCgpqPR68ssK51WptPR4sLy+XzWZTSEiIVqxYoR3bKJoDvQlFcwAAAABAn1FdXa3s7Owbbtc8ePBg/d//+3+vmuPt7S1JampquuHnNjc3a8AATqEBAAAAwN58Hpqnr04UyVpaoK/K/1OP/e2tdgsL+fn5amho0OjRoxUfH6/c3RTNAXu78Kc/qKnmc3nd/wMN/s4ibV43q93xjY2NiomJUUpKiuLj46UJDokJAECfVW1tUfbvf3/DeyFms1kzZszQsGHDDE6Kvsrd3V379+/X2rVrlZqaqrKyMpWVlUm6vKONpKt2vPH29lZkZKRiY2OvWxAKQM/HXXIAuIlVq1bp3Llzlw+EphqdBgAAAG25cOGCoqOjlZ6erubm5htu1yxdvrD10EMP6YMPPpCPj4/CwsL06quv6s0331RsbOx14//xj3+ooKBADzzwgP6pf9rzawAAAABAv+fk7im/BRt0ft/rqv/0oPbt26fc3LbL4zabTU5OTpo3b542btwoHx8fx4YF+inr3/+PXHwDNeTRX3RovKurq5KTk5WXl6fMzEx5TfCyc0IAAPqmC5dsiv7oktJLvlaznr7hvRCTySRnZ2ctWLBAGzZs4DgZduHm5qbExEStWbNGBQUFOn78uM6cOaOLFy9Kkjw9PRUQEKAJEyZo8uTJcnFxMTgxgFtF0RwAbiIzM1OlpaUymUy6Z+o9RscBAADANWpraxUaGqrS0lL5+voqLCzshts1Hz58WOnp6SooKFBQUJAKCgo0efJkLV68WAkJCfriiy+0cOFCjRo1SufPn29djeGrr77S0qVLFVcbZ/C3BQAAAIC+z/m2QRoWtkyDv/NTrX2gqd3CwvTp0+Xn52dwYqB/aa4/L7dvje30vHHjxmnXrl3yEkVzAAA6q/aSTaFp9SqtbpGvh0lhc56+4b2QI0eOKCsrS1u2bFFhYaEOHz5scPp+LN6742PvCLBfDjtycXGRxWKRxWIxOgoAO6FoDgA3ERkZqerqaknSdm03OA0AAACuFR8fr9LSUkVFRWndunVydXW94djFixdr5cqVCg0NVU1Nje655x6NHDlSI0aMkMlk0qZNm7Rp06ar5thsNq1Zs0azZs1S3NsUzQEAAADAUZw9B2vhwu8bHQPANZw9Bqux8h+y2VpkMjl1aE5zc7OKioo0fPhwO6cDgN5r1IsfdnjsKXc7BkGPFL+/QaXVLYr6H65a95ibXNdubnd8Y2OjYmJilJKSovj4eP3cQTkBAH0PRXMAuImIiIjWX29/m6I5AODWff7558rNzdW5c+fk4eGhiRMn6tvf/rbRsYBeb+fOnRo/frySk5M7NH7MmDGqrKxUYGCgqqur9dlnn+mzzz67bpy7u7umTZum5cuXKzQ0tLtjAwAAAHAAzsUBoPsNvGuS6oo/UPXuVzXkseduOr66ulqLFy/WiRMnFBUVpVzlOiAlAAB9y86/fa3xtzsp+fGOPWXg6uqq5ORk5eXlKTMzUz93v83OCYH+iesO6A8omgMAAADd5PXXX9eYMWP08MMPX/V6S0uLYmJi9Nvf/lZNTU1XvXfffffpvffeU1BQkCOjAn1KZWVlp4vgrq6uslgs2rVrl06ePKm//vWvOn/+vFpaWuTp6anAwECNHTu23dXRAQAAABiv7liOXIZ8S+4B9171OufiAHqivlJC8Xlonr46USRraYG+Kv9PPfa3tzRx4kT5+/tr4MCBkiSr1aqKigodOXJE+fn5amho0OjRoxUfH6/c3RTNAQDorMqLNoWOdO70vHHjxmnXrl1S4KhuzwT0B13pAAB9BUVzAP3W0aNHlZWVpZKSEp0+fVp1dXWSJC8vLwUGBspsNissLEzBwcEGJwUA9BbPPvusFi5ceN1J5vPPP69NmzbJ1dVVP/7xj3XXXXfp/Pnz+vDDD3X06FE98sgjOn78uEGpgd7Pz89PRUVFamlpkZNT57dr9vf3l7+/v51TAgAAALCHmo9S5XHvI9cVzTkX719WrVqlc+fOyWQySVONToP+rCsPv/QmTu6e8luwQef3va76Tw9q3759ys1tuzxus9nk5OSkefPmaePGjfLx8XFsWAAA+gg/T5OKzraoxWaTk8nUoTnfvBcC4NZ0pQMw8H8NlPPAzj8gAvQ0FM0B9DunTp3SokWLdODAAUmXL3Bdq7i4WJmZmUpISJDFYlFaWppGjRrl4KQAgL6gtLRUr732moYMGaKDBw/qnnvuaX2vsbFR4eHhev/99/Wb3/xGCjAwKNCLzZw5UykpKZozZ45SU1Pl6+vb7vhrt2sGAAAA0LdwLt7/ZGZmqrS0VCaTSfdMvefmEwA76crDL72thOJ82yANC1umwd/5qdY+0KTjx4/rzJkzunjxoiTJ09NTAQEBmjBhgqZPny4/Pz+DEwMA0LvNHOOilP9s1JztXyl1hrvavxPSxr2QnI8ckhPoDzp63WHY3mG6febtBiYFugdFcwD9ytmzZxUSEqKqqiqZzWbNnj27dSs/Dw8PSVJ9fX3rVn4ZGRnKy8tTaGioiouLDU4PAOiNsrKyZLPZlJiYeNUJpiS5urrqjTfe0Mcff6z3339fijQoJNDLJSQkKDs7W9u3b1dWVpamTJnSoe2a77jjDo0dO1bLli274Q43M2bM0LBhw4z8egAAAAA6iXPx/icyMlLV1dWSpO3abnAa4Gp9vYTi7DlYCxd+3+gYAAD0eQnfcVN2WZO2/7VJWX+/qCnHH+vQvZDRo0crPj5e5yiaA92mo9cd6o7V9cpjfOBaFM0B9CtxcXGqqqpSUlKSli5desNxV0pFsbGxSkpK0rJly7R69WppiuOyAgD6hpMnT8pkMunxxx9v8/1hw4bp/vvvV3FxsQJYRg24JT4+Pjp06JCWLFmibdu23XS7ZpPJpDvvvFNnzpxRREREmzvcSJLJZJKzs7MWLFigDRs2sLUzAAAA0EtwLt7/REREtP56+9sUzdGzUEIBAADdwcfdpEM/HaglOQ3a9snXN70X4uTkpHnz5mnjxo3y8fHROQfnBfqyjl53OHDogIOTAfZB0RxAv5KTk6NJkya1WzK/VnR0tDIyMrRnzx4NmTLEfuEAAH2Ss/Pl7W7b2xp2xIgRKiwsdFQkoE8aOnSo0tPTtX79euXk5Nxwu+a77rpLv/71r1VeXi5fX1+FhYW1u8NNVlaWtmzZosLCQh0+fNjIrwgAAACggzgXB9CTUEIBAADdZehAJ6X/6Datf8xNOeNTbngvZMKECZo+fXq750QAbl1HrzvYvm57sSugt6FoDqBfqamp0dSpUzs9LzAwUMeOHdMQUTQHALSvsrJSBw8ebP3ZZDJJkioqKhQUFNTmnC+//FJDhw51SD6gr/Pz89PChQtv+P4LL7yg8vJyRUVFad26dXJ1dW338xobGxUTE6OUlBTFx8dLE7o3LwAAAICua64/r0uffSJJOnjQi3PxPqTxi3K99NJLKikp0enTp1VXVydJ8vLyUmBgoMxms8LCwhQcHGxwUuDGKKFctmrVKp07d+7y39Gdv1UHAAC+wc/Tqd17IQC61612AJw9nR2SD7A3iuYA+pWAgADl5+fLarVq4MCBHZpjtVqVn5+vkSNH2jkdAKAv+Oijj/TRRx9d9/rHH3/c5klmY2OjioqKNHbsWP2X/ssREYF+befOnRo/frySk5M7NN7V1VXJycnKy8tTZmamvCZ42TkhAAAAgM66dPKoLp08Kkn6zrb/fp1z8d6rqfYLVWcnq+GzT5Rgkmy26wu4xcXFyszMVEJCgiwWi9LS0jRq1CjHhwWucasPv/T1EkpmZqZKS0tlMpl0z9R7jI4DAAAAdNitdgBch7W/4BXQW1A0B9CvhIeHKzExUdOmTVNqaqrMZnO740tKShQREaHKykrFxcVph3Y4KCkAoDd66qmnbvjepUuX2nz9vffe0/nz5xUSEqI/6o/2igbg/6msrFRoaGin540bN067du2SlyiaAwAAAD2Jx/hHrvr53x7wb/015+K9U1PdP3XunX9XS32tXG4fpdVRizRx4kT5+/vLw8NDklRfX6+KigodOXJEGRkZysvLU2hoqIqLiw1OD9z6wy99vYQSGRmp6upqSdJ2bTc4DQAAALpVvHfnxt8RYJ8cdtCVDsCQB4fYKxbgUBTNAfQrK1eu1N69e1VQUKDg4GAFBQW1XqC+ssK51WptvUBdXl4um82mkJAQrVixQju2UTQHANzYli1bOj3nwQcfVF5enu6++2798Y/c3Abszc/PT0VFRVq5cqUqKytlMpmUlpbW7pzm5mYVFRVp+PDhDkoJAAAAoKOGfX/pVT9veeX7N53DuXjPdiE/XS31tRr83Z9p0IMzFRvb9v+nZrNZM2bMUGxsrJKSkrRs2TKtXr1amuLgwMA3dOXhl75eQomIiGj99fa3KZoDAOAIq1at0rlz52QymbTM6DBAL9WVDsAvjv3CDokAx6NoDqBfcXd31/79+7V27VqlpqaqrKxMZWVlktS6deE3t+D09vZWZGSkYmNj5ebmZkhmAEDfNmbMGI0ZM8boGOiHPv/8c+Xm5urcuXPy8PDQxIkT9e1vf9voWHY3c+ZMpaSk6Le//a3q6urk5OTUbtG8urpaixcv1okTJxQVFaVc5TowLQAAAAB74Fy8Z7t0sliuI+7WoAdndnhOdHS0MjIytGfPHg2Z0rfLuujZuvLwCyUUAADQ3TIzM1VaWnq5aH7X3UbHAfqNK9cdXE65GB0F6BYUzQH0O25ubkpMTNSaNWtUUFCg48eP68yZM7p48aIkydPTUwEBAZowYYImT54sFxf+ow8AAHqf119/XWPGjNHDDz981estLS2KiYnRb3/7WzU1NV313n333af33nuvzW2c+4qEhARlZ2ervLxcAwYMUEBAgF588cUb7nCTn5+vhoYGjR49WvHx8crdTdEcAAAAAOyp5dJFuY0c3+l5gYGBOnbsmIaIojl6l95eQmn8olwvvfSSSkpKdPr0adXV1UmSvLy8FBgYKLPZrLCwMAUHBxucFAAA4zl6EaDIyEhVV1df/mHrNrv9PgCAvo2iOYB+y8XFRRaLRRaLxegoAIA+qLq6WtnZ2e3eYJkxY4aGDRtmcFL0Vc8++6wWLlx4XdH8+eef16ZNm+Tq6qof//jHuuuuu3T+/Hl9+OGHOnr0qB555BEdP35c3gbltjcfHx8dOnRIS5Ys0bZt23Ty5EmtW7euzbE2m01OTk6aN2+eNm7cKB8fH8eGBQAAANApzdZa/f73v+dcvJdzHuSrhs/+opavL8nJxb1Dc6xWq/Lz8zVy5Eg7pwNwRVPtF6rOTlbDZ58owXT1jsFXFBcXKzMzUwkJCbJYLEpLS9OoUaMcHxYAAAfp0iJAdsgTERHR+utPKZoDXUYHAP0VRXMAAACgG124cEHR0dFKT09Xc3NzmzdYJMlkMsnZ2VkLFizQhg0bKLDCIUpLS/Xaa69pyJAhOnjwoO65557W9xobGxUeHq73339fv/nNbxRnYE57Gzp0qNLT07V+/Xrl5OS0u8PN9OnT5efnZ3BiAAAAAO1puXRRNR9vVv1f9utptXAu3st5jJ2i2sJ3VfXeag353nM3HV9SUqKIiAhVVlYqLi5OO7TDASmBm+vLD7801f1T5975d7XU18rl9lFaHbVIEydOlL+/vzw8PCRJ9fX1rTvGZWRkKC8vT6GhoSouLjY4PQAA9tOlRYDm2OTtbjIoOYD23GoHAOgrKJoDAAAA3aS2tlahoaEqLS2Vr6+vwsLC2r3BkpWVpS1btqiwsFCHDx82OD36g6ysLNlsNiUmJl5VMpckV1dXvfHGG/r444/1/vvvK+77BoXsoqNHjyorK6tD2zX7+flp4cKFxgYGAAAA0CUtDfU6984yNdV8LqeB3nr6yR9zLt7LeYf+T3116qgaKj7VubeW6O4//ab1/9OBAwdKuryC+ZX/T8vLy2Wz2RQSEqIVK1ZoxzaK5jDWrT780ptcyE9XS32tBn/3Zxr04EzFxrZ9IelKmT42NlZJSUlatmyZVq9eLU1xcGAAAAzU4UWADrso7mG3Dn3m0XPNynrppQ7dCwHQNV3pAJiWmOR8m7PB3wDoOormAAAAQDeJj49XaWmpoqKitG7dOrm6urY7vrGxUTExMUpJSVF8fLw0wTE50X+dPHlSJpNJjz/+eJvvDxs2TPfff//llaV6WdH81KlTWrRokQ4cOCCJ7ZoBAACA/uLCn/6gpprP5XX/DzT4O4u0ed2sdsdzLt7zmQa4yu/JV3ShcJsuHvlAZWVlKisru/ye6fIKj9885/P29lZkZKRiY2Pl5taxYg5gL115+KU3lVAunSyW64i7NejBmR2eEx0drYyMDO3Zs0dDpgyxYzoAAHqWDi8C9PeLNy2an7rQokW7v9KB082SKYF7IXCozz//XLm5uTp37pw8PDw0ceJEffvb3zY6lt11pQMwZNcQ/cuT/+KgpID9UDQHAAAAusnOnTs1fvx4JScnd2i8q6urkpOTlZeXp8zMTHlN8LJzQvR3zs6Xb1b6+fndcMyIESNUWFgoqffcnD979qxCQkJUVVUls9ms2bNnd2q75hEjRhj8DQAAAADcKuvf/49cfAM15NFfdGg85+K9g2mAiwZPXSCfyU/q7e976/jx4zpz5owuXrwoSfL09FRAQIAmTJigyZMny8XFxeDEwGVdefilN5VQWi5dlNvI8Z2eFxgYqGPHjmmIKJoDAPqPDi8CVJjX7uecrWtRyOZ6VdXbZB7upNmRCZ26FwLczOuvv64xY8bo4Ycfvur1lpYWxcTE6Le//a2ampqueu++++7Te++9pyBHBnWwrnQA/lb0t15zjA+0h6I5AAAA0E0qKysVGhra6Xnjxo3Trl275CVubqN7VVZW6uDBg60/X1n5raKiQkFBbV/y+fLLLzV06FBJFx0RsVvExcWpqqpKSUlJWrp06Q3H3Wi75s2bN7f7+atWrdK5c+cu//Ob2s3hAQAAAHRJc/15uX1rbKfncS7eO5icB8hischisRgdBeiQrjz80ptKKM6DfNXw2V/U8vUlObm4d2iO1WpVfn6+Ro4caed0AAD0LB1eBKjphm9LkuI+blBVvU1J09y0NMRNio1tc9yN7oX8+y1/A/QXzz77rBYuXHhd0fz555/Xpk2b5Orqqh//+Me66667dP78eX344Yc6evSoHnnkER2fY5O3u8mg5PbVlQ7AJ3/7xA6JAMejaA4AAAB0Ez8/PxUVFamlpUVOTk4dmtPc3KyioiINHz7czunQH3300Uf66KOPrnv9448/brNo3tjYqKKiIo0dO1ZS77nwkZOTo0mTJrVbMr/WN7drvpnMzEyVlpbKZDLpnqn33HQ8AAAAAMdx9hisxsp/yGZrkcnEuTgAY3Xl4ZfeVELxGDtFtYXvquq91RryveduOr6kpEQRERGqrKxUXFycdmiHA1ICAGCMW14EaGD7Jd2c8iZN8ne+XDLvoG/eC/l3r0EdnoeO+/zzz5Wbm6tz587Jw8NDEydO1Le//W2jY3Wb0tJSvfbaaxoyZIgOHjyoe+757/tkjY2NCg8P1/vvv6/fHHZR3MO9Z7fkzuhKB2DAIOq56Bv4NxkAAADoJjNnzlRKSormzJmj1NRU+fr6tju+urpaixcv1okTJxQVFaVc5TooKfqDp5566obvXbp0qc3X33vvPZ0/f14hISHqTUXzmpoaTZ3a+aXGr2zXfDORkZGqrq6WJG3X9k7/PgAAAADsZ+Bdk1RX/IGqd7+qIY/dvOzIuTgAe+rKwy+9qYTiHfo/9dWpo2qo+FTn3lqiu//0G02cOFH+/v4aOHCgpMsrmFdUVOjIkSMqLy+XzWZTSEiIVqxYoR3bKJoDAPquW14EyKf9Y4ear2yaGtj5FaNb74VQNL8lr7/+usaMGXPdKt8tLS2KiYnRb3/7WzU1Xb0c/X333af33nvvhg8W9CZZWVmy2WxKTEy8qmQuXd6d54033tDHH3+s9/9+sc8WzbvSARj8yGAHpQTsq/ecrQIAAAA9XEJCgrKzs7V9+3ZlZWVpypQp7d5gyc/PV0NDg0aPHq34+Hjl7ubmNrrPli1bOj3nwQcfVF5enu6++27p/9tsh1T2ERAQoPz8fFmt1tY/azfTme2aIyIiWn+9/W2K5gAAAEBP4vPQPH11okjW0gJ9Vf6feuxvb3EuDsAwXXn4pTeVUEwDXOX35Cu6ULhNF498oLKyMpWVlV1+7/+t2mqz2VrHe3t7KzIyUrGxsXJz65sFJAAApC4uAnS3S7ufHeDtpPzTzbJ+bdNAl44VzjtzLwRte/bZZ7Vw4cLriubPP/+8Nm3aJFdXV/34xz/WXXfdpfPnz+vDDz/U0aNH9cgjj+j48ePyNih3dzl58qRMJpMef/zxNt8fNmyY7r//fhUX5jk4meN0pQMwYBb1XPQN/JsMAAAAdBMfHx8dOnRIS5Ys0bZt27Rv3z7l5rZ9w9pms8nJyUnz5s3Txo0b5ePj49iwQBvGjBmjMWPGGB2j08LDw5WYmKhp06YpNTVVZrO53fHXbtcMAAAAoPdycveU34INOr/vddV/epBzcQCG6srDL72thGIa4KLBUxfIZ/KTevv73jp+/LjOnDmjixcvSpI8PT0VEBCgCRMmaPLkyXJxab88BwBAX9ClRYDe/0G748LHDVDiwUZNS7cqdYa72r8T0sa9kG3vdjob2lZaWqrXXntNQ4YM0cGDB69a6buxsVHh4eF6//339Zvf/Ea9/S6Us7OzJMnPz++GY0aMGKHCphu+3et1pQNg+cDi2LCAnfSus1UAAACghxs6dKjS09O1fv165eTktHuDZfr06e2elAPomJUrV2rv3r0qKChQcHCwgoKCOrRd87333quWlhbNnj1bp0+fVl1dnSTJy8tLgYGBMpvNCgsLU3BwsJFfDwAAAMBNON82SMPClmnwd36qtQ80cS4OwDBdefilt5ZQTM4DZLFYZLFYjI4CAECv1LoIUJ5Tu+NWTnHT3hPNKjjTrOD/r15BuXd36F5ISEiIVqxYoRMUzbtNVlaWbDabEhMTryqZS5Krq6veeOMNffzxx3r//fcV932DQt6iyspKHTx4sPXnK7vVVFRUKCgoqM05X375pYYO7Ngq+70VHQD0dxTNAQAAADvw8/PTwoULjY4BSLq8DXN2drZKSkpuWKieMWOGhg0bZnDSW+Pu7q79+/dr7dq1Sk1Nvel2zZ6enhoyZIg++eQTffLJJ1e9d0VxcbEyMzOVkJAgi8WitLQ0jRo1yiHfBwAAAMCtcfYcrIULe9ldfAB9Dg+/AAAAe3AfYNL+pwZq7cEGpf7fxpveC/H29lZkZKRiY2Pl5uZmSOa+6uTJkzKZTHr88cfbfH/YsGG6//77VVxcLPWyU9SPPvpIH3300XWvf/zxx20WzRsbG1VUVKSxPu0/KNFX0AFAf0XRHED/Fu/dufF3BNgnBwAAgB1cuHBB0dHRSk9PV3Nzc5uFaunyBUhnZ2ctWLBAGzZs6JXbx7u5uSkxMVFr1qxRQUHBDW/ifutb31JkZKTOnDkjs9ms2bNnt6744eHhIUmqr69vXfEjIyNDeXl5Cg0NvXxBEAAAAAAAoAN4+AUAgP7NHosAuQ0wKfG77lrzsJsKHnm/3QfaJk+eLBcXF7t8t/7O2dlZktp9YHDEiBEqLCyU1HtK/k899dQN37t06VKbr7/33ns6f/68Qu7m3zWgL6NoDgAAAAB9UG1trUJDQ1VaWipfX1+FhYW1W6jOysrSli1bVFhYqMOHD2uQwflvlYuLS7vbNf/0pz9VVVWVkpKStHTp0ht+zpULvLGxsUpKStKyZcu0evVqaYp9cgMAAAAAAAAAgN7vlhcB6sTv4eJsavdeCLpXZWWlDh482PrzlRXkKyoq2lzlW5K+/PJLDR06VNJFR0TsFlu2bOn0nAcffFB5eXm6+/0f2CERgJ6CojkAAABgoFWrVuncuXOXL0hMNToN+pL4+HiVlpYqKipK69atk6ura7vjGxsbFRMTo5SUFMXHxyuptzbNbyInJ0eTJk1qt2R+rejoaGVkZGjPnj0aMmWI/cIBAAAAcAjOxQEAAADYQ5cWAZpl0yA3k8HfAG356KOP9NFHH133+scff9xm0byxsVFFRUUaO3aspE8ckNA4Y8aM0ZgxY6Q8J6Oj9ChXrjtUlFXI/6f+RscBuoyiOQAAAGCgzMxMlZaWymQy6Z6p9xgdB33Izp07NX78eCUnJ3dovKurq5KTk5WXl6fMzEwlLbRvPqPU1NRo6tTON0kCAwN17NgxDRFFcwAAAKC341wcQE9CCQUAgL6jS4sA7XdR0jR3ByVFRz311FM3fO/SpUttvv7ee+/p/PnzCgkJUV8vmqNtV6472GTjGB99AkVzAAAAwECRkZGqrq6WJG3XdoPToC+prKxUaGhop+eNGzdOu3btktT+xc/eKiAgQPn5+bJarRo4cGCH5litVuXn52vkyJF2TgcAAADAETgXB9CTUEIBAKDv6NIiQJ9+QtG8B9qyZUun5zz44IPKy8vT3XffLf1/m+2Qyv6qq6uVnZ2tkpISnT59WnV1dZIkLy8vBQYGymw2a8aMGRo2bJjBSXumK9cdNh3bZHQUoFtQNAcAAAAMFBER0frr7W9zcxvdx8/PT0VFRWppaZGTU8e2q2tublZRUZGGDx8u6bx9AxokPDxciYmJmjZtmlJTU2U2m9sdX1JSooiICFVWViouLk47tMNBSQEAAADYC+fivUy8d+fG3xFgnxyAnVBCAQCg7+jSIkCf/tkOiWCEMWPGaMyYMUbHuCUXLlxQdHS00tPT1dzcLJvN1uY4k8kkZ2dnLViwQBs2bJCPY2M6RElJiS5cuHBLOyVfue7ANQf0FRTNAQAAAKAPmjlzplJSUjRnzhylpqbK19e33fHV1dVavHixTpw4oaioKEmdX6GhN1i5cqX27t2rgoICBQcHKygoSBMnTpS/v3/rCudWq1UVFRU6cuSIysvLZbPZFBISohUrVmjHNormAAAAAACg+1BCAQCg7+jSIkAeJjunA9pXW1ur0NBQlZaWytfXV2FhYa330Dw8PCRJ9fX1rffQsrKytGXLFhUWFurwLJsGufWtf4eXLFmi/Px8NTU1GR0FMBxFcwAAAMAOjh49qqysrHa3EwsLC1NwcLDBSdFXJSQkKDs7W9u3b1dWVpamTJnSbqE6Pz9fDQ0NGj16tOLj46WNfbNo7u7urv3792vt2rVKTU1VWVmZysrKJF1efUHSVaszeHt7KzIyUrGxsXJzczMkMwAAAICOafyiXC+99BLn4gAAAAAM0aVFgB50cVBK3Krq6mplZ2e3e845Y8YMDRs2zOCktyY+Pl6lpaWKiorSunXr5Orq2u74xsZGxcTEKCUlRfH7XZQ0zd1BSR3n2hXd6QCgv6JoDgAAAHSjU6dOadGiRTpw4ICk608+Jam4uFiZmZlKSEiQxWJRWlqaRo0a5eCk6Ot8fHx06NAhLVmyRNu2bdO+ffuUm5vb5libzSYnJyfNmzdPGzdulI+Pj2PDOpibm5sSExO1Zs0aFRQU6Pjx4zpz5owuXrwoSfL09FRAQIAmTJigyZMny8WFi7sAAABAT9ZU+4Wqs5PV8NknSjBxLg6gZ+DhFwAA+p8uLQJkqTQ4PW7kwoULio6OVnp6upqbm9s855QuL2jk7OysBQsWaMOGDb3uftvOnTs1fvx4JScnd2i8q6urkpOTlZeXp8xPP+k1RfObFeivaG5ubh1vs9la/793cnLq8HUHoK+gaA4AAAB0UUlJiS5cuKDRo0crJCREVVVVMpvNmj17drvbiWVkZCgvL0+hoaEqLi42+FugLxo6dKjS09O1fv165eTktFuonj59uvz8/AxO7FguLi6yWCyyWCxGRwEAoNe4cuw7depUo6MAgCSpqe6fOvfOv6ulvlYut4/S6qhFnIsDMNStPvzSq8V7d278HQH2yQEAgMG6tAhQyp0OTouOqK2tVWhoqEpLS+Xr66uwsLB2zzmzsrK0ZcsWFRYW6vDhwxpkcP7OqKysVGhoaKfnjRs3Trs+/bMdEtlHU1OTTCbTDR8YuNbXX3991c8JCQkdvu7g/b+85TKYBa3Q+1E0BwAAALpoyZIlys/P11NPPaWqqiolJSVp6dKlNxx/Zdu02NhYJSUladmyZVq9erU0xXGZ0b/4+flp4cKFRscAAAB9wJVj36amJqOjAIAk6UJ+ulrqazX4uz/ToAdnKjb2+22O41wcgCN05eEXSigAAPQNLALUt8THx6u0tFRRUVFat27dTVfDbmxsVExMjFJSUhQfH6+kXtQ09/PzU1FRkVpaWuTk5NShOc3NzSoqKtJwD5Od03WfsWPHqrS0VL/4xS/0yiuvyNu77Ycmv/Od7+jgwYN6+umntWXLllvqADTsbNC3Fn3LTt8EcByK5gAAAEA3sNlsysnJ0aRJk9o9wbxWdHS0MjIytGfPHg2ZMsR+AQEAAIBu0tHVfgDAES6dLJbriLs16MGZHZ7DuTgAe+nKwy+UUAAA6FtYBKhv2Llzp8aPH6/k5OQOjXd1dVVycrLy8vKUmZmppIX2zdedZs6cqZSUFM2ZM0epqany9fVtd3x1dbUWL16sEydOKOrB3vPA5PHjx/Xyyy/rlVde0e7du7VhwwY9+eSTNxzflQ5AUUlRNyQGjEfRHAAAALiBmz2RfkVzc7Mk6ezZszp37pxcXV1lMpnU0NDQofmBgYE6duyYhoib2wAAADBGZ499vzm+M8e+ANDdWi5dlNvI8Z2ex7k4AHvoysMvlFAAAEBn3Pv2vZ0a/56dcvR1lZWVCg0N7fS8cePGadeuXZI6ds2tJ0hISFB2dra2b9+urKwsTZkypXV3noEDB0qSrFZr6+48+fn5amho0OjRoxVvqTQ4fce5uLgoPj5e4eHheuaZZzR//ny99dZb2rRpk4KCgq4bX1NTo6lTp3b69wkMDNTh4sPdERkwHEVzAAAA4AaamppkMpk6tWKjzWbT119/LZOpY9uDWa1W5efna+TIkbcaE+g2q1at0rlz52QymZTWS/+VHPXih50af+qVtlcWAwCgv+nssW9TU5OdEwFAxzgP8lXDZ39Ry9eX5OTi3qE5nIsDsJeuPPxCCQUAAKDn8fPzU1FRkVpaWuTk5NShOc3NzSoqKtLw4cMlnbdvwG7k4+OjQ4cOacmSJdq2bZv27dun3NzcNsfabDY5OTlp3rx52rhxo3xS7nRw2q7713/9V+Xn5+t3v/udVqxYoXvvvVcrVqzQiy++KBeX/16hPSAgQPn5+bJara2F+5u5ct3BZUjvWekdaE/H/vYDAAAA+qGxY8dKkn7xi1/o/PnzamlpafN/Dz/8sEwmk+Li4mQymfTQQw/p2LFjN/38kpISTZs2TZWVlZo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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "print(\"DuckDB times:\", [[t] for t in duckdb_times])\n", + "print(\"chDB times:\", [[t] for t in chdb_times])\n", + "print(\"Pandas times:\", [[t] for t in pandas_times])\n", + "print(\"Polars times:\", [[t] for t in polars_times])\n", + "\n", + "x = range(len(queries))\n", + "xlable = [f\"Q{num}\" for num in x]\n", + "width = 0.2\n", + "\n", + "fig, ax = plt.subplots(figsize=(10, 6), dpi=300)\n", + "\n", + "rects1 = ax.bar(x, duckdb_times, width, label=\"DuckDB\")\n", + "rects2 = ax.bar([i + width for i in x], chdb_times, width, label=\"chDB\")\n", + "rects3 = ax.bar([i + 2 * width for i in x], pandas_times, width, label=\"Pandas\")\n", + "rects4 = ax.bar([i + 3 * width for i in x], polars_times, width, label=\"Polars\")\n", + "\n", + "ax.set_ylabel(\"Time (s)\")\n", + "# ax.set_ylim(0, max(chdb_times) * 1.1)\n", + "ax.set_title(f\"SQL on DataFrame Benchmark Results on {hits.shape[0]} rows of ClickBench\")\n", + "ax.set_xticks([i + width / 2 for i in x])\n", + "ax.set_xticklabels(xlable, rotation=90)\n", + "ax.legend()\n", + "\n", + "# Add the value of each bar on top\n", + "for rect in rects1 + rects2 + rects3 + rects4:\n", + " height = rect.get_height()\n", + " ax.annotate(\n", + " f\"{height:.2f}\",\n", + " xy=(rect.get_x() + rect.get_width() / 2, height),\n", + " xytext=(0, 3),\n", + " textcoords=\"offset points\",\n", + " ha=\"center\",\n", + " va=\"bottom\",\n", + " rotation=90, # Rotate the text 90°\n", + " fontsize=5, # Set the font size to a smaller value\n", + " )\n", + "\n", + "# Compute comparison counts and total times\n", + "better = []\n", + "for i in range(len(queries)):\n", + " min_val = min(duckdb_times[i], chdb_times[i], pandas_times[i])\n", + " if min_val == duckdb_times[i]:\n", + " better.append(\"DuckDB\")\n", + " elif min_val == chdb_times[i]:\n", + " better.append(\"chDB\")\n", + " elif min_val == pandas_times[i]:\n", + " better.append(\"Pandas\")\n", + " elif min_val == polars_times[i]:\n", + " better.append(\"Polars\")\n", + " else:\n", + " better.append(\"Unknown\")\n", + "print(\"DuckDB faster count:\", better.count(\"DuckDB\"))\n", + "print(\"chDB faster count:\", better.count(\"chDB\"))\n", + "print(\"Pandas faster count:\", better.count(\"Pandas\"))\n", + "print(\"Polars faster count:\", better.count(\"Polars\"))\n", + "print(\"DuckDB total time:\", sum(duckdb_times))\n", + "print(\"chDB total time:\", sum(chdb_times))\n", + "print(\"Pandas total time:\", sum(pandas_times))\n", + "print(\"Polars total time:\", sum(polars_times))\n", + "\n", + "\n", + "# Display summary statistics on the plot\n", + "summary_text = f\"Pandas faster count: {better.count('Pandas')}\\n\"\n", + "summary_text += f\"chDB faster count: {better.count('chDB')}\\n\"\n", + "summary_text += f\"DuckDB faster count: {better.count('DuckDB')}\\n\"\n", + "summary_text += f\"Polars faster count: {better.count('Polars')}\\n\\n\"\n", + "summary_text += f\"Pandas total time: {sum(pandas_times):.2f} s\\n\"\n", + "summary_text += f\"chDB total time: {sum(chdb_times):.2f} s\\n\"\n", + "summary_text += f\"DuckDB total time: {sum(duckdb_times):.2f} s\\n\"\n", + "summary_text += f\"Polars total time: {sum(polars_times):.2f} s\\n\\n\"\n", + "\n", + "summary_text += (\n", + " f\"Pandas time range: {min(pandas_times):.2f} ~ {max(pandas_times):.2f} s\\n\"\n", + ")\n", + "summary_text += f\"chDB time range: {min(chdb_times):.2f} ~ {max(chdb_times):.2f} s\\n\"\n", + "summary_text += f\"DuckDB time range: {min(duckdb_times):.2f} ~ {max(duckdb_times):.2f} s\\n\"\n", + "summary_text += f\"Polars time range: {min(polars_times):.2f} ~ {max(polars_times):.2f} s\"\n", + "\n", + "# Position the text at the top right of the chart\n", + "ax.text(\n", + " 0.02,\n", + " 0.98,\n", + " summary_text,\n", + " transform=ax.transAxes,\n", + " fontsize=8,\n", + " verticalalignment=\"top\",\n", + " horizontalalignment=\"left\",\n", + " fontfamily=\"monospace\",\n", + ")\n", + "\n", + "fig.tight_layout()\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.2" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From bb20111f87b82d1d204abf01322d7f472c026afd Mon Sep 17 00:00:00 2001 From: auxten Date: Mon, 19 Aug 2024 18:03:57 +0800 Subject: [PATCH 12/16] Use clickbench index.html for result --- benchmark/cb_index.html.tpl | 917 ++++++++++++++++ benchmark/dataframe.ipynb | 2013 +++++++++++++++++++++-------------- 2 files changed, 2159 insertions(+), 771 deletions(-) create mode 100644 benchmark/cb_index.html.tpl diff --git a/benchmark/cb_index.html.tpl b/benchmark/cb_index.html.tpl new file mode 100644 index 00000000000..363dd5ccacf --- /dev/null +++ b/benchmark/cb_index.html.tpl @@ -0,0 +1,917 @@ + + + + + ClickBench — a Benchmark For Analytical DBMS + + + + + + + + + + + +
+ 🌚🌞 +

ClickBench — a Benchmark For Analytical DBMS

+ Methodology | Reproduce and Validate the Results | Add a System | Report Mistake | Hardware Benchmark | Versions Benchmark +
+ + + + + + + + + + + + + + + + + + + + + + +
System: + All +
Type: + All +
Machine: + All +
Cluster size: + All +
Metric: + Cold Run + Hot Run + Load Time + Storage Size +
+ + + + + + + + + + +
+ System & Machine + + Relative time (lower is better) +
+ +
Nothing selected
+ +
+

Detailed Comparison

+
+ + + + + + + + +
+ + + + + diff --git a/benchmark/dataframe.ipynb b/benchmark/dataframe.ipynb index e7dcd1eeffe..cef55377153 100644 --- a/benchmark/dataframe.ipynb +++ b/benchmark/dataframe.ipynb @@ -17,9 +17,9 @@ "Collecting pandas\n", " Using cached pandas-2.2.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.1 MB)\n", " Using cached pandas-2.2.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.0 MB)\n", - "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.9/dist-packages (from pandas) (2022.7)\n", "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.9/dist-packages (from pandas) (2.8.2)\n", "Requirement already satisfied: numpy>=1.22.4 in /usr/local/lib/python3.9/dist-packages (from pandas) (1.24.2)\n", + "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.9/dist-packages (from pandas) (2022.7)\n", "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.9/dist-packages (from pandas) (2023.3)\n", "Requirement already satisfied: six>=1.5 in /usr/lib/python3/dist-packages (from python-dateutil>=2.8.2->pandas) (1.16.0)\n", "Requirement already satisfied: polars in /usr/local/lib/python3.9/dist-packages (1.5.0)\n", @@ -74,7 +74,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -83,9 +83,9 @@ "text": [ "-rw-r--r-- 1 root root 880M Aug 19 11:34 /tmp/hits10m.parquet\n", "-rw-r--r-- 1 root root 117M Jul 3 2022 /tmp/hits_0.parquet\n", - "Read parquet file into memory. Time cost: 0.465517520904541 s\n", + "Read parquet file into memory. Time cost: 0.47272610664367676 s\n", "Parquet file size: 922699018 bytes\n", - "Read parquet file as old pandas dataframe. Time cost: 10.397734880447388 s\n", + "Read parquet file as old pandas dataframe. Time cost: 10.32185673713684 s\n", "Dataframe(numpy) size: 4700000128 bytes\n" ] } @@ -130,7 +130,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -150,7 +150,7 @@ "Length: 105, dtype: object" ] }, - "execution_count": 2, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -177,14 +177,14 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Convert dataframe to polars dataframe. Time cost: 22.901316165924072 s\n" + "Convert dataframe to polars dataframe. Time cost: 22.842999935150146 s\n" ] } ], @@ -194,12 +194,13 @@ "\n", "t = time.time()\n", "pl_df = pl.DataFrame(hits)\n", - "print(\"Convert dataframe to polars dataframe. Time cost:\", time.time() - t, \"s\")" + "pl_load_time = time.time() - t\n", + "print(\"Convert dataframe to polars dataframe. Time cost:\", pl_load_time, \"s\")" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -224,7 +225,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -429,7 +430,7 @@ " (pl.col(\"URL\").str.contains(\"google\")) & (pl.col(\"SearchPhrase\") != \"\")\n", " )\n", " .group_by(\"SearchPhrase\")\n", - " .agg([pl.col(\"URL\").min(), pl.len()])\n", + " .agg([pl.col(\"URL\").min(), pl.len().alias(\"count\")])\n", " .sort(\"count\", descending=True)\n", " .head(10),\n", " ),\n", @@ -456,7 +457,7 @@ " [\n", " pl.col(\"URL\").min(),\n", " pl.col(\"Title\").min(),\n", - " pl.len(),\n", + " pl.len().alias(\"count\"),\n", " pl.col(\"UserID\").n_unique(),\n", " ]\n", " )\n", @@ -863,7 +864,7 @@ " .nlargest(10)\n", " .reset_index(name=\"PageViews\")\n", " .iloc[1000:1010],\n", - " lambda x: time.sleep(1)\n", + " lambda x: None,\n", " # Crash with:\n", " # thread '' panicked at crates/polars-time/src/windows/duration.rs:215:21:\n", " # expected leading integer in the duration string, found m\n", @@ -962,7 +963,7 @@ " .size()\n", " .reset_index(name=\"PageViews\")\n", " .iloc[1000:1010],\n", - " lambda x: time.sleep(1)\n", + " lambda x: None,\n", " # Crash with:\n", " # thread '' panicked at crates/polars-time/src/windows/duration.rs:215:21:\n", " # expected leading integer in the duration string, found m\n", @@ -982,7 +983,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -990,7 +991,7 @@ "\n", "\n", "def runDuckDB(con, sql):\n", - " used_time = -1\n", + " used_time = None\n", " try:\n", " t = time.time()\n", " ret = con.execute(sql).fetch_df()\n", @@ -1002,7 +1003,7 @@ " return used_time\n", "\n", "def runChDB(sess, sql):\n", - " used_time = -1\n", + " used_time = None\n", " # replace 'hits' with 'Python(df_reader)'\n", " sql = sql.replace(\"hits\", \"Python(hits)\")\n", " # sql = sql.replace(\"hits\", \"__hits__\")\n", @@ -1028,18 +1029,20 @@ " return used_time\n", "\n", "def runPolars(f):\n", - " used_time = -1\n", + " used_time = None\n", " try:\n", " t = time.time()\n", " ret = f(pl_df)\n", " used_time = time.time() - t\n", " print(\"Polars time:\", used_time)\n", " print(\"Polars return:\\n\", ret)\n", + " if ret is None:\n", + " return None\n", " except Exception as e:\n", " print(\"Polars error:\", e)\n", " return used_time\n", "\n", - "def bench(q):\n", + "def bench(q, N=1):\n", " global counter\n", " con = duckdb.connect()\n", " # df_reader = myReader(hits)\n", @@ -1049,18 +1052,20 @@ " polars_time = []\n", " sql = q[1]\n", " print(q[0], sql)\n", - " for i in range(1):\n", + " # pandas is too slow, only run once\n", + " pandas_time.append(runPandas(q[2]))\n", + " for i in range(N):\n", " duckdb_time.append(runDuckDB(con, sql))\n", " chdb_time.append(runChDB(None, sql))\n", - " pandas_time.append(runPandas(q[2]))\n", " polars_time.append(runPolars(q[3]))\n", " counter += 1\n", + " pandas_time = pandas_time * N\n", " return duckdb_time, chdb_time, pandas_time, polars_time" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -1068,15 +1073,7 @@ "output_type": "stream", "text": [ "Q0 SELECT COUNT(*) FROM hits;\n", - "DuckDB time: 0.034766435623168945\n", - "DuckDB return:\n", - " count_star()\n", - "0 10000000\n", - "chDB time: 0.0491330623626709\n", - "chDB return:\n", - " 10000000\n", - "\n", - "Pandas time: 8.846198797225952\n", + "Pandas time: 8.789468765258789\n", "Pandas return:\n", " WatchID 10000000\n", "JavaEnable 10000000\n", @@ -1090,19 +1087,19 @@ "URLHash 10000000\n", "CLID 10000000\n", "Length: 105, dtype: int64\n", - "Polars time: 1.8835067749023438e-05\n", - "Polars return:\n", - " 10000000\n", - "Q1 SELECT COUNT(*) FROM hits WHERE AdvEngineID <> 0;\n", - "DuckDB time: 0.024944543838500977\n", + "DuckDB time: 0.03433990478515625\n", "DuckDB return:\n", " count_star()\n", - "0 99649\n", - "chDB time: 0.025159835815429688\n", + "0 10000000\n", + "chDB time: 0.06516456604003906\n", "chDB return:\n", - " 99649\n", + " 10000000\n", "\n", - "Pandas time: 0.18808650970458984\n", + "Polars time: 1.6450881958007812e-05\n", + "Polars return:\n", + " 10000000\n", + "Q1 SELECT COUNT(*) FROM hits WHERE AdvEngineID <> 0;\n", + "Pandas time: 0.16229581832885742\n", "Pandas return:\n", " WatchID 99649\n", "JavaEnable 99649\n", @@ -1116,86 +1113,110 @@ "URLHash 99649\n", "CLID 99649\n", "Length: 105, dtype: int64\n", - "Polars time: 0.02273273468017578\n", + "DuckDB time: 0.026508569717407227\n", + "DuckDB return:\n", + " count_star()\n", + "0 99649\n", + "chDB time: 0.027498722076416016\n", + "chDB return:\n", + " 99649\n", + "\n", + "Polars time: 0.02317357063293457\n", "Polars return:\n", " 99649\n", "Q2 SELECT SUM(AdvEngineID), COUNT(*), AVG(ResolutionWidth) FROM hits;\n", - "DuckDB time: 0.024078369140625\n", + "Pandas time: 0.007686138153076172\n", + "Pandas return:\n", + " (1635226, 10000000, 1507.7792377)\n", + "DuckDB time: 0.02513861656188965\n", "DuckDB return:\n", " sum(AdvEngineID) count_star() avg(ResolutionWidth)\n", "0 1635226.0 10000000 1507.779238\n", - "chDB time: 0.023288726806640625\n", + "chDB time: 0.02389240264892578\n", "chDB return:\n", " 1635226,10000000,1507.7792377\n", "\n", - "Pandas time: 0.007757902145385742\n", - "Pandas return:\n", - " (1635226, 10000000, 1507.7792377)\n", - "Polars time: 0.03901386260986328\n", + "Polars time: 0.03767538070678711\n", "Polars return:\n", " (1635226, 10000000, 1507.7792377)\n", "Q3 SELECT AVG(UserID) FROM hits;\n", - "DuckDB time: 0.02106475830078125\n", + "Pandas time: 0.007529735565185547\n", + "Pandas return:\n", + " 2.50007340441956e+18\n", + "DuckDB time: 0.021852970123291016\n", "DuckDB return:\n", " avg(UserID)\n", "0 2.500073e+18\n", - "chDB time: 0.022477149963378906\n", + "chDB time: 0.026594877243041992\n", "chDB return:\n", " -907169442272.5032\n", "\n", - "Pandas time: 0.007812023162841797\n", - "Pandas return:\n", - " 2.50007340441956e+18\n", - "Polars time: 0.0026862621307373047\n", + "Polars time: 0.004158496856689453\n", "Polars return:\n", " 2.5000734044195615e+18\n", "Q4 SELECT COUNT(DISTINCT UserID) FROM hits;\n", - "DuckDB time: 0.07841730117797852\n", + "Pandas time: 0.21137714385986328\n", + "Pandas return:\n", + " 2161466\n", + "DuckDB time: 0.07819533348083496\n", "DuckDB return:\n", " count(DISTINCT UserID)\n", "0 2161466\n", - "chDB time: 0.17466950416564941\n", + "chDB time: 0.18276023864746094\n", "chDB return:\n", " 2161466\n", "\n", - "Pandas time: 0.26064276695251465\n", - "Pandas return:\n", - " 2161466\n", - "Polars time: 0.14067935943603516\n", + "Polars time: 0.13331985473632812\n", "Polars return:\n", " 2161466\n", "Q5 SELECT COUNT(DISTINCT SearchPhrase) FROM hits;\n", - "DuckDB time: 0.13242697715759277\n", + "Pandas time: 0.6686234474182129\n", + "Pandas return:\n", + " 849107\n", + "DuckDB time: 0.08364367485046387\n", "DuckDB return:\n", " count(DISTINCT SearchPhrase)\n", "0 849107\n", - "chDB time: 0.17357873916625977\n", + "chDB time: 0.1492304801940918\n", "chDB return:\n", " 849107\n", "\n", - "Pandas time: 0.6738917827606201\n", - "Pandas return:\n", - " 849107\n", - "Polars time: 0.30411481857299805\n", + "Polars time: 0.3041989803314209\n", "Polars return:\n", " 849107\n", "Q6 SELECT MIN(EventDate), MAX(EventDate) FROM hits;\n", - "DuckDB time: 0.023054838180541992\n", + "Pandas time: 0.02013540267944336\n", + "Pandas return:\n", + " (Timestamp('2013-07-02 00:00:00'), Timestamp('2013-07-31 00:00:00'))\n", + "DuckDB time: 0.024533987045288086\n", "DuckDB return:\n", " min(EventDate) max(EventDate)\n", "0 2013-07-02 2013-07-31\n", - "chDB time: 0.028813600540161133\n", + "chDB time: 0.025769948959350586\n", "chDB return:\n", " \"2013-07-02 08:00:00.000000000\",\"2013-07-31 08:00:00.000000000\"\n", "\n", - "Pandas time: 0.021489381790161133\n", - "Pandas return:\n", - " (Timestamp('2013-07-02 00:00:00'), Timestamp('2013-07-31 00:00:00'))\n", - "Polars time: 0.006089925765991211\n", + "Polars time: 0.00613856315612793\n", "Polars return:\n", " (datetime.datetime(2013, 7, 2, 0, 0), datetime.datetime(2013, 7, 31, 0, 0))\n", "Q7 SELECT AdvEngineID, COUNT(*) FROM hits WHERE AdvEngineID <> 0 GROUP BY AdvEngineID ORDER BY COUNT(*) DESC;\n", - "DuckDB time: 0.0420222282409668\n", + "Pandas time: 0.07054853439331055\n", + "Pandas return:\n", + " AdvEngineID\n", + "2 46435\n", + "27 39607\n", + "45 5764\n", + "13 4216\n", + "44 3067\n", + "52 330\n", + "3 79\n", + "50 62\n", + "28 59\n", + "61 15\n", + "53 14\n", + "25 1\n", + "dtype: int64\n", + "DuckDB time: 0.046100616455078125\n", "DuckDB return:\n", " AdvEngineID count_star()\n", "0 2 46435\n", @@ -1210,7 +1231,7 @@ "9 61 15\n", "10 53 14\n", "11 25 1\n", - "chDB time: 0.052686214447021484\n", + "chDB time: 0.054378509521484375\n", "chDB return:\n", " 2,46435\n", "27,39607\n", @@ -1225,23 +1246,7 @@ "53,14\n", "25,1\n", "\n", - "Pandas time: 0.08373761177062988\n", - "Pandas return:\n", - " AdvEngineID\n", - "2 46435\n", - "27 39607\n", - "45 5764\n", - "13 4216\n", - "44 3067\n", - "52 330\n", - "3 79\n", - "50 62\n", - "28 59\n", - "61 15\n", - "53 14\n", - "25 1\n", - "dtype: int64\n", - "Polars time: 0.02827906608581543\n", + "Polars time: 0.027820348739624023\n", "Polars return:\n", " shape: (12, 2)\n", "┌─────────────┬───────┐\n", @@ -1262,7 +1267,21 @@ "│ 25 ┆ 1 │\n", "└─────────────┴───────┘\n", "Q8 SELECT RegionID, COUNT(DISTINCT UserID) AS u FROM hits GROUP BY RegionID ORDER BY u DESC LIMIT 10;\n", - "DuckDB time: 0.09740638732910156\n", + "Pandas time: 0.5789997577667236\n", + "Pandas return:\n", + " RegionID\n", + "229 356130\n", + "2 150316\n", + "208 100038\n", + "169 69299\n", + "107 37571\n", + "34 35246\n", + "184 34285\n", + "55 33522\n", + "158 31849\n", + "42 31432\n", + "Name: UserID, dtype: int64\n", + "DuckDB time: 0.09088969230651855\n", "DuckDB return:\n", " RegionID u\n", "0 229 356130\n", @@ -1275,7 +1294,7 @@ "7 55 33522\n", "8 158 31849\n", "9 42 31432\n", - "chDB time: 0.0731050968170166\n", + "chDB time: 0.08289217948913574\n", "chDB return:\n", " 229,356130\n", "2,150316\n", @@ -1288,21 +1307,7 @@ "158,31849\n", "42,31432\n", "\n", - "Pandas time: 0.6383168697357178\n", - "Pandas return:\n", - " RegionID\n", - "229 356130\n", - "2 150316\n", - "208 100038\n", - "169 69299\n", - "107 37571\n", - "34 35246\n", - "184 34285\n", - "55 33522\n", - "158 31849\n", - "42 31432\n", - "Name: UserID, dtype: int64\n", - "Polars time: 0.23999881744384766\n", + "Polars time: 0.2607238292694092\n", "Polars return:\n", " shape: (10, 2)\n", "┌──────────┬────────┐\n", @@ -1322,7 +1327,21 @@ "│ 42 ┆ 31432 │\n", "└──────────┴────────┘\n", "Q9 SELECT RegionID, SUM(AdvEngineID), COUNT(*) AS c, AVG(ResolutionWidth), COUNT(DISTINCT UserID) FROM hits GROUP BY RegionID ORDER BY c DESC LIMIT 10;\n", - "DuckDB time: 0.12623929977416992\n", + "Pandas time: 0.6821517944335938\n", + "Pandas return:\n", + " AdvEngineID ResolutionWidth UserID\n", + "RegionID \n", + "229 391301 1511.768654 356130\n", + "2 101985 1426.560820 150316\n", + "208 69554 1291.526935 100038\n", + "34 32232 1560.577018 35246\n", + "42 27753 1593.974549 31432\n", + "55 26257 1346.594102 33522\n", + "1 25468 1571.634042 28590\n", + "107 25014 1415.724206 37571\n", + "169 23595 1460.090695 69299\n", + "51 22510 1584.785671 25803\n", + "DuckDB time: 0.12663817405700684\n", "DuckDB return:\n", " RegionID sum(AdvEngineID) c avg(ResolutionWidth) \\\n", "0 229 391301.0 1819609 1511.768654 \n", @@ -1347,7 +1366,7 @@ "7 37571 \n", "8 35246 \n", "9 33522 \n", - "chDB time: 0.09501290321350098\n", + "chDB time: 0.09233450889587402\n", "chDB return:\n", " 229,391301,1819609,1511.7686535953603,356130\n", "2,101985,732566,1426.560820458498,150316\n", @@ -1360,21 +1379,7 @@ "34,32232,141992,1560.5770184235732,35246\n", "55,26257,138998,1346.594102073411,33522\n", "\n", - "Pandas time: 0.7432992458343506\n", - "Pandas return:\n", - " AdvEngineID ResolutionWidth UserID\n", - "RegionID \n", - "229 391301 1511.768654 356130\n", - "2 101985 1426.560820 150316\n", - "208 69554 1291.526935 100038\n", - "34 32232 1560.577018 35246\n", - "42 27753 1593.974549 31432\n", - "55 26257 1346.594102 33522\n", - "1 25468 1571.634042 28590\n", - "107 25014 1415.724206 37571\n", - "169 23595 1460.090695 69299\n", - "51 22510 1584.785671 25803\n", - "Polars time: 0.23104381561279297\n", + "Polars time: 0.24764204025268555\n", "Polars return:\n", " shape: (10, 4)\n", "┌──────────┬─────────────────┬──────────────────────┬────────────────┐\n", @@ -1394,7 +1399,21 @@ "│ 51 ┆ 22510 ┆ 1584.785671 ┆ 25803 │\n", "└──────────┴─────────────────┴──────────────────────┴────────────────┘\n", "Q10 SELECT MobilePhoneModel, COUNT(DISTINCT UserID) AS u FROM hits WHERE MobilePhoneModel <> '' GROUP BY MobilePhoneModel ORDER BY u DESC LIMIT 10;\n", - "DuckDB time: 0.06863808631896973\n", + "Pandas time: 0.839637279510498\n", + "Pandas return:\n", + " MobilePhoneModel\n", + "iPad 127994\n", + "iPhone 5736\n", + "A500 2177\n", + "N8-00 680\n", + "iPho 364\n", + "ONE TOUCH 6030A 315\n", + "GT-P7300B 239\n", + "3110000 217\n", + "GT-I9500 198\n", + "eagle75 181\n", + "Name: UserID, dtype: int64\n", + "DuckDB time: 0.052741050720214844\n", "DuckDB return:\n", " MobilePhoneModel u\n", "0 iPad 127994\n", @@ -1407,7 +1426,7 @@ "7 3110000 217\n", "8 GT-I9500 198\n", "9 eagle75 181\n", - "chDB time: 0.09412217140197754\n", + "chDB time: 0.09442925453186035\n", "chDB return:\n", " \"iPad\",127994\n", "\"iPhone\",5736\n", @@ -1420,21 +1439,7 @@ "\"GT-I9500\",198\n", "\"eagle75\",181\n", "\n", - "Pandas time: 0.8355112075805664\n", - "Pandas return:\n", - " MobilePhoneModel\n", - "iPad 127994\n", - "iPhone 5736\n", - "A500 2177\n", - "N8-00 680\n", - "iPho 364\n", - "ONE TOUCH 6030A 315\n", - "GT-P7300B 239\n", - "3110000 217\n", - "GT-I9500 198\n", - "eagle75 181\n", - "Name: UserID, dtype: int64\n", - "Polars time: 0.11121845245361328\n", + "Polars time: 0.12893366813659668\n", "Polars return:\n", " shape: (10, 2)\n", "┌──────────────────┬────────┐\n", @@ -1454,7 +1459,21 @@ "│ eagle75 ┆ 181 │\n", "└──────────────────┴────────┘\n", "Q11 SELECT MobilePhone, MobilePhoneModel, COUNT(DISTINCT UserID) AS u FROM hits WHERE MobilePhoneModel <> '' GROUP BY MobilePhone, MobilePhoneModel ORDER BY u DESC LIMIT 10;\n", - "DuckDB time: 0.06034088134765625\n", + "Pandas time: 0.8696815967559814\n", + "Pandas return:\n", + " MobilePhone MobilePhoneModel\n", + "1 iPad 108339\n", + "5 iPad 6054\n", + "6 iPad 3638\n", + "7 iPad 3356\n", + "118 A500 2167\n", + "6 iPhone 1844\n", + "26 iPhone 1584\n", + "10 iPad 1370\n", + "32 iPad 1196\n", + "13 iPad 1163\n", + "Name: UserID, dtype: int64\n", + "DuckDB time: 0.0588836669921875\n", "DuckDB return:\n", " MobilePhone MobilePhoneModel u\n", "0 1 iPad 108339\n", @@ -1467,7 +1486,7 @@ "7 10 iPad 1370\n", "8 32 iPad 1196\n", "9 13 iPad 1163\n", - "chDB time: 0.05431222915649414\n", + "chDB time: 0.05849885940551758\n", "chDB return:\n", " 1,\"iPad\",108339\n", "5,\"iPad\",6054\n", @@ -1480,21 +1499,7 @@ "32,\"iPad\",1196\n", "13,\"iPad\",1163\n", "\n", - "Pandas time: 0.858731746673584\n", - "Pandas return:\n", - " MobilePhone MobilePhoneModel\n", - "1 iPad 108339\n", - "5 iPad 6054\n", - "6 iPad 3638\n", - "7 iPad 3356\n", - "118 A500 2167\n", - "6 iPhone 1844\n", - "26 iPhone 1584\n", - "10 iPad 1370\n", - "32 iPad 1196\n", - "13 iPad 1163\n", - "Name: UserID, dtype: int64\n", - "Polars time: 0.10175633430480957\n", + "Polars time: 0.1208345890045166\n", "Polars return:\n", " shape: (10, 3)\n", "┌─────────────┬──────────────────┬────────┐\n", @@ -1514,7 +1519,21 @@ "│ 13 ┆ iPad ┆ 1163 │\n", "└─────────────┴──────────────────┴────────┘\n", "Q12 SELECT SearchPhrase, COUNT(*) AS c FROM hits WHERE SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;\n", - "DuckDB time: 0.10154414176940918\n", + "Pandas time: 2.7713074684143066\n", + "Pandas return:\n", + " SearchPhrase\n", + "албатрутдин 6310\n", + "какой областиков 3120\n", + "смотреть онлайн 2678\n", + "какой областиницы цена 2497\n", + "смотреть онлайн бесплатно 2485\n", + "galaxy table 1996\n", + "смотреть 1944\n", + "ведомосквы вместу 1559\n", + "экзоидные 1432\n", + "карелки 1280\n", + "dtype: int64\n", + "DuckDB time: 0.09914731979370117\n", "DuckDB return:\n", " SearchPhrase c\n", "0 албатрутдин 6310\n", @@ -1527,7 +1546,7 @@ "7 ведомосквы вместу 1559\n", "8 экзоидные 1432\n", "9 карелки 1280\n", - "chDB time: 0.11616373062133789\n", + "chDB time: 0.12346029281616211\n", "chDB return:\n", " \"албатрутдин\",6310\n", "\"какой областиков\",3120\n", @@ -1540,21 +1559,7 @@ "\"экзоидные\",1432\n", "\"карелки\",1280\n", "\n", - "Pandas time: 2.808490514755249\n", - "Pandas return:\n", - " SearchPhrase\n", - "албатрутдин 6310\n", - "какой областиков 3120\n", - "смотреть онлайн 2678\n", - "какой областиницы цена 2497\n", - "смотреть онлайн бесплатно 2485\n", - "galaxy table 1996\n", - "смотреть 1944\n", - "ведомосквы вместу 1559\n", - "экзоидные 1432\n", - "карелки 1280\n", - "dtype: int64\n", - "Polars time: 0.19967889785766602\n", + "Polars time: 0.19979619979858398\n", "Polars return:\n", " shape: (10, 2)\n", "┌───────────────────────────┬───────┐\n", @@ -1574,7 +1579,21 @@ "│ карелки ┆ 1280 │\n", "└───────────────────────────┴───────┘\n", "Q13 SELECT SearchPhrase, COUNT(DISTINCT UserID) AS u FROM hits WHERE SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY u DESC LIMIT 10;\n", - "DuckDB time: 0.18241262435913086\n", + "Pandas time: 2.760340929031372\n", + "Pandas return:\n", + " SearchPhrase\n", + "албатрутдин 3373\n", + "какой областиков 2360\n", + "смотреть онлайн 2199\n", + "смотреть онлайн бесплатно 2066\n", + "какой областиницы цена 1860\n", + "смотреть 1498\n", + "экзоидные 1256\n", + "тайны избавлению акручить 960\n", + "какой области за улыбки бмв е34 936\n", + "galaxy table 868\n", + "Name: UserID, dtype: int64\n", + "DuckDB time: 0.1588895320892334\n", "DuckDB return:\n", " SearchPhrase u\n", "0 албатрутдин 3373\n", @@ -1587,7 +1606,7 @@ "7 тайны избавлению акручить 960\n", "8 какой области за улыбки бмв е34 936\n", "9 galaxy table 868\n", - "chDB time: 0.12112832069396973\n", + "chDB time: 0.11397171020507812\n", "chDB return:\n", " \"албатрутдин\",3373\n", "\"какой областиков\",2360\n", @@ -1600,21 +1619,7 @@ "\"какой области за улыбки бмв е34\",936\n", "\"galaxy table\",868\n", "\n", - "Pandas time: 2.7532732486724854\n", - "Pandas return:\n", - " SearchPhrase\n", - "албатрутдин 3373\n", - "какой областиков 2360\n", - "смотреть онлайн 2199\n", - "смотреть онлайн бесплатно 2066\n", - "какой областиницы цена 1860\n", - "смотреть 1498\n", - "экзоидные 1256\n", - "тайны избавлению акручить 960\n", - "какой области за улыбки бмв е34 936\n", - "galaxy table 868\n", - "Name: UserID, dtype: int64\n", - "Polars time: 21.907146692276\n", + "Polars time: 22.400670289993286\n", "Polars return:\n", " shape: (10, 2)\n", "┌─────────────────────────────────┬────────┐\n", @@ -1634,7 +1639,21 @@ "│ galaxy table ┆ 868 │\n", "└─────────────────────────────────┴────────┘\n", "Q14 SELECT SearchEngineID, SearchPhrase, COUNT(*) AS c FROM hits WHERE SearchPhrase <> '' GROUP BY SearchEngineID, SearchPhrase ORDER BY c DESC LIMIT 10;\n", - "DuckDB time: 0.12200570106506348\n", + "Pandas time: 8.411752223968506\n", + "Pandas return:\n", + " SearchEngineID SearchPhrase \n", + "3 албатрутдин 3016\n", + "2 албатрутдин 2585\n", + " какой областиницы цена 2432\n", + " смотреть онлайн 1964\n", + " смотреть онлайн бесплатно 1765\n", + " какой областиков 1599\n", + " смотреть 1291\n", + " тайны избавлению акручить 1273\n", + " экзоидные 1187\n", + " тихоокеанский списание пределирова 1079\n", + "dtype: int64\n", + "DuckDB time: 0.10474276542663574\n", "DuckDB return:\n", " SearchEngineID SearchPhrase c\n", "0 3 албатрутдин 3016\n", @@ -1647,7 +1666,7 @@ "7 2 тайны избавлению акручить 1273\n", "8 2 экзоидные 1187\n", "9 2 тихоокеанский списание пределирова 1079\n", - "chDB time: 0.11324310302734375\n", + "chDB time: 0.10899591445922852\n", "chDB return:\n", " 3,\"албатрутдин\",3016\n", "2,\"албатрутдин\",2585\n", @@ -1660,21 +1679,7 @@ "2,\"экзоидные\",1187\n", "2,\"тихоокеанский списание пределирова\",1079\n", "\n", - "Pandas time: 8.408371925354004\n", - "Pandas return:\n", - " SearchEngineID SearchPhrase \n", - "3 албатрутдин 3016\n", - "2 албатрутдин 2585\n", - " какой областиницы цена 2432\n", - " смотреть онлайн 1964\n", - " смотреть онлайн бесплатно 1765\n", - " какой областиков 1599\n", - " смотреть 1291\n", - " тайны избавлению акручить 1273\n", - " экзоидные 1187\n", - " тихоокеанский списание пределирова 1079\n", - "dtype: int64\n", - "Polars time: 0.22452998161315918\n", + "Polars time: 0.18914175033569336\n", "Polars return:\n", " shape: (10, 3)\n", "┌────────────────┬─────────────────────────────────┬───────┐\n", @@ -1694,7 +1699,21 @@ "│ 2 ┆ тихоокеанский списание предели… ┆ 1079 │\n", "└────────────────┴─────────────────────────────────┴───────┘\n", "Q15 SELECT UserID, COUNT(*) FROM hits GROUP BY UserID ORDER BY COUNT(*) DESC LIMIT 10;\n", - "DuckDB time: 0.07353830337524414\n", + "Pandas time: 0.7016208171844482\n", + "Pandas return:\n", + " UserID\n", + "1313338681122956954 15792\n", + "1907779576417363396 6229\n", + "5730251990344211405 6019\n", + "7280399273658728997 6015\n", + "835157184735512989 5211\n", + "823824530034798601 2897\n", + "938290163257834024 2685\n", + "4931847376428061501 2537\n", + "6949028786848070043 2496\n", + "2763860660987168393 2179\n", + "dtype: int64\n", + "DuckDB time: 0.08089947700500488\n", "DuckDB return:\n", " UserID count_star()\n", "0 1313338681122956954 15792\n", @@ -1707,7 +1726,7 @@ "7 4931847376428061501 2537\n", "8 6949028786848070043 2496\n", "9 2763860660987168393 2179\n", - "chDB time: 0.09562420845031738\n", + "chDB time: 0.08938097953796387\n", "chDB return:\n", " 1313338681122956954,15792\n", "1907779576417363396,6229\n", @@ -1720,21 +1739,7 @@ "6949028786848070043,2496\n", "2763860660987168393,2179\n", "\n", - "Pandas time: 0.803398847579956\n", - "Pandas return:\n", - " UserID\n", - "1313338681122956954 15792\n", - "1907779576417363396 6229\n", - "5730251990344211405 6019\n", - "7280399273658728997 6015\n", - "835157184735512989 5211\n", - "823824530034798601 2897\n", - "938290163257834024 2685\n", - "4931847376428061501 2537\n", - "6949028786848070043 2496\n", - "2763860660987168393 2179\n", - "dtype: int64\n", - "Polars time: 0.13240408897399902\n", + "Polars time: 0.12315940856933594\n", "Polars return:\n", " shape: (10, 2)\n", "┌─────────────────────┬───────┐\n", @@ -1754,7 +1759,21 @@ "│ 2763860660987168393 ┆ 2179 │\n", "└─────────────────────┴───────┘\n", "Q16 SELECT UserID, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, SearchPhrase ORDER BY COUNT(*) DESC LIMIT 10;\n", - "DuckDB time: 0.14850163459777832\n", + "Pandas time: 25.73132586479187\n", + "Pandas return:\n", + " UserID SearchPhrase\n", + "1313338681122956954 15792\n", + "1907779576417363396 6229\n", + "5730251990344211405 6019\n", + "7280399273658728997 6015\n", + "835157184735512989 5209\n", + "823824530034798601 2897\n", + "938290163257834024 2684\n", + "4931847376428061501 2537\n", + "6949028786848070043 2496\n", + "2763860660987168393 2179\n", + "dtype: int64\n", + "DuckDB time: 0.14031195640563965\n", "DuckDB return:\n", " UserID SearchPhrase count_star()\n", "0 1313338681122956954 15792\n", @@ -1767,7 +1786,7 @@ "7 4931847376428061501 2537\n", "8 6949028786848070043 2496\n", "9 2763860660987168393 2179\n", - "chDB time: 0.14157438278198242\n", + "chDB time: 0.15292119979858398\n", "chDB return:\n", " 1313338681122956954,\"\",15792\n", "1907779576417363396,\"\",6229\n", @@ -1780,21 +1799,7 @@ "6949028786848070043,\"\",2496\n", "2763860660987168393,\"\",2179\n", "\n", - "Pandas time: 25.871644020080566\n", - "Pandas return:\n", - " UserID SearchPhrase\n", - "1313338681122956954 15792\n", - "1907779576417363396 6229\n", - "5730251990344211405 6019\n", - "7280399273658728997 6015\n", - "835157184735512989 5209\n", - "823824530034798601 2897\n", - "938290163257834024 2684\n", - "4931847376428061501 2537\n", - "6949028786848070043 2496\n", - "2763860660987168393 2179\n", - "dtype: int64\n", - "Polars time: 0.19805002212524414\n", + "Polars time: 0.2002735137939453\n", "Polars return:\n", " shape: (10, 3)\n", "┌─────────────────────┬──────────────┬───────┐\n", @@ -1814,33 +1819,7 @@ "│ 2763860660987168393 ┆ ┆ 2179 │\n", "└─────────────────────┴──────────────┴───────┘\n", "Q17 SELECT UserID, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, SearchPhrase LIMIT 10;\n", - "DuckDB time: 0.15410304069519043\n", - "DuckDB return:\n", - " UserID SearchPhrase count_star()\n", - "0 1282336503961623558 13\n", - "1 1282552915108844899 1\n", - "2 1283150242784481791 4\n", - "3 1283160278491966765 2\n", - "4 1283385628089856902 1\n", - "5 1283747091700878296 3\n", - "6 1284305367319766517 3\n", - "7 1284375869523640234 4\n", - "8 1284450031855186099 4\n", - "9 1284916964337633798 1\n", - "chDB time: 0.13107848167419434\n", - "chDB return:\n", - " 64240392369242065,\"\",1\n", - "8485164694783743007,\"сила 1 сезон 14 серии петти америвод\",1\n", - "3144110468796962613,\"\",2\n", - "51580606420354603,\"\",1\n", - "119657425828985633,\"\",1\n", - "977272874002472411,\"заказочный бёрс\",1\n", - "7510587892824469257,\"sia 265 сезон 6 серии\",1\n", - "1127993622760818270,\"\",8\n", - "9195634693788664967,\"шнекамске воды легенда проекты двухэтажа б у гармошку тсж от челябинсов\",1\n", - "2013228973047199893,\"\",85\n", - "\n", - "Pandas time: 2.864093542098999\n", + "Pandas time: 2.7518060207366943\n", "Pandas return:\n", " UserID SearchPhrase \n", "-9223344277659414581 1\n", @@ -1854,27 +1833,79 @@ "-9222499855151233211 двигательная 1\n", "-9222343920573852356 1\n", "dtype: int64\n", - "Polars time: 0.12165307998657227\n", + "DuckDB time: 0.14226555824279785\n", + "DuckDB return:\n", + " UserID SearchPhrase \\\n", + "0 2067839734864177164 можно в хорошем качественности, рязани \n", + "1 2067911873864507048 \n", + "2 2067982467443095417 большая \n", + "3 2068028751116662709 страйк все \n", + "4 2068385428180252259 \n", + "5 2068785294410515426 audia dell versionald games/inter to thickelba... \n", + "6 2069137487120986808 \n", + "7 2069532975163795814 так вы без погода в москва округалии лета \n", + "8 2070057092221630566 \n", + "9 2070768471638969442 \n", + "\n", + " count_star() \n", + "0 1 \n", + "1 5 \n", + "2 1 \n", + "3 1 \n", + "4 3 \n", + "5 1 \n", + "6 1 \n", + "7 1 \n", + "8 1 \n", + "9 3 \n", + "chDB time: 0.1154947280883789\n", + "chDB return:\n", + " 5742717625414611048,\"\",8\n", + "606822877990268040,\"\",12\n", + "5018087054317440147,\"как устанонс мобиля\",1\n", + "129826221932705812,\"вишней омлет девочка+разгромка\",1\n", + "2042388960092399588,\"лучшие фильтрумента в в просмотреть\",1\n", + "7186620158467454830,\"\",29\n", + "202455993298910909,\"гост себя любимом с над ypoвнем новгороде 2\",1\n", + "6554463836776792292,\"туры и крышу себя сыне смотреть\",2\n", + "9154614177984085670,\"\",1\n", + "831971788620719538,\"\",10\n", + "\n", + "Polars time: 0.11278939247131348\n", "Polars return:\n", " shape: (10, 3)\n", - "┌─────────────────────┬─────────────────────────────────┬─────┐\n", - "│ UserID ┆ SearchPhrase ┆ len │\n", - "│ --- ┆ --- ┆ --- │\n", - "│ i64 ┆ str ┆ u32 │\n", - "╞═════════════════════╪═════════════════════════════════╪═════╡\n", - "│ 1202649428574067922 ┆ ┆ 4 │\n", - "│ 3088214486324770626 ┆ ┆ 1 │\n", - "│ 750099004694464647 ┆ ┆ 1 │\n", - "│ 1396180892504645808 ┆ ┆ 1 │\n", - "│ 5534083794574392552 ┆ ┆ 3 │\n", - "│ 4192165551454517056 ┆ ┆ 1 │\n", - "│ 1624213886631847400 ┆ ┆ 1 │\n", - "│ 2379205851600461426 ┆ горостопортал сколь ┆ 1 │\n", - "│ 98053846500825040 ┆ 5-ая пежо сектомастурбация ┆ 1 │\n", - "│ 2265155232299302110 ┆ универмени+дорожно д 114:38 се… ┆ 1 │\n", - "└─────────────────────┴─────────────────────────────────┴─────┘\n", + "┌─────────────────────┬──────────────┬─────┐\n", + "│ UserID ┆ SearchPhrase ┆ len │\n", + "│ --- ┆ --- ┆ --- │\n", + "│ i64 ┆ str ┆ u32 │\n", + "╞═════════════════════╪══════════════╪═════╡\n", + "│ 5988593630065757268 ┆ ┆ 2 │\n", + "│ 1513436774088293151 ┆ ┆ 2 │\n", + "│ 5864358838903309618 ┆ ┆ 8 │\n", + "│ 716033621076183704 ┆ ┆ 14 │\n", + "│ 916057460362160912 ┆ ┆ 2 │\n", + "│ 1100534328207389682 ┆ ┆ 1 │\n", + "│ 3265508986319153327 ┆ ┆ 2 │\n", + "│ 1048348760838071640 ┆ ┆ 1 │\n", + "│ 1355522988708024425 ┆ ┆ 17 │\n", + "│ 5174039745845605041 ┆ ┆ 1 │\n", + "└─────────────────────┴──────────────┴─────┘\n", "Q18 SELECT UserID, extract(minute FROM EventTime) AS m, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, m, SearchPhrase ORDER BY COUNT(*) DESC LIMIT 10;\n", - "DuckDB time: 0.20395946502685547\n", + "Pandas time: 54.36725902557373\n", + "Pandas return:\n", + " UserID EventTime SearchPhrase\n", + "1313338681122956954 33 324\n", + " 30 323\n", + " 28 314\n", + " 31 311\n", + " 29 308\n", + " 34 306\n", + " 32 302\n", + " 12 296\n", + " 27 296\n", + " 8 294\n", + "dtype: int64\n", + "DuckDB time: 0.2024822235107422\n", "DuckDB return:\n", " UserID m SearchPhrase count_star()\n", "0 1313338681122956954 33 324\n", @@ -1884,10 +1915,10 @@ "4 1313338681122956954 29 308\n", "5 1313338681122956954 34 306\n", "6 1313338681122956954 32 302\n", - "7 1313338681122956954 27 296\n", - "8 1313338681122956954 12 296\n", - "9 1313338681122956954 8 294\n", - "chDB time: 0.19141697883605957\n", + "7 1313338681122956954 12 296\n", + "8 1313338681122956954 27 296\n", + "9 1313338681122956954 10 294\n", + "chDB time: 0.195556640625\n", "chDB return:\n", " 1313338681122956954,33,\"\",324\n", "1313338681122956954,30,\"\",323\n", @@ -1900,21 +1931,7 @@ "1313338681122956954,27,\"\",296\n", "1313338681122956954,10,\"\",294\n", "\n", - "Pandas time: 54.19946789741516\n", - "Pandas return:\n", - " UserID EventTime SearchPhrase\n", - "1313338681122956954 33 324\n", - " 30 323\n", - " 28 314\n", - " 31 311\n", - " 29 308\n", - " 34 306\n", - " 32 302\n", - " 12 296\n", - " 27 296\n", - " 8 294\n", - "dtype: int64\n", - "Polars time: 0.4682021141052246\n", + "Polars time: 0.4637932777404785\n", "Polars return:\n", " shape: (10, 4)\n", "┌─────────────────────┬───────────┬──────────────┬───────┐\n", @@ -1929,27 +1946,27 @@ "│ 1313338681122956954 ┆ 29 ┆ ┆ 308 │\n", "│ 1313338681122956954 ┆ 34 ┆ ┆ 306 │\n", "│ 1313338681122956954 ┆ 32 ┆ ┆ 302 │\n", - "│ 1313338681122956954 ┆ 12 ┆ ┆ 296 │\n", "│ 1313338681122956954 ┆ 27 ┆ ┆ 296 │\n", - "│ 1313338681122956954 ┆ 10 ┆ ┆ 294 │\n", + "│ 1313338681122956954 ┆ 12 ┆ ┆ 296 │\n", + "│ 1313338681122956954 ┆ 8 ┆ ┆ 294 │\n", "└─────────────────────┴───────────┴──────────────┴───────┘\n", "Q19 SELECT UserID FROM hits WHERE UserID = 435090932899640449;\n", - "DuckDB time: 0.027832508087158203\n", - "DuckDB return:\n", - " Empty DataFrame\n", - "Columns: [UserID]\n", - "Index: []\n", - "chDB time: 0.02431321144104004\n", - "chDB return:\n", - " \n", - "Pandas time: 0.00603938102722168\n", + "Pandas time: 0.0063283443450927734\n", "Pandas return:\n", " Empty DataFrame\n", "Columns: [WatchID, JavaEnable, Title, GoodEvent, EventTime, EventDate, CounterID, ClientIP, RegionID, UserID, CounterClass, OS, UserAgent, URL, Referer, IsRefresh, RefererCategoryID, RefererRegionID, URLCategoryID, URLRegionID, ResolutionWidth, ResolutionHeight, ResolutionDepth, FlashMajor, FlashMinor, FlashMinor2, NetMajor, NetMinor, UserAgentMajor, UserAgentMinor, CookieEnable, JavascriptEnable, IsMobile, MobilePhone, MobilePhoneModel, Params, IPNetworkID, TraficSourceID, SearchEngineID, SearchPhrase, AdvEngineID, IsArtifical, WindowClientWidth, WindowClientHeight, ClientTimeZone, ClientEventTime, SilverlightVersion1, SilverlightVersion2, SilverlightVersion3, SilverlightVersion4, PageCharset, CodeVersion, IsLink, IsDownload, IsNotBounce, FUniqID, OriginalURL, HID, IsOldCounter, IsEvent, IsParameter, DontCountHits, WithHash, HitColor, LocalEventTime, Age, Sex, Income, Interests, Robotness, RemoteIP, WindowName, OpenerName, HistoryLength, BrowserLanguage, BrowserCountry, SocialNetwork, SocialAction, HTTPError, SendTiming, DNSTiming, ConnectTiming, ResponseStartTiming, ResponseEndTiming, FetchTiming, SocialSourceNetworkID, SocialSourcePage, ParamPrice, ParamOrderID, ParamCurrency, ParamCurrencyID, OpenstatServiceName, OpenstatCampaignID, OpenstatAdID, OpenstatSourceID, UTMSource, UTMMedium, UTMCampaign, UTMContent, UTMTerm, ...]\n", "Index: []\n", "\n", "[0 rows x 105 columns]\n", - "Polars time: 0.004159688949584961\n", + "DuckDB time: 0.02909088134765625\n", + "DuckDB return:\n", + " Empty DataFrame\n", + "Columns: [UserID]\n", + "Index: []\n", + "chDB time: 0.023262739181518555\n", + "chDB return:\n", + " \n", + "Polars time: 0.006215810775756836\n", "Polars return:\n", " shape: (0, 105)\n", "┌─────────┬────────────┬───────┬───────────┬───┬──────────┬─────────────┬─────────┬──────┐\n", @@ -1959,22 +1976,49 @@ "╞═════════╪════════════╪═══════╪═══════════╪═══╪══════════╪═════════════╪═════════╪══════╡\n", "└─────────┴────────────┴───────┴───────────┴───┴──────────┴─────────────┴─────────┴──────┘\n", "Q20 SELECT COUNT(*) FROM hits WHERE URL LIKE '%google%';\n", - "DuckDB time: 0.1195058822631836\n", + "Pandas time: 2.1297006607055664\n", + "Pandas return:\n", + " 1687\n", + "DuckDB time: 0.12494659423828125\n", "DuckDB return:\n", " count_star()\n", "0 1687\n", - "chDB time: 0.1032094955444336\n", + "chDB time: 0.08678507804870605\n", "chDB return:\n", " 1687\n", "\n", - "Pandas time: 2.1695151329040527\n", - "Pandas return:\n", - " 1687\n", - "Polars time: 0.18016314506530762\n", + "Polars time: 0.18349432945251465\n", "Polars return:\n", " 1687\n", "Q21 SELECT SearchPhrase, MIN(URL), COUNT(*) AS c FROM hits WHERE URL LIKE '%google%' AND SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;\n", - "DuckDB time: 0.13406634330749512\n", + "Pandas time: 2.5472168922424316\n", + "Pandas return:\n", + " URL \\\n", + "SearchPhrase \n", + "римском качественны for cry http:%2F%2Fwwww.googlead&aktional \n", + "рецепты салдингал иркутске дом в при http:%2F%2Fwwww.googlead&aktional \n", + "тест драмы смотреть http:%2F%2Fwwww.googlead&aktional \n", + "испанч боб новости дейская http://smeshariki.ru/recipes/show/6840872&traf... \n", + "dynamic gigabyte-kuzbassassins 6 полос http://forum2/play.google.ru/main.aspx?brands][1] \n", + "dynamic gigabyte-kuzbassassins 6 получение сери... http://forum2/play.google.ru/main.aspx?brands][1] \n", + "dynamic gigabyte-kuzbassassins 6 получение сери... http://forum2/play.google.ru/main.aspx?brands][1] \n", + "маски в горает устантиров в работа поездки видео http://forum2/play.google.ru/main.aspx?brands][1] \n", + "обезболи все переватель 2gis.ru/ha отзывы http://sslovarenovyy-s-koroshen_apps.googleBR \n", + "оборт http://forum2/play.google/eduabroad_input_bdsm... \n", + "\n", + " SearchPhrase \n", + "SearchPhrase \n", + "римском качественны for cry 24 \n", + "рецепты салдингал иркутске дом в при 6 \n", + "тест драмы смотреть 6 \n", + "испанч боб новости дейская 5 \n", + "dynamic gigabyte-kuzbassassins 6 полос 4 \n", + "dynamic gigabyte-kuzbassassins 6 получение сери... 4 \n", + "dynamic gigabyte-kuzbassassins 6 получение сери... 3 \n", + "маски в горает устантиров в работа поездки видео 3 \n", + "обезболи все переватель 2gis.ru/ha отзывы 3 \n", + "оборт 3 \n", + "DuckDB time: 0.12578415870666504\n", "DuckDB return:\n", " SearchPhrase \\\n", "0 римском качественны for cry \n", @@ -1983,10 +2027,10 @@ "3 испанч боб новости дейская \n", "4 dynamic gigabyte-kuzbassassins 6 получение сер... \n", "5 dynamic gigabyte-kuzbassassins 6 полос \n", - "6 обезболи все переватель 2gis.ru/ha отзывы \n", - "7 dynamic gigabyte-kuzbassassins 6 получение сер... \n", - "8 рецепты и мистиков в минские \n", - "9 римского духово-зуево \n", + "6 маски в горает устантиров в работа поездки видео \n", + "7 оборт \n", + "8 римского духово-зуево \n", + "9 dynamic gigabyte-kuzbassassins 6 получение сер... \n", "\n", " min(URL) c \n", "0 http:%2F%2Fwwww.googlead&aktional 24 \n", @@ -1995,11 +2039,11 @@ "3 http://smeshariki.ru/recipes/show/6840872&traf... 5 \n", "4 http://forum2/play.google.ru/main.aspx?brands][1] 4 \n", "5 http://forum2/play.google.ru/main.aspx?brands][1] 4 \n", - "6 http://sslovarenovyy-s-koroshen_apps.googleBR 3 \n", - "7 http://forum2/play.google.ru/main.aspx?brands][1] 3 \n", + "6 http://forum2/play.google.ru/main.aspx?brands][1] 3 \n", + "7 http://forum2/play.google/eduabroad_input_bdsm... 3 \n", "8 http:%2F%2Fwwww.googlead&aktional 3 \n", - "9 http:%2F%2Fwwww.googlead&aktional 3 \n", - "chDB time: 0.11961245536804199\n", + "9 http://forum2/play.google.ru/main.aspx?brands][1] 3 \n", + "chDB time: 0.11338138580322266\n", "chDB return:\n", " \"римском качественны for cry\",\"http:%2F%2Fwwww.googlead&aktional\",24\n", "\"тест драмы смотреть\",\"http:%2F%2Fwwww.googlead&aktional\",6\n", @@ -2012,36 +2056,67 @@ "\"маски в горает устантиров в работа поездки видео\",\"http://forum2/play.google.ru/main.aspx?brands][1]\",3\n", "\"dynamic gigabyte-kuzbassassins 6 получение серия сперми\",\"http://forum2/play.google.ru/main.aspx?brands][1]\",3\n", "\n", - "Pandas time: 2.556438684463501\n", + "Polars time: 0.18537497520446777\n", + "Polars return:\n", + " shape: (10, 3)\n", + "┌─────────────────────────────────┬─────────────────────────────────┬───────┐\n", + "│ SearchPhrase ┆ URL ┆ count │\n", + "│ --- ┆ --- ┆ --- │\n", + "│ str ┆ str ┆ u32 │\n", + "╞═════════════════════════════════╪═════════════════════════════════╪═══════╡\n", + "│ римском качественны for cry ┆ http:%2F%2Fwwww.googlead&aktio… ┆ 24 │\n", + "│ тест драмы смотреть ┆ http:%2F%2Fwwww.googlead&aktio… ┆ 6 │\n", + "│ рецепты салдингал иркутске дом… ┆ http:%2F%2Fwwww.googlead&aktio… ┆ 6 │\n", + "│ испанч боб новости дейская ┆ http://smeshariki.ru/recipes/s… ┆ 5 │\n", + "│ dynamic gigabyte-kuzbassassins… ┆ http://forum2/play.google.ru/m… ┆ 4 │\n", + "│ dynamic gigabyte-kuzbassassins… ┆ http://forum2/play.google.ru/m… ┆ 4 │\n", + "│ маски в горает устантиров в ра… ┆ http://forum2/play.google.ru/m… ┆ 3 │\n", + "│ римского духово-зуево ┆ http:%2F%2Fwwww.googlead&aktio… ┆ 3 │\n", + "│ обезболи все переватель 2gis.r… ┆ http://sslovarenovyy-s-koroshe… ┆ 3 │\n", + "│ оборт ┆ http://forum2/play.google/edua… ┆ 3 │\n", + "└─────────────────────────────────┴─────────────────────────────────┴───────┘\n", + "Q22 SELECT SearchPhrase, MIN(URL), MIN(Title), COUNT(*) AS c, COUNT(DISTINCT UserID) FROM hits WHERE Title LIKE '%Google%' AND URL NOT LIKE '%.google.%' AND SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;\n", + "Pandas time: 8.950557470321655\n", "Pandas return:\n", " URL \\\n", "SearchPhrase \n", - "римском качественны for cry http:%2F%2Fwwww.googlead&aktional \n", - "рецепты салдингал иркутске дом в при http:%2F%2Fwwww.googlead&aktional \n", - "тест драмы смотреть http:%2F%2Fwwww.googlead&aktional \n", - "испанч боб новости дейская http://smeshariki.ru/recipes/show/6840872&traf... \n", - "dynamic gigabyte-kuzbassassins 6 полос http://forum2/play.google.ru/main.aspx?brands][1] \n", - "dynamic gigabyte-kuzbassassins 6 получение сери... http://forum2/play.google.ru/main.aspx?brands][1] \n", - "dynamic gigabyte-kuzbassassins 6 получение сери... http://forum2/play.google.ru/main.aspx?brands][1] \n", - "маски в горает устантиров в работа поездки видео http://forum2/play.google.ru/main.aspx?brands][1] \n", - "обезболи все переватель 2gis.ru/ha отзывы http://sslovarenovyy-s-koroshen_apps.googleBR \n", - "оборт http://forum2/play.google/eduabroad_input_bdsm... \n", + "винки медведь смотреть фильмы 2013 смотреть http://smeshariki.ru/a-folder-4/#page-3.2.1; W... \n", + "винки медведь смотреть фильмы чеческия http://smeshariki.ru/a-folder-4/#page-3.2.1; W... \n", + "винки медведь смотреть объятный ветерин http://smeshariki.ru/index.ua/newsru.com/ifram... \n", + "кино 2009) смотреть онлайн бессмерти мк в россипед http://domchelove.ru/#!/search/page \n", + "коптимиквиды юриста с роуз рая https://produkty%2Fpulove.ru/booklyattion-war-... \n", + "коптимиквиды юрий жд ворожные моем https://produkty%2Fpulove.ru/booklyattion-war-... \n", + "самаре на мира матки видео 21.03.2013 смотреть http://smeshariki.ru/GameMain.aspx#location.ru... \n", + "ведомосквиталия страции https://produkty%2Fpulove.ru/booklyattion-war-... \n", + "винки медведь смотреть http://smeshariki.ru/index.ua/newsru.com/ifram... \n", + "тайны избавитель в владимира для университет ма... http://smeshariki.ru/index.ua/baby=1&with_exch... \n", "\n", - " SearchPhrase \n", - "SearchPhrase \n", - "римском качественны for cry 24 \n", - "рецепты салдингал иркутске дом в при 6 \n", - "тест драмы смотреть 6 \n", - "испанч боб новости дейская 5 \n", - "dynamic gigabyte-kuzbassassins 6 полос 4 \n", - "dynamic gigabyte-kuzbassassins 6 получение сери... 4 \n", - "dynamic gigabyte-kuzbassassins 6 получение сери... 3 \n", - "маски в горает устантиров в работа поездки видео 3 \n", - "обезболи все переватель 2gis.ru/ha отзывы 3 \n", - "оборт 3 \n", - "Polars error: \"count\" not found\n", - "Q22 SELECT SearchPhrase, MIN(URL), MIN(Title), COUNT(*) AS c, COUNT(DISTINCT UserID) FROM hits WHERE Title LIKE '%Google%' AND URL NOT LIKE '%.google.%' AND SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;\n", - "DuckDB time: 0.2151491641998291\n", + " Title \\\n", + "SearchPhrase \n", + "винки медведь смотреть фильмы 2013 смотреть видеорегионалу Google \n", + "винки медведь смотреть фильмы чеческия видеорегионалу Google - Досториа Базар автомоб... \n", + "винки медведь смотреть объятный ветерин видеорегионалу Google Gel - Курганизмом, дачи - \n", + "кино 2009) смотреть онлайн бессмерти мк в россипед Далее о коллекции в GIMI LANCIA 0K3Y318104 про... \n", + "коптимиквиды юриста с роуз рая Легко на участные участников., Цены - Стильная... \n", + "коптимиквиды юрий жд ворожные моем Легко на участные участников., Цены - Стильная... \n", + "самаре на мира матки видео 21.03.2013 смотреть Квартиры в проекты - Google rientalie Goal!, 2... \n", + "ведомосквиталия страции Легко на участные участников., Цены - Стильная... \n", + "винки медведь смотреть видеорегионалу Google - модного языке - Пульс \n", + "тайны избавитель в владимира для университет ма... Амитин обувь - Яндекс.Видео+текст песен Google... \n", + "\n", + " SearchPhrase UserID \n", + "SearchPhrase \n", + "винки медведь смотреть фильмы 2013 смотреть 112 81 \n", + "винки медведь смотреть фильмы чеческия 21 18 \n", + "винки медведь смотреть объятный ветерин 14 10 \n", + "кино 2009) смотреть онлайн бессмерти мк в россипед 13 9 \n", + "коптимиквиды юриста с роуз рая 12 3 \n", + "коптимиквиды юрий жд ворожные моем 8 2 \n", + "самаре на мира матки видео 21.03.2013 смотреть 7 1 \n", + "ведомосквиталия страции 6 2 \n", + "винки медведь смотреть 6 4 \n", + "тайны избавитель в владимира для университет ма... 6 4 \n", + "DuckDB time: 0.23342061042785645\n", "DuckDB return:\n", " SearchPhrase \\\n", "0 винки медведь смотреть фильмы 2013 смотреть \n", @@ -2090,7 +2165,7 @@ "7 4 \n", "8 2 \n", "9 4 \n", - "chDB time: 0.18262386322021484\n", + "chDB time: 0.18370819091796875\n", "chDB return:\n", " \"винки медведь смотреть фильмы 2013 смотреть\",\"http://smeshariki.ru/a-folder-4/#page-3.2.1; WOW64; Edition=1&input_age2/#over-1.3.adfox.ru/image=0&engineVolumeFrom\",\"видеорегионалу Google\",112,81\n", "\"винки медведь смотреть фильмы чеческия\",\"http://smeshariki.ru/a-folder-4/#page-3.2.1; WOW64; Edition=1&input_age2/?page_type=cated_card_330709_1_116105812\",\"видеорегионалу Google - Досториа Базар автомобили купить манские характеринбу\",21,18\n", @@ -2103,49 +2178,112 @@ "\"винки медведь смотреть\",\"http://smeshariki.ru/index.ua/newsru.com/iframe_right%3D43%26bt%3D90%26nid%3D8235.html?1=1&cid=147960&wi=1280&lo=http://video.yandex\",\"видеорегионалу Google - модного языке - Пульс\",6,4\n", "\"юрий духовиковый тумбой магазин\",\"http://video.yandex.ru/ch/meters=0&price_do=¤cy\",\"Ежедневное - Пульс цены | купить ул., доступные Челябинский рифленогопользовать Audio - Компании Google Agila дорабль в\",6,6\n", "\n", - "Pandas time: 8.927100419998169\n", + "Polars time: 0.36249494552612305\n", + "Polars return:\n", + " shape: (10, 5)\n", + "┌───────────────────────────┬──────────────────────────┬──────────────────────────┬───────┬────────┐\n", + "│ SearchPhrase ┆ URL ┆ Title ┆ count ┆ UserID │\n", + "│ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n", + "│ str ┆ str ┆ str ┆ u32 ┆ u32 │\n", + "╞═══════════════════════════╪══════════════════════════╪══════════════════════════╪═══════╪════════╡\n", + "│ винки медведь смотреть ┆ http://smeshariki.ru/a-f ┆ видеорегионалу Google ┆ 112 ┆ 81 │\n", + "│ фильмы … ┆ older-… ┆ ┆ ┆ │\n", + "│ винки медведь смотреть ┆ http://smeshariki.ru/a-f ┆ видеорегионалу Google - ┆ 21 ┆ 18 │\n", + "│ фильмы … ┆ older-… ┆ Достор… ┆ ┆ │\n", + "│ винки медведь смотреть ┆ http://smeshariki.ru/ind ┆ видеорегионалу Google ┆ 14 ┆ 10 │\n", + "│ объятны… ┆ ex.ua/… ┆ Gel - Ку… ┆ ┆ │\n", + "│ кино 2009) смотреть ┆ http://domchelove.ru/#!/ ┆ Далее о коллекции в GIMI ┆ 13 ┆ 9 │\n", + "│ онлайн бес… ┆ search… ┆ LANCI… ┆ ┆ │\n", + "│ коптимиквиды юриста с ┆ https://produkty%2Fpulov ┆ Легко на участные ┆ 12 ┆ 3 │\n", + "│ роуз рая ┆ e.ru/b… ┆ участников.,… ┆ ┆ │\n", + "│ коптимиквиды юрий жд ┆ https://produkty%2Fpulov ┆ Легко на участные ┆ 8 ┆ 2 │\n", + "│ ворожные … ┆ e.ru/b… ┆ участников.,… ┆ ┆ │\n", + "│ самаре на мира матки ┆ http://smeshariki.ru/Gam ┆ Квартиры в проекты - ┆ 7 ┆ 1 │\n", + "│ видео 21.… ┆ eMain.… ┆ Google ri… ┆ ┆ │\n", + "│ юрий духовиковый тумбой ┆ http://video.yandex.ru/c ┆ Ежедневное - Пульс цены ┆ 6 ┆ 6 │\n", + "│ магази… ┆ h/mete… ┆ | купи… ┆ ┆ │\n", + "│ тайны избавитель в ┆ http://smeshariki.ru/ind ┆ Амитин обувь - ┆ 6 ┆ 4 │\n", + "│ владимира д… ┆ ex.ua/… ┆ Яндекс.Видео+те… ┆ ┆ │\n", + "│ винки медведь смотреть ┆ http://smeshariki.ru/ind ┆ видеорегионалу Google - ┆ 6 ┆ 4 │\n", + "│ ┆ ex.ua/… ┆ модног… ┆ ┆ │\n", + "└───────────────────────────┴──────────────────────────┴──────────────────────────┴───────┴────────┘\n", + "Q23 SELECT * FROM hits WHERE URL LIKE '%google%' ORDER BY EventTime LIMIT 10;\n", + "Pandas time: 2.123731851577759\n", "Pandas return:\n", - " URL \\\n", - "SearchPhrase \n", - "винки медведь смотреть фильмы 2013 смотреть http://smeshariki.ru/a-folder-4/#page-3.2.1; W... \n", - "винки медведь смотреть фильмы чеческия http://smeshariki.ru/a-folder-4/#page-3.2.1; W... \n", - "винки медведь смотреть объятный ветерин http://smeshariki.ru/index.ua/newsru.com/ifram... \n", - "кино 2009) смотреть онлайн бессмерти мк в россипед http://domchelove.ru/#!/search/page \n", - "коптимиквиды юриста с роуз рая https://produkty%2Fpulove.ru/booklyattion-war-... \n", - "коптимиквиды юрий жд ворожные моем https://produkty%2Fpulove.ru/booklyattion-war-... \n", - "самаре на мира матки видео 21.03.2013 смотреть http://smeshariki.ru/GameMain.aspx#location.ru... \n", - "ведомосквиталия страции https://produkty%2Fpulove.ru/booklyattion-war-... \n", - "винки медведь смотреть http://smeshariki.ru/index.ua/newsru.com/ifram... \n", - "тайны избавитель в владимира для университет ма... http://smeshariki.ru/index.ua/baby=1&with_exch... \n", + " WatchID JavaEnable \\\n", + "8858875 7106264041910208868 1 \n", + "8896307 6801361853621701142 1 \n", + "8896308 7370235307579469118 1 \n", + "9646993 7299686183082339643 1 \n", + "9646995 5241207090454501610 1 \n", + "9646996 8762858360217969903 1 \n", + "8937843 5937582489445775385 1 \n", + "9656506 5585474130921985177 1 \n", + "9656507 8119609642256502216 1 \n", + "9619305 8851521334882706019 0 \n", "\n", - " Title \\\n", - "SearchPhrase \n", - "винки медведь смотреть фильмы 2013 смотреть видеорегионалу Google \n", - "винки медведь смотреть фильмы чеческия видеорегионалу Google - Досториа Базар автомоб... \n", - "винки медведь смотреть объятный ветерин видеорегионалу Google Gel - Курганизмом, дачи - \n", - "кино 2009) смотреть онлайн бессмерти мк в россипед Далее о коллекции в GIMI LANCIA 0K3Y318104 про... \n", - "коптимиквиды юриста с роуз рая Легко на участные участников., Цены - Стильная... \n", - "коптимиквиды юрий жд ворожные моем Легко на участные участников., Цены - Стильная... \n", - "самаре на мира матки видео 21.03.2013 смотреть Квартиры в проекты - Google rientalie Goal!, 2... \n", - "ведомосквиталия страции Легко на участные участников., Цены - Стильная... \n", - "винки медведь смотреть видеорегионалу Google - модного языке - Пульс \n", - "тайны избавитель в владимира для университет ма... Амитин обувь - Яндекс.Видео+текст песен Google... \n", + " Title GoodEvent \\\n", + "8858875 ГОСТЕЛЬНОЗЕРОГ ГОРНЫЙ ДОЖДЬ! - Спорт, алюминис... 1 \n", + "8896307 Смешарики SW | SexWife: Женщин - Яндекс.Афиша@... 1 \n", + "8896308 1 \n", + "9646993 Торт и продам Ford (Форд - IRR.ru (Работа и ро... 1 \n", + "9646995 Торт и продам Ford (Форд - IRR.ru (Работа и ро... 1 \n", + "9646996 1 \n", + "8937843 прода. Поиск повый бизнес 1 \n", + "9656506 Торт и продам Ford (Форд - IRR.ru (Работа и ро... 1 \n", + "9656507 1 \n", + "9619305 Вопростовый стал Петербурге. Последников в про... 1 \n", "\n", - " SearchPhrase UserID \n", - "SearchPhrase \n", - "винки медведь смотреть фильмы 2013 смотреть 112 81 \n", - "винки медведь смотреть фильмы чеческия 21 18 \n", - "винки медведь смотреть объятный ветерин 14 10 \n", - "кино 2009) смотреть онлайн бессмерти мк в россипед 13 9 \n", - "коптимиквиды юриста с роуз рая 12 3 \n", - "коптимиквиды юрий жд ворожные моем 8 2 \n", - "самаре на мира матки видео 21.03.2013 смотреть 7 1 \n", - "ведомосквиталия страции 6 2 \n", - "винки медведь смотреть 6 4 \n", - "тайны избавитель в владимира для университет ма... 6 4 \n", - "Polars error: \"count\" not found\n", - "Q23 SELECT * FROM hits WHERE URL LIKE '%google%' ORDER BY EventTime LIMIT 10;\n", - "DuckDB time: 0.46820592880249023\n", + " EventTime EventDate CounterID ClientIP RegionID \\\n", + "8858875 2013-07-01 23:31:03 2013-07-02 46429 1249584689 229 \n", + "8896307 2013-07-01 23:44:01 2013-07-02 40367 -1231921306 2 \n", + "8896308 2013-07-01 23:44:14 2013-07-02 40367 -1231921306 2 \n", + "9646993 2013-07-01 23:59:17 2013-07-02 46429 1553640326 115 \n", + "9646995 2013-07-02 01:59:29 2013-07-02 46429 1553640326 115 \n", + "9646996 2013-07-02 01:59:42 2013-07-02 46429 1553640326 115 \n", + "8937843 2013-07-02 02:46:42 2013-07-02 63621 -1801466482 229 \n", + "9656506 2013-07-02 02:50:56 2013-07-02 46429 -1366734181 44 \n", + "9656507 2013-07-02 02:51:09 2013-07-02 46429 -1366734181 44 \n", + "9619305 2013-07-02 05:18:07 2013-07-02 39641 1897404057 12 \n", + "\n", + " UserID ... UTMSource UTMMedium UTMCampaign \\\n", + "8858875 72720560134547761 ... \n", + "8896307 434272054218180613 ... \n", + "8896308 434272054218180613 ... \n", + "9646993 168449836300271247 ... \n", + "9646995 168449836300271247 ... feedburner banner ad_cpamarketing \n", + "9646996 168449836300271247 ... feedburner banner ad_cpamarketing \n", + "8937843 5639771411007874048 ... \n", + "9656506 6484173929977037196 ... \n", + "9656507 6484173929977037196 ... \n", + "9619305 2147819122923023112 ... \n", + "\n", + " UTMContent UTMTerm FromTag HasGCLID RefererHash \\\n", + "8858875 0 -3651842497912472547 \n", + "8896307 0 5673263859390493714 \n", + "8896308 0 -296158784638538920 \n", + "9646993 0 -2923571516118524499 \n", + "9646995 0 4719160989640449379 \n", + "9646996 0 -296158784638538920 \n", + "8937843 0 532293348752290058 \n", + "9656506 0 -43688538285913943 \n", + "9656507 0 -296158784638538920 \n", + "9619305 0 6285928018624721980 \n", + "\n", + " URLHash CLID \n", + "8858875 5528743655405710480 0 \n", + "8896307 -6433683654023857482 0 \n", + "8896308 -6433683654023857482 0 \n", + "9646993 1337795999976243980 0 \n", + "9646995 2196566102793075843 0 \n", + "9646996 2196566102793075843 0 \n", + "8937843 -7069763488219331997 0 \n", + "9656506 1337795999976243980 0 \n", + "9656507 1337795999976243980 0 \n", + "9619305 -6462309590271025210 0 \n", + "\n", + "[10 rows x 105 columns]\n", + "DuckDB time: 0.47556400299072266\n", "DuckDB return:\n", " WatchID JavaEnable \\\n", "0 7106264041910208868 1 \n", @@ -2220,7 +2358,7 @@ "9 -6462309590271025210 0 \n", "\n", "[10 rows x 105 columns]\n", - "chDB time: 0.45491504669189453\n", + "chDB time: 0.4304678440093994\n", "chDB return:\n", " 7106264041910208868,1,\"ГОСТЕЛЬНОЗЕРОГ ГОРНЫЙ ДОЖДЬ! - Спорт, алюминистик : играй!!!! ЦЕНЫ!! фотоальбомы и океансов в продать-взять-о и видео#!/search?film.TV) — растер - : купить\",1,\"2013-07-02 07:31:03.000000000\",\"2013-07-02 08:00:00.000000000\",46429,1249584689,229,72720560134547761,0,44,46,\"http://smeshariki.ru/users/2013-07-15,2013&To=03.07.2013-07-01:2013-07-17545/content/searchivemix).mp3ex.net/page.google-plata.ru\",\"http://smeshariki.ru/page.aspx?Countforpartments/7416543000¤cy=RUR/carpartner-peskie_kollen&item-1/nf-6\",0,16000,158,9911,216,1996,1781,37,15,7,\"700\",0,0,22,\"D�\",1,1,0,0,\"\",\"\",2221747,-1,0,\"\",0,0,1485,688,135,1372775257,4,0,46077,0,\"windows-1251;charset\",1601,0,0,0,6266009505159221854,\"\",1038228209,0,0,0,0,0,\"g\",1372737370,0,2,0,0,0,1184697127,36437,-1,2,\"S0\",\"�\f\",\"\",\"\",0,0,0,3,83,26,0,0,\"\",0,\"\",\"NH\u001c\",0,\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",0,-3651842497912472547,5528743655405710480,0\n", "6801361853621701142,1,\"Смешарики SW | SexWife: Женщин - Яндекс.Афиша@Mail.Ru - магазин модный Журнал: Абдельцев Honda с производств\",1,\"2013-07-02 07:44:01.000000000\",\"2013-07-02 08:00:00.000000000\",40367,-1231921306,2,434272054218180613,0,126,5,\"http://interinburg/detail.google,yandex.aspx#location=products\",\"http://yandex.ru/domkadrov.irr.ru/yandsearch&caU82MlBVHpMbWgwYld3JTNEZnRTYUh$MGNEb3ZMMmh2Ykc5YWf6VzcO3ZqI91PIqcL84YZg&bvm=bv.48705608,d.bGE&cad=rja&ved=0CEYQFjAD&url=http://rsdn.ru%2F~книги%2FКомпот и болгари\",0,14550,952,13164,16,1996,1781,37,15,7,\"700\",0,0,22,\"D�\",1,1,0,0,\"\",\"\",1999580,3,1,\"ани пух ходу\",0,0,567,577,135,1372784689,4,1,15738,0,\"windows\",1601,0,0,0,8352815799795997820,\"\",376469337,0,0,0,0,0,\"5\",1372759377,31,1,2,6,43,-815706743,-1,-1,-1,\"S0\",\"�\f\",\"\",\"\",0,0,0,0,453,45,0,0,\"\",0,\"\",\"NH\u001c\",0,\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",0,5673263859390493714,-6433683654023857482,0\n", @@ -2233,82 +2371,7 @@ "8119609642256502216,1,\"\",1,\"2013-07-02 10:51:09.000000000\",\"2013-07-02 08:00:00.000000000\",46429,-1366734181,44,6484173929977037196,0,74,5,\"http://smeshariki.ru/user=googleb18f7700.6384695,926425668_hornolyanovosibirsk.irr.ru/yekategory_id\",\"\",0,0,0,9911,216,339,777,23,0,0,\"\",0,0,18,\"D�\",1,1,1,0,\"\",\"\",1203796,0,0,\"\",0,1,724,2027,322,1372777497,0,0,0,0,\"windows-1251;charset\",1601,0,0,1,5395316558279634204,\"\",738865320,0,0,0,1,0,\"5\",1372783413,22,2,2,14652,92,-189312298,9866,-1,1,\"S0\",\"h1\",\"\",\"\",0,2215,0,0,0,0,0,0,\"\",0,\"\",\"NH\u001c\",0,\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",0,-296158784638538920,1337795999976243980,0\n", "8851521334882706019,0,\"Вопростовый стал Петербурге. Последников в продажа, центре парфюм\",1,\"2013-07-02 13:18:07.000000000\",\"2013-07-02 08:00:00.000000000\",39641,1897404057,12,2147819122923023112,1,44,3,\"http://domchel.ru/board.php?id=767128787753779.eccord.ru/?trafkey=4300&brand=RAINBOW - bonprix.ru/googleuserId=4&ord=крючком\",\"http://wildberries.ru/invid=19753.html?sort=rating\",0,256,20,426,22,1368,554,23,15,7,\"700\",0,0,17,\"D�\",1,1,0,0,\"\",\"\",3665494,-1,0,\"\",0,0,1863,726,135,1372753287,4,1,16561,0,\"windows-1251;charset\",1,0,0,0,7356234246907529433,\"\",1031476090,0,0,0,0,0,\"5\",1372772961,0,1,0,0,0,1451194443,-1,-1,-1,\"S0\",\"�\f\",\"\",\"\",0,0,0,0,0,0,0,0,\"\",0,\"\",\"NH\u001c\",0,\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",0,6285928018624721980,-6462309590271025210,0\n", "\n", - "Pandas time: 2.1939539909362793\n", - "Pandas return:\n", - " WatchID JavaEnable \\\n", - "8858875 7106264041910208868 1 \n", - "8896307 6801361853621701142 1 \n", - "8896308 7370235307579469118 1 \n", - "9646993 7299686183082339643 1 \n", - "9646995 5241207090454501610 1 \n", - "9646996 8762858360217969903 1 \n", - "8937843 5937582489445775385 1 \n", - "9656506 5585474130921985177 1 \n", - "9656507 8119609642256502216 1 \n", - "9619305 8851521334882706019 0 \n", - "\n", - " Title GoodEvent \\\n", - "8858875 ГОСТЕЛЬНОЗЕРОГ ГОРНЫЙ ДОЖДЬ! - Спорт, алюминис... 1 \n", - "8896307 Смешарики SW | SexWife: Женщин - Яндекс.Афиша@... 1 \n", - "8896308 1 \n", - "9646993 Торт и продам Ford (Форд - IRR.ru (Работа и ро... 1 \n", - "9646995 Торт и продам Ford (Форд - IRR.ru (Работа и ро... 1 \n", - "9646996 1 \n", - "8937843 прода. Поиск повый бизнес 1 \n", - "9656506 Торт и продам Ford (Форд - IRR.ru (Работа и ро... 1 \n", - "9656507 1 \n", - "9619305 Вопростовый стал Петербурге. Последников в про... 1 \n", - "\n", - " EventTime EventDate CounterID ClientIP RegionID \\\n", - "8858875 2013-07-01 23:31:03 2013-07-02 46429 1249584689 229 \n", - "8896307 2013-07-01 23:44:01 2013-07-02 40367 -1231921306 2 \n", - "8896308 2013-07-01 23:44:14 2013-07-02 40367 -1231921306 2 \n", - "9646993 2013-07-01 23:59:17 2013-07-02 46429 1553640326 115 \n", - "9646995 2013-07-02 01:59:29 2013-07-02 46429 1553640326 115 \n", - "9646996 2013-07-02 01:59:42 2013-07-02 46429 1553640326 115 \n", - "8937843 2013-07-02 02:46:42 2013-07-02 63621 -1801466482 229 \n", - "9656506 2013-07-02 02:50:56 2013-07-02 46429 -1366734181 44 \n", - "9656507 2013-07-02 02:51:09 2013-07-02 46429 -1366734181 44 \n", - "9619305 2013-07-02 05:18:07 2013-07-02 39641 1897404057 12 \n", - "\n", - " UserID ... UTMSource UTMMedium UTMCampaign \\\n", - "8858875 72720560134547761 ... \n", - "8896307 434272054218180613 ... \n", - "8896308 434272054218180613 ... \n", - "9646993 168449836300271247 ... \n", - "9646995 168449836300271247 ... feedburner banner ad_cpamarketing \n", - "9646996 168449836300271247 ... feedburner banner ad_cpamarketing \n", - "8937843 5639771411007874048 ... \n", - "9656506 6484173929977037196 ... \n", - "9656507 6484173929977037196 ... \n", - "9619305 2147819122923023112 ... \n", - "\n", - " UTMContent UTMTerm FromTag HasGCLID RefererHash \\\n", - "8858875 0 -3651842497912472547 \n", - "8896307 0 5673263859390493714 \n", - "8896308 0 -296158784638538920 \n", - "9646993 0 -2923571516118524499 \n", - "9646995 0 4719160989640449379 \n", - "9646996 0 -296158784638538920 \n", - "8937843 0 532293348752290058 \n", - "9656506 0 -43688538285913943 \n", - "9656507 0 -296158784638538920 \n", - "9619305 0 6285928018624721980 \n", - "\n", - " URLHash CLID \n", - "8858875 5528743655405710480 0 \n", - "8896307 -6433683654023857482 0 \n", - "8896308 -6433683654023857482 0 \n", - "9646993 1337795999976243980 0 \n", - "9646995 2196566102793075843 0 \n", - "9646996 2196566102793075843 0 \n", - "8937843 -7069763488219331997 0 \n", - "9656506 1337795999976243980 0 \n", - "9656507 1337795999976243980 0 \n", - "9619305 -6462309590271025210 0 \n", - "\n", - "[10 rows x 105 columns]\n", - "Polars time: 0.1826305389404297\n", + "Polars time: 0.18419170379638672\n", "Polars return:\n", " shape: (10, 105)\n", "┌────────────┬────────────┬────────────┬───────────┬───┬──────────┬────────────┬────────────┬──────┐\n", @@ -2353,7 +2416,20 @@ "│ ┆ ┆ П… ┆ ┆ ┆ ┆ ┆ ┆ │\n", "└────────────┴────────────┴────────────┴───────────┴───┴──────────┴────────────┴────────────┴──────┘\n", "Q24 SELECT SearchPhrase FROM hits WHERE SearchPhrase <> '' ORDER BY EventTime LIMIT 10;\n", - "DuckDB time: 0.12598967552185059\n", + "Pandas time: 2.3252789974212646\n", + "Pandas return:\n", + " SearchPhrase\n", + "5936205 ночно китая женщины\n", + "8064786 маршава нибудь в омске главнованные автобаза ф...\n", + "8851501 20 робигудинг для маске\n", + "8853400 выкупонорманский рублендодат\n", + "8828551 комнаталогическая область дней партная вечер э...\n", + "5290447 кифосов calib.ru/show отзывы июнь 2013 смотрет...\n", + "222072 безруководительное пирование групп иридиана фл...\n", + "6023605 орфограмма дачи 1 части заработа в казар кобак...\n", + "3608548 доктор крем качественна каленко 1 литель заезды\n", + "8916195 киа x2-02 mhz/17.3 казань\n", + "DuckDB time: 0.1318378448486328\n", "DuckDB return:\n", " SearchPhrase\n", "0 ночно китая женщины\n", @@ -2366,7 +2442,7 @@ "7 орфограмма дачи 1 части заработа в казар кобак...\n", "8 доктор крем качественна каленко 1 литель заезды\n", "9 киа x2-02 mhz/17.3 казань\n", - "chDB time: 0.04124927520751953\n", + "chDB time: 0.0423429012298584\n", "chDB return:\n", " \"ночно китая женщины\"\n", "\"маршава нибудь в омске главнованные автобаза физовать\"\n", @@ -2379,20 +2455,7 @@ "\"орфограмма дачи 1 части заработа в казар кобакал по гал поль+стели пожар\"\n", "\"киа x2-02 mhz/17.3 казань\"\n", "\n", - "Pandas time: 2.326787233352661\n", - "Pandas return:\n", - " SearchPhrase\n", - "5936205 ночно китая женщины\n", - "8064786 маршава нибудь в омске главнованные автобаза ф...\n", - "8851501 20 робигудинг для маске\n", - "8853400 выкупонорманский рублендодат\n", - "8828551 комнаталогическая область дней партная вечер э...\n", - "5290447 кифосов calib.ru/show отзывы июнь 2013 смотрет...\n", - "222072 безруководительное пирование групп иридиана фл...\n", - "6023605 орфограмма дачи 1 части заработа в казар кобак...\n", - "3608548 доктор крем качественна каленко 1 литель заезды\n", - "8916195 киа x2-02 mhz/17.3 казань\n", - "Polars time: 0.26840853691101074\n", + "Polars time: 0.27924275398254395\n", "Polars return:\n", " shape: (10, 1)\n", "┌─────────────────────────────────┐\n", @@ -2412,7 +2475,20 @@ "│ киа x2-02 mhz/17.3 казань │\n", "└─────────────────────────────────┘\n", "Q25 SELECT SearchPhrase FROM hits WHERE SearchPhrase <> '' ORDER BY SearchPhrase LIMIT 10;\n", - "DuckDB time: 0.22957587242126465\n", + "Pandas time: 3.9367663860321045\n", + "Pandas return:\n", + " SearchPhrase\n", + "8581793 прав\n", + "3506663 светы женске 2 сезон\n", + "3400727 !куги для мясорубкина зимняя из виолет\n", + "9472812 $_get am2 купейн в хорошем\n", + "7982167 $_get it of goodbye minecraft\n", + "3842151 $_get_series v stell \n", + "1859999 $_poslandon.ru/moscow 2 торговлю\n", + "7981418 $d причина\n", + "1467180 % стасия\n", + "5058192 ф купить шарарасота в турбации\n", + "DuckDB time: 0.2535984516143799\n", "DuckDB return:\n", " SearchPhrase\n", "0 прав\n", @@ -2425,7 +2501,7 @@ "7 $d причина\n", "8 % стасия\n", "9 ф купить шарарасота в турбации\n", - "chDB time: 0.03507590293884277\n", + "chDB time: 0.03441929817199707\n", "chDB return:\n", " \" прав\"\n", "\" светы женске 2 сезон\"\n", @@ -2434,24 +2510,11 @@ "\"$_get it of goodbye minecraft\"\n", "\"$_get_series v stell \"\n", "\"$_poslandon.ru/moscow 2 торговлю\"\n", - "\"$d причина\"\n", - "\"% стасия\"\n", - "\"ф купить шарарасота в турбации\"\n", - "\n", - "Pandas time: 3.904980421066284\n", - "Pandas return:\n", - " SearchPhrase\n", - "8581793 прав\n", - "3506663 светы женске 2 сезон\n", - "3400727 !куги для мясорубкина зимняя из виолет\n", - "9472812 $_get am2 купейн в хорошем\n", - "7982167 $_get it of goodbye minecraft\n", - "3842151 $_get_series v stell \n", - "1859999 $_poslandon.ru/moscow 2 торговлю\n", - "7981418 $d причина\n", - "1467180 % стасия\n", - "5058192 ф купить шарарасота в турбации\n", - "Polars time: 0.29048991203308105\n", + "\"$d причина\"\n", + "\"% стасия\"\n", + "\"ф купить шарарасота в турбации\"\n", + "\n", + "Polars time: 0.2817411422729492\n", "Polars return:\n", " shape: (10, 1)\n", "┌─────────────────────────────────┐\n", @@ -2471,7 +2534,20 @@ "│ ф купить шарарасота в тур… │\n", "└─────────────────────────────────┘\n", "Q26 SELECT SearchPhrase FROM hits WHERE SearchPhrase <> '' ORDER BY EventTime, SearchPhrase LIMIT 10;\n", - "DuckDB time: 0.17848896980285645\n", + "Pandas time: 4.12407112121582\n", + "Pandas return:\n", + " SearchPhrase\n", + "5936205 ночно китая женщины\n", + "8851501 20 робигудинг для маске\n", + "8064786 маршава нибудь в омске главнованные автобаза ф...\n", + "8853400 выкупонорманский рублендодат\n", + "8828551 комнаталогическая область дней партная вечер э...\n", + "5290447 кифосов calib.ru/show отзывы июнь 2013 смотрет...\n", + "222072 безруководительное пирование групп иридиана фл...\n", + "3608548 доктор крем качественна каленко 1 литель заезды\n", + "6023605 орфограмма дачи 1 части заработа в казар кобак...\n", + "8916195 киа x2-02 mhz/17.3 казань\n", + "DuckDB time: 0.18941974639892578\n", "DuckDB return:\n", " SearchPhrase\n", "0 ночно китая женщины\n", @@ -2484,7 +2560,7 @@ "7 доктор крем качественна каленко 1 литель заезды\n", "8 орфограмма дачи 1 части заработа в казар кобак...\n", "9 киа x2-02 mhz/17.3 казань\n", - "chDB time: 0.04461336135864258\n", + "chDB time: 0.046121835708618164\n", "chDB return:\n", " \"ночно китая женщины\"\n", "\"20 робигудинг для маске\"\n", @@ -2497,20 +2573,7 @@ "\"орфограмма дачи 1 части заработа в казар кобакал по гал поль+стели пожар\"\n", "\"киа x2-02 mhz/17.3 казань\"\n", "\n", - "Pandas time: 4.101372003555298\n", - "Pandas return:\n", - " SearchPhrase\n", - "5936205 ночно китая женщины\n", - "8851501 20 робигудинг для маске\n", - "8064786 маршава нибудь в омске главнованные автобаза ф...\n", - "8853400 выкупонорманский рублендодат\n", - "8828551 комнаталогическая область дней партная вечер э...\n", - "5290447 кифосов calib.ru/show отзывы июнь 2013 смотрет...\n", - "222072 безруководительное пирование групп иридиана фл...\n", - "3608548 доктор крем качественна каленко 1 литель заезды\n", - "6023605 орфограмма дачи 1 части заработа в казар кобак...\n", - "8916195 киа x2-02 mhz/17.3 казань\n", - "Polars time: 0.2666144371032715\n", + "Polars time: 0.2635948657989502\n", "Polars return:\n", " shape: (10, 1)\n", "┌─────────────────────────────────┐\n", @@ -2530,7 +2593,12 @@ "│ киа x2-02 mhz/17.3 казань │\n", "└─────────────────────────────────┘\n", "Q27 SELECT CounterID, AVG(STRLEN(URL)) AS l, COUNT(*) AS c FROM hits WHERE URL <> '' GROUP BY CounterID HAVING COUNT(*) > 100000 ORDER BY l DESC LIMIT 25;\n", - "DuckDB time: 0.11969971656799316\n", + "Pandas time: 11.973230361938477\n", + "Pandas return:\n", + " URL 8.830068e+01\n", + "CounterID 6.427221e+06\n", + "dtype: float64\n", + "DuckDB time: 0.1553800106048584\n", "DuckDB return:\n", " CounterID l c\n", "0 122612 240.497421 638968\n", @@ -2558,7 +2626,7 @@ "22 105857 40.067755 501707\n", "23 69154 37.375145 112655\n", "24 63217 34.884080 106496\n", - "chDB time: 0.13816475868225098\n", + "chDB time: 0.14062786102294922\n", "chDB return:\n", " 122612,240.49742084110628,638968\n", "1634,194.21410797451117,118954\n", @@ -2586,12 +2654,7 @@ "69154,37.37514535528827,112655\n", "63217,34.88408015324519,106496\n", "\n", - "Pandas time: 12.009446859359741\n", - "Pandas return:\n", - " URL 8.830068e+01\n", - "CounterID 6.427221e+06\n", - "dtype: float64\n", - "Polars time: 0.8645925521850586\n", + "Polars time: 0.8907685279846191\n", "Polars return:\n", " shape: (25, 3)\n", "┌───────────┬────────┬────────┐\n", @@ -2612,7 +2675,12 @@ "│ 146891 ┆ 103873 ┆ 103873 │\n", "└───────────┴────────┴────────┘\n", "Q28 SELECT REGEXP_REPLACE(Referer, '^https?://(?:www\\.)?([^/]+)/.*$', '\\1') AS k, AVG(STRLEN(Referer)) AS l, COUNT(*) AS c, MIN(Referer) FROM hits WHERE Referer <> '' GROUP BY k HAVING COUNT(*) > 100000 ORDER BY l DESC LIMIT 25;\n", - "DuckDB time: 0.3662426471710205\n", + "Pandas time: 30.965622425079346\n", + "Pandas return:\n", + " Referer\n", + "min_referer http://auto.ria.ua/\n", + "average_length 74.443681\n", + "DuckDB time: 0.5170934200286865\n", "DuckDB return:\n", " k l c \\\n", "0 google.ru 115.428171 248632 \n", @@ -2641,7 +2709,7 @@ "9 http://bdsmpeople.ru/ \n", "10 http://google.com/&http://ria \n", "11 http:%2F%2Fwwww.ukr \n", - "chDB time: 0.2807183265686035\n", + "chDB time: 0.2968788146972656\n", "chDB return:\n", " \"google.ru\",115.42817095144632,248632,\"http://google.ru/\"\n", "\"go.mail\",108.23690999765847,943831,\"http://go.mail/?ID=26175503771357/pic/8437/1/courtner-pub-61589792\"\n", @@ -2656,12 +2724,7 @@ "\"google.com\",38.55237819025522,327560,\"http://google.com/&http://ria\"\n", "\"http:%2F%2Fwwww.ukr\",19,118140,\"http:%2F%2Fwwww.ukr\"\n", "\n", - "Pandas time: 30.86491560935974\n", - "Pandas return:\n", - " Referer\n", - "min_referer http://auto.ria.ua/\n", - "average_length 74.443681\n", - "Polars time: 6.171788692474365\n", + "Polars time: 6.252786636352539\n", "Polars return:\n", " shape: (12, 4)\n", "┌─────────────────┬─────────┬─────────────────────────────────┬─────────┐\n", @@ -2682,7 +2745,10 @@ "│ mysw.info ┆ 101187 ┆ http://mysw.info/ ┆ 101187 │\n", "└─────────────────┴─────────┴─────────────────────────────────┴─────────┘\n", "Q29 SELECT SUM(ResolutionWidth), SUM(ResolutionWidth + 1), SUM(ResolutionWidth + 2), SUM(ResolutionWidth + 3), SUM(ResolutionWidth + 4), SUM(ResolutionWidth + 5), SUM(ResolutionWidth + 6), SUM(ResolutionWidth + 7), SUM(ResolutionWidth + 8), SUM(ResolutionWidth + 9), SUM(ResolutionWidth + 10), SUM(ResolutionWidth + 11), SUM(ResolutionWidth + 12), SUM(ResolutionWidth + 13), SUM(ResolutionWidth + 14), SUM(ResolutionWidth + 15), SUM(ResolutionWidth + 16), SUM(ResolutionWidth + 17), SUM(ResolutionWidth + 18), SUM(ResolutionWidth + 19), SUM(ResolutionWidth + 20), SUM(ResolutionWidth + 21), SUM(ResolutionWidth + 22), SUM(ResolutionWidth + 23), SUM(ResolutionWidth + 24), SUM(ResolutionWidth + 25), SUM(ResolutionWidth + 26), SUM(ResolutionWidth + 27), SUM(ResolutionWidth + 28), SUM(ResolutionWidth + 29), SUM(ResolutionWidth + 30), SUM(ResolutionWidth + 31), SUM(ResolutionWidth + 32), SUM(ResolutionWidth + 33), SUM(ResolutionWidth + 34), SUM(ResolutionWidth + 35), SUM(ResolutionWidth + 36), SUM(ResolutionWidth + 37), SUM(ResolutionWidth + 38), SUM(ResolutionWidth + 39), SUM(ResolutionWidth + 40), SUM(ResolutionWidth + 41), SUM(ResolutionWidth + 42), SUM(ResolutionWidth + 43), SUM(ResolutionWidth + 44), SUM(ResolutionWidth + 45), SUM(ResolutionWidth + 46), SUM(ResolutionWidth + 47), SUM(ResolutionWidth + 48), SUM(ResolutionWidth + 49), SUM(ResolutionWidth + 50), SUM(ResolutionWidth + 51), SUM(ResolutionWidth + 52), SUM(ResolutionWidth + 53), SUM(ResolutionWidth + 54), SUM(ResolutionWidth + 55), SUM(ResolutionWidth + 56), SUM(ResolutionWidth + 57), SUM(ResolutionWidth + 58), SUM(ResolutionWidth + 59), SUM(ResolutionWidth + 60), SUM(ResolutionWidth + 61), SUM(ResolutionWidth + 62), SUM(ResolutionWidth + 63), SUM(ResolutionWidth + 64), SUM(ResolutionWidth + 65), SUM(ResolutionWidth + 66), SUM(ResolutionWidth + 67), SUM(ResolutionWidth + 68), SUM(ResolutionWidth + 69), SUM(ResolutionWidth + 70), SUM(ResolutionWidth + 71), SUM(ResolutionWidth + 72), SUM(ResolutionWidth + 73), SUM(ResolutionWidth + 74), SUM(ResolutionWidth + 75), SUM(ResolutionWidth + 76), SUM(ResolutionWidth + 77), SUM(ResolutionWidth + 78), SUM(ResolutionWidth + 79), SUM(ResolutionWidth + 80), SUM(ResolutionWidth + 81), SUM(ResolutionWidth + 82), SUM(ResolutionWidth + 83), SUM(ResolutionWidth + 84), SUM(ResolutionWidth + 85), SUM(ResolutionWidth + 86), SUM(ResolutionWidth + 87), SUM(ResolutionWidth + 88), SUM(ResolutionWidth + 89) FROM hits;\n", - "DuckDB time: 0.41875171661376953\n", + "Pandas time: 2.758824586868286\n", + "Pandas return:\n", + " 1356994681947.0\n", + "DuckDB time: 0.20304656028747559\n", "DuckDB return:\n", " sum(ResolutionWidth) sum((ResolutionWidth + 1)) \\\n", "0 1.507779e+10 1.508779e+10 \n", @@ -2715,18 +2781,29 @@ "0 1.595779e+10 1.596779e+10 \n", "\n", "[1 rows x 90 columns]\n", - "chDB time: 0.05283093452453613\n", + "chDB time: 0.05274057388305664\n", "chDB return:\n", " 15077792377,15087792377,15097792377,15107792377,15117792377,15127792377,15137792377,15147792377,15157792377,15167792377,15177792377,15187792377,15197792377,15207792377,15217792377,15227792377,15237792377,15247792377,15257792377,15267792377,15277792377,15287792377,15297792377,15307792377,15317792377,15327792377,15337792377,15347792377,15357792377,15367792377,15377792377,15387792377,15397792377,15407792377,15417792377,15427792377,15437792377,15447792377,15457792377,15467792377,15477792377,15487792377,15497792377,15507792377,15517792377,15527792377,15537792377,15547792377,15557792377,15567792377,15577792377,15587792377,15597792377,15607792377,15617792377,15627792377,15637792377,15647792377,15657792377,15667792377,15677792377,15687792377,15697792377,15707792377,15717792377,15727792377,15737792377,15747792377,15757792377,15767792377,15777792377,15787792377,15797792377,15807792377,15817792377,15827792377,15837792377,15847792377,15857792377,15867792377,15877792377,15887792377,15897792377,15907792377,15917792377,15927792377,15937792377,15947792377,15957792377,15967792377\n", "\n", - "Pandas time: 3.6151206493377686\n", - "Pandas return:\n", - " 1356994681947.0\n", - "Polars time: 0.00017690658569335938\n", + "Polars time: 0.0001652240753173828\n", "Polars return:\n", " 141195\n", "Q30 SELECT SearchEngineID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM hits WHERE SearchPhrase <> '' GROUP BY SearchEngineID, ClientIP ORDER BY c DESC LIMIT 10;\n", - "DuckDB time: 0.07926249504089355\n", + "Pandas time: 1.535578966140747\n", + "Pandas return:\n", + " c IsRefreshSum AvgResolutionWidth\n", + "SearchEngineID ClientIP \n", + "2 1138507705 167 2 1383.610778\n", + " 1740861572 167 0 1601.982036\n", + " -1106675868 158 2 1507.170886\n", + " 1124827693 155 77 1749.277419\n", + " -497906719 152 1 1534.506579\n", + " -631062503 140 8 1557.242857\n", + " 1146197031 139 6 1598.287770\n", + " -1870623097 133 4 1531.691729\n", + " -265917476 133 6 1555.090226\n", + " -1089778290 132 1 1538.712121\n", + "DuckDB time: 0.08614468574523926\n", "DuckDB return:\n", " SearchEngineID ClientIP c sum(IsRefresh) avg(ResolutionWidth)\n", "0 2 1138507705 167 2.0 1383.610778\n", @@ -2739,7 +2816,7 @@ "7 2 -1870623097 133 4.0 1531.691729\n", "8 2 -265917476 133 6.0 1555.090226\n", "9 2 -1089778290 132 1.0 1538.712121\n", - "chDB time: 0.05949997901916504\n", + "chDB time: 0.06468677520751953\n", "chDB return:\n", " 2,1740861572,167,0,1601.9820359281437\n", "2,1138507705,167,2,1383.6107784431138\n", @@ -2748,25 +2825,11 @@ "2,-497906719,152,1,1534.5065789473683\n", "2,-631062503,140,8,1557.2428571428572\n", "2,1146197031,139,6,1598.2877697841727\n", - "2,-1870623097,133,4,1531.6917293233082\n", "2,-265917476,133,6,1555.0902255639098\n", + "2,-1870623097,133,4,1531.6917293233082\n", "2,-1089778290,132,1,1538.7121212121212\n", "\n", - "Pandas time: 1.5518078804016113\n", - "Pandas return:\n", - " c IsRefreshSum AvgResolutionWidth\n", - "SearchEngineID ClientIP \n", - "2 1138507705 167 2 1383.610778\n", - " 1740861572 167 0 1601.982036\n", - " -1106675868 158 2 1507.170886\n", - " 1124827693 155 77 1749.277419\n", - " -497906719 152 1 1534.506579\n", - " -631062503 140 8 1557.242857\n", - " 1146197031 139 6 1598.287770\n", - " -1870623097 133 4 1531.691729\n", - " -265917476 133 6 1555.090226\n", - " -1089778290 132 1 1538.712121\n", - "Polars time: 0.2474958896636963\n", + "Polars time: 0.24605369567871094\n", "Polars return:\n", " shape: (10, 5)\n", "┌────────────────┬─────────────┬─────┬──────────────┬────────────────────┐\n", @@ -2774,45 +2837,19 @@ "│ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n", "│ i16 ┆ i32 ┆ u32 ┆ i64 ┆ f64 │\n", "╞════════════════╪═════════════╪═════╪══════════════╪════════════════════╡\n", - "│ 2 ┆ 1138507705 ┆ 167 ┆ 2 ┆ 1383.610778 │\n", "│ 2 ┆ 1740861572 ┆ 167 ┆ 0 ┆ 1601.982036 │\n", + "│ 2 ┆ 1138507705 ┆ 167 ┆ 2 ┆ 1383.610778 │\n", "│ 2 ┆ -1106675868 ┆ 158 ┆ 2 ┆ 1507.170886 │\n", "│ 2 ┆ 1124827693 ┆ 155 ┆ 77 ┆ 1749.277419 │\n", "│ 2 ┆ -497906719 ┆ 152 ┆ 1 ┆ 1534.506579 │\n", "│ 2 ┆ -631062503 ┆ 140 ┆ 8 ┆ 1557.242857 │\n", "│ 2 ┆ 1146197031 ┆ 139 ┆ 6 ┆ 1598.28777 │\n", - "│ 2 ┆ -265917476 ┆ 133 ┆ 6 ┆ 1555.090226 │\n", "│ 2 ┆ -1870623097 ┆ 133 ┆ 4 ┆ 1531.691729 │\n", + "│ 2 ┆ -265917476 ┆ 133 ┆ 6 ┆ 1555.090226 │\n", "│ 2 ┆ -1089778290 ┆ 132 ┆ 1 ┆ 1538.712121 │\n", "└────────────────┴─────────────┴─────┴──────────────┴────────────────────┘\n", "Q31 SELECT WatchID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM hits WHERE SearchPhrase <> '' GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10;\n", - "DuckDB time: 0.11410140991210938\n", - "DuckDB return:\n", - " WatchID ClientIP c sum(IsRefresh) avg(ResolutionWidth)\n", - "0 7433617358826888022 765396521 1 0.0 1750.0\n", - "1 6845096800585140239 697577507 1 0.0 1087.0\n", - "2 7417948050699454238 1381092923 1 0.0 1750.0\n", - "3 7614647577457412141 1381092923 1 0.0 1750.0\n", - "4 6740098735982683802 1381092923 1 0.0 1750.0\n", - "5 4824664031920863261 720586547 1 0.0 1996.0\n", - "6 5821118952041186941 -729938388 1 0.0 1917.0\n", - "7 6713590791010076724 1409085022 1 0.0 1638.0\n", - "8 6548785613138596558 1714868846 1 0.0 1996.0\n", - "9 5972495615745521485 1578253175 1 0.0 1368.0\n", - "chDB time: 0.09229826927185059\n", - "chDB return:\n", - " 5055679980591148335,-247495422,1,0,1917\n", - "5268572242740516149,-2084875520,1,0,1638\n", - "4830290381830615525,1833501146,1,0,1917\n", - "5901073908092331412,1976973896,1,0,1368\n", - "7227951727328737869,1767461008,1,0,1638\n", - "6081390183502573534,911172261,1,0,1638\n", - "5053868840694598172,1338505058,1,0,184\n", - "8815896716189863724,513446242,1,0,1996\n", - "7729270990481304965,-2113508332,1,0,1638\n", - "8678109688701084511,756024604,1,0,1638\n", - "\n", - "Pandas time: 1.9441230297088623\n", + "Pandas time: 1.996917963027954\n", "Pandas return:\n", " c IsRefreshSum AvgResolutionWidth\n", "WatchID ClientIP \n", @@ -2826,7 +2863,33 @@ "4611715740922561616 -339684538 1 0 1087.0\n", "4611717928870807772 1799799829 1 0 1917.0\n", "4611720317321800760 659762682 1 0 1087.0\n", - "Polars time: 0.2849397659301758\n", + "DuckDB time: 0.10591721534729004\n", + "DuckDB return:\n", + " WatchID ClientIP c sum(IsRefresh) avg(ResolutionWidth)\n", + "0 6818582411365665958 660315215 1 0.0 1368.0\n", + "1 8791819270435807490 1473828557 1 0.0 1638.0\n", + "2 7890989371291307084 -1238271973 1 0.0 1996.0\n", + "3 4924171746038591134 1009621405 1 0.0 1368.0\n", + "4 7973320409482814316 -643969386 1 0.0 1471.0\n", + "5 4828359945228318410 -1560671451 1 0.0 1368.0\n", + "6 7478606104903083014 1439503871 1 0.0 1368.0\n", + "7 8722491948504705058 1303595993 1 0.0 582.0\n", + "8 5662656757024973392 1315069729 1 0.0 1996.0\n", + "9 6139424863805621355 1526066212 1 0.0 508.0\n", + "chDB time: 0.09296727180480957\n", + "chDB return:\n", + " 5055679980591148335,-247495422,1,0,1917\n", + "5268572242740516149,-2084875520,1,0,1638\n", + "7972036787597603422,1392047940,1,0,1750\n", + "5901073908092331412,1976973896,1,0,1368\n", + "7227951727328737869,1767461008,1,0,1638\n", + "6081390183502573534,911172261,1,0,1638\n", + "5053868840694598172,1338505058,1,0,184\n", + "8815896716189863724,513446242,1,0,1996\n", + "7729270990481304965,-2113508332,1,0,1638\n", + "8678109688701084511,756024604,1,0,1638\n", + "\n", + "Polars time: 0.2792203426361084\n", "Polars return:\n", " shape: (10, 5)\n", "┌─────────────────────┬─────────────┬─────┬──────────────┬────────────────────┐\n", @@ -2834,32 +2897,46 @@ "│ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n", "│ i64 ┆ i32 ┆ u32 ┆ i64 ┆ f64 │\n", "╞═════════════════════╪═════════════╪═════╪══════════════╪════════════════════╡\n", - "│ 8866481400707184606 ┆ 683610771 ┆ 1 ┆ 0 ┆ 1087.0 │\n", - "│ 5976446437111469971 ┆ -868572229 ┆ 1 ┆ 0 ┆ 1996.0 │\n", - "│ 8394567842376086126 ┆ 1224879233 ┆ 1 ┆ 0 ┆ 508.0 │\n", - "│ 5151723549681893012 ┆ 1507755864 ┆ 1 ┆ 0 ┆ 1828.0 │\n", - "│ 6214865211162857505 ┆ 1723654076 ┆ 1 ┆ 0 ┆ 1368.0 │\n", - "│ 5280990891245629665 ┆ -1890611862 ┆ 1 ┆ 0 ┆ 1368.0 │\n", - "│ 6651288293509706204 ┆ 2134633159 ┆ 1 ┆ 0 ┆ 1638.0 │\n", - "│ 6194544028690036767 ┆ 1723163073 ┆ 1 ┆ 0 ┆ 1250.0 │\n", - "│ 7892825946104167072 ┆ 1072342394 ┆ 1 ┆ 0 ┆ 1750.0 │\n", - "│ 6164942890021406019 ┆ 1641142800 ┆ 1 ┆ 0 ┆ 1917.0 │\n", + "│ 8460219899915854782 ┆ 1889832869 ┆ 1 ┆ 0 ┆ 1368.0 │\n", + "│ 4774246863364486494 ┆ 1677013099 ┆ 1 ┆ 0 ┆ 1996.0 │\n", + "│ 6191226534489978120 ┆ 1610203158 ┆ 1 ┆ 0 ┆ 1638.0 │\n", + "│ 8312808744143954042 ┆ 1664566209 ┆ 1 ┆ 1 ┆ 1638.0 │\n", + "│ 6813864744225277860 ┆ -1172240730 ┆ 1 ┆ 0 ┆ 582.0 │\n", + "│ 7962310428745386102 ┆ 917216780 ┆ 1 ┆ 0 ┆ 1917.0 │\n", + "│ 8355656868011943840 ┆ -902402098 ┆ 1 ┆ 0 ┆ 1638.0 │\n", + "│ 6445042513551559459 ┆ -1529360067 ┆ 1 ┆ 0 ┆ 1917.0 │\n", + "│ 8975633444743392647 ┆ 1669869597 ┆ 1 ┆ 0 ┆ 1368.0 │\n", + "│ 8864743372993907341 ┆ 1199394979 ┆ 1 ┆ 0 ┆ 1638.0 │\n", "└─────────────────────┴─────────────┴─────┴──────────────┴────────────────────┘\n", "Q32 SELECT WatchID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM hits GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10;\n", - "DuckDB time: 0.1959702968597412\n", + "Pandas time: 7.862155199050903\n", + "Pandas return:\n", + " c IsRefreshSum AvgResolutionWidth\n", + "WatchID ClientIP \n", + "6655575552203051303 1611957945 2 0 1638.0\n", + "7224410078130478461 -776509581 2 0 1368.0\n", + "4611686363500364104 1221513398 1 0 1990.0\n", + "4611686402113265154 -1339197305 1 0 1750.0\n", + "4611686851060971175 -985812753 1 0 1368.0\n", + "4611687435907085604 1760738510 1 0 1368.0\n", + "4611687575936721977 1770854750 1 0 1638.0\n", + "4611687987885605089 1362499323 1 1 1917.0\n", + "4611688643422516557 2089610172 1 0 1368.0\n", + "4611688965700267127 564621555 1 0 1087.0\n", + "DuckDB time: 0.20980262756347656\n", "DuckDB return:\n", " WatchID ClientIP c sum(IsRefresh) avg(ResolutionWidth)\n", "0 7224410078130478461 -776509581 2 0.0 1368.0\n", "1 6655575552203051303 1611957945 2 0.0 1638.0\n", - "2 7578409505237148051 55707432 1 0.0 1368.0\n", - "3 6042985109837859254 1090782696 1 0.0 1368.0\n", - "4 7853636214732658170 -428889112 1 0.0 348.0\n", - "5 4823078680023084693 913985713 1 0.0 1917.0\n", - "6 4811313877556335245 1887535095 1 0.0 1917.0\n", - "7 9211680604818810870 -1272751583 1 0.0 430.0\n", - "8 5479010330340839726 842336962 1 0.0 1990.0\n", - "9 7612916189797209960 537065003 1 0.0 1996.0\n", - "chDB time: 0.20939183235168457\n", + "2 5627139650043745980 -1487414388 1 1.0 1828.0\n", + "3 8322353452734212386 -1031601240 1 0.0 1087.0\n", + "4 7456736512784606779 -1031601240 1 0.0 1087.0\n", + "5 5592741995199699900 -1990988318 1 1.0 1996.0\n", + "6 7580754668976847738 -1990988318 1 0.0 1996.0\n", + "7 5747877532050934590 -1990988318 1 1.0 1996.0\n", + "8 7488286597677165751 -1990988318 1 0.0 1996.0\n", + "9 4709156312375759729 -1990988318 1 1.0 1996.0\n", + "chDB time: 0.20761418342590332\n", "chDB return:\n", " 7224410078130478461,-776509581,2,0,1368\n", "6655575552203051303,1611957945,2,0,1638\n", @@ -2872,21 +2949,7 @@ "7812846363567359668,1659478732,1,0,508\n", "6700068120218951102,788087753,1,0,1996\n", "\n", - "Pandas time: 7.934078216552734\n", - "Pandas return:\n", - " c IsRefreshSum AvgResolutionWidth\n", - "WatchID ClientIP \n", - "6655575552203051303 1611957945 2 0 1638.0\n", - "7224410078130478461 -776509581 2 0 1368.0\n", - "4611686363500364104 1221513398 1 0 1990.0\n", - "4611686402113265154 -1339197305 1 0 1750.0\n", - "4611686851060971175 -985812753 1 0 1368.0\n", - "4611687435907085604 1760738510 1 0 1368.0\n", - "4611687575936721977 1770854750 1 0 1638.0\n", - "4611687987885605089 1362499323 1 1 1917.0\n", - "4611688643422516557 2089610172 1 0 1368.0\n", - "4611688965700267127 564621555 1 0 1087.0\n", - "Polars time: 0.6120898723602295\n", + "Polars time: 0.5795397758483887\n", "Polars return:\n", " shape: (10, 5)\n", "┌─────────────────────┬─────────────┬─────┬──────────────┬────────────────────┐\n", @@ -2894,19 +2957,32 @@ "│ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n", "│ i64 ┆ i32 ┆ u32 ┆ i64 ┆ f64 │\n", "╞═════════════════════╪═════════════╪═════╪══════════════╪════════════════════╡\n", - "│ 7224410078130478461 ┆ -776509581 ┆ 2 ┆ 0 ┆ 1368.0 │\n", "│ 6655575552203051303 ┆ 1611957945 ┆ 2 ┆ 0 ┆ 1638.0 │\n", - "│ 8770873791278154909 ┆ -1227628113 ┆ 1 ┆ 0 ┆ 1638.0 │\n", - "│ 5175983413994784880 ┆ -1623685973 ┆ 1 ┆ 0 ┆ 0.0 │\n", - "│ 7354852826398121421 ┆ 1148053479 ┆ 1 ┆ 0 ┆ 508.0 │\n", - "│ 7390510824302185303 ┆ -1069506224 ┆ 1 ┆ 0 ┆ 1638.0 │\n", - "│ 8119706864054503675 ┆ 1671265206 ┆ 1 ┆ 0 ┆ 1087.0 │\n", - "│ 7978246246625630775 ┆ 797036316 ┆ 1 ┆ 0 ┆ 1638.0 │\n", - "│ 4782320985610228979 ┆ 1250194442 ┆ 1 ┆ 0 ┆ 1917.0 │\n", - "│ 8933510620274997644 ┆ 1545187692 ┆ 1 ┆ 0 ┆ 1750.0 │\n", + "│ 7224410078130478461 ┆ -776509581 ┆ 2 ┆ 0 ┆ 1368.0 │\n", + "│ 6461300558573284255 ┆ -862970696 ┆ 1 ┆ 0 ┆ 1917.0 │\n", + "│ 8583375600809868473 ┆ 864819352 ┆ 1 ┆ 0 ┆ 1638.0 │\n", + "│ 5553133204352700174 ┆ 1902209793 ┆ 1 ┆ 0 ┆ 1250.0 │\n", + "│ 9071624092466570549 ┆ 1394440351 ┆ 1 ┆ 0 ┆ 582.0 │\n", + "│ 6137278582682151328 ┆ 1558448566 ┆ 1 ┆ 0 ┆ 1996.0 │\n", + "│ 7811543113991803283 ┆ 1623937648 ┆ 1 ┆ 0 ┆ 1996.0 │\n", + "│ 6357221719449919802 ┆ 2064408433 ┆ 1 ┆ 0 ┆ 1750.0 │\n", + "│ 6323188556852872827 ┆ -1817931181 ┆ 1 ┆ 0 ┆ 1996.0 │\n", "└─────────────────────┴─────────────┴─────┴──────────────┴────────────────────┘\n", "Q33 SELECT URL, COUNT(*) AS c FROM hits GROUP BY URL ORDER BY c DESC LIMIT 10;\n", - "DuckDB time: 0.2761256694793701\n", + "Pandas time: 7.771429538726807\n", + "Pandas return:\n", + " URL c\n", + "0 http://kinopoisk.ru 141486\n", + "1 http://bdsm_po_yers=0&with_video 82623\n", + "2 http://liver.ru/belgorod/page/1006.jки/доп_при... 78593\n", + "3 http://smeshariki.ru/region 59652\n", + "4 http://kinopoisk.ru/search 58276\n", + "5 http://tienskaia-moda 52965\n", + "6 http://video.yandex 47719\n", + "7 http://kinopoisk.ru/vladimir.irr.ru 29715\n", + "8 http://bjdleaks.php?produkty%2Fproduct 26809\n", + "9 http://pogoda.yandex 26589\n", + "DuckDB time: 0.1876978874206543\n", "DuckDB return:\n", " URL c\n", "0 http://kinopoisk.ru 141486\n", @@ -2919,7 +2995,7 @@ "7 http://kinopoisk.ru/vladimir.irr.ru 29715\n", "8 http://bjdleaks.php?produkty%2Fproduct 26809\n", "9 http://pogoda.yandex 26589\n", - "chDB time: 0.21467256546020508\n", + "chDB time: 0.21751952171325684\n", "chDB return:\n", " \"http://kinopoisk.ru\",141486\n", "\"http://bdsm_po_yers=0&with_video\",82623\n", @@ -2931,7 +3007,495 @@ "\"http://kinopoisk.ru/vladimir.irr.ru\",29715\n", "\"http://bjdleaks.php?produkty%2Fproduct\",26809\n", "\"http://pogoda.yandex\",26589\n", - "\n" + "\n", + "Polars time: 0.18122506141662598\n", + "Polars return:\n", + " shape: (10, 2)\n", + "┌─────────────────────────────────┬────────┐\n", + "│ URL ┆ c │\n", + "│ --- ┆ --- │\n", + "│ str ┆ u32 │\n", + "╞═════════════════════════════════╪════════╡\n", + "│ http://kinopoisk.ru ┆ 141486 │\n", + "│ http://bdsm_po_yers=0&with_vid… ┆ 82623 │\n", + "│ http://liver.ru/belgorod/page/… ┆ 78593 │\n", + "│ http://smeshariki.ru/region ┆ 59652 │\n", + "│ http://kinopoisk.ru/search ┆ 58276 │\n", + "│ http://tienskaia-moda ┆ 52965 │\n", + "│ http://video.yandex ┆ 47719 │\n", + "│ http://kinopoisk.ru/vladimir.i… ┆ 29715 │\n", + "│ http://bjdleaks.php?produkty%2… ┆ 26809 │\n", + "│ http://pogoda.yandex ┆ 26589 │\n", + "└─────────────────────────────────┴────────┘\n", + "Q34 SELECT 1, URL, COUNT(*) AS c FROM hits GROUP BY 1, URL ORDER BY c DESC LIMIT 10;\n", + "Pandas time: 7.3071815967559814\n", + "Pandas return:\n", + " URL c\n", + "0 http://kinopoisk.ru 141486\n", + "1 http://bdsm_po_yers=0&with_video 82623\n", + "2 http://liver.ru/belgorod/page/1006.jки/доп_при... 78593\n", + "3 http://smeshariki.ru/region 59652\n", + "4 http://kinopoisk.ru/search 58276\n", + "5 http://tienskaia-moda 52965\n", + "6 http://video.yandex 47719\n", + "7 http://kinopoisk.ru/vladimir.irr.ru 29715\n", + "8 http://bjdleaks.php?produkty%2Fproduct 26809\n", + "9 http://pogoda.yandex 26589\n", + "DuckDB time: 0.18941712379455566\n", + "DuckDB return:\n", + " 1 URL c\n", + "0 1 http://kinopoisk.ru 141486\n", + "1 1 http://bdsm_po_yers=0&with_video 82623\n", + "2 1 http://liver.ru/belgorod/page/1006.jки/доп_при... 78593\n", + "3 1 http://smeshariki.ru/region 59652\n", + "4 1 http://kinopoisk.ru/search 58276\n", + "5 1 http://tienskaia-moda 52965\n", + "6 1 http://video.yandex 47719\n", + "7 1 http://kinopoisk.ru/vladimir.irr.ru 29715\n", + "8 1 http://bjdleaks.php?produkty%2Fproduct 26809\n", + "9 1 http://pogoda.yandex 26589\n", + "chDB time: 0.19516444206237793\n", + "chDB return:\n", + " 1,\"http://kinopoisk.ru\",141486\n", + "1,\"http://bdsm_po_yers=0&with_video\",82623\n", + "1,\"http://liver.ru/belgorod/page/1006.jки/доп_приборы\",78593\n", + "1,\"http://smeshariki.ru/region\",59652\n", + "1,\"http://kinopoisk.ru/search\",58276\n", + "1,\"http://tienskaia-moda\",52965\n", + "1,\"http://video.yandex\",47719\n", + "1,\"http://kinopoisk.ru/vladimir.irr.ru\",29715\n", + "1,\"http://bjdleaks.php?produkty%2Fproduct\",26809\n", + "1,\"http://pogoda.yandex\",26589\n", + "\n", + "Polars time: 0.172119140625\n", + "Polars return:\n", + " shape: (10, 2)\n", + "┌─────────────────────────────────┬────────┐\n", + "│ URL ┆ c │\n", + "│ --- ┆ --- │\n", + "│ str ┆ u32 │\n", + "╞═════════════════════════════════╪════════╡\n", + "│ http://kinopoisk.ru ┆ 141486 │\n", + "│ http://bdsm_po_yers=0&with_vid… ┆ 82623 │\n", + "│ http://liver.ru/belgorod/page/… ┆ 78593 │\n", + "│ http://smeshariki.ru/region ┆ 59652 │\n", + "│ http://kinopoisk.ru/search ┆ 58276 │\n", + "│ http://tienskaia-moda ┆ 52965 │\n", + "│ http://video.yandex ┆ 47719 │\n", + "│ http://kinopoisk.ru/vladimir.i… ┆ 29715 │\n", + "│ http://bjdleaks.php?produkty%2… ┆ 26809 │\n", + "│ http://pogoda.yandex ┆ 26589 │\n", + "└─────────────────────────────────┴────────┘\n", + "Q35 SELECT ClientIP, ClientIP - 1, ClientIP - 2, ClientIP - 3, COUNT(*) AS c FROM hits GROUP BY ClientIP, ClientIP - 1, ClientIP - 2, ClientIP - 3 ORDER BY c DESC LIMIT 10;\n", + "Pandas time: 32.501299142837524\n", + "Pandas return:\n", + " ClientIP ClientIP_minus_1 ClientIP_minus_2 ClientIP_minus_3 c\n", + "0 -1698104457 -1698104458 -1698104459 -1698104460 15792\n", + "1 -1175819552 -1175819553 -1175819554 -1175819555 6229\n", + "2 1990169817 1990169816 1990169815 1990169814 6019\n", + "3 1844870420 1844870419 1844870418 1844870417 6015\n", + "4 1215815219 1215815218 1215815217 1215815216 4384\n", + "5 -39921974 -39921975 -39921976 -39921977 3168\n", + "6 1151807695 1151807694 1151807693 1151807692 2738\n", + "7 1416368349 1416368348 1416368347 1416368346 2685\n", + "8 1676284222 1676284221 1676284220 1676284219 2609\n", + "9 1704860211 1704860210 1704860209 1704860208 2554\n", + "DuckDB time: 0.10219049453735352\n", + "DuckDB return:\n", + " ClientIP (ClientIP - 1) (ClientIP - 2) (ClientIP - 3) c\n", + "0 -1698104457 -1698104458 -1698104459 -1698104460 15792\n", + "1 -1175819552 -1175819553 -1175819554 -1175819555 6229\n", + "2 1990169817 1990169816 1990169815 1990169814 6019\n", + "3 1844870420 1844870419 1844870418 1844870417 6015\n", + "4 1215815219 1215815218 1215815217 1215815216 4384\n", + "5 -39921974 -39921975 -39921976 -39921977 3168\n", + "6 1151807695 1151807694 1151807693 1151807692 2738\n", + "7 1416368349 1416368348 1416368347 1416368346 2685\n", + "8 1676284222 1676284221 1676284220 1676284219 2609\n", + "9 1704860211 1704860210 1704860209 1704860208 2554\n", + "chDB time: 0.08132767677307129\n", + "chDB return:\n", + " -1698104457,-1698104458,-1698104459,-1698104460,15792\n", + "-1175819552,-1175819553,-1175819554,-1175819555,6229\n", + "1990169817,1990169816,1990169815,1990169814,6019\n", + "1844870420,1844870419,1844870418,1844870417,6015\n", + "1215815219,1215815218,1215815217,1215815216,4384\n", + "-39921974,-39921975,-39921976,-39921977,3168\n", + "1151807695,1151807694,1151807693,1151807692,2738\n", + "1416368349,1416368348,1416368347,1416368346,2685\n", + "1676284222,1676284221,1676284220,1676284219,2609\n", + "1704860211,1704860210,1704860209,1704860208,2554\n", + "\n", + "Polars time: 0.06913375854492188\n", + "Polars return:\n", + " shape: (10, 2)\n", + "┌─────────────┬───────┐\n", + "│ ClientIP ┆ c │\n", + "│ --- ┆ --- │\n", + "│ i32 ┆ u32 │\n", + "╞═════════════╪═══════╡\n", + "│ -1698104457 ┆ 15792 │\n", + "│ -1175819552 ┆ 6229 │\n", + "│ 1990169817 ┆ 6019 │\n", + "│ 1844870420 ┆ 6015 │\n", + "│ 1215815219 ┆ 4384 │\n", + "│ -39921974 ┆ 3168 │\n", + "│ 1151807695 ┆ 2738 │\n", + "│ 1416368349 ┆ 2685 │\n", + "│ 1676284222 ┆ 2609 │\n", + "│ 1704860211 ┆ 2554 │\n", + "└─────────────┴───────┘\n", + "Q36 SELECT URL, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND DontCountHits = 0 AND IsRefresh = 0 AND URL <> '' GROUP BY URL ORDER BY PageViews DESC LIMIT 10;\n", + "Pandas time: 0.7082381248474121\n", + "Pandas return:\n", + " URL\n", + "http://irr.ru/index.php?showalbum/login-leniya7777294,938303130 15378\n", + "http://komme%2F27.0.1453.116 6942\n", + "http://irr.ru/index.php?showalbum/login-kapusta-advert2668]=0&order_by=0 2546\n", + "http://irr.ru/index.php?showalbum/login-kapustic/product_name 2131\n", + "http://irr.ru/index.php?showalbum/login 1574\n", + "http://irr.ru/index.php 1550\n", + "http://komme%2F27.0.1453.116 Safari%2F5.0 (compatible; MSIE 9.0; 1045\n", + "http://irr.ru/index.php?showalbum/login-kupalnik 593\n", + "http://komme%2F27.0.1453.116 Safari 517\n", + "http://irr.ru/index.php?showalbum/login-kapusta-advert27256.html_params 511\n", + "dtype: int64\n", + "DuckDB time: 0.05800819396972656\n", + "DuckDB return:\n", + " URL PageViews\n", + "0 http://irr.ru/index.php?showalbum/login-leniya... 15378\n", + "1 http://komme%2F27.0.1453.116 6942\n", + "2 http://irr.ru/index.php?showalbum/login-kapust... 2546\n", + "3 http://irr.ru/index.php?showalbum/login-kapust... 2131\n", + "4 http://irr.ru/index.php?showalbum/login 1574\n", + "5 http://irr.ru/index.php 1550\n", + "6 http://komme%2F27.0.1453.116 Safari%2F5.0 (com... 1045\n", + "7 http://irr.ru/index.php?showalbum/login-kupalnik 593\n", + "8 http://komme%2F27.0.1453.116 Safari 517\n", + "9 http://irr.ru/index.php?showalbum/login-kapust... 511\n", + "chDB time: 0.10596656799316406\n", + "chDB return:\n", + " \"http://irr.ru/index.php?showalbum/login-leniya7777294,938303130\",15378\n", + "\"http://komme%2F27.0.1453.116\",6942\n", + "\"http://irr.ru/index.php?showalbum/login-kapusta-advert2668]=0&order_by=0\",2546\n", + "\"http://irr.ru/index.php?showalbum/login-kapustic/product_name\",2131\n", + "\"http://irr.ru/index.php?showalbum/login\",1574\n", + "\"http://irr.ru/index.php\",1550\n", + "\"http://komme%2F27.0.1453.116 Safari%2F5.0 (compatible; MSIE 9.0;\",1045\n", + "\"http://irr.ru/index.php?showalbum/login-kupalnik\",593\n", + "\"http://komme%2F27.0.1453.116 Safari\",517\n", + "\"http://irr.ru/index.php?showalbum/login-kapusta-advert27256.html_params\",511\n", + "\n", + "Polars time: 2.07474422454834\n", + "Polars return:\n", + " shape: (10, 2)\n", + "┌─────────────────────────────────┬───────────┐\n", + "│ URL ┆ PageViews │\n", + "│ --- ┆ --- │\n", + "│ str ┆ u32 │\n", + "╞═════════════════════════════════╪═══════════╡\n", + "│ http://irr.ru/index.php?showal… ┆ 15378 │\n", + "│ http://komme%2F27.0.1453.116 ┆ 6942 │\n", + "│ http://irr.ru/index.php?showal… ┆ 2546 │\n", + "│ http://irr.ru/index.php?showal… ┆ 2131 │\n", + "│ http://irr.ru/index.php?showal… ┆ 1574 │\n", + "│ http://irr.ru/index.php ┆ 1550 │\n", + "│ http://komme%2F27.0.1453.116 S… ┆ 1045 │\n", + "│ http://irr.ru/index.php?showal… ┆ 593 │\n", + "│ http://komme%2F27.0.1453.116 S… ┆ 517 │\n", + "│ http://irr.ru/index.php?showal… ┆ 511 │\n", + "└─────────────────────────────────┴───────────┘\n", + "Q37 SELECT Title, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND DontCountHits = 0 AND IsRefresh = 0 AND Title <> '' GROUP BY Title ORDER BY PageViews DESC LIMIT 10;\n", + "Pandas time: 0.6800808906555176\n", + "Pandas return:\n", + " Title\n", + "Тест (Россия) - Яндекс 18486\n", + "Шарарай), Выбрать! - обсуждаются на голд: Шоубиз - Свободная историс 11533\n", + "Приморск - IRR.ru 10785\n", + "Брюки New Era H (Асус) 258 общая выплаток, горшечными 5916\n", + "Теплоску на 2997\n", + "Dave and Hotpoint sport – самые вещие 2283\n", + "AUTO.ria.ua ™ - Аппер 1835\n", + "OWAProfessign), продать 1828\n", + "Приморск (Россия) - Яндекс.Видео 1781\n", + "бассе» внутренчкоты 1464\n", + "dtype: int64\n", + "DuckDB time: 0.1615283489227295\n", + "DuckDB return:\n", + " Title PageViews\n", + "0 Тест (Россия) - Яндекс 18486\n", + "1 Шарарай), Выбрать! - обсуждаются на голд: Шоуб... 11533\n", + "2 Приморск - IRR.ru 10785\n", + "3 Брюки New Era H (Асус) 258 общая выплаток, гор... 5916\n", + "4 Теплоску на 2997\n", + "5 Dave and Hotpoint sport – самые вещие 2283\n", + "6 AUTO.ria.ua ™ - Аппер 1835\n", + "7 OWAProfessign), продать 1828\n", + "8 Приморск (Россия) - Яндекс.Видео 1781\n", + "9 бассе» внутренчкоты 1464\n", + "chDB time: 0.14129924774169922\n", + "chDB return:\n", + " \"Тест (Россия) - Яндекс\",18486\n", + "\"Шарарай), Выбрать! - обсуждаются на голд: Шоубиз - Свободная историс\",11533\n", + "\"Приморск - IRR.ru\",10785\n", + "\"Брюки New Era H (Асус) 258 общая выплаток, горшечными\",5916\n", + "\"Теплоску на\",2997\n", + "\"Dave and Hotpoint sport – самые вещие\",2283\n", + "\"AUTO.ria.ua ™ - Аппер\",1835\n", + "\"OWAProfessign), продать\",1828\n", + "\"Приморск (Россия) - Яндекс.Видео\",1781\n", + "\"бассе» внутренчкоты \",1464\n", + "\n", + "Polars time: 1.865403413772583\n", + "Polars return:\n", + " shape: (10, 2)\n", + "┌─────────────────────────────────┬───────────┐\n", + "│ Title ┆ PageViews │\n", + "│ --- ┆ --- │\n", + "│ str ┆ u32 │\n", + "╞═════════════════════════════════╪═══════════╡\n", + "│ Тест (Россия) - Яндекс ┆ 18486 │\n", + "│ Шарарай), Выбрать! - обсуждают… ┆ 11533 │\n", + "│ Приморск - IRR.ru ┆ 10785 │\n", + "│ Брюки New Era H (Асус) 258 общ… ┆ 5916 │\n", + "│ Теплоску на ┆ 2997 │\n", + "│ Dave and Hotpoint sport – самы… ┆ 2283 │\n", + "│ AUTO.ria.ua ™ - Аппер ┆ 1835 │\n", + "│ OWAProfessign), продать ┆ 1828 │\n", + "│ Приморск (Россия) - Яндекс.Вид… ┆ 1781 │\n", + "│ бассе» внутренчкоты ┆ 1464 │\n", + "└─────────────────────────────────┴───────────┘\n", + "Q38 SELECT URL, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 AND IsLink <> 0 AND IsDownload = 0 GROUP BY URL ORDER BY PageViews DESC LIMIT 10 OFFSET 1000;\n", + "Pandas time: 0.05269670486450195\n", + "Pandas return:\n", + " Empty DataFrame\n", + "Columns: [URL, PageViews]\n", + "Index: []\n", + "DuckDB time: 0.04982304573059082\n", + "DuckDB return:\n", + " URL PageViews\n", + "0 http://netcatalog/0/search/?q=подростойка-стре... 1\n", + "1 http://stalker-pub-20087898675494,960948/#page... 1\n", + "2 https://mr7.ru/catalog 1\n", + "3 http://stalker-pub-20087898675494,960948/#page... 1\n", + "4 http://bdsmpeople.ru/search?text 1\n", + "5 http://stalker-pub-20087898675494,960948/#page... 1\n", + "6 http://povarenok.ru 1\n", + "7 http://wildberries.aspx#location/group_cod_1s=... 1\n", + "8 http://stalker-pub-20087898675494,960948/#page... 1\n", + "9 http://stalker-pub-20087898675494,960948/#page... 1\n", + "chDB time: 0.12198710441589355\n", + "chDB return:\n", + " \"http://wildberries.aspx#location/group_cod_1s=53&butto_638_1360/3/women.aspx?group_cod_1s=8577/~7/?cauth=0&color=0&auto_ria=0&type\",1\n", + "\"http://stalker-pub-20087898675494,960948/#page_type%3D0%26pz%3D0%26rleurl%3D//ad.adriver.ru/photo=0&is_hot=0&auto_id=577&oki=1&op_prodam-1-komn-kvarti-m.ru/allprice/arts-total=больше 100 до 1500&price_do=50\",1\n", + "\"http://stalker-pub-20087898675494,960948/#page_type%3D0%26pz%3D0%26rleurl%3D%26xpid%3D158197%26anbieter%3DYandex.ru/novosibirsk-gorjache/wm/2013-07-29#sched_car=364499cnD0Ril3dX-UhABIABQgMfhxARghOXxhbAewCl55A%26uid\",1\n", + "\"http://bibidohertki--962845.html?locatid,14.20\",1\n", + "\"http://stalker-pub-20087898675494,960948/#page_type%3D260117152337&spn=1395,94552/photo-3.xhtml?&ss=1&ru=1&expand_seasons/lg/?area/frl-2/bags.spinningradex\",1\n", + "\"http://afisha.yandex.ru/Web/price=меньше 19876/kseniye-rebenok\",1\n", + "\"http://stalker-pub-20087898675494,960948/#page_type%3D0%26pz%3D0%26rleurl%3D%26CompPath%3D278885%26bid%3D0%26u_h%3D728%26fh_page=1080&with_exchangeTypeId=0&engineVolumeTo=&fuelRatesType=0&mode=Отправлик темно\",1\n", + "\"http://stalker-pub-20087898675494,960948/#page_type%3D260117152337&spn=1395,9455989.ya.ru/world/photo/hair_appleWebKit%2F5.0 (Windows NT 6.1; WOW64; Tridential/Volkswagen_liver.ru/catalog/topic,8081e.21152007881277.0&he=768&wi=13625857912233596767_dumalu\",1\n", + "\"http://stalker-pub-20087898675494,960948/#page_type%3D260117152337&spn=1395,9455989.ya.ru/world/photo=1&search?text=маша грибыльские приборы&ch=utf-8&sF=11,7,700&aN=Netscape&aV=9.80 (Windole.ru/cinema/artiru-Podgotovim-doma.ru/real\",1\n", + "\"http://stalker-pub-20087898675494,960948/#page_type%3D260117152337&spn=1395,9455989.ya.ru/workman/krasnodar.pulscen.ru/bios.html5/v12/?from]=&int[153][from]=&input_city=0&page=4&marka=0&po_yers=20073192641#/view_type%3D0%26aktion/russinsk/details/?cat_number\",1\n", + "\n", + "Polars time: 0.726616382598877\n", + "Polars return:\n", + " shape: (10, 2)\n", + "┌─────────────────────────────────┬───────────┐\n", + "│ URL ┆ PageViews │\n", + "│ --- ┆ --- │\n", + "│ str ┆ u32 │\n", + "╞═════════════════════════════════╪═══════════╡\n", + "│ http://stalker-pub-20087898675… ┆ 1 │\n", + "│ http://smeshariki.ru/cated_cou… ┆ 1 │\n", + "│ http://wildberries.aspx#locati… ┆ 1 │\n", + "│ http://stalker-pub-20087898675… ┆ 1 │\n", + "│ http://wildberries.aspx#locati… ┆ 1 │\n", + "│ http://stalker-pub-20087898675… ┆ 1 │\n", + "│ http://maps#ru_5_ru_227_ru_363… ┆ 1 │\n", + "│ http://stalker-pub-20087898675… ┆ 1 │\n", + "│ http://stalker-pub-20087898675… ┆ 1 │\n", + "│ http://irr.ru/index.php?showal… ┆ 1 │\n", + "└─────────────────────────────────┴───────────┘\n", + "Q39 SELECT TraficSourceID, SearchEngineID, AdvEngineID, CASE WHEN (SearchEngineID = 0 AND AdvEngineID = 0) THEN Referer ELSE '' END AS Src, URL AS Dst, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 GROUP BY TraficSourceID, SearchEngineID, AdvEngineID, Src, Dst ORDER BY PageViews DESC LIMIT 10 OFFSET 1000;\n", + "Pandas time: 0.654062032699585\n", + "Pandas return:\n", + " Empty DataFrame\n", + "Columns: [TraficSourceID, SearchEngineID, AdvEngineID, Referer, URL, PageViews]\n", + "Index: []\n", + "DuckDB time: 0.13443231582641602\n", + "DuckDB return:\n", + " TraficSourceID SearchEngineID AdvEngineID \\\n", + "0 -1 0 0 \n", + "1 -1 0 0 \n", + "2 0 0 0 \n", + "3 -1 0 0 \n", + "4 -1 0 0 \n", + "5 3 4 0 \n", + "6 -1 0 0 \n", + "7 1 0 0 \n", + "8 -1 0 0 \n", + "9 -1 0 0 \n", + "\n", + " Src \\\n", + "0 http://kinopoisk.ru/?state \n", + "1 http://state=19945206/foto-4/login-2006/makumi... \n", + "2 \n", + "3 http://state=19945206/foto-4/login-2491724/?bu... \n", + "4 http://state=19945206/foto-4/login-2491724/?bu... \n", + "5 \n", + "6 http://state=19945206/foto-4/login-2491724/?bu... \n", + "7 http://kinopoisk.ru/offer/rative-english \n", + "8 http://state=19945206/foto-4/login-2491724/?bu... \n", + "9 http://state=19945206/foto-4/login-2006/makumi... \n", + "\n", + " Dst PageViews \n", + "0 http://irr.ru/index.php?showalbum/login-kapust... 5 \n", + "1 http://irr.ru/index.php?showalbum/login-leniya... 5 \n", + "2 http://irr.ru/index.php?showalbum/login-kapust... 5 \n", + "3 http://irr.ru/index.php?showalbum/login-tatars... 5 \n", + "4 http://irr.ru/index.php?showalbum/login-kapust... 5 \n", + "5 http://komme%2F27.0.1453.116 5 \n", + "6 http://irr.ru/index.php?showalbum/login-kapust... 5 \n", + "7 http://komme%2F27.0.1453.116 Safari%2F5.0 (com... 5 \n", + "8 http://irr.ru/index.php?showalbum/login-kapust... 5 \n", + "9 http://irr.ru/index.php?showalbum/login-leniya... 5 \n", + "chDB time: 0.1535947322845459\n", + "chDB return:\n", + " -1,0,0,\"http://state=19945206/foto-4/login-2491724/?bundlers/search?text\",\"http://irr.ru/index.php?showalbum/login-kapusta-advert2760798712/27000&categoriya%2Ffieiiervices\",5\n", + "0,0,0,\"\",\"http://irr.ru/index.php?showalbum/login-kapusta-advert278888885%26bn%3D0%26ad%3D2%26nid%3DBSf_Y\",5\n", + "-1,0,0,\"http://state=19945206/foto-4/login-2006/makumirostova.rambler.ru/malding_max=250&sz=waterior\",\"http://irr.ru/index.php?showalbum/login-kapusta-advert2631920&lo=http:%2F%2Fwwww\",5\n", + "-1,0,0,\"http://state=19945206/foto-4/login-bikini-02-19458%26key%3D72673810274&price=1&wr=0&matchen/перевосход\",\"http://irr.ru/index.php?showalbum/login-kapustic/product_name\",5\n", + "0,0,0,\"\",\"http://irr.ru/index.php?showalbum/login-kapusta-advert2792648/?cat=55.01.2013-07-04/2/womenskaia\",5\n", + "-1,0,0,\"http://state=19945206/foto-4/login-kurtka-album/loginInvNww&bvm=bv.48705608,d.bGE&cad=rja&sqi=2&ved=0CDoQFjAA&url=http://saint-petersburg and togets/yandex.ru/Web/PageSplit=&isgray=KW&marka=23&parking_card-2.aspx?group\",\"http://irr.ru/index.php?showalbum/login-kapusta-advert2728549/region=308#postered/main.asp?dom=5009\",5\n", + "-1,0,0,\"http://state=19945206/foto-4/login-2006/makumirosomahachka/saledParam\",\"http://irr.ru/index.php?showalbum/login-kapusta-advert26930&pt=b&pd=6&pvno=2&evlg=VC,6;VL,235,0\",5\n", + "5,0,0,\"http://kinopoisk.ru/?state\",\"http://lib.ru/exp?sid=3205&bt=7&bn\",5\n", + "-1,0,0,\"http://state=19945206/foto-4/login_airbag=&source=web&cd=1&ved=0CC4QFjABOAo&url=http://yands][0]=смали из шоу смотреть онлайн 2013-06-00-0/0/movie//holodilnik.ru/catalog/2894/page37/?date&y1=20&text=словинки на дачу&source=web&cd=4&maxpriceMax=20000 до 5000&price=&all=1&redirect.yandex.ru/user=asc&pagead/ads/sanitary_id=0&only_owners=0&price=от 14003119c05cb506bb0af0b7e4d46345f3666&price=&built_info/node/226595?analogmineer.ru/real-estate/rent/page2/add/adset=userrova71\",\"http://irr.ru/index.php?showalbum/login&tag=video.yandex.ru/regular&bid=3205&bt=7&bn=1&bc=3&ct=1&pr=4433714.last_autodoc.ru/sort=actures/year=2&auto_id=1156&station&op_product&op_product_brand=BODYFLIRT - bonprix.ru/filmId=5MBbVszf9xc&where=all&text=нло аллак.html%3Fhtml?1=1&cmguide.trashbox.ru/search/d-1/foto.ashx/1014;IC,4896991269.html%3Fhtml?brand=bpc bonprix.ru/ency=1#country=&op_page1=18&model.ru/search?text§ion=20268639709948.html?1=1&cid=577&oki=1\",5\n", + "-1,0,0,\"http://state=19945206/foto-4/login-2006/makumirostova.ru/cars/passe/1/2/men/waterinburg.irr\",\"http://irr.ru/index.php?showalbum/login-leniya7777294,938303130\",5\n", + "\n", + "Polars time: 9.5367431640625e-07\n", + "Polars return:\n", + " None\n", + "Q40 SELECT URLHash, EventDate, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 AND TraficSourceID IN (-1, 6) AND RefererHash = 3594120000172545465 GROUP BY URLHash, EventDate ORDER BY PageViews DESC LIMIT 10 OFFSET 100;\n", + "Pandas time: 0.14491891860961914\n", + "Pandas return:\n", + " Empty DataFrame\n", + "Columns: [URLHash, EventDate, PageViews]\n", + "Index: []\n", + "DuckDB time: 0.05103349685668945\n", + "DuckDB return:\n", + " URLHash EventDate PageViews\n", + "0 -1802686817589810185 2013-07-15 10\n", + "1 -2136824408703480407 2013-07-15 10\n", + "2 -2900068695914218823 2013-07-15 10\n", + "3 -3334426674884931276 2013-07-15 10\n", + "4 7745798256146114954 2013-07-15 10\n", + "5 5607000794197120606 2013-07-15 10\n", + "6 6873670041144843393 2013-07-15 10\n", + "7 650616115218363097 2013-07-15 10\n", + "8 -7564973518176820847 2013-07-15 10\n", + "9 -5974687391226976818 2013-07-15 10\n", + "chDB time: 0.07001781463623047\n", + "chDB return:\n", + " 650616115218363097,\"2013-07-15 08:00:00.000000000\",10\n", + "1518554308732023915,\"2013-07-15 08:00:00.000000000\",10\n", + "1285560673132798759,\"2013-07-15 08:00:00.000000000\",10\n", + "-7564973518176820847,\"2013-07-15 08:00:00.000000000\",10\n", + "5607000794197120606,\"2013-07-15 08:00:00.000000000\",10\n", + "7459640648655452865,\"2013-07-15 08:00:00.000000000\",10\n", + "7745798256146114954,\"2013-07-15 08:00:00.000000000\",10\n", + "-3451071041994192989,\"2013-07-15 08:00:00.000000000\",10\n", + "-573217089863865205,\"2013-07-15 08:00:00.000000000\",10\n", + "5533436450043627195,\"2013-07-15 08:00:00.000000000\",10\n", + "\n", + "Polars time: 0.23132848739624023\n", + "Polars return:\n", + " shape: (10, 3)\n", + "┌──────────────────────┬─────────────────────┬───────────┐\n", + "│ URLHash ┆ EventDate ┆ PageViews │\n", + "│ --- ┆ --- ┆ --- │\n", + "│ i64 ┆ datetime[ns] ┆ u32 │\n", + "╞══════════════════════╪═════════════════════╪═══════════╡\n", + "│ 9117416179998756751 ┆ 2013-07-15 00:00:00 ┆ 10 │\n", + "│ 6061487698837678125 ┆ 2013-07-15 00:00:00 ┆ 10 │\n", + "│ 1518554308732023915 ┆ 2013-07-15 00:00:00 ┆ 10 │\n", + "│ 2465537114496173148 ┆ 2013-07-15 00:00:00 ┆ 10 │\n", + "│ -2900068695914218823 ┆ 2013-07-15 00:00:00 ┆ 10 │\n", + "│ 5533436450043627195 ┆ 2013-07-15 00:00:00 ┆ 10 │\n", + "│ -1802686817589810185 ┆ 2013-07-15 00:00:00 ┆ 10 │\n", + "│ 7459640648655452865 ┆ 2013-07-15 00:00:00 ┆ 10 │\n", + "│ -3334426674884931276 ┆ 2013-07-15 00:00:00 ┆ 10 │\n", + "│ 6873670041144843393 ┆ 2013-07-15 00:00:00 ┆ 10 │\n", + "└──────────────────────┴─────────────────────┴───────────┘\n", + "Q41 SELECT WindowClientWidth, WindowClientHeight, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 AND DontCountHits = 0 AND URLHash = 2868770270353813622 GROUP BY WindowClientWidth, WindowClientHeight ORDER BY PageViews DESC LIMIT 10 OFFSET 10000;\n", + "Pandas time: 0.07189512252807617\n", + "Pandas return:\n", + " Empty DataFrame\n", + "Columns: [WindowClientWidth, WindowClientHeight, PageViews]\n", + "Index: []\n", + "DuckDB time: 0.05136418342590332\n", + "DuckDB return:\n", + " Empty DataFrame\n", + "Columns: [WindowClientWidth, WindowClientHeight, PageViews]\n", + "Index: []\n", + "chDB time: 0.06618666648864746\n", + "chDB return:\n", + " \n", + "Polars time: 0.0189208984375\n", + "Polars return:\n", + " shape: (0, 3)\n", + "┌───────────────────┬────────────────────┬───────────┐\n", + "│ WindowClientWidth ┆ WindowClientHeight ┆ PageViews │\n", + "│ --- ┆ --- ┆ --- │\n", + "│ i16 ┆ i16 ┆ u32 │\n", + "╞═══════════════════╪════════════════════╪═══════════╡\n", + "└───────────────────┴────────────────────┴───────────┘\n", + "Q42 SELECT DATE_TRUNC('minute', EventTime) AS M, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-14' AND EventDate <= '2013-07-15' AND IsRefresh = 0 AND DontCountHits = 0 GROUP BY DATE_TRUNC('minute', EventTime) ORDER BY DATE_TRUNC('minute', EventTime) LIMIT 10 OFFSET 1000;\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_873169/4080565043.py:731: FutureWarning: 'T' is deprecated and will be removed in a future version, please use 'min' instead.\n", + " .groupby(pd.Grouper(key=\"EventTime\", freq=\"T\"))\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Pandas time: 0.18853545188903809\n", + "Pandas return:\n", + " EventTime PageViews\n", + "1000 2013-07-15 12:40:00 59\n", + "1001 2013-07-15 12:41:00 57\n", + "1002 2013-07-15 12:42:00 77\n", + "1003 2013-07-15 12:43:00 56\n", + "1004 2013-07-15 12:44:00 46\n", + "1005 2013-07-15 12:45:00 51\n", + "1006 2013-07-15 12:46:00 62\n", + "1007 2013-07-15 12:47:00 90\n", + "1008 2013-07-15 12:48:00 90\n", + "1009 2013-07-15 12:49:00 80\n", + "DuckDB time: 0.05023622512817383\n", + "DuckDB return:\n", + " M PageViews\n", + "0 2013-07-15 12:40:00 59\n", + "1 2013-07-15 12:41:00 57\n", + "2 2013-07-15 12:42:00 77\n", + "3 2013-07-15 12:43:00 56\n", + "4 2013-07-15 12:44:00 46\n", + "5 2013-07-15 12:45:00 51\n", + "6 2013-07-15 12:46:00 62\n", + "7 2013-07-15 12:47:00 90\n", + "8 2013-07-15 12:48:00 90\n", + "9 2013-07-15 12:49:00 80\n", + "chDB time: 0.052018165588378906\n", + "chDB return:\n", + " \n", + "Polars time: 9.5367431640625e-07\n", + "Polars return:\n", + " None\n" ] } ], @@ -2945,149 +3509,56 @@ "\n", "counter = 0\n", "for q in queries:\n", - " duckdb_time, chdb_time, pandas_time, polars_time = bench(q)\n", - " # remove the min/max time, take the average time\n", - " if len(duckdb_time) > 2:\n", - " duckdb_time = sorted(duckdb_time)[1:-1]\n", - " chdb_time = sorted(chdb_time)[1:-1]\n", - " pandas_time = sorted(pandas_time)[1:-1]\n", - " polars_time = sorted(polars_time)[1:-1]\n", + " duckdb_time, chdb_time, pandas_time, polars_time = bench(q, N=1)\n", "\n", - " duckdb_times.append(sum(duckdb_time) / len(duckdb_time))\n", - " chdb_times.append(sum(chdb_time) / len(chdb_time))\n", - " pandas_times.append(sum(pandas_time) / len(pandas_time))\n", - " polars_times.append(sum(polars_time) / len(polars_time))" + " duckdb_times.append(duckdb_time)\n", + " chdb_times.append(chdb_time)\n", + " pandas_times.append(pandas_time)\n", + " polars_times.append(polars_time)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "DuckDB times: [[0.03473329544067383], [0.025869369506835938], [0.02449941635131836], [0.021502971649169922], [0.07661056518554688], [0.11784601211547852], [0.023169994354248047], [0.041997432708740234], [0.08279561996459961], [0.12752676010131836], [0.049619197845458984], [0.05812263488769531], [0.10427713394165039], [0.16024351119995117], [0.12470531463623047], [0.07800555229187012], [0.14101672172546387], [0.13824796676635742], [0.19573760032653809], [0.04209160804748535], [0.12423968315124512], [0.13030076026916504], [0.23919463157653809], [0.4751307964324951], [0.16602039337158203], [0.23991131782531738], [0.19497394561767578], [0.14258074760437012], [0.37261152267456055], [0.3752312660217285], [0.08300089836120605], [0.10579490661621094], [0.2147054672241211], [0.2616574764251709], [0.21707653999328613], [0.1144096851348877], [0.0702214241027832], [0.15410351753234863], [0.04920172691345215], [0.13008761405944824], [0.04686141014099121], [0.04792666435241699], [0.04334378242492676]]\n", - "chDB times: [[0.06221914291381836], [0.027338027954101562], [0.02335381507873535], [0.024204492568969727], [0.15731096267700195], [0.148162841796875], [0.02401590347290039], [0.05284929275512695], [0.08579301834106445], [0.09726285934448242], [0.09742522239685059], [0.05577349662780762], [0.12464475631713867], [0.12720394134521484], [0.11488032341003418], [0.0947573184967041], [0.1408531665802002], [0.12751054763793945], [0.19252252578735352], [0.025123119354248047], [0.1013326644897461], [0.1148073673248291], [0.17513012886047363], [0.4328289031982422], [0.05282235145568848], [0.03336310386657715], [0.060570478439331055], [0.13329815864562988], [0.3007791042327881], [0.05272984504699707], [0.05916261672973633], [0.08487057685852051], [0.20470118522644043], [0.21042490005493164], [0.1943037509918213], [0.07967042922973633], [0.10769414901733398], [0.14104270935058594], [0.11770820617675781], [0.1456921100616455], [0.07047486305236816], [0.06691765785217285], [0.05282926559448242]]\n", - "Pandas times: [[8.810486316680908], [0.18511605262756348], [0.007769346237182617], [0.007940053939819336], [0.2557411193847656], [0.6752357482910156], [0.020006418228149414], [0.07879805564880371], [0.6391797065734863], [0.7415461540222168], [0.8452174663543701], [0.8568341732025146], [2.7391467094421387], [2.740976333618164], [8.468678712844849], [0.808772087097168], [25.723305225372314], [2.8686487674713135], [54.3118736743927], [0.006058454513549805], [2.172792434692383], [2.5811095237731934], [10.12513256072998], [2.172769784927368], [2.291555881500244], [3.873861789703369], [4.094628095626831], [11.906651496887207], [30.80293369293213], [3.698624849319458], [1.5433671474456787], [1.97343111038208], [7.936391353607178], [8.008706092834473], [7.5324859619140625], [32.06308960914612], [0.7074093818664551], [0.6838343143463135], [0.05820012092590332], [0.6777045726776123], [0.14009356498718262], [0.07429075241088867], [0.27022314071655273]]\n", - "Polars times: [[1.9073486328125e-05], [0.02214503288269043], [0.03725171089172363], [0.0027332305908203125], [0.14108967781066895], [0.30224037170410156], [0.006073951721191406], [-1.0], [0.25276756286621094], [0.2742159366607666], [0.11061525344848633], [0.10920023918151855], [-1.0], [22.80822205543518], [-1.0], [-1.0], [-1.0], [0.11651134490966797], [-1.0], [0.004508018493652344], [0.1802678108215332], [-1.0], [-1.0], [0.18322491645812988], [0.267641544342041], [0.2900557518005371], [0.2738926410675049], [0.8539285659790039], [6.305335283279419], [0.0001761913299560547], [0.23777556419372559], [0.28878021240234375], [0.5600228309631348], [0.18396663665771484], [0.1676928997039795], [0.07762742042541504], [2.0668680667877197], [1.8747799396514893], [0.7213089466094971], [1.001046895980835], [0.22947144508361816], [0.020848989486694336], [1.0009913444519043]]\n", - "DuckDB faster count: 15\n", - "chDB faster count: 24\n", - "Pandas faster count: 4\n", - "Polars faster count: 0\n", - "DuckDB total time: 5.667204856872559\n", - "chDB total time: 4.796359300613403\n", - "Pandas total time: 246.18061780929565\n", - "Polars total time: 32.973297357559204\n" + "{\"DuckDB\": [[0.03433990478515625], [0.026508569717407227], [0.02513861656188965], [0.021852970123291016], [0.07819533348083496], [0.08364367485046387], [0.024533987045288086], [0.046100616455078125], [0.09088969230651855], [0.12663817405700684], [0.052741050720214844], [0.0588836669921875], [0.09914731979370117], [0.1588895320892334], [0.10474276542663574], [0.08089947700500488], [0.14031195640563965], [0.14226555824279785], [0.2024822235107422], [0.02909088134765625], [0.12494659423828125], [0.12578415870666504], [0.23342061042785645], [0.47556400299072266], [0.1318378448486328], [0.2535984516143799], [0.18941974639892578], [0.1553800106048584], [0.5170934200286865], [0.20304656028747559], [0.08614468574523926], [0.10591721534729004], [0.20980262756347656], [0.1876978874206543], [0.18941712379455566], [0.10219049453735352], [0.05800819396972656], [0.1615283489227295], [0.04982304573059082], [0.13443231582641602], [0.05103349685668945], [0.05136418342590332], [0.05023622512817383]], \"chDB\": [[0.06516456604003906], [0.027498722076416016], [0.02389240264892578], [0.026594877243041992], [0.18276023864746094], [0.1492304801940918], [0.025769948959350586], [0.054378509521484375], [0.08289217948913574], [0.09233450889587402], [0.09442925453186035], [0.05849885940551758], [0.12346029281616211], [0.11397171020507812], [0.10899591445922852], [0.08938097953796387], [0.15292119979858398], [0.1154947280883789], [0.195556640625], [0.023262739181518555], [0.08678507804870605], [0.11338138580322266], [0.18370819091796875], [0.4304678440093994], [0.0423429012298584], [0.03441929817199707], [0.046121835708618164], [0.14062786102294922], [0.2968788146972656], [0.05274057388305664], [0.06468677520751953], [0.09296727180480957], [0.20761418342590332], [0.21751952171325684], [0.19516444206237793], [0.08132767677307129], [0.10596656799316406], [0.14129924774169922], [0.12198710441589355], [0.1535947322845459], [0.07001781463623047], [0.06618666648864746], [0.052018165588378906]], \"Pandas\": [[8.789468765258789], [0.16229581832885742], [0.007686138153076172], [0.007529735565185547], [0.21137714385986328], [0.6686234474182129], [0.02013540267944336], [0.07054853439331055], [0.5789997577667236], [0.6821517944335938], [0.839637279510498], [0.8696815967559814], [2.7713074684143066], [2.760340929031372], [8.411752223968506], [0.7016208171844482], [25.73132586479187], [2.7518060207366943], [54.36725902557373], [0.0063283443450927734], [2.1297006607055664], [2.5472168922424316], [8.950557470321655], [2.123731851577759], [2.3252789974212646], [3.9367663860321045], [4.12407112121582], [11.973230361938477], [30.965622425079346], [2.758824586868286], [1.535578966140747], [1.996917963027954], [7.862155199050903], [7.771429538726807], [7.3071815967559814], [32.501299142837524], [0.7082381248474121], [0.6800808906555176], [0.05269670486450195], [0.654062032699585], [0.14491891860961914], 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[null]]}\n" ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", + "import json\n", "\n", - "print(\"DuckDB times:\", [[t] for t in duckdb_times])\n", - "print(\"chDB times:\", [[t] for t in chdb_times])\n", - "print(\"Pandas times:\", [[t] for t in pandas_times])\n", - "print(\"Polars times:\", [[t] for t in polars_times])\n", - "\n", - "x = range(len(queries))\n", - "xlable = [f\"Q{num}\" for num in x]\n", - "width = 0.2\n", - "\n", - "fig, ax = plt.subplots(figsize=(10, 6), dpi=300)\n", - "\n", - "rects1 = ax.bar(x, duckdb_times, width, label=\"DuckDB\")\n", - "rects2 = ax.bar([i + width for i in x], chdb_times, width, label=\"chDB\")\n", - "rects3 = ax.bar([i + 2 * width for i in x], pandas_times, width, label=\"Pandas\")\n", - "rects4 = ax.bar([i + 3 * width for i in x], polars_times, width, label=\"Polars\")\n", - "\n", - "ax.set_ylabel(\"Time (s)\")\n", - "# ax.set_ylim(0, max(chdb_times) * 1.1)\n", - "ax.set_title(f\"SQL on DataFrame Benchmark Results on {hits.shape[0]} rows of ClickBench\")\n", - "ax.set_xticks([i + width / 2 for i in x])\n", - "ax.set_xticklabels(xlable, rotation=90)\n", - "ax.legend()\n", - "\n", - "# Add the value of each bar on top\n", - "for rect in rects1 + rects2 + rects3 + rects4:\n", - " height = rect.get_height()\n", - " ax.annotate(\n", - " f\"{height:.2f}\",\n", - " xy=(rect.get_x() + rect.get_width() / 2, height),\n", - " xytext=(0, 3),\n", - " textcoords=\"offset points\",\n", - " ha=\"center\",\n", - " va=\"bottom\",\n", - " rotation=90, # Rotate the text 90°\n", - " fontsize=5, # Set the font size to a smaller value\n", - " )\n", - "\n", - "# Compute comparison counts and total times\n", - "better = []\n", - "for i in range(len(queries)):\n", - " min_val = min(duckdb_times[i], chdb_times[i], pandas_times[i])\n", - " if min_val == duckdb_times[i]:\n", - " better.append(\"DuckDB\")\n", - " elif min_val == chdb_times[i]:\n", - " better.append(\"chDB\")\n", - " elif min_val == pandas_times[i]:\n", - " better.append(\"Pandas\")\n", - " elif min_val == polars_times[i]:\n", - " better.append(\"Polars\")\n", - " else:\n", - " better.append(\"Unknown\")\n", - "print(\"DuckDB faster count:\", better.count(\"DuckDB\"))\n", - "print(\"chDB faster count:\", better.count(\"chDB\"))\n", - "print(\"Pandas faster count:\", better.count(\"Pandas\"))\n", - "print(\"Polars faster count:\", better.count(\"Polars\"))\n", - "print(\"DuckDB total time:\", sum(duckdb_times))\n", - "print(\"chDB total time:\", sum(chdb_times))\n", - "print(\"Pandas total time:\", sum(pandas_times))\n", - "print(\"Polars total time:\", sum(polars_times))\n", - "\n", - "\n", - "# Display summary statistics on the plot\n", - "summary_text = f\"Pandas faster count: {better.count('Pandas')}\\n\"\n", - "summary_text += f\"chDB faster count: {better.count('chDB')}\\n\"\n", - "summary_text += f\"DuckDB faster count: {better.count('DuckDB')}\\n\"\n", - "summary_text += f\"Polars faster count: {better.count('Polars')}\\n\\n\"\n", - "summary_text += f\"Pandas total time: {sum(pandas_times):.2f} s\\n\"\n", - "summary_text += f\"chDB total time: {sum(chdb_times):.2f} s\\n\"\n", - "summary_text += f\"DuckDB total time: {sum(duckdb_times):.2f} s\\n\"\n", - "summary_text += f\"Polars total time: {sum(polars_times):.2f} s\\n\\n\"\n", + "data_map = {\n", + " \"DuckDB\": duckdb_times,\n", + " \"chDB\": chdb_times,\n", + " \"Pandas\": pandas_times,\n", + " \"Polars\": polars_times,\n", + "}\n", + "print(json.dumps(data_map))\n", "\n", - "summary_text += (\n", - " f\"Pandas time range: {min(pandas_times):.2f} ~ {max(pandas_times):.2f} s\\n\"\n", - ")\n", - "summary_text += f\"chDB time range: {min(chdb_times):.2f} ~ {max(chdb_times):.2f} s\\n\"\n", - "summary_text += f\"DuckDB time range: {min(duckdb_times):.2f} ~ {max(duckdb_times):.2f} s\\n\"\n", - "summary_text += f\"Polars time range: {min(polars_times):.2f} ~ {max(polars_times):.2f} s\"\n", + "data_tpl = {\"system\": None,\"date\":\"2024-02-05\",\"machine\":\"EPYC 9654, 128G, 4TB\",\"cluster_size\":1,\"tags\":[\"C++\",\"column-oriented\",\"Pandas Compatible\"],\"load_time\":0,\"data_size\":922699018,\"result\": None,\"source\":\"\"}\n", "\n", - "# Position the text at the top right of the chart\n", - "ax.text(\n", - " 0.02,\n", - " 0.98,\n", - " summary_text,\n", - " transform=ax.transAxes,\n", - " fontsize=8,\n", - " verticalalignment=\"top\",\n", - " horizontalalignment=\"left\",\n", - " fontfamily=\"monospace\",\n", - ")\n", + "data_to_render = []\n", + "for k, v in data_map.items():\n", + " data = data_tpl.copy()\n", + " data[\"system\"] = k\n", + " data[\"result\"] = v\n", + " data[\"date\"] = datetime.datetime.now().strftime(\"%Y-%m-%d\")\n", + " if k == \"Polars\":\n", + " data[\"load_time\"] = pl_load_time\n", + " data_to_render.append(data)\n", "\n", - "fig.tight_layout()\n", - "plt.show()" + "with open(\"/auxten/chdb/benchmark/cb_index.html.tpl\", \"r\") as f:\n", + " html = f.read()\n", + " html = html.replace(\"DATA_PLACEHOLDER\", f\"const data = {json.dumps(data_to_render)};\")\n", + " with open(\"/auxten/chdb/benchmark/cb_index.html\", \"w\") as f:\n", + " f.write(html)" ] } ], From f184f585ad931deff628aad872995571940282d5 Mon Sep 17 00:00:00 2001 From: auxten Date: Mon, 19 Aug 2024 18:04:42 +0800 Subject: [PATCH 13/16] Set max_thread_pool_free_size to 1000 --- programs/local/LocalServer.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/programs/local/LocalServer.cpp b/programs/local/LocalServer.cpp index 4c900be18ab..32c40a95364 100644 --- a/programs/local/LocalServer.cpp +++ b/programs/local/LocalServer.cpp @@ -136,7 +136,7 @@ void LocalServer::initialize(Poco::Util::Application & self) GlobalThreadPool::initialize( config().getUInt("max_thread_pool_size", std::max(getNumberOfPhysicalCPUCores(), 1024u)), - config().getUInt("max_thread_pool_free_size", 0), + config().getUInt("max_thread_pool_free_size", 1000), config().getUInt("thread_pool_queue_size", 10000)); #if USE_AZURE_BLOB_STORAGE From b40660638286e470e0fb4ad087711a9ef027ab08 Mon Sep 17 00:00:00 2001 From: auxten Date: Thu, 22 Aug 2024 16:58:25 +0800 Subject: [PATCH 14/16] Fix NaN and complex object type handling --- src/Processors/Sources/PythonSource.cpp | 52 ++++++++++++++++++++++--- src/Processors/Sources/PythonSource.h | 1 + 2 files changed, 48 insertions(+), 5 deletions(-) diff --git a/src/Processors/Sources/PythonSource.cpp b/src/Processors/Sources/PythonSource.cpp index 25f4f0ebf04..fc96a80ef9f 100644 --- a/src/Processors/Sources/PythonSource.cpp +++ b/src/Processors/Sources/PythonSource.cpp @@ -1,4 +1,5 @@ #include +#include "object.h" #if USE_PYTHON #include @@ -113,6 +114,13 @@ void PythonSource::insert_string_from_array_raw( for (size_t i = offset; i < offset + row_count; ++i) { size_t str_len; + auto * obj = buf[i]; + if (!PyUnicode_Check(obj)) + { + insert_obj_to_string_column(obj, static_cast(column.get())); + continue; + } + const char * ptr = GetPyUtf8StrData(buf[i], str_len); column->insertData(ptr, str_len); } @@ -132,11 +140,8 @@ void PythonSource::convert_string_array_to_block( auto * obj = buf[i]; if (!PyUnicode_Check(obj)) { - LOG_ERROR( - logger, - "Unsupported Python object type {}, Unicode string expected here. Try convert column type to str with `astype(str)`", - Py_TYPE(obj)->tp_name); - throw Exception(ErrorCodes::BAD_TYPE_OF_FIELD, "Unsupported Python object type {}", Py_TYPE(obj)->tp_name); + insert_obj_to_string_column(obj, string_column); + continue; } FillColumnString(obj, string_column); // Try to help reserve memory for the string column data every 100 rows to avoid frequent reallocations @@ -157,6 +162,43 @@ void PythonSource::convert_string_array_to_block( } } +void PythonSource::insert_obj_to_string_column(PyObject * obj, ColumnString * string_column) +{ + // check if the object is NaN + if (PyFloat_Check(obj) && Py_IS_NAN(PyFloat_AS_DOUBLE(obj))) + { + // insert default value for string column, which is empty string + string_column->insertDefault(); + return; + } + // if object is list, tuple, or dict, convert it to json string + if (PyList_Check(obj) || PyTuple_Check(obj) || PyDict_Check(obj)) + { + py::gil_scoped_acquire acquire; + std::string str = py::module::import("json").attr("dumps")(py::reinterpret_borrow(obj)).cast(); + string_column->insertData(str.data(), str.size()); + return; + } + // try convert the object to string + try + { + py::gil_scoped_acquire acquire; + std::string str = py::str(obj); + string_column->insertData(str.data(), str.size()); + return; + } + catch (const py::error_already_set & e) + { + LOG_ERROR( + logger, + "Error converting Python object {} to string: {}, Unicode string expected here. Try convert column type to str with " + "`astype(str)`", + Py_TYPE(obj)->tp_name, + e.what()); + throw Exception(ErrorCodes::BAD_TYPE_OF_FIELD, "Error converting Python object {} to string: {}", Py_TYPE(obj)->tp_name, e.what()); + } +} + template void PythonSource::insert_from_ptr(const void * ptr, const MutableColumnPtr & column, const size_t offset, const size_t row_count) { diff --git a/src/Processors/Sources/PythonSource.h b/src/Processors/Sources/PythonSource.h index 2e71f25f058..c210020db9e 100644 --- a/src/Processors/Sources/PythonSource.h +++ b/src/Processors/Sources/PythonSource.h @@ -68,6 +68,7 @@ class PythonSource : public ISource void convert_string_array_to_block(PyObject ** buf, const MutableColumnPtr & column, size_t offset, size_t row_count); + void insert_obj_to_string_column(PyObject * obj, ColumnString * string_column); template void insert_from_list(const py::list & obj, const MutableColumnPtr & column); From fc43fda85c4ddd5c4fa4c41670f52a8f3b2f7464 Mon Sep 17 00:00:00 2001 From: auxten Date: Thu, 22 Aug 2024 16:58:58 +0800 Subject: [PATCH 15/16] Test for NaN and complex type handling --- tests/test_complex_pyobj.py | 79 +++++++++++++++++++++++++++++++++++++ 1 file changed, 79 insertions(+) create mode 100644 tests/test_complex_pyobj.py diff --git a/tests/test_complex_pyobj.py b/tests/test_complex_pyobj.py new file mode 100644 index 00000000000..241fffc0105 --- /dev/null +++ b/tests/test_complex_pyobj.py @@ -0,0 +1,79 @@ +import unittest +import pandas as pd +import chdb + +df_with_na = pd.DataFrame( + { + "A": [1, 2, 3, pd.NA], + "B": [4.0, 5.0, 6.0, pd.NA], + "C": [True, False, True, pd.NA], + "D": ["a", "b", "c", pd.NA], + "E": [pd.NA, pd.NA, pd.NA, pd.NA], + "F": [[1, 2], [3, 4], [5, 6], pd.NA], + "G": [{"a": 1, "b": 2}, {"c": 3, "d": 4}, {"e": 5, "f": 6}, pd.NA], + } +) + +df_without_na = pd.DataFrame( + { + "A": [1, 2, 3, 4], + "B": [4.0, 5.0, 6.0, 7.0], + "C": [True, False, True, False], + "D": ["a", "b", "c", "d"], + "E": ["a", "b", "c", "d"], + "F": [[1, 2], [3, 4], [5, 6], [7, 8]], + "G": [{"a": 1, "b": 2}, {"c": 3, "d": 4}, {"e": 5, "f": 6}, {"g": 7, "h": 8}], + } +) + + +class TestComplexPyObj(unittest.TestCase): + def test_df_with_na(self): + ret = chdb.query( + """ + select * from Python(df_with_na) limit 10 + """, + "dataframe", + ) + self.assertEqual(ret.dtypes["A"], "object") + self.assertEqual(ret.dtypes["B"], "object") + self.assertEqual(ret.dtypes["C"], "object") + self.assertEqual(ret.dtypes["D"], "object") + self.assertEqual(ret.dtypes["E"], "object") + self.assertEqual(ret.dtypes["F"], "object") + self.assertEqual(ret.dtypes["G"], "object") + self.assertEqual( + str(ret), + """ A B C D E F G +0 1 4.0 True a [1, 2] {"a": 1, "b": 2} +1 2 5.0 False b [3, 4] {"c": 3, "d": 4} +2 3 6.0 True c [5, 6] {"e": 5, "f": 6} +3 """, + ) + + def test_df_without_na(self): + ret = chdb.query( + """ + select * from Python(df_without_na) limit 10 + """, + "dataframe", + ) + self.assertEqual(ret.dtypes["A"], "int64") + self.assertEqual(ret.dtypes["B"], "float64") + self.assertEqual(ret.dtypes["C"], "uint8") + self.assertEqual(ret.dtypes["D"], "object") + self.assertEqual(ret.dtypes["E"], "object") + self.assertEqual(ret.dtypes["F"], "object") + self.assertEqual(ret.dtypes["G"], "object") + self.assertEqual( + str(ret), + """ A B C D E F G +0 1 4.0 1 a a [1, 2] {"a": 1, "b": 2} +1 2 5.0 0 b b [3, 4] {"c": 3, "d": 4} +2 3 6.0 1 c c [5, 6] {"e": 5, "f": 6} +3 4 7.0 0 d d [7, 8] {"g": 7, "h": 8}""", + ) + + +if __name__ == "__main__": + unittest.main() From 3c8cd64399e2197019f428f67f6408bf57cbd3bf Mon Sep 17 00:00:00 2001 From: auxten Date: Thu, 22 Aug 2024 17:09:50 +0800 Subject: [PATCH 16/16] Fix miss include --- src/Processors/Sources/PythonSource.cpp | 1 - 1 file changed, 1 deletion(-) diff --git a/src/Processors/Sources/PythonSource.cpp b/src/Processors/Sources/PythonSource.cpp index fc96a80ef9f..f62d2069825 100644 --- a/src/Processors/Sources/PythonSource.cpp +++ b/src/Processors/Sources/PythonSource.cpp @@ -1,5 +1,4 @@ #include -#include "object.h" #if USE_PYTHON #include