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PCDM Delta Latest Values to Delta (rtdip#512)
Signed-off-by: GBBBAS <[email protected]>
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docs/sdk/code-reference/pipelines/destinations/spark/pcdm_latest_to_delta.md
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| # Write Process Control Data Model Latest Values to Delta | ||
| ::: src.sdk.python.rtdip_sdk.pipelines.destinations.spark.pcdm_latest_to_delta |
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docs/sdk/code-reference/pipelines/destinations/spark/pcdm_to_delta.md
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| # Write to Delta | ||
| # Write Process Control Data Model to Delta | ||
| ::: src.sdk.python.rtdip_sdk.pipelines.destinations.spark.pcdm_to_delta |
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src/sdk/python/rtdip_sdk/pipelines/destinations/spark/pcdm_latest_to_delta.py
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| # Copyright 2022 RTDIP | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
|
|
||
| import logging | ||
| import time | ||
| from pyspark.sql import DataFrame, SparkSession | ||
| from pyspark.sql.functions import col, when, struct, max | ||
| from pyspark.sql import Window | ||
| from py4j.protocol import Py4JJavaError | ||
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| from ..interfaces import DestinationInterface | ||
| from .delta import SparkDeltaDestination | ||
| from .delta_merge import ( | ||
| SparkDeltaMergeDestination, | ||
| DeltaMergeCondition, | ||
| DeltaMergeConditionValues, | ||
| ) | ||
| from ..._pipeline_utils.models import Libraries, SystemType | ||
| from ..._pipeline_utils.constants import get_default_package | ||
|
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|
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||
| class ValueTypeConstants: | ||
| INTEGER_VALUE = "ValueType = 'integer'" | ||
| FLOAT_VALUE = "ValueType = 'float'" | ||
| STRING_VALUE = "ValueType = 'string'" | ||
|
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|
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| class SparkPCDMLatestToDeltaDestination(DestinationInterface): | ||
| """ | ||
| The Process Control Data Model Latest Values written to Delta | ||
| Args: | ||
| data (DataFrame): Dataframe to be merged into a Delta Table | ||
| options (dict): Options that can be specified for a Delta Table read operation (See Attributes table below). Further information on the options is available for [batch](https://docs.delta.io/latest/delta-batch.html#write-to-a-table){ target="_blank" } and [streaming](https://docs.delta.io/latest/delta-streaming.html#delta-table-as-a-sink){ target="_blank" }. | ||
| destination (str): Either the name of the Hive Metastore or Unity Catalog Delta Table **or** the path to the Delta table to store the latest values | ||
| mode (str): Method of writing to Delta Table - append/overwrite (batch), append/complete (stream) | ||
| trigger (optional str): Frequency of the write operation. Specify "availableNow" to execute a trigger once, otherwise specify a time period such as "30 seconds", "5 minutes". Set to "0 seconds" if you do not want to use a trigger. (stream) Default is 10 seconds | ||
| query_name (str): Unique name for the query in associated SparkSession | ||
| query_wait_interval (optional int): If set, waits for the streaming query to complete before returning. (stream) Default is None | ||
| Attributes: | ||
| checkpointLocation (str): Path to checkpoint files. (Streaming) | ||
| """ | ||
|
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||
| spark: SparkSession | ||
| data: DataFrame | ||
| options: dict | ||
| destination: str | ||
| mode: str | ||
| trigger: str | ||
| query_name: str | ||
| query_wait_interval: int | ||
|
|
||
| def __init__( | ||
| self, | ||
| spark: SparkSession, | ||
| data: DataFrame, | ||
| options: dict, | ||
| destination: str, | ||
| mode: str = None, | ||
| trigger="10 seconds", | ||
| query_name: str = "PCDMLatestToDeltaDestination", | ||
| query_wait_interval: int = None, | ||
| ) -> None: | ||
| self.spark = spark | ||
| self.data = data | ||
| self.destination = destination | ||
| self.options = options | ||
| self.mode = mode | ||
| self.trigger = trigger | ||
| self.query_name = query_name | ||
| self.query_wait_interval = query_wait_interval | ||
|
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||
| @staticmethod | ||
| def system_type(): | ||
| """ | ||
| Attributes: | ||
| SystemType (Environment): Requires PYSPARK | ||
| """ | ||
| return SystemType.PYSPARK | ||
|
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||
| @staticmethod | ||
| def libraries(): | ||
| libraries = Libraries() | ||
| libraries.add_maven_library(get_default_package("spark_delta_core")) | ||
| return libraries | ||
|
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||
| @staticmethod | ||
| def settings() -> dict: | ||
| return {} | ||
|
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| def pre_write_validation(self): | ||
| return True | ||
|
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| def post_write_validation(self): | ||
| return True | ||
|
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| def _write_latest_to_delta(self, df: DataFrame, epoch_id=None): # NOSONAR | ||
| df.persist() | ||
|
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||
| latest_df = ( | ||
| df.withColumn( | ||
| "Latest", | ||
| max(struct("EventTime", "Status")).over(Window.partitionBy("TagName")), | ||
| ) | ||
| .withColumn( | ||
| "GoodLatest", | ||
| when( | ||
| col("Latest.Status") == "Good", | ||
| struct(col("EventTime"), col("Value"), col("ValueType")), | ||
| ).otherwise( | ||
| max( | ||
| when( | ||
| col("Status") == "Good", | ||
| struct("EventTime", "Value", "ValueType"), | ||
| ) | ||
| ).over(Window.partitionBy("TagName")) | ||
| ), | ||
| ) | ||
| .filter(col("EventTime") == col("Latest.EventTime")) | ||
| .drop("Latest") | ||
| .dropDuplicates(["TagName"]) | ||
| ) | ||
|
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| when_matched_update_list = [ | ||
| DeltaMergeConditionValues( | ||
| condition="source.EventTime > target.EventTime", | ||
| values={ | ||
| "EventDate": "source.EventDate", | ||
| "EventTime": "source.EventTime", | ||
| "Status": "source.Status", | ||
| "Value": "source.Value", | ||
| "ValueType": "source.ValueType", | ||
| }, | ||
| ), | ||
| DeltaMergeConditionValues( | ||
| condition="source.GoodLatest.EventTime IS NOT NULL AND source.GoodLatest.EventTime > target.GoodEventTime", | ||
| values={ | ||
| "GoodEventTime": "source.GoodLatest.EventTime", | ||
| "GoodValue": "source.GoodLatest.Value", | ||
| "GoodValueType": "source.GoodLatest.ValueType", | ||
| }, | ||
| ), | ||
| ] | ||
|
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| when_not_matched_insert_list = [ | ||
| DeltaMergeConditionValues( | ||
| values={ | ||
| "EventDate": "source.EventDate", | ||
| "TagName": "source.TagName", | ||
| "EventTime": "source.EventTime", | ||
| "Status": "source.Status", | ||
| "Value": "source.Value", | ||
| "ValueType": "source.ValueType", | ||
| "GoodEventTime": "source.GoodLatest.EventTime", | ||
| "GoodValue": "source.GoodLatest.Value", | ||
| "GoodValueType": "source.GoodLatest.ValueType", | ||
| }, | ||
| ) | ||
| ] | ||
|
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| merge_condition = "source.TagName = target.TagName" | ||
|
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| SparkDeltaMergeDestination( | ||
| spark=self.spark, | ||
| data=latest_df, | ||
| destination=self.destination, | ||
| options=self.options, | ||
| merge_condition=merge_condition, | ||
| when_matched_update_list=when_matched_update_list, | ||
| when_not_matched_insert_list=when_not_matched_insert_list, | ||
| trigger=self.trigger, | ||
| query_name=self.query_name, | ||
| ).write_batch() | ||
|
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| df.unpersist() | ||
|
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| def write_batch(self): | ||
| """ | ||
| Writes Process Control Data Model data to Delta | ||
| """ | ||
| try: | ||
| self._write_latest_to_delta(self.data) | ||
|
|
||
| except Py4JJavaError as e: | ||
| logging.exception(e.errmsg) | ||
| raise e | ||
| except Exception as e: | ||
| logging.exception(str(e)) | ||
| raise e | ||
|
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| def write_stream(self): | ||
| """ | ||
| Writes streaming Process Control Data Model data to Delta using foreachBatch | ||
| """ | ||
| try: | ||
| TRIGGER_OPTION = ( | ||
| {"availableNow": True} | ||
| if self.trigger == "availableNow" | ||
| else {"processingTime": self.trigger} | ||
| ) | ||
|
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| query = ( | ||
| self.data.writeStream.trigger(**TRIGGER_OPTION) | ||
| .format("delta") | ||
| .foreachBatch(self._write_latest_to_delta) | ||
| .queryName(self.query_name) | ||
| .outputMode("append") | ||
| .options(**self.options) | ||
| .start() | ||
| ) | ||
|
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| if self.query_wait_interval: | ||
| while query.isActive: | ||
| if query.lastProgress: | ||
| logging.info(query.lastProgress) | ||
| time.sleep(self.query_wait_interval) | ||
|
|
||
| except Py4JJavaError as e: | ||
| logging.exception(e.errmsg) | ||
| raise e | ||
| except Exception as e: | ||
| logging.exception(str(e)) | ||
| raise e |
Oops, something went wrong.