rocksdb/util/dynamic_bloom.h
Peter Dillinger 966be1cc4e Clean up some FastRange calls (#11707)
Summary:
* JemallocNodumpAllocator was passing a size_t to FastRange32, which could cause compilation errors or warnings (seen with clang)
* Fixed the order of arguments to match what would be used with modulo operator (%), for clarity.

Fixes https://github.com/facebook/rocksdb/issues/11006

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11707

Test Plan: no functional change, existing tests

Reviewed By: ajkr

Differential Revision: D48435149

Pulled By: pdillinger

fbshipit-source-id: e6e8b107ded4eceda37db20df59985c846a2546b
2023-08-17 11:52:38 -07:00

215 lines
7.5 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).
#pragma once
#include <array>
#include <atomic>
#include <memory>
#include <string>
#include "port/port.h"
#include "rocksdb/slice.h"
#include "table/multiget_context.h"
#include "util/hash.h"
namespace ROCKSDB_NAMESPACE {
class Slice;
class Allocator;
class Logger;
// A Bloom filter intended only to be used in memory, never serialized in a way
// that could lead to schema incompatibility. Supports opt-in lock-free
// concurrent access.
//
// This implementation is also intended for applications generally preferring
// speed vs. maximum accuracy: roughly 0.9x BF op latency for 1.1x FP rate.
// For 1% FP rate, that means that the latency of a look-up triggered by an FP
// should be less than roughly 100x the cost of a Bloom filter op.
//
// For simplicity and performance, the current implementation requires
// num_probes to be a multiple of two and <= 10.
//
class DynamicBloom {
public:
// allocator: pass allocator to bloom filter, hence trace the usage of memory
// total_bits: fixed total bits for the bloom
// num_probes: number of hash probes for a single key
// hash_func: customized hash function
// huge_page_tlb_size: if >0, try to allocate bloom bytes from huge page TLB
// within this page size. Need to reserve huge pages for
// it to be allocated, like:
// sysctl -w vm.nr_hugepages=20
// See linux doc Documentation/vm/hugetlbpage.txt
explicit DynamicBloom(Allocator* allocator, uint32_t total_bits,
uint32_t num_probes = 6, size_t huge_page_tlb_size = 0,
Logger* logger = nullptr);
~DynamicBloom() {}
// Assuming single threaded access to this function.
void Add(const Slice& key);
// Like Add, but may be called concurrent with other functions.
void AddConcurrently(const Slice& key);
// Assuming single threaded access to this function.
void AddHash(uint32_t hash);
// Like AddHash, but may be called concurrent with other functions.
void AddHashConcurrently(uint32_t hash);
// Multithreaded access to this function is OK
bool MayContain(const Slice& key) const;
void MayContain(int num_keys, Slice* keys, bool* may_match) const;
// Multithreaded access to this function is OK
bool MayContainHash(uint32_t hash) const;
void Prefetch(uint32_t h);
private:
// Length of the structure, in 64-bit words. For this structure, "word"
// will always refer to 64-bit words.
uint32_t kLen;
// We make the k probes in pairs, two for each 64-bit read/write. Thus,
// this stores k/2, the number of words to double-probe.
const uint32_t kNumDoubleProbes;
std::atomic<uint64_t>* data_;
// or_func(ptr, mask) should effect *ptr |= mask with the appropriate
// concurrency safety, working with bytes.
template <typename OrFunc>
void AddHash(uint32_t hash, const OrFunc& or_func);
bool DoubleProbe(uint32_t h32, size_t a) const;
};
inline void DynamicBloom::Add(const Slice& key) { AddHash(BloomHash(key)); }
inline void DynamicBloom::AddConcurrently(const Slice& key) {
AddHashConcurrently(BloomHash(key));
}
inline void DynamicBloom::AddHash(uint32_t hash) {
AddHash(hash, [](std::atomic<uint64_t>* ptr, uint64_t mask) {
ptr->store(ptr->load(std::memory_order_relaxed) | mask,
std::memory_order_relaxed);
});
}
inline void DynamicBloom::AddHashConcurrently(uint32_t hash) {
AddHash(hash, [](std::atomic<uint64_t>* ptr, uint64_t mask) {
// Happens-before between AddHash and MaybeContains is handled by
// access to versions_->LastSequence(), so all we have to do here is
// avoid races (so we don't give the compiler a license to mess up
// our code) and not lose bits. std::memory_order_relaxed is enough
// for that.
if ((mask & ptr->load(std::memory_order_relaxed)) != mask) {
ptr->fetch_or(mask, std::memory_order_relaxed);
}
});
}
inline bool DynamicBloom::MayContain(const Slice& key) const {
return (MayContainHash(BloomHash(key)));
}
inline void DynamicBloom::MayContain(int num_keys, Slice* keys,
bool* may_match) const {
std::array<uint32_t, MultiGetContext::MAX_BATCH_SIZE> hashes;
std::array<size_t, MultiGetContext::MAX_BATCH_SIZE> byte_offsets;
for (int i = 0; i < num_keys; ++i) {
hashes[i] = BloomHash(keys[i]);
size_t a = FastRange32(hashes[i], kLen);
PREFETCH(data_ + a, 0, 3);
byte_offsets[i] = a;
}
for (int i = 0; i < num_keys; i++) {
may_match[i] = DoubleProbe(hashes[i], byte_offsets[i]);
}
}
#if defined(_MSC_VER)
#pragma warning(push)
// local variable is initialized but not referenced
#pragma warning(disable : 4189)
#endif
inline void DynamicBloom::Prefetch(uint32_t h32) {
size_t a = FastRange32(h32, kLen);
PREFETCH(data_ + a, 0, 3);
}
#if defined(_MSC_VER)
#pragma warning(pop)
#endif
// Speed hacks in this implementation:
// * Uses fastrange instead of %
// * Minimum logic to determine first (and all) probed memory addresses.
// (Uses constant bit-xor offsets from the starting probe address.)
// * (Major) Two probes per 64-bit memory fetch/write.
// Code simplification / optimization: only allow even number of probes.
// * Very fast and effective (murmur-like) hash expansion/re-mixing. (At
// least on recent CPUs, integer multiplication is very cheap. Each 64-bit
// remix provides five pairs of bit addresses within a uint64_t.)
// Code simplification / optimization: only allow up to 10 probes, from a
// single 64-bit remix.
//
// The FP rate penalty for this implementation, vs. standard Bloom filter, is
// roughly 1.12x on top of the 1.15x penalty for a 512-bit cache-local Bloom.
// This implementation does not explicitly use the cache line size, but is
// effectively cache-local (up to 16 probes) because of the bit-xor offsetting.
//
// NB: could easily be upgraded to support a 64-bit hash and
// total_bits > 2^32 (512MB). (The latter is a bad idea without the former,
// because of false positives.)
inline bool DynamicBloom::MayContainHash(uint32_t h32) const {
size_t a = FastRange32(h32, kLen);
PREFETCH(data_ + a, 0, 3);
return DoubleProbe(h32, a);
}
inline bool DynamicBloom::DoubleProbe(uint32_t h32, size_t byte_offset) const {
// Expand/remix with 64-bit golden ratio
uint64_t h = 0x9e3779b97f4a7c13ULL * h32;
for (unsigned i = 0;; ++i) {
// Two bit probes per uint64_t probe
uint64_t mask =
((uint64_t)1 << (h & 63)) | ((uint64_t)1 << ((h >> 6) & 63));
uint64_t val = data_[byte_offset ^ i].load(std::memory_order_relaxed);
if (i + 1 >= kNumDoubleProbes) {
return (val & mask) == mask;
} else if ((val & mask) != mask) {
return false;
}
h = (h >> 12) | (h << 52);
}
}
template <typename OrFunc>
inline void DynamicBloom::AddHash(uint32_t h32, const OrFunc& or_func) {
size_t a = FastRange32(h32, kLen);
PREFETCH(data_ + a, 0, 3);
// Expand/remix with 64-bit golden ratio
uint64_t h = 0x9e3779b97f4a7c13ULL * h32;
for (unsigned i = 0;; ++i) {
// Two bit probes per uint64_t probe
uint64_t mask =
((uint64_t)1 << (h & 63)) | ((uint64_t)1 << ((h >> 6) & 63));
or_func(&data_[a ^ i], mask);
if (i + 1 >= kNumDoubleProbes) {
return;
}
h = (h >> 12) | (h << 52);
}
}
} // namespace ROCKSDB_NAMESPACE