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rocksdb/util/filter_bench.cc

462 lines
15 KiB

// Copyright (c) 2011-present, Facebook, Inc. All rights reserved.
// This source code is licensed under both the GPLv2 (found in the
// COPYING file in the root directory) and Apache 2.0 License
// (found in the LICENSE.Apache file in the root directory).
#ifndef GFLAGS
#include <cstdio>
int main() {
fprintf(stderr, "Please install gflags to run rocksdb tools\n");
return 1;
}
#else
#include <cinttypes>
#include <iostream>
#include <random>
#include <vector>
#include "port/port.h"
#include "port/stack_trace.h"
#include "rocksdb/filter_policy.h"
#include "table/block_based/full_filter_block.h"
#include "table/block_based/mock_block_based_table.h"
#include "util/gflags_compat.h"
#include "util/hash.h"
#include "util/stop_watch.h"
using GFLAGS_NAMESPACE::ParseCommandLineFlags;
using GFLAGS_NAMESPACE::RegisterFlagValidator;
using GFLAGS_NAMESPACE::SetUsageMessage;
DEFINE_int64(seed, 0, "Seed for random number generators");
DEFINE_double(working_mem_size_mb, 200,
"MB of memory to get up to among all filters");
DEFINE_uint32(average_keys_per_filter, 10000,
"Average number of keys per filter");
DEFINE_uint32(key_size, 16, "Number of bytes each key should be");
DEFINE_uint32(batch_size, 8, "Number of keys to group in each batch");
DEFINE_uint32(bits_per_key, 10, "Bits per key setting for filters");
DEFINE_double(m_queries, 200, "Millions of queries for each test mode");
DEFINE_bool(use_full_block_reader, false,
"Use FullFilterBlockReader interface rather than FilterBitsReader");
DEFINE_bool(quick, false, "Run more limited set of tests, fewer queries");
DEFINE_bool(allow_bad_fp_rate, false, "Continue even if FP rate is bad");
DEFINE_bool(legend, false,
"Print more information about interpreting results instead of "
"running tests");
void _always_assert_fail(int line, const char *file, const char *expr) {
fprintf(stderr, "%s: %d: Assertion %s failed\n", file, line, expr);
abort();
}
#define ALWAYS_ASSERT(cond) \
((cond) ? (void)0 : ::_always_assert_fail(__LINE__, __FILE__, #cond))
using rocksdb::BlockContents;
using rocksdb::CachableEntry;
using rocksdb::fastrange32;
using rocksdb::FilterBitsBuilder;
using rocksdb::FilterBitsReader;
using rocksdb::FullFilterBlockReader;
using rocksdb::Slice;
using rocksdb::mock::MockBlockBasedTableTester;
struct KeyMaker {
KeyMaker(size_t size)
: data_(new char[size]),
slice_(data_.get(), size),
vals_(reinterpret_cast<uint32_t *>(data_.get())) {
assert(size >= 8);
memset(data_.get(), 0, size);
}
std::unique_ptr<char[]> data_;
Slice slice_;
uint32_t *vals_;
Slice Get(uint32_t filter_num, uint32_t val_num) {
vals_[0] = filter_num + val_num;
vals_[1] = val_num;
return slice_;
}
};
void PrintWarnings() {
#if defined(__GNUC__) && !defined(__OPTIMIZE__)
fprintf(stdout,
"WARNING: Optimization is disabled: benchmarks unnecessarily slow\n");
#endif
#ifndef NDEBUG
fprintf(stdout,
"WARNING: Assertions are enabled; benchmarks unnecessarily slow\n");
#endif
}
struct FilterInfo {
uint32_t filter_id_ = 0;
std::unique_ptr<const char[]> owner_;
Slice filter_;
uint32_t keys_added_ = 0;
std::unique_ptr<FilterBitsReader> reader_;
std::unique_ptr<FullFilterBlockReader> full_block_reader_;
uint64_t outside_queries_ = 0;
uint64_t false_positives_ = 0;
};
enum TestMode {
kSingleFilter,
kBatchPrepared,
kBatchUnprepared,
kFiftyOneFilter,
kEightyTwentyFilter,
kRandomFilter,
};
static const std::vector<TestMode> allTestModes = {
kSingleFilter, kBatchPrepared, kBatchUnprepared,
kFiftyOneFilter, kEightyTwentyFilter, kRandomFilter,
};
static const std::vector<TestMode> quickTestModes = {
kSingleFilter,
kRandomFilter,
};
const char *TestModeToString(TestMode tm) {
switch (tm) {
case kSingleFilter:
return "Single filter";
case kBatchPrepared:
return "Batched, prepared";
case kBatchUnprepared:
return "Batched, unprepared";
case kFiftyOneFilter:
return "Skewed 50% in 1%";
case kEightyTwentyFilter:
return "Skewed 80% in 20%";
case kRandomFilter:
return "Random filter";
}
return "Bad TestMode";
}
struct FilterBench : public MockBlockBasedTableTester {
std::vector<KeyMaker> kms_;
std::vector<FilterInfo> infos_;
std::mt19937 random_;
FilterBench()
: MockBlockBasedTableTester(
rocksdb::NewBloomFilterPolicy(FLAGS_bits_per_key)),
random_(FLAGS_seed) {
for (uint32_t i = 0; i < FLAGS_batch_size; ++i) {
kms_.emplace_back(FLAGS_key_size < 8 ? 8 : FLAGS_key_size);
}
}
void Go();
void RandomQueryTest(bool inside, bool dry_run, TestMode mode);
};
void FilterBench::Go() {
std::unique_ptr<FilterBitsBuilder> builder(
table_options_.filter_policy->GetFilterBitsBuilder());
uint32_t variance_mask = 1;
while (variance_mask * variance_mask * 4 < FLAGS_average_keys_per_filter) {
variance_mask = variance_mask * 2 + 1;
}
const std::vector<TestMode> &testModes =
FLAGS_quick ? quickTestModes : allTestModes;
if (FLAGS_quick) {
FLAGS_m_queries /= 10.0;
}
std::cout << "Building..." << std::endl;
size_t total_memory_used = 0;
size_t total_keys_added = 0;
rocksdb::StopWatchNano timer(rocksdb::Env::Default(), true);
while (total_memory_used < 1024 * 1024 * FLAGS_working_mem_size_mb) {
uint32_t filter_id = random_();
uint32_t keys_to_add = FLAGS_average_keys_per_filter +
(random_() & variance_mask) - (variance_mask / 2);
for (uint32_t i = 0; i < keys_to_add; ++i) {
builder->AddKey(kms_[0].Get(filter_id, i));
}
infos_.emplace_back();
FilterInfo &info = infos_.back();
info.filter_id_ = filter_id;
info.filter_ = builder->Finish(&info.owner_);
info.keys_added_ = keys_to_add;
info.reader_.reset(
table_options_.filter_policy->GetFilterBitsReader(info.filter_));
CachableEntry<BlockContents> block(
new BlockContents(info.filter_), nullptr /* cache */,
nullptr /* cache_handle */, true /* own_value */);
info.full_block_reader_.reset(
new FullFilterBlockReader(table_.get(), std::move(block)));
total_memory_used += info.filter_.size();
total_keys_added += keys_to_add;
}
uint64_t elapsed_nanos = timer.ElapsedNanos();
double ns = double(elapsed_nanos) / total_keys_added;
std::cout << "Build avg ns/key: " << ns << std::endl;
std::cout << "Number of filters: " << infos_.size() << std::endl;
std::cout << "Total memory (MB): " << total_memory_used / 1024.0 / 1024.0
<< std::endl;
double bpk = total_memory_used * 8.0 / total_keys_added;
std::cout << "Bits/key actual: " << bpk << std::endl;
if (!FLAGS_quick) {
double tolerable_rate = std::pow(2.0, -(bpk - 1.0) / (1.4 + bpk / 50.0));
std::cout << "Best possible FP rate %: " << 100.0 * std::pow(2.0, -bpk)
<< std::endl;
std::cout << "Tolerable FP rate %: " << 100.0 * tolerable_rate << std::endl;
std::cout << "----------------------------" << std::endl;
std::cout << "Verifying..." << std::endl;
uint32_t outside_q_per_f = 1000000 / infos_.size();
uint64_t fps = 0;
for (uint32_t i = 0; i < infos_.size(); ++i) {
FilterInfo &info = infos_[i];
for (uint32_t j = 0; j < info.keys_added_; ++j) {
ALWAYS_ASSERT(info.reader_->MayMatch(kms_[0].Get(info.filter_id_, j)));
}
for (uint32_t j = 0; j < outside_q_per_f; ++j) {
fps += info.reader_->MayMatch(
kms_[0].Get(info.filter_id_, j | 0x80000000));
}
}
std::cout << " No FNs :)" << std::endl;
double prelim_rate = double(fps) / outside_q_per_f / infos_.size();
std::cout << " Prelim FP rate %: " << (100.0 * prelim_rate) << std::endl;
if (!FLAGS_allow_bad_fp_rate) {
ALWAYS_ASSERT(prelim_rate < tolerable_rate);
}
}
std::cout << "----------------------------" << std::endl;
std::cout << "Inside queries..." << std::endl;
random_.seed(FLAGS_seed + 1);
RandomQueryTest(/*inside*/ true, /*dry_run*/ true, kRandomFilter);
for (TestMode tm : testModes) {
random_.seed(FLAGS_seed + 1);
RandomQueryTest(/*inside*/ true, /*dry_run*/ false, tm);
}
std::cout << "----------------------------" << std::endl;
std::cout << "Outside queries..." << std::endl;
random_.seed(FLAGS_seed + 2);
RandomQueryTest(/*inside*/ false, /*dry_run*/ true, kRandomFilter);
for (TestMode tm : testModes) {
random_.seed(FLAGS_seed + 2);
RandomQueryTest(/*inside*/ false, /*dry_run*/ false, tm);
}
std::cout << "----------------------------" << std::endl;
std::cout << "Done. (For more info, run with -legend or -help.)" << std::endl;
}
void FilterBench::RandomQueryTest(bool inside, bool dry_run, TestMode mode) {
for (auto &info : infos_) {
info.outside_queries_ = 0;
info.false_positives_ = 0;
}
uint32_t dry_run_hash = 0;
uint64_t max_queries =
static_cast<uint64_t>(FLAGS_m_queries * 1000000 + 0.50);
// Some filters may be considered secondary in order to implement skewed
// queries. num_primary_filters is the number that are to be treated as
// equal, and any remainder will be treated as secondary.
size_t num_primary_filters = infos_.size();
// The proportion (when divided by 2^32 - 1) of filter queries going to
// the primary filters (default = all). The remainder of queries are
// against secondary filters.
uint32_t primary_filter_threshold = 0xffffffff;
if (mode == kSingleFilter) {
// 100% of queries to 1 filter
num_primary_filters = 1;
} else if (mode == kFiftyOneFilter) {
// 50% of queries
primary_filter_threshold /= 2;
// to 1% of filters
num_primary_filters = (num_primary_filters + 99) / 100;
} else if (mode == kEightyTwentyFilter) {
// 80% of queries
primary_filter_threshold = primary_filter_threshold / 5 * 4;
// to 20% of filters
num_primary_filters = (num_primary_filters + 4) / 5;
}
size_t batch_size = 1;
std::unique_ptr<Slice *[]> batch_slices;
std::unique_ptr<bool[]> batch_results;
if (mode == kBatchPrepared || mode == kBatchUnprepared) {
batch_size = kms_.size();
batch_slices.reset(new Slice *[batch_size]);
batch_results.reset(new bool[batch_size]);
for (size_t i = 0; i < batch_size; ++i) {
batch_slices[i] = &kms_[i].slice_;
batch_results[i] = false;
}
}
rocksdb::StopWatchNano timer(rocksdb::Env::Default(), true);
for (uint64_t q = 0; q < max_queries; q += batch_size) {
uint32_t filter_index;
if (random_() <= primary_filter_threshold) {
filter_index = fastrange32(num_primary_filters, random_());
} else {
// secondary
filter_index =
num_primary_filters +
fastrange32(infos_.size() - num_primary_filters, random_());
}
FilterInfo &info = infos_[filter_index];
for (size_t i = 0; i < batch_size; ++i) {
if (inside) {
kms_[i].Get(info.filter_id_, fastrange32(info.keys_added_, random_()));
} else {
kms_[i].Get(info.filter_id_, random_() | 0x80000000);
info.outside_queries_++;
}
}
// TODO: implement batched interface to full block reader
if (mode == kBatchPrepared && !dry_run && !FLAGS_use_full_block_reader) {
for (size_t i = 0; i < batch_size; ++i) {
batch_results[i] = false;
}
info.reader_->MayMatch(batch_size, batch_slices.get(),
batch_results.get());
for (size_t i = 0; i < batch_size; ++i) {
if (inside) {
ALWAYS_ASSERT(batch_results[i]);
} else {
info.false_positives_ += batch_results[i];
}
}
} else {
for (size_t i = 0; i < batch_size; ++i) {
if (dry_run) {
dry_run_hash ^= rocksdb::BloomHash(kms_[i].slice_);
} else {
bool may_match;
if (FLAGS_use_full_block_reader) {
may_match = info.full_block_reader_->KeyMayMatch(
kms_[i].slice_,
/*prefix_extractor=*/nullptr,
/*block_offset=*/rocksdb::kNotValid,
/*no_io=*/false, /*const_ikey_ptr=*/nullptr,
/*get_context=*/nullptr,
/*lookup_context=*/nullptr);
} else {
may_match = info.reader_->MayMatch(kms_[i].slice_);
}
if (inside) {
ALWAYS_ASSERT(may_match);
} else {
info.false_positives_ += may_match;
}
}
}
}
}
uint64_t elapsed_nanos = timer.ElapsedNanos();
double ns = double(elapsed_nanos) / max_queries;
if (dry_run) {
// Printing part of hash prevents dry run components from being optimized
// away by compiler
std::cout << " Dry run (" << std::hex << (dry_run_hash & 0xfff) << std::dec
<< ") ";
} else {
std::cout << " " << TestModeToString(mode) << " ";
}
std::cout << "ns/op: " << ns << std::endl;
if (!inside && !dry_run && mode == kRandomFilter) {
uint64_t q = 0;
uint64_t fp = 0;
double worst_fp_rate = 0.0;
double best_fp_rate = 1.0;
for (auto &info : infos_) {
q += info.outside_queries_;
fp += info.false_positives_;
if (info.outside_queries_ > 0) {
double fp_rate = double(info.false_positives_) / info.outside_queries_;
worst_fp_rate = std::max(worst_fp_rate, fp_rate);
best_fp_rate = std::min(best_fp_rate, fp_rate);
}
}
std::cout << " Average FP rate %: " << 100.0 * fp / q << std::endl;
if (!FLAGS_quick) {
std::cout << " Worst FP rate %: " << 100.0 * worst_fp_rate
<< std::endl;
std::cout << " Best FP rate %: " << 100.0 * best_fp_rate
<< std::endl;
std::cout << " Best possible bits/key: "
<< -std::log(double(fp) / q) / std::log(2.0) << std::endl;
}
}
}
int main(int argc, char **argv) {
rocksdb::port::InstallStackTraceHandler();
SetUsageMessage(std::string("\nUSAGE:\n") + std::string(argv[0]) +
" [-quick] [OTHER OPTIONS]...");
ParseCommandLineFlags(&argc, &argv, true);
PrintWarnings();
if (FLAGS_legend) {
std::cout
<< "Legend:" << std::endl
<< " \"Inside\" - key that was added to filter" << std::endl
<< " \"Outside\" - key that was not added to filter" << std::endl
<< " \"FN\" - false negative query (must not happen)" << std::endl
<< " \"FP\" - false positive query (OK at low rate)" << std::endl
<< " \"Dry run\" - cost of testing and hashing overhead. Consider"
<< "\n subtracting this cost from the others." << std::endl
<< " \"Single filter\" - essentially minimum cost, assuming filter"
<< "\n fits easily in L1 CPU cache." << std::endl
<< " \"Batched, prepared\" - several queries at once against a"
<< "\n randomly chosen filter, using multi-query interface."
<< std::endl
<< " \"Batched, unprepared\" - similar, but using serial calls"
<< "\n to single query interface." << std::endl
<< " \"Random filter\" - a filter is chosen at random as target"
<< "\n of each query." << std::endl
<< " \"Skewed X% in Y%\" - like \"Random filter\" except Y% of"
<< "\n the filters are designated as \"hot\" and receive X%"
<< "\n of queries." << std::endl;
} else {
FilterBench b;
b.Go();
}
return 0;
}
#endif // GFLAGS