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126c223714
Summary: In https://github.com/facebook/rocksdb/issues/9535, release 7.0, we hid the old block-based filter from being created using the public API, because of its inefficiency. Although we normally maintain read compatibility on old DBs forever, filters are not required for reading a DB, only for optimizing read performance. Thus, it should be acceptable to remove this code and the substantial maintenance burden it carries as useful features are developed and validated (such as user timestamp). This change completely removes the code for reading and writing the old block-based filters, net removing about 1370 lines of code no longer needed. Options removed from testing / benchmarking tools. The prior existence is only evident in a couple of places: * `CacheEntryRole::kDeprecatedFilterBlock` - We can update this public API enum in a major release to minimize source code incompatibilities. * A warning is logged when an old table file is opened that used the old block-based filter. This is provided as a courtesy, and would be a pain to unit test, so manual testing should suffice. Unfortunately, sst_dump does not tell you whether a file uses block-based filter, and the structure of the code makes it very difficult to fix. * To detect that case, `kObsoleteFilterBlockPrefix` (renamed from `kFilterBlockPrefix`) for metaindex is maintained (for now). Other notes: * In some cases where numbers are associated with filter configurations, we have had to update the assigned numbers so that they all correspond to something that exists. * Fixed potential stat counting bug by assuming `filter_checked = false` for cases like `filter == nullptr` rather than assuming `filter_checked = true` * Removed obsolete `block_offset` and `prefix_extractor` parameters from several functions. * Removed some unnecessary checks `if (!table_prefix_extractor() && !prefix_extractor)` because the caller guarantees the prefix extractor exists and is compatible Pull Request resolved: https://github.com/facebook/rocksdb/pull/10184 Test Plan: tests updated, manually test new warning in LOG using base version to generate a DB Reviewed By: riversand963 Differential Revision: D37212647 Pulled By: pdillinger fbshipit-source-id: 06ee020d8de3b81260ffc36ad0c1202cbf463a80
1179 lines
41 KiB
C++
1179 lines
41 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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//
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// Copyright (c) 2012 The LevelDB Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style license that can be
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// found in the LICENSE file. See the AUTHORS file for names of contributors.
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#ifndef GFLAGS
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#include <cstdio>
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int main() {
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fprintf(stderr, "Please install gflags to run this test... Skipping...\n");
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return 0;
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}
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#else
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#include <array>
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#include <cmath>
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#include <vector>
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#include "cache/cache_entry_roles.h"
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#include "cache/cache_reservation_manager.h"
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#include "memory/arena.h"
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#include "port/jemalloc_helper.h"
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#include "rocksdb/filter_policy.h"
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#include "table/block_based/filter_policy_internal.h"
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#include "test_util/testharness.h"
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#include "test_util/testutil.h"
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#include "util/gflags_compat.h"
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#include "util/hash.h"
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using GFLAGS_NAMESPACE::ParseCommandLineFlags;
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// The test is not fully designed for bits_per_key other than 10, but with
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// this parameter you can easily explore the behavior of other bits_per_key.
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// See also filter_bench.
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DEFINE_int32(bits_per_key, 10, "");
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namespace ROCKSDB_NAMESPACE {
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namespace {
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const std::string kLegacyBloom = test::LegacyBloomFilterPolicy::kClassName();
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const std::string kFastLocalBloom =
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test::FastLocalBloomFilterPolicy::kClassName();
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const std::string kStandard128Ribbon =
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test::Standard128RibbonFilterPolicy::kClassName();
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} // namespace
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static const int kVerbose = 1;
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static Slice Key(int i, char* buffer) {
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std::string s;
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PutFixed32(&s, static_cast<uint32_t>(i));
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memcpy(buffer, s.c_str(), sizeof(i));
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return Slice(buffer, sizeof(i));
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}
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static int NextLength(int length) {
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if (length < 10) {
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length += 1;
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} else if (length < 100) {
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length += 10;
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} else if (length < 1000) {
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length += 100;
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} else {
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length += 1000;
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}
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return length;
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}
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class FullBloomTest : public testing::TestWithParam<std::string> {
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protected:
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BlockBasedTableOptions table_options_;
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private:
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std::shared_ptr<const FilterPolicy>& policy_;
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std::unique_ptr<FilterBitsBuilder> bits_builder_;
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std::unique_ptr<FilterBitsReader> bits_reader_;
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std::unique_ptr<const char[]> buf_;
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size_t filter_size_;
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public:
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FullBloomTest() : policy_(table_options_.filter_policy), filter_size_(0) {
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ResetPolicy();
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}
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BuiltinFilterBitsBuilder* GetBuiltinFilterBitsBuilder() {
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// Throws on bad cast
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return dynamic_cast<BuiltinFilterBitsBuilder*>(bits_builder_.get());
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}
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const BloomLikeFilterPolicy* GetBloomLikeFilterPolicy() {
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// Throws on bad cast
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return &dynamic_cast<const BloomLikeFilterPolicy&>(*policy_);
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}
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void Reset() {
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bits_builder_.reset(BloomFilterPolicy::GetBuilderFromContext(
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FilterBuildingContext(table_options_)));
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bits_reader_.reset(nullptr);
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buf_.reset(nullptr);
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filter_size_ = 0;
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}
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void ResetPolicy(double bits_per_key) {
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policy_ = BloomLikeFilterPolicy::Create(GetParam(), bits_per_key);
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Reset();
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}
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void ResetPolicy() { ResetPolicy(FLAGS_bits_per_key); }
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void Add(const Slice& s) {
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bits_builder_->AddKey(s);
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}
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void OpenRaw(const Slice& s) {
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bits_reader_.reset(policy_->GetFilterBitsReader(s));
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}
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void Build() {
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Slice filter = bits_builder_->Finish(&buf_);
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bits_reader_.reset(policy_->GetFilterBitsReader(filter));
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filter_size_ = filter.size();
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}
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size_t FilterSize() const {
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return filter_size_;
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}
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Slice FilterData() { return Slice(buf_.get(), filter_size_); }
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int GetNumProbesFromFilterData() {
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assert(filter_size_ >= 5);
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int8_t raw_num_probes = static_cast<int8_t>(buf_.get()[filter_size_ - 5]);
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if (raw_num_probes == -1) { // New bloom filter marker
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return static_cast<uint8_t>(buf_.get()[filter_size_ - 3]);
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} else {
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return raw_num_probes;
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}
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}
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int GetRibbonSeedFromFilterData() {
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assert(filter_size_ >= 5);
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// Check for ribbon marker
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assert(-2 == static_cast<int8_t>(buf_.get()[filter_size_ - 5]));
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return static_cast<uint8_t>(buf_.get()[filter_size_ - 4]);
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}
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bool Matches(const Slice& s) {
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if (bits_reader_ == nullptr) {
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Build();
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}
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return bits_reader_->MayMatch(s);
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}
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// Provides a kind of fingerprint on the Bloom filter's
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// behavior, for reasonbly high FP rates.
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uint64_t PackedMatches() {
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char buffer[sizeof(int)];
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uint64_t result = 0;
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for (int i = 0; i < 64; i++) {
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if (Matches(Key(i + 12345, buffer))) {
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result |= uint64_t{1} << i;
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}
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}
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return result;
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}
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// Provides a kind of fingerprint on the Bloom filter's
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// behavior, for lower FP rates.
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std::string FirstFPs(int count) {
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char buffer[sizeof(int)];
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std::string rv;
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int fp_count = 0;
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for (int i = 0; i < 1000000; i++) {
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// Pack four match booleans into each hexadecimal digit
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if (Matches(Key(i + 1000000, buffer))) {
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++fp_count;
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rv += std::to_string(i);
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if (fp_count == count) {
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break;
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}
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rv += ',';
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}
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}
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return rv;
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}
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double FalsePositiveRate() {
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char buffer[sizeof(int)];
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int result = 0;
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for (int i = 0; i < 10000; i++) {
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if (Matches(Key(i + 1000000000, buffer))) {
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result++;
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}
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}
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return result / 10000.0;
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}
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};
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TEST_P(FullBloomTest, FilterSize) {
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// In addition to checking the consistency of space computation, we are
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// checking that denoted and computed doubles are interpreted as expected
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// as bits_per_key values.
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bool some_computed_less_than_denoted = false;
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// Note: to avoid unproductive configurations, bits_per_key < 0.5 is rounded
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// down to 0 (no filter), and 0.5 <= bits_per_key < 1.0 is rounded up to 1
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// bit per key (1000 millibits). Also, enforced maximum is 100 bits per key
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// (100000 millibits).
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for (auto bpk : std::vector<std::pair<double, int> >{{-HUGE_VAL, 0},
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{-INFINITY, 0},
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{0.0, 0},
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{0.499, 0},
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{0.5, 1000},
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{1.234, 1234},
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{3.456, 3456},
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{9.5, 9500},
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{10.0, 10000},
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{10.499, 10499},
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{21.345, 21345},
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{99.999, 99999},
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{1234.0, 100000},
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{HUGE_VAL, 100000},
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{INFINITY, 100000},
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{NAN, 100000}}) {
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ResetPolicy(bpk.first);
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auto bfp = GetBloomLikeFilterPolicy();
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EXPECT_EQ(bpk.second, bfp->GetMillibitsPerKey());
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EXPECT_EQ((bpk.second + 500) / 1000, bfp->GetWholeBitsPerKey());
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double computed = bpk.first;
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// This transforms e.g. 9.5 -> 9.499999999999998, which we still
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// round to 10 for whole bits per key.
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computed += 0.5;
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computed /= 1234567.0;
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computed *= 1234567.0;
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computed -= 0.5;
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some_computed_less_than_denoted |= (computed < bpk.first);
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ResetPolicy(computed);
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bfp = GetBloomLikeFilterPolicy();
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EXPECT_EQ(bpk.second, bfp->GetMillibitsPerKey());
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EXPECT_EQ((bpk.second + 500) / 1000, bfp->GetWholeBitsPerKey());
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auto bits_builder = GetBuiltinFilterBitsBuilder();
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if (bpk.second == 0) {
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ASSERT_EQ(bits_builder, nullptr);
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continue;
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}
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size_t n = 1;
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size_t space = 0;
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for (; n < 1000000; n += 1 + n / 1000) {
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// Ensure consistency between CalculateSpace and ApproximateNumEntries
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space = bits_builder->CalculateSpace(n);
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size_t n2 = bits_builder->ApproximateNumEntries(space);
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EXPECT_GE(n2, n);
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size_t space2 = bits_builder->CalculateSpace(n2);
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if (n > 12000 && GetParam() == kStandard128Ribbon) {
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// TODO(peterd): better approximation?
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EXPECT_GE(space2, space);
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EXPECT_LE(space2 * 0.998, space * 1.0);
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} else {
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EXPECT_EQ(space2, space);
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}
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}
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// Until size_t overflow
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for (; n < (n + n / 3); n += n / 3) {
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// Ensure space computation is not overflowing; capped is OK
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size_t space2 = bits_builder->CalculateSpace(n);
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EXPECT_GE(space2, space);
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space = space2;
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}
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}
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// Check that the compiler hasn't optimized our computation into nothing
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EXPECT_TRUE(some_computed_less_than_denoted);
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ResetPolicy();
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}
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TEST_P(FullBloomTest, FullEmptyFilter) {
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// Empty filter is not match, at this level
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ASSERT_TRUE(!Matches("hello"));
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ASSERT_TRUE(!Matches("world"));
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}
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TEST_P(FullBloomTest, FullSmall) {
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Add("hello");
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Add("world");
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ASSERT_TRUE(Matches("hello"));
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ASSERT_TRUE(Matches("world"));
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ASSERT_TRUE(!Matches("x"));
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ASSERT_TRUE(!Matches("foo"));
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}
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TEST_P(FullBloomTest, FullVaryingLengths) {
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char buffer[sizeof(int)];
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// Count number of filters that significantly exceed the false positive rate
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int mediocre_filters = 0;
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int good_filters = 0;
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for (int length = 1; length <= 10000; length = NextLength(length)) {
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Reset();
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for (int i = 0; i < length; i++) {
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Add(Key(i, buffer));
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}
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Build();
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EXPECT_LE(FilterSize(), (size_t)((length * FLAGS_bits_per_key / 8) +
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CACHE_LINE_SIZE * 2 + 5));
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// All added keys must match
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for (int i = 0; i < length; i++) {
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ASSERT_TRUE(Matches(Key(i, buffer)))
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<< "Length " << length << "; key " << i;
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}
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// Check false positive rate
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double rate = FalsePositiveRate();
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if (kVerbose >= 1) {
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fprintf(stderr, "False positives: %5.2f%% @ length = %6d ; bytes = %6d\n",
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rate*100.0, length, static_cast<int>(FilterSize()));
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}
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if (FLAGS_bits_per_key == 10) {
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EXPECT_LE(rate, 0.02); // Must not be over 2%
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if (rate > 0.0125) {
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mediocre_filters++; // Allowed, but not too often
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} else {
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good_filters++;
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}
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}
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}
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if (kVerbose >= 1) {
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fprintf(stderr, "Filters: %d good, %d mediocre\n",
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good_filters, mediocre_filters);
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}
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EXPECT_LE(mediocre_filters, good_filters / 5);
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}
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TEST_P(FullBloomTest, OptimizeForMemory) {
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char buffer[sizeof(int)];
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for (bool offm : {true, false}) {
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table_options_.optimize_filters_for_memory = offm;
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ResetPolicy();
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Random32 rnd(12345);
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uint64_t total_size = 0;
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uint64_t total_mem = 0;
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int64_t total_keys = 0;
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double total_fp_rate = 0;
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constexpr int nfilters = 100;
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for (int i = 0; i < nfilters; ++i) {
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int nkeys = static_cast<int>(rnd.Uniformish(10000)) + 100;
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Reset();
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for (int j = 0; j < nkeys; ++j) {
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Add(Key(j, buffer));
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}
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Build();
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size_t size = FilterData().size();
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total_size += size;
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// optimize_filters_for_memory currently depends on malloc_usable_size
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// but we run the rest of the test to ensure no bad behavior without it.
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#ifdef ROCKSDB_MALLOC_USABLE_SIZE
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size = malloc_usable_size(const_cast<char*>(FilterData().data()));
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#endif // ROCKSDB_MALLOC_USABLE_SIZE
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total_mem += size;
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total_keys += nkeys;
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total_fp_rate += FalsePositiveRate();
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}
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if (FLAGS_bits_per_key == 10) {
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EXPECT_LE(total_fp_rate / double{nfilters}, 0.011);
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EXPECT_GE(total_fp_rate / double{nfilters},
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CACHE_LINE_SIZE >= 256 ? 0.007 : 0.008);
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}
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int64_t ex_min_total_size = int64_t{FLAGS_bits_per_key} * total_keys / 8;
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if (GetParam() == kStandard128Ribbon) {
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// ~ 30% savings vs. Bloom filter
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ex_min_total_size = 7 * ex_min_total_size / 10;
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}
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EXPECT_GE(static_cast<int64_t>(total_size), ex_min_total_size);
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int64_t blocked_bloom_overhead = nfilters * (CACHE_LINE_SIZE + 5);
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if (GetParam() == kLegacyBloom) {
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// this config can add extra cache line to make odd number
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blocked_bloom_overhead += nfilters * CACHE_LINE_SIZE;
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}
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EXPECT_GE(total_mem, total_size);
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// optimize_filters_for_memory not implemented with legacy Bloom
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if (offm && GetParam() != kLegacyBloom) {
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// This value can include a small extra penalty for kExtraPadding
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fprintf(stderr, "Internal fragmentation (optimized): %g%%\n",
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(total_mem - total_size) * 100.0 / total_size);
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// Less than 1% internal fragmentation
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EXPECT_LE(total_mem, total_size * 101 / 100);
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// Up to 2% storage penalty
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EXPECT_LE(static_cast<int64_t>(total_size),
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ex_min_total_size * 102 / 100 + blocked_bloom_overhead);
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} else {
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fprintf(stderr, "Internal fragmentation (not optimized): %g%%\n",
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(total_mem - total_size) * 100.0 / total_size);
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// TODO: add control checks for more allocators?
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#ifdef ROCKSDB_JEMALLOC
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fprintf(stderr, "Jemalloc detected? %d\n", HasJemalloc());
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if (HasJemalloc()) {
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#ifdef ROCKSDB_MALLOC_USABLE_SIZE
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// More than 5% internal fragmentation
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EXPECT_GE(total_mem, total_size * 105 / 100);
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#endif // ROCKSDB_MALLOC_USABLE_SIZE
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}
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#endif // ROCKSDB_JEMALLOC
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// No storage penalty, just usual overhead
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EXPECT_LE(static_cast<int64_t>(total_size),
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ex_min_total_size + blocked_bloom_overhead);
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}
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}
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}
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class ChargeFilterConstructionTest : public testing::Test {};
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TEST_F(ChargeFilterConstructionTest, RibbonFilterFallBackOnLargeBanding) {
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constexpr std::size_t kCacheCapacity =
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8 * CacheReservationManagerImpl<
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CacheEntryRole::kFilterConstruction>::GetDummyEntrySize();
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constexpr std::size_t num_entries_for_cache_full = kCacheCapacity / 8;
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for (CacheEntryRoleOptions::Decision charge_filter_construction_mem :
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{CacheEntryRoleOptions::Decision::kEnabled,
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CacheEntryRoleOptions::Decision::kDisabled}) {
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bool will_fall_back = charge_filter_construction_mem ==
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CacheEntryRoleOptions::Decision::kEnabled;
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BlockBasedTableOptions table_options;
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table_options.cache_usage_options.options_overrides.insert(
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{CacheEntryRole::kFilterConstruction,
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{/*.charged = */ charge_filter_construction_mem}});
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LRUCacheOptions lo;
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lo.capacity = kCacheCapacity;
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lo.num_shard_bits = 0; // 2^0 shard
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lo.strict_capacity_limit = true;
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std::shared_ptr<Cache> cache(NewLRUCache(lo));
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table_options.block_cache = cache;
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table_options.filter_policy =
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BloomLikeFilterPolicy::Create(kStandard128Ribbon, FLAGS_bits_per_key);
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FilterBuildingContext ctx(table_options);
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std::unique_ptr<FilterBitsBuilder> filter_bits_builder(
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table_options.filter_policy->GetBuilderWithContext(ctx));
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char key_buffer[sizeof(int)];
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for (std::size_t i = 0; i < num_entries_for_cache_full; ++i) {
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filter_bits_builder->AddKey(Key(static_cast<int>(i), key_buffer));
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}
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std::unique_ptr<const char[]> buf;
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|
Slice filter = filter_bits_builder->Finish(&buf);
|
|
|
|
// To verify Ribbon Filter fallbacks to Bloom Filter properly
|
|
// based on cache charging result
|
|
// See BloomFilterPolicy::GetBloomBitsReader re: metadata
|
|
// -1 = Marker for newer Bloom implementations
|
|
// -2 = Marker for Standard128 Ribbon
|
|
if (will_fall_back) {
|
|
EXPECT_EQ(filter.data()[filter.size() - 5], static_cast<char>(-1));
|
|
} else {
|
|
EXPECT_EQ(filter.data()[filter.size() - 5], static_cast<char>(-2));
|
|
}
|
|
|
|
if (charge_filter_construction_mem ==
|
|
CacheEntryRoleOptions::Decision::kEnabled) {
|
|
const size_t dummy_entry_num = static_cast<std::size_t>(std::ceil(
|
|
filter.size() * 1.0 /
|
|
CacheReservationManagerImpl<
|
|
CacheEntryRole::kFilterConstruction>::GetDummyEntrySize()));
|
|
EXPECT_GE(
|
|
cache->GetPinnedUsage(),
|
|
dummy_entry_num *
|
|
CacheReservationManagerImpl<
|
|
CacheEntryRole::kFilterConstruction>::GetDummyEntrySize());
|
|
EXPECT_LT(
|
|
cache->GetPinnedUsage(),
|
|
(dummy_entry_num + 1) *
|
|
CacheReservationManagerImpl<
|
|
CacheEntryRole::kFilterConstruction>::GetDummyEntrySize());
|
|
} else {
|
|
EXPECT_EQ(cache->GetPinnedUsage(), 0);
|
|
}
|
|
}
|
|
}
|
|
|
|
namespace {
|
|
inline uint32_t SelectByCacheLineSize(uint32_t for64, uint32_t for128,
|
|
uint32_t for256) {
|
|
(void)for64;
|
|
(void)for128;
|
|
(void)for256;
|
|
#if CACHE_LINE_SIZE == 64
|
|
return for64;
|
|
#elif CACHE_LINE_SIZE == 128
|
|
return for128;
|
|
#elif CACHE_LINE_SIZE == 256
|
|
return for256;
|
|
#else
|
|
#error "CACHE_LINE_SIZE unknown or unrecognized"
|
|
#endif
|
|
}
|
|
} // namespace
|
|
|
|
// Ensure the implementation doesn't accidentally change in an
|
|
// incompatible way. This test doesn't check the reading side
|
|
// (FirstFPs/PackedMatches) for LegacyBloom because it requires the
|
|
// ability to read filters generated using other cache line sizes.
|
|
// See RawSchema.
|
|
TEST_P(FullBloomTest, Schema) {
|
|
#define EXPECT_EQ_Bloom(a, b) \
|
|
{ \
|
|
if (GetParam() != kStandard128Ribbon) { \
|
|
EXPECT_EQ(a, b); \
|
|
} \
|
|
}
|
|
#define EXPECT_EQ_Ribbon(a, b) \
|
|
{ \
|
|
if (GetParam() == kStandard128Ribbon) { \
|
|
EXPECT_EQ(a, b); \
|
|
} \
|
|
}
|
|
#define EXPECT_EQ_FastBloom(a, b) \
|
|
{ \
|
|
if (GetParam() == kFastLocalBloom) { \
|
|
EXPECT_EQ(a, b); \
|
|
} \
|
|
}
|
|
#define EXPECT_EQ_LegacyBloom(a, b) \
|
|
{ \
|
|
if (GetParam() == kLegacyBloom) { \
|
|
EXPECT_EQ(a, b); \
|
|
} \
|
|
}
|
|
#define EXPECT_EQ_NotLegacy(a, b) \
|
|
{ \
|
|
if (GetParam() != kLegacyBloom) { \
|
|
EXPECT_EQ(a, b); \
|
|
} \
|
|
}
|
|
|
|
char buffer[sizeof(int)];
|
|
|
|
// First do a small number of keys, where Ribbon config will fall back on
|
|
// fast Bloom filter and generate the same data
|
|
ResetPolicy(5); // num_probes = 3
|
|
for (int key = 0; key < 87; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ(GetNumProbesFromFilterData(), 3);
|
|
|
|
EXPECT_EQ_NotLegacy(BloomHash(FilterData()), 4130687756U);
|
|
|
|
EXPECT_EQ_NotLegacy("31,38,40,43,61,83,86,112,125,131", FirstFPs(10));
|
|
|
|
// Now use enough keys so that changing bits / key by 1 is guaranteed to
|
|
// change number of allocated cache lines. So keys > max cache line bits.
|
|
|
|
// Note that the first attempted Ribbon seed is determined by the hash
|
|
// of the first key added (for pseudorandomness in practice, determinism in
|
|
// testing)
|
|
|
|
ResetPolicy(2); // num_probes = 1
|
|
for (int key = 0; key < 2087; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ_Bloom(GetNumProbesFromFilterData(), 1);
|
|
EXPECT_EQ_Ribbon(GetRibbonSeedFromFilterData(), 61);
|
|
|
|
EXPECT_EQ_LegacyBloom(
|
|
BloomHash(FilterData()),
|
|
SelectByCacheLineSize(1567096579, 1964771444, 2659542661U));
|
|
EXPECT_EQ_FastBloom(BloomHash(FilterData()), 3817481309U);
|
|
EXPECT_EQ_Ribbon(BloomHash(FilterData()), 1705851228U);
|
|
|
|
EXPECT_EQ_FastBloom("11,13,17,25,29,30,35,37,45,53", FirstFPs(10));
|
|
EXPECT_EQ_Ribbon("3,8,10,17,19,20,23,28,31,32", FirstFPs(10));
|
|
|
|
ResetPolicy(3); // num_probes = 2
|
|
for (int key = 0; key < 2087; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ_Bloom(GetNumProbesFromFilterData(), 2);
|
|
EXPECT_EQ_Ribbon(GetRibbonSeedFromFilterData(), 61);
|
|
|
|
EXPECT_EQ_LegacyBloom(
|
|
BloomHash(FilterData()),
|
|
SelectByCacheLineSize(2707206547U, 2571983456U, 218344685));
|
|
EXPECT_EQ_FastBloom(BloomHash(FilterData()), 2807269961U);
|
|
EXPECT_EQ_Ribbon(BloomHash(FilterData()), 1095342358U);
|
|
|
|
EXPECT_EQ_FastBloom("4,15,17,24,27,28,29,53,63,70", FirstFPs(10));
|
|
EXPECT_EQ_Ribbon("3,17,20,28,32,33,36,43,49,54", FirstFPs(10));
|
|
|
|
ResetPolicy(5); // num_probes = 3
|
|
for (int key = 0; key < 2087; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ_Bloom(GetNumProbesFromFilterData(), 3);
|
|
EXPECT_EQ_Ribbon(GetRibbonSeedFromFilterData(), 61);
|
|
|
|
EXPECT_EQ_LegacyBloom(
|
|
BloomHash(FilterData()),
|
|
SelectByCacheLineSize(515748486, 94611728, 2436112214U));
|
|
EXPECT_EQ_FastBloom(BloomHash(FilterData()), 204628445U);
|
|
EXPECT_EQ_Ribbon(BloomHash(FilterData()), 3971337699U);
|
|
|
|
EXPECT_EQ_FastBloom("15,24,29,39,53,87,89,100,103,104", FirstFPs(10));
|
|
EXPECT_EQ_Ribbon("3,33,36,43,67,70,76,78,84,102", FirstFPs(10));
|
|
|
|
ResetPolicy(8); // num_probes = 5
|
|
for (int key = 0; key < 2087; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ_Bloom(GetNumProbesFromFilterData(), 5);
|
|
EXPECT_EQ_Ribbon(GetRibbonSeedFromFilterData(), 61);
|
|
|
|
EXPECT_EQ_LegacyBloom(
|
|
BloomHash(FilterData()),
|
|
SelectByCacheLineSize(1302145999, 2811644657U, 756553699));
|
|
EXPECT_EQ_FastBloom(BloomHash(FilterData()), 355564975U);
|
|
EXPECT_EQ_Ribbon(BloomHash(FilterData()), 3651449053U);
|
|
|
|
EXPECT_EQ_FastBloom("16,60,66,126,220,238,244,256,265,287", FirstFPs(10));
|
|
EXPECT_EQ_Ribbon("33,187,203,296,300,322,411,419,547,582", FirstFPs(10));
|
|
|
|
ResetPolicy(9); // num_probes = 6
|
|
for (int key = 0; key < 2087; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ_Bloom(GetNumProbesFromFilterData(), 6);
|
|
EXPECT_EQ_Ribbon(GetRibbonSeedFromFilterData(), 61);
|
|
|
|
EXPECT_EQ_LegacyBloom(
|
|
BloomHash(FilterData()),
|
|
SelectByCacheLineSize(2092755149, 661139132, 1182970461));
|
|
EXPECT_EQ_FastBloom(BloomHash(FilterData()), 2137566013U);
|
|
EXPECT_EQ_Ribbon(BloomHash(FilterData()), 1005676675U);
|
|
|
|
EXPECT_EQ_FastBloom("156,367,791,872,945,1015,1139,1159,1265", FirstFPs(9));
|
|
EXPECT_EQ_Ribbon("33,187,203,296,411,419,604,612,615,619", FirstFPs(10));
|
|
|
|
ResetPolicy(11); // num_probes = 7
|
|
for (int key = 0; key < 2087; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ_Bloom(GetNumProbesFromFilterData(), 7);
|
|
EXPECT_EQ_Ribbon(GetRibbonSeedFromFilterData(), 61);
|
|
|
|
EXPECT_EQ_LegacyBloom(
|
|
BloomHash(FilterData()),
|
|
SelectByCacheLineSize(3755609649U, 1812694762, 1449142939));
|
|
EXPECT_EQ_FastBloom(BloomHash(FilterData()), 2561502687U);
|
|
EXPECT_EQ_Ribbon(BloomHash(FilterData()), 3129900846U);
|
|
|
|
EXPECT_EQ_FastBloom("34,74,130,236,643,882,962,1015,1035,1110", FirstFPs(10));
|
|
EXPECT_EQ_Ribbon("411,419,623,665,727,794,955,1052,1323,1330", FirstFPs(10));
|
|
|
|
// This used to be 9 probes, but 8 is a better choice for speed,
|
|
// especially with SIMD groups of 8 probes, with essentially no
|
|
// change in FP rate.
|
|
// FP rate @ 9 probes, old Bloom: 0.4321%
|
|
// FP rate @ 9 probes, new Bloom: 0.1846%
|
|
// FP rate @ 8 probes, new Bloom: 0.1843%
|
|
ResetPolicy(14); // num_probes = 8 (new), 9 (old)
|
|
for (int key = 0; key < 2087; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ_LegacyBloom(GetNumProbesFromFilterData(), 9);
|
|
EXPECT_EQ_FastBloom(GetNumProbesFromFilterData(), 8);
|
|
EXPECT_EQ_Ribbon(GetRibbonSeedFromFilterData(), 61);
|
|
|
|
EXPECT_EQ_LegacyBloom(
|
|
BloomHash(FilterData()),
|
|
SelectByCacheLineSize(178861123, 379087593, 2574136516U));
|
|
EXPECT_EQ_FastBloom(BloomHash(FilterData()), 3709876890U);
|
|
EXPECT_EQ_Ribbon(BloomHash(FilterData()), 1855638875U);
|
|
|
|
EXPECT_EQ_FastBloom("130,240,522,565,989,2002,2526,3147,3543", FirstFPs(9));
|
|
EXPECT_EQ_Ribbon("665,727,1323,1755,3866,4232,4442,4492,4736", FirstFPs(9));
|
|
|
|
// This used to be 11 probes, but 9 is a better choice for speed
|
|
// AND accuracy.
|
|
// FP rate @ 11 probes, old Bloom: 0.3571%
|
|
// FP rate @ 11 probes, new Bloom: 0.0884%
|
|
// FP rate @ 9 probes, new Bloom: 0.0843%
|
|
ResetPolicy(16); // num_probes = 9 (new), 11 (old)
|
|
for (int key = 0; key < 2087; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ_LegacyBloom(GetNumProbesFromFilterData(), 11);
|
|
EXPECT_EQ_FastBloom(GetNumProbesFromFilterData(), 9);
|
|
EXPECT_EQ_Ribbon(GetRibbonSeedFromFilterData(), 61);
|
|
|
|
EXPECT_EQ_LegacyBloom(
|
|
BloomHash(FilterData()),
|
|
SelectByCacheLineSize(1129406313, 3049154394U, 1727750964));
|
|
EXPECT_EQ_FastBloom(BloomHash(FilterData()), 1087138490U);
|
|
EXPECT_EQ_Ribbon(BloomHash(FilterData()), 459379967U);
|
|
|
|
EXPECT_EQ_FastBloom("3299,3611,3916,6620,7822,8079,8482,8942", FirstFPs(8));
|
|
EXPECT_EQ_Ribbon("727,1323,1755,4442,4736,5386,6974,7154,8222", FirstFPs(9));
|
|
|
|
ResetPolicy(10); // num_probes = 6, but different memory ratio vs. 9
|
|
for (int key = 0; key < 2087; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ_Bloom(GetNumProbesFromFilterData(), 6);
|
|
EXPECT_EQ_Ribbon(GetRibbonSeedFromFilterData(), 61);
|
|
|
|
EXPECT_EQ_LegacyBloom(
|
|
BloomHash(FilterData()),
|
|
SelectByCacheLineSize(1478976371, 2910591341U, 1182970461));
|
|
EXPECT_EQ_FastBloom(BloomHash(FilterData()), 2498541272U);
|
|
EXPECT_EQ_Ribbon(BloomHash(FilterData()), 1273231667U);
|
|
|
|
EXPECT_EQ_FastBloom("16,126,133,422,466,472,813,1002,1035", FirstFPs(9));
|
|
EXPECT_EQ_Ribbon("296,411,419,612,619,623,630,665,686,727", FirstFPs(10));
|
|
|
|
ResetPolicy(10);
|
|
for (int key = /*CHANGED*/ 1; key < 2087; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ_Bloom(GetNumProbesFromFilterData(), 6);
|
|
EXPECT_EQ_Ribbon(GetRibbonSeedFromFilterData(), /*CHANGED*/ 184);
|
|
|
|
EXPECT_EQ_LegacyBloom(
|
|
BloomHash(FilterData()),
|
|
SelectByCacheLineSize(4205696321U, 1132081253U, 2385981855U));
|
|
EXPECT_EQ_FastBloom(BloomHash(FilterData()), 2058382345U);
|
|
EXPECT_EQ_Ribbon(BloomHash(FilterData()), 3007790572U);
|
|
|
|
EXPECT_EQ_FastBloom("16,126,133,422,466,472,813,1002,1035", FirstFPs(9));
|
|
EXPECT_EQ_Ribbon("33,152,383,497,589,633,737,781,911,990", FirstFPs(10));
|
|
|
|
ResetPolicy(10);
|
|
for (int key = 1; key < /*CHANGED*/ 2088; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ_Bloom(GetNumProbesFromFilterData(), 6);
|
|
EXPECT_EQ_Ribbon(GetRibbonSeedFromFilterData(), 184);
|
|
|
|
EXPECT_EQ_LegacyBloom(
|
|
BloomHash(FilterData()),
|
|
SelectByCacheLineSize(2885052954U, 769447944, 4175124908U));
|
|
EXPECT_EQ_FastBloom(BloomHash(FilterData()), 23699164U);
|
|
EXPECT_EQ_Ribbon(BloomHash(FilterData()), 1942323379U);
|
|
|
|
EXPECT_EQ_FastBloom("16,126,133,422,466,472,813,1002,1035", FirstFPs(9));
|
|
EXPECT_EQ_Ribbon("33,95,360,589,737,911,990,1048,1081,1414", FirstFPs(10));
|
|
|
|
// With new fractional bits_per_key, check that we are rounding to
|
|
// whole bits per key for old Bloom filters but fractional for
|
|
// new Bloom filter.
|
|
ResetPolicy(9.5);
|
|
for (int key = 1; key < 2088; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ_Bloom(GetNumProbesFromFilterData(), 6);
|
|
EXPECT_EQ_Ribbon(GetRibbonSeedFromFilterData(), 184);
|
|
|
|
EXPECT_EQ_LegacyBloom(
|
|
BloomHash(FilterData()),
|
|
/*SAME*/ SelectByCacheLineSize(2885052954U, 769447944, 4175124908U));
|
|
EXPECT_EQ_FastBloom(BloomHash(FilterData()), 3166884174U);
|
|
EXPECT_EQ_Ribbon(BloomHash(FilterData()), 1148258663U);
|
|
|
|
EXPECT_EQ_FastBloom("126,156,367,444,458,791,813,976,1015", FirstFPs(9));
|
|
EXPECT_EQ_Ribbon("33,54,95,360,589,693,737,911,990,1048", FirstFPs(10));
|
|
|
|
ResetPolicy(10.499);
|
|
for (int key = 1; key < 2088; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ_LegacyBloom(GetNumProbesFromFilterData(), 6);
|
|
EXPECT_EQ_FastBloom(GetNumProbesFromFilterData(), 7);
|
|
EXPECT_EQ_Ribbon(GetRibbonSeedFromFilterData(), 184);
|
|
|
|
EXPECT_EQ_LegacyBloom(
|
|
BloomHash(FilterData()),
|
|
/*SAME*/ SelectByCacheLineSize(2885052954U, 769447944, 4175124908U));
|
|
EXPECT_EQ_FastBloom(BloomHash(FilterData()), 4098502778U);
|
|
EXPECT_EQ_Ribbon(BloomHash(FilterData()), 792138188U);
|
|
|
|
EXPECT_EQ_FastBloom("16,236,240,472,1015,1045,1111,1409,1465", FirstFPs(9));
|
|
EXPECT_EQ_Ribbon("33,95,360,589,737,990,1048,1081,1414,1643", FirstFPs(10));
|
|
|
|
ResetPolicy();
|
|
}
|
|
|
|
// A helper class for testing custom or corrupt filter bits as read by
|
|
// built-in FilterBitsReaders.
|
|
struct RawFilterTester {
|
|
// Buffer, from which we always return a tail Slice, so the
|
|
// last five bytes are always the metadata bytes.
|
|
std::array<char, 3000> data_;
|
|
// Points five bytes from the end
|
|
char* metadata_ptr_;
|
|
|
|
RawFilterTester() : metadata_ptr_(&*(data_.end() - 5)) {}
|
|
|
|
Slice ResetNoFill(uint32_t len_without_metadata, uint32_t num_lines,
|
|
uint32_t num_probes) {
|
|
metadata_ptr_[0] = static_cast<char>(num_probes);
|
|
EncodeFixed32(metadata_ptr_ + 1, num_lines);
|
|
uint32_t len = len_without_metadata + /*metadata*/ 5;
|
|
assert(len <= data_.size());
|
|
return Slice(metadata_ptr_ - len_without_metadata, len);
|
|
}
|
|
|
|
Slice Reset(uint32_t len_without_metadata, uint32_t num_lines,
|
|
uint32_t num_probes, bool fill_ones) {
|
|
data_.fill(fill_ones ? 0xff : 0);
|
|
return ResetNoFill(len_without_metadata, num_lines, num_probes);
|
|
}
|
|
|
|
Slice ResetWeirdFill(uint32_t len_without_metadata, uint32_t num_lines,
|
|
uint32_t num_probes) {
|
|
for (uint32_t i = 0; i < data_.size(); ++i) {
|
|
data_[i] = static_cast<char>(0x7b7b >> (i % 7));
|
|
}
|
|
return ResetNoFill(len_without_metadata, num_lines, num_probes);
|
|
}
|
|
};
|
|
|
|
TEST_P(FullBloomTest, RawSchema) {
|
|
RawFilterTester cft;
|
|
// Legacy Bloom configurations
|
|
// Two probes, about 3/4 bits set: ~50% "FP" rate
|
|
// One 256-byte cache line.
|
|
OpenRaw(cft.ResetWeirdFill(256, 1, 2));
|
|
EXPECT_EQ(uint64_t{11384799501900898790U}, PackedMatches());
|
|
|
|
// Two 128-byte cache lines.
|
|
OpenRaw(cft.ResetWeirdFill(256, 2, 2));
|
|
EXPECT_EQ(uint64_t{10157853359773492589U}, PackedMatches());
|
|
|
|
// Four 64-byte cache lines.
|
|
OpenRaw(cft.ResetWeirdFill(256, 4, 2));
|
|
EXPECT_EQ(uint64_t{7123594913907464682U}, PackedMatches());
|
|
|
|
// Fast local Bloom configurations (marker 255 -> -1)
|
|
// Two probes, about 3/4 bits set: ~50% "FP" rate
|
|
// Four 64-byte cache lines.
|
|
OpenRaw(cft.ResetWeirdFill(256, 2U << 8, 255));
|
|
EXPECT_EQ(uint64_t{9957045189927952471U}, PackedMatches());
|
|
|
|
// Ribbon configurations (marker 254 -> -2)
|
|
|
|
// Even though the builder never builds configurations this
|
|
// small (preferring Bloom), we can test that the configuration
|
|
// can be read, for possible future-proofing.
|
|
|
|
// 256 slots, one result column = 32 bytes (2 blocks, seed 0)
|
|
// ~50% FP rate:
|
|
// 0b0101010111110101010000110000011011011111100100001110010011101010
|
|
OpenRaw(cft.ResetWeirdFill(32, 2U << 8, 254));
|
|
EXPECT_EQ(uint64_t{6193930559317665002U}, PackedMatches());
|
|
|
|
// 256 slots, three-to-four result columns = 112 bytes
|
|
// ~ 1 in 10 FP rate:
|
|
// 0b0000000000100000000000000000000001000001000000010000101000000000
|
|
OpenRaw(cft.ResetWeirdFill(112, 2U << 8, 254));
|
|
EXPECT_EQ(uint64_t{9007200345328128U}, PackedMatches());
|
|
}
|
|
|
|
TEST_P(FullBloomTest, CorruptFilters) {
|
|
RawFilterTester cft;
|
|
|
|
for (bool fill : {false, true}) {
|
|
// Legacy Bloom configurations
|
|
// Good filter bits - returns same as fill
|
|
OpenRaw(cft.Reset(CACHE_LINE_SIZE, 1, 6, fill));
|
|
ASSERT_EQ(fill, Matches("hello"));
|
|
ASSERT_EQ(fill, Matches("world"));
|
|
|
|
// Good filter bits - returns same as fill
|
|
OpenRaw(cft.Reset(CACHE_LINE_SIZE * 3, 3, 6, fill));
|
|
ASSERT_EQ(fill, Matches("hello"));
|
|
ASSERT_EQ(fill, Matches("world"));
|
|
|
|
// Good filter bits - returns same as fill
|
|
// 256 is unusual but legal cache line size
|
|
OpenRaw(cft.Reset(256 * 3, 3, 6, fill));
|
|
ASSERT_EQ(fill, Matches("hello"));
|
|
ASSERT_EQ(fill, Matches("world"));
|
|
|
|
// Good filter bits - returns same as fill
|
|
// 30 should be max num_probes
|
|
OpenRaw(cft.Reset(CACHE_LINE_SIZE, 1, 30, fill));
|
|
ASSERT_EQ(fill, Matches("hello"));
|
|
ASSERT_EQ(fill, Matches("world"));
|
|
|
|
// Good filter bits - returns same as fill
|
|
// 1 should be min num_probes
|
|
OpenRaw(cft.Reset(CACHE_LINE_SIZE, 1, 1, fill));
|
|
ASSERT_EQ(fill, Matches("hello"));
|
|
ASSERT_EQ(fill, Matches("world"));
|
|
|
|
// Type 1 trivial filter bits - returns true as if FP by zero probes
|
|
OpenRaw(cft.Reset(CACHE_LINE_SIZE, 1, 0, fill));
|
|
ASSERT_TRUE(Matches("hello"));
|
|
ASSERT_TRUE(Matches("world"));
|
|
|
|
// Type 2 trivial filter bits - returns false as if built from zero keys
|
|
OpenRaw(cft.Reset(0, 0, 6, fill));
|
|
ASSERT_FALSE(Matches("hello"));
|
|
ASSERT_FALSE(Matches("world"));
|
|
|
|
// Type 2 trivial filter bits - returns false as if built from zero keys
|
|
OpenRaw(cft.Reset(0, 37, 6, fill));
|
|
ASSERT_FALSE(Matches("hello"));
|
|
ASSERT_FALSE(Matches("world"));
|
|
|
|
// Type 2 trivial filter bits - returns false as 0 size trumps 0 probes
|
|
OpenRaw(cft.Reset(0, 0, 0, fill));
|
|
ASSERT_FALSE(Matches("hello"));
|
|
ASSERT_FALSE(Matches("world"));
|
|
|
|
// Bad filter bits - returns true for safety
|
|
// No solution to 0 * x == CACHE_LINE_SIZE
|
|
OpenRaw(cft.Reset(CACHE_LINE_SIZE, 0, 6, fill));
|
|
ASSERT_TRUE(Matches("hello"));
|
|
ASSERT_TRUE(Matches("world"));
|
|
|
|
// Bad filter bits - returns true for safety
|
|
// Can't have 3 * x == 4 for integer x
|
|
OpenRaw(cft.Reset(4, 3, 6, fill));
|
|
ASSERT_TRUE(Matches("hello"));
|
|
ASSERT_TRUE(Matches("world"));
|
|
|
|
// Bad filter bits - returns true for safety
|
|
// 97 bytes is not a power of two, so not a legal cache line size
|
|
OpenRaw(cft.Reset(97 * 3, 3, 6, fill));
|
|
ASSERT_TRUE(Matches("hello"));
|
|
ASSERT_TRUE(Matches("world"));
|
|
|
|
// Bad filter bits - returns true for safety
|
|
// 65 bytes is not a power of two, so not a legal cache line size
|
|
OpenRaw(cft.Reset(65 * 3, 3, 6, fill));
|
|
ASSERT_TRUE(Matches("hello"));
|
|
ASSERT_TRUE(Matches("world"));
|
|
|
|
// Bad filter bits - returns false as if built from zero keys
|
|
// < 5 bytes overall means missing even metadata
|
|
OpenRaw(cft.Reset(static_cast<uint32_t>(-1), 3, 6, fill));
|
|
ASSERT_FALSE(Matches("hello"));
|
|
ASSERT_FALSE(Matches("world"));
|
|
|
|
OpenRaw(cft.Reset(static_cast<uint32_t>(-5), 3, 6, fill));
|
|
ASSERT_FALSE(Matches("hello"));
|
|
ASSERT_FALSE(Matches("world"));
|
|
|
|
// Dubious filter bits - returns same as fill (for now)
|
|
// 31 is not a useful num_probes, nor generated by RocksDB unless directly
|
|
// using filter bits API without BloomFilterPolicy.
|
|
OpenRaw(cft.Reset(CACHE_LINE_SIZE, 1, 31, fill));
|
|
ASSERT_EQ(fill, Matches("hello"));
|
|
ASSERT_EQ(fill, Matches("world"));
|
|
|
|
// Dubious filter bits - returns same as fill (for now)
|
|
// Similar, with 127, largest positive char
|
|
OpenRaw(cft.Reset(CACHE_LINE_SIZE, 1, 127, fill));
|
|
ASSERT_EQ(fill, Matches("hello"));
|
|
ASSERT_EQ(fill, Matches("world"));
|
|
|
|
// Dubious filter bits - returns true (for now)
|
|
// num_probes set to 128 / -128, lowest negative char
|
|
// NB: Bug in implementation interprets this as negative and has same
|
|
// effect as zero probes, but effectively reserves negative char values
|
|
// for future use.
|
|
OpenRaw(cft.Reset(CACHE_LINE_SIZE, 1, 128, fill));
|
|
ASSERT_TRUE(Matches("hello"));
|
|
ASSERT_TRUE(Matches("world"));
|
|
|
|
// Dubious filter bits - returns true (for now)
|
|
// Similar, with 253 / -3
|
|
OpenRaw(cft.Reset(CACHE_LINE_SIZE, 1, 253, fill));
|
|
ASSERT_TRUE(Matches("hello"));
|
|
ASSERT_TRUE(Matches("world"));
|
|
|
|
// #########################################################
|
|
// Fast local Bloom configurations (marker 255 -> -1)
|
|
// Good config with six probes
|
|
OpenRaw(cft.Reset(CACHE_LINE_SIZE, 6U << 8, 255, fill));
|
|
ASSERT_EQ(fill, Matches("hello"));
|
|
ASSERT_EQ(fill, Matches("world"));
|
|
|
|
// Becomes bad/reserved config (always true) if any other byte set
|
|
OpenRaw(cft.Reset(CACHE_LINE_SIZE, (6U << 8) | 1U, 255, fill));
|
|
ASSERT_TRUE(Matches("hello"));
|
|
ASSERT_TRUE(Matches("world"));
|
|
|
|
OpenRaw(cft.Reset(CACHE_LINE_SIZE, (6U << 8) | (1U << 16), 255, fill));
|
|
ASSERT_TRUE(Matches("hello"));
|
|
ASSERT_TRUE(Matches("world"));
|
|
|
|
OpenRaw(cft.Reset(CACHE_LINE_SIZE, (6U << 8) | (1U << 24), 255, fill));
|
|
ASSERT_TRUE(Matches("hello"));
|
|
ASSERT_TRUE(Matches("world"));
|
|
|
|
// Good config, max 30 probes
|
|
OpenRaw(cft.Reset(CACHE_LINE_SIZE, 30U << 8, 255, fill));
|
|
ASSERT_EQ(fill, Matches("hello"));
|
|
ASSERT_EQ(fill, Matches("world"));
|
|
|
|
// Bad/reserved config (always true) if more than 30
|
|
OpenRaw(cft.Reset(CACHE_LINE_SIZE, 31U << 8, 255, fill));
|
|
ASSERT_TRUE(Matches("hello"));
|
|
ASSERT_TRUE(Matches("world"));
|
|
|
|
OpenRaw(cft.Reset(CACHE_LINE_SIZE, 33U << 8, 255, fill));
|
|
ASSERT_TRUE(Matches("hello"));
|
|
ASSERT_TRUE(Matches("world"));
|
|
|
|
OpenRaw(cft.Reset(CACHE_LINE_SIZE, 66U << 8, 255, fill));
|
|
ASSERT_TRUE(Matches("hello"));
|
|
ASSERT_TRUE(Matches("world"));
|
|
|
|
OpenRaw(cft.Reset(CACHE_LINE_SIZE, 130U << 8, 255, fill));
|
|
ASSERT_TRUE(Matches("hello"));
|
|
ASSERT_TRUE(Matches("world"));
|
|
}
|
|
|
|
// #########################################################
|
|
// Ribbon configurations (marker 254 -> -2)
|
|
// ("fill" doesn't work to detect good configurations, we just
|
|
// have to rely on TN probability)
|
|
|
|
// Good: 2 blocks * 16 bytes / segment * 4 columns = 128 bytes
|
|
// seed = 123
|
|
OpenRaw(cft.Reset(128, (2U << 8) + 123U, 254, false));
|
|
ASSERT_FALSE(Matches("hello"));
|
|
ASSERT_FALSE(Matches("world"));
|
|
|
|
// Good: 2 blocks * 16 bytes / segment * 8 columns = 256 bytes
|
|
OpenRaw(cft.Reset(256, (2U << 8) + 123U, 254, false));
|
|
ASSERT_FALSE(Matches("hello"));
|
|
ASSERT_FALSE(Matches("world"));
|
|
|
|
// Surprisingly OK: 5000 blocks (640,000 slots) in only 1024 bits
|
|
// -> average close to 0 columns
|
|
OpenRaw(cft.Reset(128, (5000U << 8) + 123U, 254, false));
|
|
// *Almost* all FPs
|
|
ASSERT_TRUE(Matches("hello"));
|
|
ASSERT_TRUE(Matches("world"));
|
|
// Need many queries to find a "true negative"
|
|
for (int i = 0; Matches(std::to_string(i)); ++i) {
|
|
ASSERT_LT(i, 1000);
|
|
}
|
|
|
|
// Bad: 1 block not allowed (for implementation detail reasons)
|
|
OpenRaw(cft.Reset(128, (1U << 8) + 123U, 254, false));
|
|
ASSERT_TRUE(Matches("hello"));
|
|
ASSERT_TRUE(Matches("world"));
|
|
|
|
// Bad: 0 blocks not allowed
|
|
OpenRaw(cft.Reset(128, (0U << 8) + 123U, 254, false));
|
|
ASSERT_TRUE(Matches("hello"));
|
|
ASSERT_TRUE(Matches("world"));
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Full, FullBloomTest,
|
|
testing::Values(kLegacyBloom, kFastLocalBloom,
|
|
kStandard128Ribbon));
|
|
|
|
static double GetEffectiveBitsPerKey(FilterBitsBuilder* builder) {
|
|
union {
|
|
uint64_t key_value = 0;
|
|
char key_bytes[8];
|
|
};
|
|
|
|
const unsigned kNumKeys = 1000;
|
|
|
|
Slice key_slice{key_bytes, 8};
|
|
for (key_value = 0; key_value < kNumKeys; ++key_value) {
|
|
builder->AddKey(key_slice);
|
|
}
|
|
|
|
std::unique_ptr<const char[]> buf;
|
|
auto filter = builder->Finish(&buf);
|
|
return filter.size() * /*bits per byte*/ 8 / (1.0 * kNumKeys);
|
|
}
|
|
|
|
static void SetTestingLevel(int levelish, FilterBuildingContext* ctx) {
|
|
if (levelish == -1) {
|
|
// Flush is treated as level -1 for this option but actually level 0
|
|
ctx->level_at_creation = 0;
|
|
ctx->reason = TableFileCreationReason::kFlush;
|
|
} else {
|
|
ctx->level_at_creation = levelish;
|
|
ctx->reason = TableFileCreationReason::kCompaction;
|
|
}
|
|
}
|
|
|
|
TEST(RibbonTest, RibbonTestLevelThreshold) {
|
|
BlockBasedTableOptions opts;
|
|
FilterBuildingContext ctx(opts);
|
|
// A few settings
|
|
for (CompactionStyle cs : {kCompactionStyleLevel, kCompactionStyleUniversal,
|
|
kCompactionStyleFIFO, kCompactionStyleNone}) {
|
|
ctx.compaction_style = cs;
|
|
for (int bloom_before_level : {-1, 0, 1, 10}) {
|
|
std::vector<std::unique_ptr<const FilterPolicy> > policies;
|
|
policies.emplace_back(NewRibbonFilterPolicy(10, bloom_before_level));
|
|
|
|
if (bloom_before_level == 0) {
|
|
// Also test new API default
|
|
policies.emplace_back(NewRibbonFilterPolicy(10));
|
|
}
|
|
|
|
for (std::unique_ptr<const FilterPolicy>& policy : policies) {
|
|
// Claim to be generating filter for this level
|
|
SetTestingLevel(bloom_before_level, &ctx);
|
|
|
|
std::unique_ptr<FilterBitsBuilder> builder{
|
|
policy->GetBuilderWithContext(ctx)};
|
|
|
|
// Must be Ribbon (more space efficient than 10 bits per key)
|
|
ASSERT_LT(GetEffectiveBitsPerKey(builder.get()), 8);
|
|
|
|
if (bloom_before_level >= 0) {
|
|
// Claim to be generating filter for previous level
|
|
SetTestingLevel(bloom_before_level - 1, &ctx);
|
|
|
|
builder.reset(policy->GetBuilderWithContext(ctx));
|
|
|
|
if (cs == kCompactionStyleLevel || cs == kCompactionStyleUniversal) {
|
|
// Level is considered.
|
|
// Must be Bloom (~ 10 bits per key)
|
|
ASSERT_GT(GetEffectiveBitsPerKey(builder.get()), 9);
|
|
} else {
|
|
// Level is ignored under non-traditional compaction styles.
|
|
// Must be Ribbon (more space efficient than 10 bits per key)
|
|
ASSERT_LT(GetEffectiveBitsPerKey(builder.get()), 8);
|
|
}
|
|
}
|
|
|
|
// Like SST file writer
|
|
ctx.level_at_creation = -1;
|
|
ctx.reason = TableFileCreationReason::kMisc;
|
|
|
|
builder.reset(policy->GetBuilderWithContext(ctx));
|
|
|
|
// Must be Ribbon (more space efficient than 10 bits per key)
|
|
ASSERT_LT(GetEffectiveBitsPerKey(builder.get()), 8);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
} // namespace ROCKSDB_NAMESPACE
|
|
|
|
int main(int argc, char** argv) {
|
|
::testing::InitGoogleTest(&argc, argv);
|
|
ParseCommandLineFlags(&argc, &argv, true);
|
|
|
|
return RUN_ALL_TESTS();
|
|
}
|
|
|
|
#endif // GFLAGS
|