mirror of
https://github.com/facebook/rocksdb.git
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966be1cc4e
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
215 lines
7.5 KiB
C++
215 lines
7.5 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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#pragma once
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#include <array>
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#include <atomic>
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#include <memory>
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#include <string>
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#include "port/port.h"
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#include "rocksdb/slice.h"
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#include "table/multiget_context.h"
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#include "util/hash.h"
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namespace ROCKSDB_NAMESPACE {
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class Slice;
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class Allocator;
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class Logger;
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// A Bloom filter intended only to be used in memory, never serialized in a way
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// that could lead to schema incompatibility. Supports opt-in lock-free
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// concurrent access.
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//
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// This implementation is also intended for applications generally preferring
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// speed vs. maximum accuracy: roughly 0.9x BF op latency for 1.1x FP rate.
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// For 1% FP rate, that means that the latency of a look-up triggered by an FP
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// should be less than roughly 100x the cost of a Bloom filter op.
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//
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// For simplicity and performance, the current implementation requires
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// num_probes to be a multiple of two and <= 10.
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//
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class DynamicBloom {
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public:
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// allocator: pass allocator to bloom filter, hence trace the usage of memory
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// total_bits: fixed total bits for the bloom
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// num_probes: number of hash probes for a single key
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// hash_func: customized hash function
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// huge_page_tlb_size: if >0, try to allocate bloom bytes from huge page TLB
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// within this page size. Need to reserve huge pages for
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// it to be allocated, like:
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// sysctl -w vm.nr_hugepages=20
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// See linux doc Documentation/vm/hugetlbpage.txt
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explicit DynamicBloom(Allocator* allocator, uint32_t total_bits,
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uint32_t num_probes = 6, size_t huge_page_tlb_size = 0,
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Logger* logger = nullptr);
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~DynamicBloom() {}
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// Assuming single threaded access to this function.
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void Add(const Slice& key);
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// Like Add, but may be called concurrent with other functions.
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void AddConcurrently(const Slice& key);
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// Assuming single threaded access to this function.
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void AddHash(uint32_t hash);
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// Like AddHash, but may be called concurrent with other functions.
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void AddHashConcurrently(uint32_t hash);
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// Multithreaded access to this function is OK
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bool MayContain(const Slice& key) const;
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void MayContain(int num_keys, Slice* keys, bool* may_match) const;
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// Multithreaded access to this function is OK
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bool MayContainHash(uint32_t hash) const;
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void Prefetch(uint32_t h);
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private:
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// Length of the structure, in 64-bit words. For this structure, "word"
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// will always refer to 64-bit words.
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uint32_t kLen;
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// We make the k probes in pairs, two for each 64-bit read/write. Thus,
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// this stores k/2, the number of words to double-probe.
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const uint32_t kNumDoubleProbes;
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std::atomic<uint64_t>* data_;
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// or_func(ptr, mask) should effect *ptr |= mask with the appropriate
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// concurrency safety, working with bytes.
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template <typename OrFunc>
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void AddHash(uint32_t hash, const OrFunc& or_func);
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bool DoubleProbe(uint32_t h32, size_t a) const;
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};
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inline void DynamicBloom::Add(const Slice& key) { AddHash(BloomHash(key)); }
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inline void DynamicBloom::AddConcurrently(const Slice& key) {
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AddHashConcurrently(BloomHash(key));
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}
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inline void DynamicBloom::AddHash(uint32_t hash) {
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AddHash(hash, [](std::atomic<uint64_t>* ptr, uint64_t mask) {
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ptr->store(ptr->load(std::memory_order_relaxed) | mask,
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std::memory_order_relaxed);
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});
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}
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inline void DynamicBloom::AddHashConcurrently(uint32_t hash) {
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AddHash(hash, [](std::atomic<uint64_t>* ptr, uint64_t mask) {
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// Happens-before between AddHash and MaybeContains is handled by
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// access to versions_->LastSequence(), so all we have to do here is
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// avoid races (so we don't give the compiler a license to mess up
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// our code) and not lose bits. std::memory_order_relaxed is enough
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// for that.
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if ((mask & ptr->load(std::memory_order_relaxed)) != mask) {
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ptr->fetch_or(mask, std::memory_order_relaxed);
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}
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});
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}
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inline bool DynamicBloom::MayContain(const Slice& key) const {
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return (MayContainHash(BloomHash(key)));
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}
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inline void DynamicBloom::MayContain(int num_keys, Slice* keys,
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bool* may_match) const {
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std::array<uint32_t, MultiGetContext::MAX_BATCH_SIZE> hashes;
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std::array<size_t, MultiGetContext::MAX_BATCH_SIZE> byte_offsets;
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for (int i = 0; i < num_keys; ++i) {
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hashes[i] = BloomHash(keys[i]);
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size_t a = FastRange32(hashes[i], kLen);
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PREFETCH(data_ + a, 0, 3);
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byte_offsets[i] = a;
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}
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for (int i = 0; i < num_keys; i++) {
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may_match[i] = DoubleProbe(hashes[i], byte_offsets[i]);
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}
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}
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#if defined(_MSC_VER)
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#pragma warning(push)
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// local variable is initialized but not referenced
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#pragma warning(disable : 4189)
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#endif
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inline void DynamicBloom::Prefetch(uint32_t h32) {
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size_t a = FastRange32(h32, kLen);
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PREFETCH(data_ + a, 0, 3);
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}
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#if defined(_MSC_VER)
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#pragma warning(pop)
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#endif
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// Speed hacks in this implementation:
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// * Uses fastrange instead of %
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// * Minimum logic to determine first (and all) probed memory addresses.
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// (Uses constant bit-xor offsets from the starting probe address.)
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// * (Major) Two probes per 64-bit memory fetch/write.
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// Code simplification / optimization: only allow even number of probes.
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// * Very fast and effective (murmur-like) hash expansion/re-mixing. (At
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// least on recent CPUs, integer multiplication is very cheap. Each 64-bit
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// remix provides five pairs of bit addresses within a uint64_t.)
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// Code simplification / optimization: only allow up to 10 probes, from a
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// single 64-bit remix.
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//
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// The FP rate penalty for this implementation, vs. standard Bloom filter, is
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// roughly 1.12x on top of the 1.15x penalty for a 512-bit cache-local Bloom.
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// This implementation does not explicitly use the cache line size, but is
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// effectively cache-local (up to 16 probes) because of the bit-xor offsetting.
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//
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// NB: could easily be upgraded to support a 64-bit hash and
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// total_bits > 2^32 (512MB). (The latter is a bad idea without the former,
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// because of false positives.)
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inline bool DynamicBloom::MayContainHash(uint32_t h32) const {
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size_t a = FastRange32(h32, kLen);
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PREFETCH(data_ + a, 0, 3);
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return DoubleProbe(h32, a);
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}
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inline bool DynamicBloom::DoubleProbe(uint32_t h32, size_t byte_offset) const {
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// Expand/remix with 64-bit golden ratio
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uint64_t h = 0x9e3779b97f4a7c13ULL * h32;
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for (unsigned i = 0;; ++i) {
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// Two bit probes per uint64_t probe
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uint64_t mask =
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((uint64_t)1 << (h & 63)) | ((uint64_t)1 << ((h >> 6) & 63));
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uint64_t val = data_[byte_offset ^ i].load(std::memory_order_relaxed);
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if (i + 1 >= kNumDoubleProbes) {
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return (val & mask) == mask;
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} else if ((val & mask) != mask) {
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return false;
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}
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h = (h >> 12) | (h << 52);
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}
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}
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template <typename OrFunc>
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inline void DynamicBloom::AddHash(uint32_t h32, const OrFunc& or_func) {
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size_t a = FastRange32(h32, kLen);
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PREFETCH(data_ + a, 0, 3);
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// Expand/remix with 64-bit golden ratio
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uint64_t h = 0x9e3779b97f4a7c13ULL * h32;
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for (unsigned i = 0;; ++i) {
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// Two bit probes per uint64_t probe
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uint64_t mask =
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((uint64_t)1 << (h & 63)) | ((uint64_t)1 << ((h >> 6) & 63));
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or_func(&data_[a ^ i], mask);
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if (i + 1 >= kNumDoubleProbes) {
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return;
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}
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h = (h >> 12) | (h << 52);
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}
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}
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} // namespace ROCKSDB_NAMESPACE
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