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f87adcfb3f
Summary: Ribbon micro-bench needs updating after re-numbering `BloomLikeFilterPolicy::GetAllFixedImpls()` entries. (CircleCI nightly failure.) Also fixed memory leaks while using ASAN to validate my fix. (I assume the leaks weren't intentional for some performance characteristic.) Pull Request resolved: https://github.com/facebook/rocksdb/pull/10195 Test Plan: run with ASAN Reviewed By: jay-zhuang Differential Revision: D37244459 Pulled By: pdillinger fbshipit-source-id: 5a363e10de3c4c9c88099c937e3dc3b4cf24fd30
156 lines
5.5 KiB
C++
156 lines
5.5 KiB
C++
// Copyright (c) 2011-present, Facebook, Inc. All rights reserved.
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// This source code is licensed under both the GPLv2 (found in the
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// COPYING file in the root directory) and Apache 2.0 License
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// (found in the LICENSE.Apache file in the root directory).
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// this is a simple micro-benchmark for compare ribbon filter vs. other filter
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// for more comprehensive, please check the dedicate util/filter_bench.
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#include "benchmark/benchmark.h"
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#include "table/block_based/filter_policy_internal.h"
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#include "table/block_based/mock_block_based_table.h"
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namespace ROCKSDB_NAMESPACE {
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struct KeyMaker {
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explicit KeyMaker(size_t avg_size)
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: smallest_size_(avg_size),
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buf_size_(avg_size + 11), // pad to vary key size and alignment
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buf_(new char[buf_size_]) {
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memset(buf_.get(), 0, buf_size_);
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assert(smallest_size_ > 8);
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}
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size_t smallest_size_;
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size_t buf_size_;
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std::unique_ptr<char[]> buf_;
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// Returns a unique(-ish) key based on the given parameter values. Each
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// call returns a Slice from the same buffer so previously returned
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// Slices should be considered invalidated.
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Slice Get(uint32_t filter_num, uint32_t val_num) const {
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size_t start = val_num % 4;
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size_t len = smallest_size_;
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// To get range [avg_size - 2, avg_size + 2]
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// use range [smallest_size, smallest_size + 4]
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len += FastRange32((val_num >> 5) * 1234567891, 5);
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char *data = buf_.get() + start;
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// Populate key data such that all data makes it into a key of at
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// least 8 bytes. We also don't want all the within-filter key
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// variance confined to a contiguous 32 bits, because then a 32 bit
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// hash function can "cheat" the false positive rate by
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// approximating a perfect hash.
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EncodeFixed32(data, val_num);
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EncodeFixed32(data + 4, filter_num + val_num);
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// ensure clearing leftovers from different alignment
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EncodeFixed32(data + 8, 0);
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return {data, len};
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}
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};
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// benchmark arguments:
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// 0. filter impl (like filter_bench -impl)
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// 1. filter config bits_per_key
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// 2. average data key length
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// 3. data entry number
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static void CustomArguments(benchmark::internal::Benchmark *b) {
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const auto kImplCount =
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static_cast<int>(BloomLikeFilterPolicy::GetAllFixedImpls().size());
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for (int filter_impl = 0; filter_impl < kImplCount; ++filter_impl) {
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for (int bits_per_key : {10, 20}) {
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for (int key_len_avg : {10, 100}) {
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for (int64_t entry_num : {1 << 10, 1 << 20}) {
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b->Args({filter_impl, bits_per_key, key_len_avg, entry_num});
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}
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}
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}
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}
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b->ArgNames({"filter_impl", "bits_per_key", "key_len_avg", "entry_num"});
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}
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static void FilterBuild(benchmark::State &state) {
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// setup data
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auto filter = BloomLikeFilterPolicy::Create(
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BloomLikeFilterPolicy::GetAllFixedImpls().at(state.range(0)),
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static_cast<double>(state.range(1)));
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auto tester = std::make_unique<mock::MockBlockBasedTableTester>(filter);
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KeyMaker km(state.range(2));
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std::unique_ptr<const char[]> owner;
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const int64_t kEntryNum = state.range(3);
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auto rnd = Random32(12345);
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uint32_t filter_num = rnd.Next();
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// run the test
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for (auto _ : state) {
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std::unique_ptr<FilterBitsBuilder> builder(tester->GetBuilder());
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for (uint32_t i = 0; i < kEntryNum; i++) {
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builder->AddKey(km.Get(filter_num, i));
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}
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auto ret = builder->Finish(&owner);
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state.counters["size"] = static_cast<double>(ret.size());
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}
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}
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BENCHMARK(FilterBuild)->Apply(CustomArguments);
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static void FilterQueryPositive(benchmark::State &state) {
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// setup data
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auto filter = BloomLikeFilterPolicy::Create(
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BloomLikeFilterPolicy::GetAllFixedImpls().at(state.range(0)),
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static_cast<double>(state.range(1)));
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auto tester = std::make_unique<mock::MockBlockBasedTableTester>(filter);
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KeyMaker km(state.range(2));
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std::unique_ptr<const char[]> owner;
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const int64_t kEntryNum = state.range(3);
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auto rnd = Random32(12345);
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uint32_t filter_num = rnd.Next();
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std::unique_ptr<FilterBitsBuilder> builder(tester->GetBuilder());
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for (uint32_t i = 0; i < kEntryNum; i++) {
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builder->AddKey(km.Get(filter_num, i));
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}
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auto data = builder->Finish(&owner);
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std::unique_ptr<FilterBitsReader> reader{filter->GetFilterBitsReader(data)};
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// run test
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uint32_t i = 0;
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for (auto _ : state) {
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i++;
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i = i % kEntryNum;
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reader->MayMatch(km.Get(filter_num, i));
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}
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}
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BENCHMARK(FilterQueryPositive)->Apply(CustomArguments);
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static void FilterQueryNegative(benchmark::State &state) {
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// setup data
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auto filter = BloomLikeFilterPolicy::Create(
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BloomLikeFilterPolicy::GetAllFixedImpls().at(state.range(0)),
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static_cast<double>(state.range(1)));
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auto tester = std::make_unique<mock::MockBlockBasedTableTester>(filter);
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KeyMaker km(state.range(2));
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std::unique_ptr<const char[]> owner;
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const int64_t kEntryNum = state.range(3);
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auto rnd = Random32(12345);
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uint32_t filter_num = rnd.Next();
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std::unique_ptr<FilterBitsBuilder> builder(tester->GetBuilder());
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for (uint32_t i = 0; i < kEntryNum; i++) {
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builder->AddKey(km.Get(filter_num, i));
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}
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auto data = builder->Finish(&owner);
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std::unique_ptr<FilterBitsReader> reader{filter->GetFilterBitsReader(data)};
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// run test
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uint32_t i = 0;
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double fp_cnt = 0;
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for (auto _ : state) {
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i++;
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auto result = reader->MayMatch(km.Get(filter_num + 1, i));
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if (result) {
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fp_cnt++;
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}
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}
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state.counters["fp_pct"] =
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benchmark::Counter(fp_cnt * 100, benchmark::Counter::kAvgIterations);
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}
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BENCHMARK(FilterQueryNegative)->Apply(CustomArguments);
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} // namespace ROCKSDB_NAMESPACE
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BENCHMARK_MAIN();
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