Refactor/consolidate legacy Bloom implementation details (#5784)
Summary: Refactoring to consolidate implementation details of legacy Bloom filters. This helps to organize and document some related, obscure code. Also added make/cpp var TEST_CACHE_LINE_SIZE so that it's easy to compile and run unit tests for non-native cache line size. (Fixed a related test failure in db_properties_test.) Pull Request resolved: https://github.com/facebook/rocksdb/pull/5784 Test Plan: make check, including Recently added Bloom schema unit tests (in ./plain_table_db_test && ./bloom_test), and including with TEST_CACHE_LINE_SIZE=128U and TEST_CACHE_LINE_SIZE=256U. Tested the schema tests with temporary fault injection into new implementations. Some performance testing with modified unit tests suggest a small to moderate improvement in speed. Differential Revision: D17381384 Pulled By: pdillinger fbshipit-source-id: ee42586da996798910fc45ac0b6289147f16d8dfmain
Peter Dillinger
5 years ago
committed by
Facebook Github Bot
parent
638d239507
commit
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// Copyright (c) 2019-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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// Implementation details of various Bloom filter implementations used in
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// RocksDB. (DynamicBloom is in a separate file for now because it
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// supports concurrent write.)
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#pragma once |
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#include <stddef.h> |
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#include <stdint.h> |
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#include "rocksdb/slice.h" |
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namespace rocksdb { |
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// A legacy Bloom filter implementation with no locality of probes (slow).
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// It uses double hashing to generate a sequence of hash values.
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// Asymptotic analysis is in [Kirsch,Mitzenmacher 2006], but known to have
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// subtle accuracy flaws for practical sizes [Dillinger,Manolios 2004].
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//
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// DO NOT REUSE - faster and more predictably accurate implementations
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// are available at
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// https://github.com/pdillinger/wormhashing/blob/master/bloom_simulation_tests/foo.cc
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// See e.g. RocksDB DynamicBloom.
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//
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class LegacyNoLocalityBloomImpl { |
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public: |
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static inline void AddHash(uint32_t h, uint32_t total_bits, |
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int num_probes, char *data) { |
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const uint32_t delta = (h >> 17) | (h << 15); // Rotate right 17 bits
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for (int i = 0; i < num_probes; i++) { |
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const uint32_t bitpos = h % total_bits; |
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data[bitpos/8] |= (1 << (bitpos % 8)); |
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h += delta; |
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} |
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} |
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static inline bool HashMayMatch(uint32_t h, uint32_t total_bits, |
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int num_probes, const char *data) { |
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const uint32_t delta = (h >> 17) | (h << 15); // Rotate right 17 bits
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for (int i = 0; i < num_probes; i++) { |
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const uint32_t bitpos = h % total_bits; |
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if ((data[bitpos/8] & (1 << (bitpos % 8))) == 0) { |
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return false; |
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} |
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h += delta; |
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} |
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return true; |
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} |
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}; |
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// A legacy Bloom filter implementation with probes local to a single
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// cache line (fast). Because SST files might be transported between
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// platforms, the cache line size is a parameter rather than hard coded.
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// (But if specified as a constant parameter, an optimizing compiler
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// should take advantage of that.)
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//
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// When ExtraRotates is false, this implementation is notably deficient in
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// accuracy. Specifically, it uses double hashing with a 1/512 chance of the
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// increment being zero (when cache line size is 512 bits). Thus, there's a
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// 1/512 chance of probing only one index, which we'd expect to incur about
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// a 1/2 * 1/512 or absolute 0.1% FP rate penalty. More detail at
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// https://github.com/facebook/rocksdb/issues/4120
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//
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// DO NOT REUSE - faster and more predictably accurate implementations
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// are available at
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// https://github.com/pdillinger/wormhashing/blob/master/bloom_simulation_tests/foo.cc
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// See e.g. RocksDB DynamicBloom.
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//
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template <bool ExtraRotates> |
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class LegacyLocalityBloomImpl { |
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private: |
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static inline uint32_t GetLine(uint32_t h, uint32_t num_lines) { |
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uint32_t offset_h = ExtraRotates ? (h >> 11) | (h << 21) : h; |
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return offset_h % num_lines; |
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} |
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public: |
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static inline void AddHash(uint32_t h, uint32_t num_lines, |
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int num_probes, char *data, |
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int log2_cache_line_bytes) { |
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const int log2_cache_line_bits = log2_cache_line_bytes + 3; |
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char *data_at_offset = |
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data + (GetLine(h, num_lines) << log2_cache_line_bytes); |
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const uint32_t delta = (h >> 17) | (h << 15); |
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for (int i = 0; i < num_probes; ++i) { |
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// Mask to bit-within-cache-line address
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const uint32_t bitpos = h & ((1 << log2_cache_line_bits) - 1); |
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data_at_offset[bitpos / 8] |= (1 << (bitpos % 8)); |
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if (ExtraRotates) { |
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h = (h >> log2_cache_line_bits) | (h << (32 - log2_cache_line_bits)); |
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} |
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h += delta; |
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} |
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} |
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static inline void PrepareHashMayMatch(uint32_t h, uint32_t num_lines, |
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const char *data, |
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uint32_t /*out*/*byte_offset, |
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int log2_cache_line_bytes) { |
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uint32_t b = GetLine(h, num_lines) << log2_cache_line_bytes; |
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PREFETCH(data + b, 0 /* rw */, 1 /* locality */); |
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PREFETCH(data + b + ((1 << log2_cache_line_bytes) - 1), |
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0 /* rw */, 1 /* locality */); |
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*byte_offset = b; |
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} |
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static inline bool HashMayMatch(uint32_t h, uint32_t num_lines, |
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int num_probes, const char *data, |
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int log2_cache_line_bytes) { |
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uint32_t b = GetLine(h, num_lines) << log2_cache_line_bytes; |
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return HashMayMatchPrepared(h, num_probes, |
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data + b, log2_cache_line_bytes); |
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} |
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static inline bool HashMayMatchPrepared(uint32_t h, int num_probes, |
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const char *data_at_offset, |
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int log2_cache_line_bytes) { |
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const int log2_cache_line_bits = log2_cache_line_bytes + 3; |
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const uint32_t delta = (h >> 17) | (h << 15); |
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for (int i = 0; i < num_probes; ++i) { |
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// Mask to bit-within-cache-line address
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const uint32_t bitpos = h & ((1 << log2_cache_line_bits) - 1); |
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if (((data_at_offset[bitpos / 8]) & (1 << (bitpos % 8))) == 0) { |
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return false; |
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} |
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if (ExtraRotates) { |
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h = (h >> log2_cache_line_bits) | (h << (32 - log2_cache_line_bits)); |
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} |
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h += delta; |
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} |
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return true; |
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} |
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}; |
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} // namespace rocksdb
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