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Vary key size and alignment in filter_bench (#5933)

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Summary:
The first version of filter_bench has selectable key size
but that size does not vary throughout a test run. This artificially
favors "branchy" hash functions like the existing BloomHash,
MurmurHash1, probably because of optimal return for branch prediction.

This change primarily varies those key sizes from -2 to +2 bytes vs.
the average selected size. We also set the default key size at 24 to
better reflect our best guess of typical key size.

But steadily random key sizes may not be realistic either. So this
change introduces a new filter_bench option:
-vary_key_size_log2_interval=n where the same key size is used 2^n
times and then changes to another size. I've set the default at 5
(32 times same size) as a compromise between deployments with
rather consistent vs. rather variable key sizes. On my Skylake
system, the performance boost to MurmurHash1 largely lies between
n=10 and n=15.

Also added -vary_key_alignment (bool, now default=true), though this
doesn't currently seem to matter in hash functions under
consideration.

This change also does a "dry run" for each testing scenario, to improve
the accuracy of those numbers, as there was more difference between
scenarios than expected. Subtracting gross test run times from dry run
times is now also embedded in the output, because these "net" times are
generally the most useful.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5933

Differential Revision: D18121683

Pulled By: pdillinger

fbshipit-source-id: 3c7efee1c5661a5fe43de555e786754ddf80dc1e
main
Peter Dillinger 5 years ago committed by Facebook Github Bot
parent 2509531123
commit 2837008525
1 changed files with 106 additions and 52 deletions
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
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  1. 138
      util/filter_bench.cc

138
util/filter_bench.cc
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@ -13,6 +13,7 @@ int main() {
#include <cinttypes>
#include <iostream>
#include <sstream>
#include <vector>
#include "port/port.h"
@ -37,7 +38,15 @@ DEFINE_double(working_mem_size_mb, 200,
DEFINE_uint32(average_keys_per_filter, 10000,
"Average number of keys per filter");
DEFINE_uint32(key_size, 16, "Number of bytes each key should be");
DEFINE_uint32(key_size, 24, "Average number of bytes for each key");
DEFINE_bool(vary_key_alignment, true,
"Whether to vary key alignment (default: at least 32-bit "
"alignment)");
DEFINE_uint32(vary_key_size_log2_interval, 5,
"Use same key size 2^n times, then change. Key size varies from "
"-2 to +2 bytes vs. average, unless n>=30 to fix key size.");
DEFINE_uint32(batch_size, 8, "Number of keys to group in each batch");
@ -66,6 +75,7 @@ void _always_assert_fail(int line, const char *file, const char *expr) {
using rocksdb::BlockContents;
using rocksdb::CachableEntry;
using rocksdb::EncodeFixed32;
using rocksdb::fastrange32;
using rocksdb::FilterBitsBuilder;
using rocksdb::FilterBitsReader;
@ -76,21 +86,41 @@ using rocksdb::Slice;
using rocksdb::mock::MockBlockBasedTableTester;
struct KeyMaker {
KeyMaker(size_t size)
: data_(new char[size]),
slice_(data_.get(), size),
vals_(reinterpret_cast<uint32_t *>(data_.get())) {
assert(size >= 8);
memset(data_.get(), 0, size);
}
std::unique_ptr<char[]> data_;
Slice slice_;
uint32_t *vals_;
KeyMaker(size_t avg_size)
: smallest_size_(avg_size -
(FLAGS_vary_key_size_log2_interval >= 30 ? 2 : 0)),
buf_size_(avg_size + 11), // pad to vary key size and alignment
buf_(new char[buf_size_]) {
memset(buf_.get(), 0, buf_size_);
assert(smallest_size_ > 8);
}
size_t smallest_size_;
size_t buf_size_;
std::unique_ptr<char[]> buf_;
// Returns a unique(-ish) key based on the given parameter values. Each
// call returns a Slice from the same buffer so previously returned
// Slices should be considered invalidated.
Slice Get(uint32_t filter_num, uint32_t val_num) {
vals_[0] = filter_num + val_num;
vals_[1] = val_num;
return slice_;
size_t start = FLAGS_vary_key_alignment ? val_num % 4 : 0;
size_t len = smallest_size_;
if (FLAGS_vary_key_size_log2_interval < 30) {
// To get range [avg_size - 2, avg_size + 2]
// use range [smallest_size, smallest_size + 4]
len += fastrange32(
(val_num >> FLAGS_vary_key_size_log2_interval) * 1234567891, 5);
}
char * data = buf_.get() + start;
// Populate key data such that all data makes it into a key of at
// least 8 bytes. We also don't want all the within-filter key
// variance confined to a contiguous 32 bits, because then a 32 bit
// hash function can "cheat" the false positive rate by
// approximating a perfect hash.
EncodeFixed32(data, val_num);
EncodeFixed32(data + 4, filter_num + val_num);
// ensure clearing leftovers from different alignment
EncodeFixed32(data + 8, 0);
return Slice(data, len);
}
};
@ -157,6 +187,7 @@ struct FilterBench : public MockBlockBasedTableTester {
std::vector<KeyMaker> kms_;
std::vector<FilterInfo> infos_;
Random32 random_;
std::ostringstream fp_rate_report_;
FilterBench()
: MockBlockBasedTableTester(
@ -169,7 +200,7 @@ struct FilterBench : public MockBlockBasedTableTester {
void Go();
void RandomQueryTest(bool inside, bool dry_run, TestMode mode);
double RandomQueryTest(bool inside, bool dry_run, TestMode mode);
};
void FilterBench::Go() {
@ -184,7 +215,7 @@ void FilterBench::Go() {
const std::vector<TestMode> &testModes =
FLAGS_quick ? quickTestModes : allTestModes;
if (FLAGS_quick) {
FLAGS_m_queries /= 10.0;
FLAGS_m_queries /= 7.0;
}
std::cout << "Building..." << std::endl;
@ -260,27 +291,33 @@ void FilterBench::Go() {
std::cout << "----------------------------" << std::endl;
std::cout << "Inside queries..." << std::endl;
random_.Seed(FLAGS_seed + 1);
RandomQueryTest(/*inside*/ true, /*dry_run*/ true, kRandomFilter);
for (TestMode tm : testModes) {
random_.Seed(FLAGS_seed + 1);
RandomQueryTest(/*inside*/ true, /*dry_run*/ false, tm);
double f = RandomQueryTest(/*inside*/ true, /*dry_run*/ false, tm);
random_.Seed(FLAGS_seed + 1);
double d = RandomQueryTest(/*inside*/ true, /*dry_run*/ true, tm);
std::cout << " " << TestModeToString(tm) << " net ns/op: " << (f - d)
<< std::endl;
}
std::cout << fp_rate_report_.str();
std::cout << "----------------------------" << std::endl;
std::cout << "Outside queries..." << std::endl;
random_.Seed(FLAGS_seed + 2);
RandomQueryTest(/*inside*/ false, /*dry_run*/ true, kRandomFilter);
for (TestMode tm : testModes) {
random_.Seed(FLAGS_seed + 2);
RandomQueryTest(/*inside*/ false, /*dry_run*/ false, tm);
double f = RandomQueryTest(/*inside*/ false, /*dry_run*/ false, tm);
random_.Seed(FLAGS_seed + 2);
double d = RandomQueryTest(/*inside*/ false, /*dry_run*/ true, tm);
std::cout << " " << TestModeToString(tm) << " net ns/op: " << (f - d)
<< std::endl;
}
std::cout << fp_rate_report_.str();
std::cout << "----------------------------" << std::endl;
std::cout << "Done. (For more info, run with -legend or -help.)" << std::endl;
}
void FilterBench::RandomQueryTest(bool inside, bool dry_run, TestMode mode) {
double FilterBench::RandomQueryTest(bool inside, bool dry_run, TestMode mode) {
for (auto &info : infos_) {
info.outside_queries_ = 0;
info.false_positives_ = 0;
@ -313,16 +350,19 @@ void FilterBench::RandomQueryTest(bool inside, bool dry_run, TestMode mode) {
num_primary_filters = (num_primary_filters + 4) / 5;
}
uint32_t batch_size = 1;
std::unique_ptr<Slice *[]> batch_slices;
std::unique_ptr<Slice[]> batch_slices;
std::unique_ptr<Slice *[]> batch_slice_ptrs;
std::unique_ptr<bool[]> batch_results;
if (mode == kBatchPrepared || mode == kBatchUnprepared) {
batch_size = static_cast<uint32_t>(kms_.size());
batch_slices.reset(new Slice *[batch_size]);
}
batch_slices.reset(new Slice[batch_size]);
batch_slice_ptrs.reset(new Slice *[batch_size]);
batch_results.reset(new bool[batch_size]);
for (uint32_t i = 0; i < batch_size; ++i) {
batch_slices[i] = &kms_[i].slice_;
batch_results[i] = false;
}
batch_slice_ptrs[i] = &batch_slices[i];
}
rocksdb::StopWatchNano timer(rocksdb::Env::Default(), true);
@ -339,9 +379,12 @@ void FilterBench::RandomQueryTest(bool inside, bool dry_run, TestMode mode) {
FilterInfo &info = infos_[filter_index];
for (uint32_t i = 0; i < batch_size; ++i) {
if (inside) {
batch_slices[i] =
kms_[i].Get(info.filter_id_, random_.Uniformish(info.keys_added_));
} else {
kms_[i].Get(info.filter_id_, random_.Next() | uint32_t{0x80000000});
batch_slices[i] =
kms_[i].Get(info.filter_id_, random_.Uniformish(info.keys_added_) |
uint32_t{0x80000000});
info.outside_queries_++;
}
}
@ -350,7 +393,7 @@ void FilterBench::RandomQueryTest(bool inside, bool dry_run, TestMode mode) {
for (uint32_t i = 0; i < batch_size; ++i) {
batch_results[i] = false;
}
info.reader_->MayMatch(batch_size, batch_slices.get(),
info.reader_->MayMatch(batch_size, batch_slice_ptrs.get(),
batch_results.get());
for (uint32_t i = 0; i < batch_size; ++i) {
if (inside) {
@ -362,19 +405,19 @@ void FilterBench::RandomQueryTest(bool inside, bool dry_run, TestMode mode) {
} else {
for (uint32_t i = 0; i < batch_size; ++i) {
if (dry_run) {
dry_run_hash ^= rocksdb::BloomHash(kms_[i].slice_);
dry_run_hash ^= rocksdb::BloomHash(batch_slices[i]);
} else {
bool may_match;
if (FLAGS_use_full_block_reader) {
may_match = info.full_block_reader_->KeyMayMatch(
kms_[i].slice_,
batch_slices[i],
/*prefix_extractor=*/nullptr,
/*block_offset=*/rocksdb::kNotValid,
/*no_io=*/false, /*const_ikey_ptr=*/nullptr,
/*get_context=*/nullptr,
/*lookup_context=*/nullptr);
} else {
may_match = info.reader_->MayMatch(kms_[i].slice_);
may_match = info.reader_->MayMatch(batch_slices[i]);
}
if (inside) {
ALWAYS_ASSERT(may_match);
@ -389,15 +432,17 @@ void FilterBench::RandomQueryTest(bool inside, bool dry_run, TestMode mode) {
uint64_t elapsed_nanos = timer.ElapsedNanos();
double ns = double(elapsed_nanos) / max_queries;
if (!FLAGS_quick) {
if (dry_run) {
// Printing part of hash prevents dry run components from being optimized
// away by compiler
std::cout << " Dry run (" << std::hex << (dry_run_hash & 0xfff) << std::dec
<< ") ";
std::cout << " Dry run (" << std::hex << (dry_run_hash & 0xfffff)
<< std::dec << ") ";
} else {
std::cout << " " << TestModeToString(mode) << " ";
std::cout << " Gross filter ";
}
std::cout << "ns/op: " << ns << std::endl;
}
if (!inside && !dry_run && mode == kRandomFilter) {
uint64_t q = 0;
@ -413,16 +458,19 @@ void FilterBench::RandomQueryTest(bool inside, bool dry_run, TestMode mode) {
best_fp_rate = std::min(best_fp_rate, fp_rate);
}
}
std::cout << " Average FP rate %: " << 100.0 * fp / q << std::endl;
fp_rate_report_ << " Average FP rate %: " << 100.0 * fp / q << std::endl;
if (!FLAGS_quick) {
std::cout << " Worst FP rate %: " << 100.0 * worst_fp_rate
fp_rate_report_ << " Worst FP rate %: " << 100.0 * worst_fp_rate
<< std::endl;
std::cout << " Best FP rate %: " << 100.0 * best_fp_rate
fp_rate_report_ << " Best FP rate %: " << 100.0 * best_fp_rate
<< std::endl;
std::cout << " Best possible bits/key: "
fp_rate_report_ << " Best possible bits/key: "
<< -std::log(double(fp) / q) / std::log(2.0) << std::endl;
}
} else {
fp_rate_report_.clear();
}
return ns;
}
int main(int argc, char **argv) {
@ -440,8 +488,14 @@ int main(int argc, char **argv) {
<< " \"Outside\" - key that was not added to filter" << std::endl
<< " \"FN\" - false negative query (must not happen)" << std::endl
<< " \"FP\" - false positive query (OK at low rate)" << std::endl
<< " \"Dry run\" - cost of testing and hashing overhead. Consider"
<< "\n subtracting this cost from the others." << std::endl
<< " \"Dry run\" - cost of testing and hashing overhead." << std::endl
<< " \"Gross filter\" - cost of filter queries including testing "
<< "\n and hashing overhead." << std::endl
<< " \"net\" - best estimate of time in filter operation, without "
<< "\n testing and hashing overhead (gross filter - dry run)"
<< std::endl
<< " \"ns/op\" - nanoseconds per operation (key query or add)"
<< std::endl
<< " \"Single filter\" - essentially minimum cost, assuming filter"
<< "\n fits easily in L1 CPU cache." << std::endl
<< " \"Batched, prepared\" - several queries at once against a"

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