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57f3032285
Summary: There's no technological impediment to allowing the Bloom filter bits/key to be non-integer (fractional/decimal) values, and it provides finer control over the memory vs. accuracy trade-off. This is especially handy in using the format_version=5 Bloom filter in place of the old one, because bits_per_key=9.55 provides the same accuracy as the old bits_per_key=10. This change not only requires refining the logic for choosing the best num_probes for a given bits/key setting, it revealed a flaw in that logic. As bits/key gets higher, the best num_probes for a cache-local Bloom filter is closer to bpk / 2 than to bpk * 0.69, the best choice for a standard Bloom filter. For example, at 16 bits per key, the best num_probes is 9 (FP rate = 0.0843%) not 11 (FP rate = 0.0884%). This change fixes and refines that logic (for the format_version=5 Bloom filter only, just in case) based on empirical tests to find accuracy inflection points between each num_probes. Although bits_per_key is now specified as a double, the new Bloom filter converts/rounds this to "millibits / key" for predictable/precise internal computations. Just in case of unforeseen compatibility issues, we round to the nearest whole number bits / key for the legacy Bloom filter, so as not to unlock new behaviors for it. Pull Request resolved: https://github.com/facebook/rocksdb/pull/6092 Test Plan: unit tests included Differential Revision: D18711313 Pulled By: pdillinger fbshipit-source-id: 1aa73295f152a995328cb846ef9157ae8a05522a
912 lines
28 KiB
C++
912 lines
28 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 "logging/logging.h"
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#include "memory/arena.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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DEFINE_int32(bits_per_key, 10, "");
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namespace rocksdb {
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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 BlockBasedBloomTest : public testing::Test {
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private:
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std::unique_ptr<const FilterPolicy> policy_;
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std::string filter_;
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std::vector<std::string> keys_;
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public:
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BlockBasedBloomTest() { ResetPolicy(); }
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void Reset() {
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keys_.clear();
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filter_.clear();
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}
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void ResetPolicy(double bits_per_key) {
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policy_.reset(new BloomFilterPolicy(bits_per_key,
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BloomFilterPolicy::kDeprecatedBlock));
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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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keys_.push_back(s.ToString());
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}
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void Build() {
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std::vector<Slice> key_slices;
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for (size_t i = 0; i < keys_.size(); i++) {
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key_slices.push_back(Slice(keys_[i]));
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}
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filter_.clear();
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policy_->CreateFilter(&key_slices[0], static_cast<int>(key_slices.size()),
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&filter_);
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keys_.clear();
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if (kVerbose >= 2) DumpFilter();
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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() const { return Slice(filter_); }
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void DumpFilter() {
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fprintf(stderr, "F(");
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for (size_t i = 0; i+1 < filter_.size(); i++) {
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const unsigned int c = static_cast<unsigned int>(filter_[i]);
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for (int j = 0; j < 8; j++) {
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fprintf(stderr, "%c", (c & (1 <<j)) ? '1' : '.');
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}
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}
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fprintf(stderr, ")\n");
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}
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bool Matches(const Slice& s) {
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if (!keys_.empty()) {
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Build();
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}
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return policy_->KeyMayMatch(s, filter_);
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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_F(BlockBasedBloomTest, EmptyFilter) {
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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_F(BlockBasedBloomTest, Small) {
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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_F(BlockBasedBloomTest, VaryingLengths) {
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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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ASSERT_LE(FilterSize(), (size_t)((length * 10 / 8) + 40)) << length;
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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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ASSERT_LE(rate, 0.02); // Must not be over 2%
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if (rate > 0.0125) mediocre_filters++; // Allowed, but not too often
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else good_filters++;
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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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ASSERT_LE(mediocre_filters, good_filters/5);
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}
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// Ensure the implementation doesn't accidentally change in an
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// incompatible way
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TEST_F(BlockBasedBloomTest, Schema) {
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char buffer[sizeof(int)];
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ResetPolicy(8); // num_probes = 5
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for (int key = 0; key < 87; key++) {
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Add(Key(key, buffer));
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}
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Build();
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ASSERT_EQ(BloomHash(FilterData()), 3589896109U);
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ResetPolicy(9); // num_probes = 6
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for (int key = 0; key < 87; key++) {
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Add(Key(key, buffer));
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}
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Build();
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ASSERT_EQ(BloomHash(FilterData()), 969445585);
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ResetPolicy(11); // num_probes = 7
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for (int key = 0; key < 87; key++) {
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Add(Key(key, buffer));
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}
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Build();
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ASSERT_EQ(BloomHash(FilterData()), 1694458207);
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ResetPolicy(10); // num_probes = 6
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for (int key = 0; key < 87; key++) {
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Add(Key(key, buffer));
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}
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Build();
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ASSERT_EQ(BloomHash(FilterData()), 2373646410U);
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ResetPolicy(10);
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for (int key = /*CHANGED*/ 1; key < 87; key++) {
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Add(Key(key, buffer));
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}
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Build();
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ASSERT_EQ(BloomHash(FilterData()), 1908442116);
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ResetPolicy(10);
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for (int key = 1; key < /*CHANGED*/ 88; key++) {
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Add(Key(key, buffer));
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}
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Build();
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ASSERT_EQ(BloomHash(FilterData()), 3057004015U);
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// With new fractional bits_per_key, check that we are rounding to
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// whole bits per key for old Bloom filters.
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ResetPolicy(9.5); // Treated as 10
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for (int key = 1; key < 88; key++) {
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Add(Key(key, buffer));
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}
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Build();
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ASSERT_EQ(BloomHash(FilterData()), /*SAME*/ 3057004015U);
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ResetPolicy(10.499); // Treated as 10
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for (int key = 1; key < 88; key++) {
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Add(Key(key, buffer));
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}
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Build();
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ASSERT_EQ(BloomHash(FilterData()), /*SAME*/ 3057004015U);
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ResetPolicy();
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}
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// Different bits-per-byte
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class FullBloomTest : public testing::TestWithParam<BloomFilterPolicy::Mode> {
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private:
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BlockBasedTableOptions table_options_;
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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_);
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}
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const BloomFilterPolicy* GetBloomFilterPolicy() {
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// Throws on bad cast
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return &dynamic_cast<const BloomFilterPolicy&>(*policy_);
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}
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void Reset() {
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bits_builder_.reset(FilterBuildingContext(table_options_).GetBuilder());
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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_.reset(new BloomFilterPolicy(bits_per_key, GetParam()));
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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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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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uint32_t SelectByImpl(uint32_t for_legacy_bloom,
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uint32_t for_fast_local_bloom) {
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switch (GetParam()) {
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case BloomFilterPolicy::kLegacyBloom:
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return for_legacy_bloom;
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case BloomFilterPolicy::kFastLocalBloom:
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return for_fast_local_bloom;
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case BloomFilterPolicy::kDeprecatedBlock:
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case BloomFilterPolicy::kAuto:
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/* N/A */;
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}
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// otherwise
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assert(false);
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return 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: enforced minimum is 1 bit per key (1000 millibits), and enforced
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// maximum is 100 bits per key (100000 millibits).
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for (auto bpk :
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std::vector<std::pair<double, int> >{{-HUGE_VAL, 1000},
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{-INFINITY, 1000},
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{0.0, 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 = GetBloomFilterPolicy();
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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 = GetBloomFilterPolicy();
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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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for (int n = 1; n < 100; n++) {
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auto space = bits_builder->CalculateSpace(n);
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auto n2 = bits_builder->CalculateNumEntry(space);
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EXPECT_GE(n2, n);
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auto space2 = bits_builder->CalculateSpace(n2);
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EXPECT_EQ(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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ASSERT_LE(FilterSize(),
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(size_t)((length * 10 / 8) + 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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ASSERT_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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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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ASSERT_LE(mediocre_filters, good_filters/5);
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}
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namespace {
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inline uint32_t SelectByCacheLineSize(uint32_t for64, uint32_t for128,
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uint32_t for256) {
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(void)for64;
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(void)for128;
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(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) {
|
|
char buffer[sizeof(int)];
|
|
|
|
// 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.
|
|
|
|
ResetPolicy(2); // num_probes = 1
|
|
for (int key = 0; key < 2087; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ(GetNumProbesFromFilterData(), 1);
|
|
EXPECT_EQ(
|
|
BloomHash(FilterData()),
|
|
SelectByImpl(SelectByCacheLineSize(1567096579, 1964771444, 2659542661U),
|
|
3817481309U));
|
|
if (GetParam() == BloomFilterPolicy::kFastLocalBloom) {
|
|
EXPECT_EQ("11,13,17,25,29,30,35,37,45,53", FirstFPs(10));
|
|
}
|
|
|
|
ResetPolicy(3); // num_probes = 2
|
|
for (int key = 0; key < 2087; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ(GetNumProbesFromFilterData(), 2);
|
|
EXPECT_EQ(
|
|
BloomHash(FilterData()),
|
|
SelectByImpl(SelectByCacheLineSize(2707206547U, 2571983456U, 218344685),
|
|
2807269961U));
|
|
if (GetParam() == BloomFilterPolicy::kFastLocalBloom) {
|
|
EXPECT_EQ("4,15,17,24,27,28,29,53,63,70", FirstFPs(10));
|
|
}
|
|
|
|
ResetPolicy(5); // num_probes = 3
|
|
for (int key = 0; key < 2087; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ(GetNumProbesFromFilterData(), 3);
|
|
EXPECT_EQ(
|
|
BloomHash(FilterData()),
|
|
SelectByImpl(SelectByCacheLineSize(515748486, 94611728, 2436112214U),
|
|
204628445));
|
|
if (GetParam() == BloomFilterPolicy::kFastLocalBloom) {
|
|
EXPECT_EQ("15,24,29,39,53,87,89,100,103,104", FirstFPs(10));
|
|
}
|
|
|
|
ResetPolicy(8); // num_probes = 5
|
|
for (int key = 0; key < 2087; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ(GetNumProbesFromFilterData(), 5);
|
|
EXPECT_EQ(
|
|
BloomHash(FilterData()),
|
|
SelectByImpl(SelectByCacheLineSize(1302145999, 2811644657U, 756553699),
|
|
355564975));
|
|
if (GetParam() == BloomFilterPolicy::kFastLocalBloom) {
|
|
EXPECT_EQ("16,60,66,126,220,238,244,256,265,287", FirstFPs(10));
|
|
}
|
|
|
|
ResetPolicy(9); // num_probes = 6
|
|
for (int key = 0; key < 2087; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ(GetNumProbesFromFilterData(), 6);
|
|
EXPECT_EQ(
|
|
BloomHash(FilterData()),
|
|
SelectByImpl(SelectByCacheLineSize(2092755149, 661139132, 1182970461),
|
|
2137566013U));
|
|
if (GetParam() == BloomFilterPolicy::kFastLocalBloom) {
|
|
EXPECT_EQ("156,367,791,872,945,1015,1139,1159,1265,1435", FirstFPs(10));
|
|
}
|
|
|
|
ResetPolicy(11); // num_probes = 7
|
|
for (int key = 0; key < 2087; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ(GetNumProbesFromFilterData(), 7);
|
|
EXPECT_EQ(
|
|
BloomHash(FilterData()),
|
|
SelectByImpl(SelectByCacheLineSize(3755609649U, 1812694762, 1449142939),
|
|
2561502687U));
|
|
if (GetParam() == BloomFilterPolicy::kFastLocalBloom) {
|
|
EXPECT_EQ("34,74,130,236,643,882,962,1015,1035,1110", 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(GetNumProbesFromFilterData(), SelectByImpl(9, 8));
|
|
EXPECT_EQ(
|
|
BloomHash(FilterData()),
|
|
SelectByImpl(SelectByCacheLineSize(178861123, 379087593, 2574136516U),
|
|
3709876890U));
|
|
if (GetParam() == BloomFilterPolicy::kFastLocalBloom) {
|
|
EXPECT_EQ("130,240,522,565,989,2002,2526,3147,3543", 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(GetNumProbesFromFilterData(), SelectByImpl(11, 9));
|
|
EXPECT_EQ(
|
|
BloomHash(FilterData()),
|
|
SelectByImpl(SelectByCacheLineSize(1129406313, 3049154394U, 1727750964),
|
|
1087138490));
|
|
if (GetParam() == BloomFilterPolicy::kFastLocalBloom) {
|
|
EXPECT_EQ("3299,3611,3916,6620,7822,8079,8482,8942,10167", 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(GetNumProbesFromFilterData(), 6);
|
|
EXPECT_EQ(
|
|
BloomHash(FilterData()),
|
|
SelectByImpl(SelectByCacheLineSize(1478976371, 2910591341U, 1182970461),
|
|
2498541272U));
|
|
if (GetParam() == BloomFilterPolicy::kFastLocalBloom) {
|
|
EXPECT_EQ("16,126,133,422,466,472,813,1002,1035,1159", FirstFPs(10));
|
|
}
|
|
|
|
ResetPolicy(10);
|
|
for (int key = /*CHANGED*/ 1; key < 2087; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ(GetNumProbesFromFilterData(), 6);
|
|
EXPECT_EQ(
|
|
BloomHash(FilterData()),
|
|
SelectByImpl(SelectByCacheLineSize(4205696321U, 1132081253U, 2385981855U),
|
|
2058382345U));
|
|
if (GetParam() == BloomFilterPolicy::kFastLocalBloom) {
|
|
EXPECT_EQ("16,126,133,422,466,472,813,1002,1035,1159", FirstFPs(10));
|
|
}
|
|
|
|
ResetPolicy(10);
|
|
for (int key = 1; key < /*CHANGED*/ 2088; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ(GetNumProbesFromFilterData(), 6);
|
|
EXPECT_EQ(
|
|
BloomHash(FilterData()),
|
|
SelectByImpl(SelectByCacheLineSize(2885052954U, 769447944, 4175124908U),
|
|
23699164));
|
|
if (GetParam() == BloomFilterPolicy::kFastLocalBloom) {
|
|
EXPECT_EQ("16,126,133,422,466,472,813,1002,1035,1159", 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(GetNumProbesFromFilterData(), 6);
|
|
EXPECT_EQ(BloomHash(FilterData()),
|
|
SelectByImpl(/*SAME*/ SelectByCacheLineSize(2885052954U, 769447944,
|
|
4175124908U),
|
|
/*CHANGED*/ 3166884174U));
|
|
if (GetParam() == BloomFilterPolicy::kFastLocalBloom) {
|
|
EXPECT_EQ(/*CHANGED*/ "126,156,367,444,458,791,813,976,1015,1035",
|
|
FirstFPs(10));
|
|
}
|
|
|
|
ResetPolicy(10.499);
|
|
for (int key = 1; key < 2088; key++) {
|
|
Add(Key(key, buffer));
|
|
}
|
|
Build();
|
|
EXPECT_EQ(GetNumProbesFromFilterData(), SelectByImpl(6, 7));
|
|
EXPECT_EQ(BloomHash(FilterData()),
|
|
SelectByImpl(/*SAME*/ SelectByCacheLineSize(2885052954U, 769447944,
|
|
4175124908U),
|
|
/*CHANGED*/ 4098502778U));
|
|
if (GetParam() == BloomFilterPolicy::kFastLocalBloom) {
|
|
EXPECT_EQ(/*CHANGED*/ "16,236,240,472,1015,1045,1111,1409,1465,1612",
|
|
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;
|
|
// 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());
|
|
}
|
|
|
|
TEST_P(FullBloomTest, CorruptFilters) {
|
|
RawFilterTester cft;
|
|
|
|
for (bool fill : {false, true}) {
|
|
// 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(-1, 3, 6, fill));
|
|
ASSERT_FALSE(Matches("hello"));
|
|
ASSERT_FALSE(Matches("world"));
|
|
|
|
OpenRaw(cft.Reset(-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 255 / -1
|
|
OpenRaw(cft.Reset(CACHE_LINE_SIZE, 1, 255, fill));
|
|
ASSERT_TRUE(Matches("hello"));
|
|
ASSERT_TRUE(Matches("world"));
|
|
}
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Full, FullBloomTest,
|
|
testing::Values(BloomFilterPolicy::kLegacyBloom,
|
|
BloomFilterPolicy::kFastLocalBloom));
|
|
|
|
} // namespace rocksdb
|
|
|
|
int main(int argc, char** argv) {
|
|
::testing::InitGoogleTest(&argc, argv);
|
|
ParseCommandLineFlags(&argc, &argv, true);
|
|
|
|
return RUN_ALL_TESTS();
|
|
}
|
|
|
|
#endif // GFLAGS
|