text: // 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 <string>
  #include "port/port.h"
  #include "rocksdb/slice.h"
  #include "table/multiget_context.h"
  #include "util/hash.h"
  
  #include <atomic>
  #include <memory>
  
  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(kLen, hashes[i]);
      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(kLen, h32);
    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(kLen, h32);
    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(kLen, h32);
    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
  