rocksdb/util/bloom_test.cc
Peter Dillinger 57f3032285 Allow fractional bits/key in BloomFilterPolicy (#6092)
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
2019-11-26 15:59:34 -08:00

912 lines
28 KiB
C++

// Copyright (c) 2011-present, Facebook, Inc. All rights reserved.
// This source code is licensed under both the GPLv2 (found in the
// COPYING file in the root directory) and Apache 2.0 License
// (found in the LICENSE.Apache file in the root directory).
//
// Copyright (c) 2012 The LevelDB Authors. All rights reserved.
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file. See the AUTHORS file for names of contributors.
#ifndef GFLAGS
#include <cstdio>
int main() {
fprintf(stderr, "Please install gflags to run this test... Skipping...\n");
return 0;
}
#else
#include <array>
#include <cmath>
#include <vector>
#include "logging/logging.h"
#include "memory/arena.h"
#include "rocksdb/filter_policy.h"
#include "table/block_based/filter_policy_internal.h"
#include "test_util/testharness.h"
#include "test_util/testutil.h"
#include "util/gflags_compat.h"
#include "util/hash.h"
using GFLAGS_NAMESPACE::ParseCommandLineFlags;
DEFINE_int32(bits_per_key, 10, "");
namespace rocksdb {
static const int kVerbose = 1;
static Slice Key(int i, char* buffer) {
std::string s;
PutFixed32(&s, static_cast<uint32_t>(i));
memcpy(buffer, s.c_str(), sizeof(i));
return Slice(buffer, sizeof(i));
}
static int NextLength(int length) {
if (length < 10) {
length += 1;
} else if (length < 100) {
length += 10;
} else if (length < 1000) {
length += 100;
} else {
length += 1000;
}
return length;
}
class BlockBasedBloomTest : public testing::Test {
private:
std::unique_ptr<const FilterPolicy> policy_;
std::string filter_;
std::vector<std::string> keys_;
public:
BlockBasedBloomTest() { ResetPolicy(); }
void Reset() {
keys_.clear();
filter_.clear();
}
void ResetPolicy(double bits_per_key) {
policy_.reset(new BloomFilterPolicy(bits_per_key,
BloomFilterPolicy::kDeprecatedBlock));
Reset();
}
void ResetPolicy() { ResetPolicy(FLAGS_bits_per_key); }
void Add(const Slice& s) {
keys_.push_back(s.ToString());
}
void Build() {
std::vector<Slice> key_slices;
for (size_t i = 0; i < keys_.size(); i++) {
key_slices.push_back(Slice(keys_[i]));
}
filter_.clear();
policy_->CreateFilter(&key_slices[0], static_cast<int>(key_slices.size()),
&filter_);
keys_.clear();
if (kVerbose >= 2) DumpFilter();
}
size_t FilterSize() const {
return filter_.size();
}
Slice FilterData() const { return Slice(filter_); }
void DumpFilter() {
fprintf(stderr, "F(");
for (size_t i = 0; i+1 < filter_.size(); i++) {
const unsigned int c = static_cast<unsigned int>(filter_[i]);
for (int j = 0; j < 8; j++) {
fprintf(stderr, "%c", (c & (1 <<j)) ? '1' : '.');
}
}
fprintf(stderr, ")\n");
}
bool Matches(const Slice& s) {
if (!keys_.empty()) {
Build();
}
return policy_->KeyMayMatch(s, filter_);
}
double FalsePositiveRate() {
char buffer[sizeof(int)];
int result = 0;
for (int i = 0; i < 10000; i++) {
if (Matches(Key(i + 1000000000, buffer))) {
result++;
}
}
return result / 10000.0;
}
};
TEST_F(BlockBasedBloomTest, EmptyFilter) {
ASSERT_TRUE(! Matches("hello"));
ASSERT_TRUE(! Matches("world"));
}
TEST_F(BlockBasedBloomTest, Small) {
Add("hello");
Add("world");
ASSERT_TRUE(Matches("hello"));
ASSERT_TRUE(Matches("world"));
ASSERT_TRUE(! Matches("x"));
ASSERT_TRUE(! Matches("foo"));
}
TEST_F(BlockBasedBloomTest, VaryingLengths) {
char buffer[sizeof(int)];
// Count number of filters that significantly exceed the false positive rate
int mediocre_filters = 0;
int good_filters = 0;
for (int length = 1; length <= 10000; length = NextLength(length)) {
Reset();
for (int i = 0; i < length; i++) {
Add(Key(i, buffer));
}
Build();
ASSERT_LE(FilterSize(), (size_t)((length * 10 / 8) + 40)) << length;
// All added keys must match
for (int i = 0; i < length; i++) {
ASSERT_TRUE(Matches(Key(i, buffer)))
<< "Length " << length << "; key " << i;
}
// Check false positive rate
double rate = FalsePositiveRate();
if (kVerbose >= 1) {
fprintf(stderr, "False positives: %5.2f%% @ length = %6d ; bytes = %6d\n",
rate*100.0, length, static_cast<int>(FilterSize()));
}
ASSERT_LE(rate, 0.02); // Must not be over 2%
if (rate > 0.0125) mediocre_filters++; // Allowed, but not too often
else good_filters++;
}
if (kVerbose >= 1) {
fprintf(stderr, "Filters: %d good, %d mediocre\n",
good_filters, mediocre_filters);
}
ASSERT_LE(mediocre_filters, good_filters/5);
}
// Ensure the implementation doesn't accidentally change in an
// incompatible way
TEST_F(BlockBasedBloomTest, Schema) {
char buffer[sizeof(int)];
ResetPolicy(8); // num_probes = 5
for (int key = 0; key < 87; key++) {
Add(Key(key, buffer));
}
Build();
ASSERT_EQ(BloomHash(FilterData()), 3589896109U);
ResetPolicy(9); // num_probes = 6
for (int key = 0; key < 87; key++) {
Add(Key(key, buffer));
}
Build();
ASSERT_EQ(BloomHash(FilterData()), 969445585);
ResetPolicy(11); // num_probes = 7
for (int key = 0; key < 87; key++) {
Add(Key(key, buffer));
}
Build();
ASSERT_EQ(BloomHash(FilterData()), 1694458207);
ResetPolicy(10); // num_probes = 6
for (int key = 0; key < 87; key++) {
Add(Key(key, buffer));
}
Build();
ASSERT_EQ(BloomHash(FilterData()), 2373646410U);
ResetPolicy(10);
for (int key = /*CHANGED*/ 1; key < 87; key++) {
Add(Key(key, buffer));
}
Build();
ASSERT_EQ(BloomHash(FilterData()), 1908442116);
ResetPolicy(10);
for (int key = 1; key < /*CHANGED*/ 88; key++) {
Add(Key(key, buffer));
}
Build();
ASSERT_EQ(BloomHash(FilterData()), 3057004015U);
// With new fractional bits_per_key, check that we are rounding to
// whole bits per key for old Bloom filters.
ResetPolicy(9.5); // Treated as 10
for (int key = 1; key < 88; key++) {
Add(Key(key, buffer));
}
Build();
ASSERT_EQ(BloomHash(FilterData()), /*SAME*/ 3057004015U);
ResetPolicy(10.499); // Treated as 10
for (int key = 1; key < 88; key++) {
Add(Key(key, buffer));
}
Build();
ASSERT_EQ(BloomHash(FilterData()), /*SAME*/ 3057004015U);
ResetPolicy();
}
// Different bits-per-byte
class FullBloomTest : public testing::TestWithParam<BloomFilterPolicy::Mode> {
private:
BlockBasedTableOptions table_options_;
std::shared_ptr<const FilterPolicy>& policy_;
std::unique_ptr<FilterBitsBuilder> bits_builder_;
std::unique_ptr<FilterBitsReader> bits_reader_;
std::unique_ptr<const char[]> buf_;
size_t filter_size_;
public:
FullBloomTest() : policy_(table_options_.filter_policy), filter_size_(0) {
ResetPolicy();
}
BuiltinFilterBitsBuilder* GetBuiltinFilterBitsBuilder() {
// Throws on bad cast
return &dynamic_cast<BuiltinFilterBitsBuilder&>(*bits_builder_);
}
const BloomFilterPolicy* GetBloomFilterPolicy() {
// Throws on bad cast
return &dynamic_cast<const BloomFilterPolicy&>(*policy_);
}
void Reset() {
bits_builder_.reset(FilterBuildingContext(table_options_).GetBuilder());
bits_reader_.reset(nullptr);
buf_.reset(nullptr);
filter_size_ = 0;
}
void ResetPolicy(double bits_per_key) {
policy_.reset(new BloomFilterPolicy(bits_per_key, GetParam()));
Reset();
}
void ResetPolicy() { ResetPolicy(FLAGS_bits_per_key); }
void Add(const Slice& s) {
bits_builder_->AddKey(s);
}
void OpenRaw(const Slice& s) {
bits_reader_.reset(policy_->GetFilterBitsReader(s));
}
void Build() {
Slice filter = bits_builder_->Finish(&buf_);
bits_reader_.reset(policy_->GetFilterBitsReader(filter));
filter_size_ = filter.size();
}
size_t FilterSize() const {
return filter_size_;
}
Slice FilterData() { return Slice(buf_.get(), filter_size_); }
int GetNumProbesFromFilterData() {
assert(filter_size_ >= 5);
int8_t raw_num_probes = static_cast<int8_t>(buf_.get()[filter_size_ - 5]);
if (raw_num_probes == -1) { // New bloom filter marker
return static_cast<uint8_t>(buf_.get()[filter_size_ - 3]);
} else {
return raw_num_probes;
}
}
bool Matches(const Slice& s) {
if (bits_reader_ == nullptr) {
Build();
}
return bits_reader_->MayMatch(s);
}
// Provides a kind of fingerprint on the Bloom filter's
// behavior, for reasonbly high FP rates.
uint64_t PackedMatches() {
char buffer[sizeof(int)];
uint64_t result = 0;
for (int i = 0; i < 64; i++) {
if (Matches(Key(i + 12345, buffer))) {
result |= uint64_t{1} << i;
}
}
return result;
}
// Provides a kind of fingerprint on the Bloom filter's
// behavior, for lower FP rates.
std::string FirstFPs(int count) {
char buffer[sizeof(int)];
std::string rv;
int fp_count = 0;
for (int i = 0; i < 1000000; i++) {
// Pack four match booleans into each hexadecimal digit
if (Matches(Key(i + 1000000, buffer))) {
++fp_count;
rv += std::to_string(i);
if (fp_count == count) {
break;
}
rv += ',';
}
}
return rv;
}
double FalsePositiveRate() {
char buffer[sizeof(int)];
int result = 0;
for (int i = 0; i < 10000; i++) {
if (Matches(Key(i + 1000000000, buffer))) {
result++;
}
}
return result / 10000.0;
}
uint32_t SelectByImpl(uint32_t for_legacy_bloom,
uint32_t for_fast_local_bloom) {
switch (GetParam()) {
case BloomFilterPolicy::kLegacyBloom:
return for_legacy_bloom;
case BloomFilterPolicy::kFastLocalBloom:
return for_fast_local_bloom;
case BloomFilterPolicy::kDeprecatedBlock:
case BloomFilterPolicy::kAuto:
/* N/A */;
}
// otherwise
assert(false);
return 0;
}
};
TEST_P(FullBloomTest, FilterSize) {
// In addition to checking the consistency of space computation, we are
// checking that denoted and computed doubles are interpreted as expected
// as bits_per_key values.
bool some_computed_less_than_denoted = false;
// Note: enforced minimum is 1 bit per key (1000 millibits), and enforced
// maximum is 100 bits per key (100000 millibits).
for (auto bpk :
std::vector<std::pair<double, int> >{{-HUGE_VAL, 1000},
{-INFINITY, 1000},
{0.0, 1000},
{1.234, 1234},
{3.456, 3456},
{9.5, 9500},
{10.0, 10000},
{10.499, 10499},
{21.345, 21345},
{99.999, 99999},
{1234.0, 100000},
{HUGE_VAL, 100000},
{INFINITY, 100000},
{NAN, 100000}}) {
ResetPolicy(bpk.first);
auto bfp = GetBloomFilterPolicy();
EXPECT_EQ(bpk.second, bfp->GetMillibitsPerKey());
EXPECT_EQ((bpk.second + 500) / 1000, bfp->GetWholeBitsPerKey());
double computed = bpk.first;
// This transforms e.g. 9.5 -> 9.499999999999998, which we still
// round to 10 for whole bits per key.
computed += 0.5;
computed /= 1234567.0;
computed *= 1234567.0;
computed -= 0.5;
some_computed_less_than_denoted |= (computed < bpk.first);
ResetPolicy(computed);
bfp = GetBloomFilterPolicy();
EXPECT_EQ(bpk.second, bfp->GetMillibitsPerKey());
EXPECT_EQ((bpk.second + 500) / 1000, bfp->GetWholeBitsPerKey());
auto bits_builder = GetBuiltinFilterBitsBuilder();
for (int n = 1; n < 100; n++) {
auto space = bits_builder->CalculateSpace(n);
auto n2 = bits_builder->CalculateNumEntry(space);
EXPECT_GE(n2, n);
auto space2 = bits_builder->CalculateSpace(n2);
EXPECT_EQ(space, space2);
}
}
// Check that the compiler hasn't optimized our computation into nothing
EXPECT_TRUE(some_computed_less_than_denoted);
ResetPolicy();
}
TEST_P(FullBloomTest, FullEmptyFilter) {
// Empty filter is not match, at this level
ASSERT_TRUE(!Matches("hello"));
ASSERT_TRUE(!Matches("world"));
}
TEST_P(FullBloomTest, FullSmall) {
Add("hello");
Add("world");
ASSERT_TRUE(Matches("hello"));
ASSERT_TRUE(Matches("world"));
ASSERT_TRUE(!Matches("x"));
ASSERT_TRUE(!Matches("foo"));
}
TEST_P(FullBloomTest, FullVaryingLengths) {
char buffer[sizeof(int)];
// Count number of filters that significantly exceed the false positive rate
int mediocre_filters = 0;
int good_filters = 0;
for (int length = 1; length <= 10000; length = NextLength(length)) {
Reset();
for (int i = 0; i < length; i++) {
Add(Key(i, buffer));
}
Build();
ASSERT_LE(FilterSize(),
(size_t)((length * 10 / 8) + CACHE_LINE_SIZE * 2 + 5));
// All added keys must match
for (int i = 0; i < length; i++) {
ASSERT_TRUE(Matches(Key(i, buffer)))
<< "Length " << length << "; key " << i;
}
// Check false positive rate
double rate = FalsePositiveRate();
if (kVerbose >= 1) {
fprintf(stderr, "False positives: %5.2f%% @ length = %6d ; bytes = %6d\n",
rate*100.0, length, static_cast<int>(FilterSize()));
}
ASSERT_LE(rate, 0.02); // Must not be over 2%
if (rate > 0.0125)
mediocre_filters++; // Allowed, but not too often
else
good_filters++;
}
if (kVerbose >= 1) {
fprintf(stderr, "Filters: %d good, %d mediocre\n",
good_filters, mediocre_filters);
}
ASSERT_LE(mediocre_filters, good_filters/5);
}
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) {
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