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unodb

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Introduction

UnoDB is a library that implements of Adaptive Radix Tree (ART) data structure, designed for efficient indexing in main-memory databases. The ART is a trie-based data structure that dynamically adapts to the distribution of keys, ensuring good search performance and memory usage. UnoDB offers two variants of ART: a regular one and a concurrent one based on Optimistic Lock Coupling (OLC) with Quiescent State Based Reclamation (QSBR).

This library serves as a playground for experimenting with various C++ tools and ideas. I am describing some of the things I learned at my blog.

Requirements

UnoDB' source code is written in C++17, and relies on the following platform-specific features:

  • On Intel platforms, it requires SSE4.1 intrinsics (Nehalem and higher), AVX for MSVC builds, and optional AVX2 support, when available. This differs from the original ART paper, which only required SSE2.
  • On ARM, it uses NEON intrinsics.

Please note that this personal project only supports the following compilers: GCC 10 and later, LLVM 11 and later, XCode 13.2, and MSVC 2022 compilers. If you require support for an earlier compiler version, feel free to drop me a note.

Out-of-source builds are recommended. Before anything else, do

# --recursive is not strictly required at the moment, but a good habit to have
git submodule update --init --recursive

Some platform-specific notes:

Ubuntu 22.04

# libc6-dev-i386 is for DeepState
sudo apt-get install -y libboost-dev libc6-dev-i386

Amazon Linux 2023

sudo dnf install git gcc g++ cmake boost-devel
# Optional, if you want to use Boost.Stacktrace:
git clone https://github.com/ianlancetaylor/libbacktrace
(cd libbacktrace && ./configure && make && sudo make install)
# Build as usual

Amazon Linux 2

sudo yum install git gcc10 gcc10-c++ cmake3 boost-devel
# Pass -DCMAKE_C_COMPILER=gcc10-gcc -DCMAKE_CXX_COMPILER=gcc10-c++ to cmake3

Usage

All the declarations live in the unodb namespace, which is omitted in the descriptions below.

The only currently supported key type is std::uint64_t, aliased as key. To add new key types, instantiate art_key type with the desired type, and specialize art_key::make_binary_comparable according to the ART paper.

Values are treated opaquely. For unodb::db, they are passed as non-owning objects of value_view (a gsl::span<std::byte>), and insertion copies them internally. The same applies for get, which returns a non-owning value_view. For unodb::olc_db, get returns a qsbr_value_view, a span guaranteed to remain valid until the current thread passes through a quiescent state.

All ART classes share the same API:

  • constructor.
  • get(key k) returns get_result (a std::optional<value_view>).
  • bool insert(key k, value_view v) returns whether the insert was successful (i.e. the key was not already present).
  • bool remove(key k) returns whether delete was successful (i.e. the key was found in the tree).
  • clear() empties the tree. For olc_db, it must be called from a single-threaded context.
  • bool empty() returns whether the tree is empty.
  • void dump(std::ostream &) outputs the tree representation.
  • Several getters provide tree info, such as current memory use, and internal operation counters (e.g. number of times Node4 grew to Node16, key prefix was split, etc - see the source code for details).

Three ART classes available:

  • db: unsychronized ART tree, for single-thread contexts or with external synchronization
  • mutex_db: ART tree with single global mutex synchronization
  • olc_db: a concurrent ART tree, implementing Optimistic Lock Coupling as described in "The ART of Practical Synchronization" paper by Leis et al.; nodes are versioned, writers lock per-node optimistic locks, readers don't lock but check node versions and restart if they change.

Do not use macros starting with UNODB_DETAIL_ or declarations in unodb::detail and unob::test namespaces as they are internal and may change at any time.

Technical Details

Sequential Lock

The optimistic lock concept seems to be nearly identical to that of sequential locks as used in the Linux kernel, with the addition of "obsolete" state. The lock implementation uses the seqlock memory model implementation as described by Boehm in "Can seqlocks get along with programming language memory models?" 2012 paper.

Quiescent State-Based Reclamation (QSBR)

The OLC ART implementation necessitates a memory reclamation scheme as required by lock-free data structures (even though olc_db is not lock-free in the general sense, the readers do not take locks), and for that a Quiescent State Based Reclamation (QSBR) was chosen. In QSBR, each thread periodically announces that it is not using any pointers to a shared data structures. After all the threads have done so, a new epoch starts, and the memory reclamation requests from two epochs ago are executed. To participate in QSBR, a thread must an instance of unodb::qsbr_thread, which derives from std::thread. A thread may temporarily or permanently stop its participation in QSBR by calling unodb::this_thread().qsbr_pause() and resume by calling unodb::this_thread().qsbr_resume().

The registered threads must periodically signal their quiescent states. They can do this by using the unodb::quiescent_state_on_scope_exit scope guard, which automatically reports the quiescent state when the scope is exited.

Dependencies

  • CMake, at least 3.12
  • Boost library, specifically Boost.Accumulator and optional Boost.Stacktrace.
  • Guidelines Support Library for gsl::span, bundled as a git submodule.
  • Google Test for tests, bundled as a git submodule.
  • Google Benchmark for microbenchmarks, bundled, as a git submodule.
  • DeepState for fuzzing tests, bundled as a git submodule.
  • (optional) clang-format
  • (optional) lcov
  • (optional) clang-tidy
  • (optional) clangd
  • (optional) cppcheck
  • (optional) cpplint
  • (optional) include-what-you-use
  • (optional) libfuzzer

Development

Source code is formatted with Google C++ style. Automatic code formatting is configured through git clean/fuzz filters. To enable this feature, do git config --local include.path ../.gitconfig. If you need to temporarily disable it, run git config --local --unset include.path.

When building this project independently and not as part of another project, add -DSTANDALONE=ON CMake option. It will enable extra global debug checks that require entire programs to be compiled with them. Currently, this consists of the libstdc++ debug mode.

To enable maintainer diagnostics, add -DMAINTAINER_MODE=ON CMake option. This makes compilation and include-what-you-use warnings fatal.

clang-tidy, cppcheck, and cpplint will be invoked automatically during the build if found. The current diagnostic level for them, as well as for compiler warnings, is set very high and can be relaxed if needed.

To disable AVX2 intrinsics to use SSE4.1/AVX only, add -DWITH_AVX2=OFF.

To enable AddressSanitizer and LeakSanitizer (the latter if available), add -DSANITIZE_ADDRESS=ON CMake option. It is incompatible with the -DSANITIZE_THREAD=ON option.

To enable ThreadSanitizer, add -DSANITIZE_THREAD=ON CMake option. It is incompatible with the -DSANITIZE_ADDRESS=ON option and will disable libfuzzer support if specified. Not available under MSVC.

To enable UndefinedBehaviorSanitizer, add the -DSANITIZE_UB=ON CMake option. It is compatible with both -DSANITIZE_ADDRESS=ON and -DSANITIZE_THREAD=ON options, although some false positives might occur. Not available under MSVC.

To enable GCC or MSVC compiler static analysis, add the -DSTATIC_ANALYSIS=ON CMake option. For LLVM static analysis, no special CMake option is needed; instead prepend scan-build to make.

To invoke include-what-you-use without enabling the whole of maintainer mode, add the -DIWYU=ON CMake option. It will take effect if CMake configures to build project with clang.

To enable inconclusive cppcheck diagnostics, add the -DCPPCHECK_AGGRESSIVE=ON CMake option. These diagnostics will not fail a build.

To generate coverage reports on tests, excluding fuzzers, using lcov, add the -DCOVERAGE=ON CMake option.

Google Test and DeepState are used for testing. There will be no unit tests for each private implementation class. For DeepState, both LLVM libfuzzer and built-in fuzzer are supported.

Fuzzing

Fuzzer tests for ART and QSBR components are located in the fuzz_deepstate subdirectory. The tests use DeepState with either a brute force or libfuzzer-based backend. However, not all platforms and configurations support them. For isntance, MSVC builds completely skip them, and libfuzzer-based tests are skipped if ThreadSanitizer is enabled or if building non-XCode clang release configuration.

Several Make targets are available for fuzzing. For time-based brute-force fuzzing of all components, use one of the following: deepstate_2s, deepstate_1m, deepstate_20m, or deepstate_8h. To use individual fuzzers, insert art or qsbr, for example: deepstate_qsbr_20m or deepstate_art_8h. Running fuzzer under Valgrind is available through valgrind_deepstate for everything or valgrind_{art|qsbr}_deepstate for individual fuzzers.

Fuzzers that use libfuzzer mirror the above by adding _lf before the time suffix, such as deepstate_lf_8h, deepstate_qsbr_lf_20m, valgrind_deepstate_lf, and so on.

Related Projects

art_map is a C++14 template library providing std::-like interface over the ART data structure. It shares some code with UnoDB.

Literature

ART Trie: V. Leis, A. Kemper and T. Neumann, "The adaptive radix tree: ARTful indexing for main-memory databases," 2013 29th IEEE International Conference on Data Engineering (ICDE 2013)(ICDE), Brisbane, QLD, 2013, pp. 38-49. doi:10.1109/ICDE.2013.6544812

ART Sync: V. Leis, F. Schneiber, A. Kemper and T. Neumann, "The ART of Practical Synchronization," 2016 Proceedings of the 12th International Workshop on Data Management on New Hardware (DaMoN), pages 3:1--3:8, 2016.

qsbr: P. E. McKenney, J. D. Slingwine, "Read-copy update: using execution history to solve concurrency problems," Parallel and Distributed Computing and Systems, 1998, pages 509--518.

seqlock sync: H-J. Boehm, "Can seqlocks get along with programming language memory models?," Proceedings of the 2012 ACM SIGPLAN Workshop on Memory Systems Performance and Correctness, June 2012, pages 12--21, 2012.