Improve Cuckoo Table Reader performance. Inlined hash function and number of...

Improve Cuckoo Table Reader performance. Inlined hash function and number of buckets a power of two. Summary: Use inlined hash functions instead of function pointer. Make number of buckets a power of two and use bitwise and instead of mod. After these changes, we get almost 50% improvement in performance. Results: With 120000000 items, utilization is 89.41%, number of hash functions: 2. Time taken per op is 0.231us (4.3 Mqps) with batch size of 0 Time taken per op is 0.229us (4.4 Mqps) with batch size of 0 Time taken per op is 0.185us (5.4 Mqps) with batch size of 0 With 120000000 items, utilization is 89.41%, number of hash functions: 2. Time taken per op is 0.108us (9.3 Mqps) with batch size of 10 Time taken per op is 0.100us (10.0 Mqps) with batch size of 10 Time taken per op is 0.103us (9.7 Mqps) with batch size of 10 With 120000000 items, utilization is 89.41%, number of hash functions: 2. Time taken per op is 0.101us (9.9 Mqps) with batch size of 25 Time taken per op is 0.098us (10.2 Mqps) with batch size of 25 Time taken per op is 0.097us (10.3 Mqps) with batch size of 25 With 120000000 items, utilization is 89.41%, number of hash functions: 2. Time taken per op is 0.100us (10.0 Mqps) with batch size of 50 Time taken per op is 0.097us (10.3 Mqps) with batch size of 50 Time taken per op is 0.097us (10.3 Mqps) with batch size of 50 With 120000000 items, utilization is 89.41%, number of hash functions: 2. Time taken per op is 0.102us (9.8 Mqps) with batch size of 100 Time taken per op is 0.098us (10.2 Mqps) with batch size of 100 Time taken per op is 0.115us (8.7 Mqps) with batch size of 100 With 100000000 items, utilization is 74.51%, number of hash functions: 2. Time taken per op is 0.201us (5.0 Mqps) with batch size of 0 Time taken per op is 0.155us (6.5 Mqps) with batch size of 0 Time taken per op is 0.152us (6.6 Mqps) with batch size of 0 With 100000000 items, utilization is 74.51%, number of hash functions: 2. Time taken per op is 0.089us (11.3 Mqps) with batch size of 10 Time taken per op is 0.084us (11.9 Mqps) with batch size of 10 Time taken per op is 0.086us (11.6 Mqps) with batch size of 10 With 100000000 items, utilization is 74.51%, number of hash functions: 2. Time taken per op is 0.087us (11.5 Mqps) with batch size of 25 Time taken per op is 0.085us (11.7 Mqps) with batch size of 25 Time taken per op is 0.093us (10.8 Mqps) with batch size of 25 With 100000000 items, utilization is 74.51%, number of hash functions: 2. Time taken per op is 0.094us (10.6 Mqps) with batch size of 50 Time taken per op is 0.094us (10.7 Mqps) with batch size of 50 Time taken per op is 0.093us (10.8 Mqps) with batch size of 50 With 100000000 items, utilization is 74.51%, number of hash functions: 2. Time taken per op is 0.092us (10.9 Mqps) with batch size of 100 Time taken per op is 0.089us (11.2 Mqps) with batch size of 100 Time taken per op is 0.088us (11.3 Mqps) with batch size of 100 With 80000000 items, utilization is 59.60%, number of hash functions: 2. Time taken per op is 0.154us (6.5 Mqps) with batch size of 0 Time taken per op is 0.168us (6.0 Mqps) with batch size of 0 Time taken per op is 0.190us (5.3 Mqps) with batch size of 0 With 80000000 items, utilization is 59.60%, number of hash functions: 2. Time taken per op is 0.081us (12.4 Mqps) with batch size of 10 Time taken per op is 0.077us (13.0 Mqps) with batch size of 10 Time taken per op is 0.083us (12.1 Mqps) with batch size of 10 With 80000000 items, utilization is 59.60%, number of hash functions: 2. Time taken per op is 0.077us (13.0 Mqps) with batch size of 25 Time taken per op is 0.073us (13.7 Mqps) with batch size of 25 Time taken per op is 0.073us (13.7 Mqps) with batch size of 25 With 80000000 items, utilization is 59.60%, number of hash functions: 2. Time taken per op is 0.076us (13.1 Mqps) with batch size of 50 Time taken per op is 0.072us (13.8 Mqps) with batch size of 50 Time taken per op is 0.072us (13.8 Mqps) with batch size of 50 With 80000000 items, utilization is 59.60%, number of hash functions: 2. Time taken per op is 0.077us (13.0 Mqps) with batch size of 100 Time taken per op is 0.074us (13.6 Mqps) with batch size of 100 Time taken per op is 0.073us (13.6 Mqps) with batch size of 100 With 70000000 items, utilization is 52.15%, number of hash functions: 2. Time taken per op is 0.190us (5.3 Mqps) with batch size of 0 Time taken per op is 0.186us (5.4 Mqps) with batch size of 0 Time taken per op is 0.184us (5.4 Mqps) with batch size of 0 With 70000000 items, utilization is 52.15%, number of hash functions: 2. Time taken per op is 0.079us (12.7 Mqps) with batch size of 10 Time taken per op is 0.070us (14.2 Mqps) with batch size of 10 Time taken per op is 0.072us (14.0 Mqps) with batch size of 10 With 70000000 items, utilization is 52.15%, number of hash functions: 2. Time taken per op is 0.080us (12.5 Mqps) with batch size of 25 Time taken per op is 0.072us (14.0 Mqps) with batch size of 25 Time taken per op is 0.071us (14.1 Mqps) with batch size of 25 With 70000000 items, utilization is 52.15%, number of hash functions: 2. Time taken per op is 0.082us (12.1 Mqps) with batch size of 50 Time taken per op is 0.071us (14.1 Mqps) with batch size of 50 Time taken per op is 0.073us (13.6 Mqps) with batch size of 50 With 70000000 items, utilization is 52.15%, number of hash functions: 2. Time taken per op is 0.080us (12.5 Mqps) with batch size of 100 Time taken per op is 0.077us (13.0 Mqps) with batch size of 100 Time taken per op is 0.078us (12.8 Mqps) with batch size of 100 Test Plan: make check all make valgrind_check make asan_check Reviewers: sdong, ljin Reviewed By: ljin Subscribers: leveldb Differential Revision: https://reviews.facebook.net/D22539

Improve Cuckoo Table Reader performance. Inlined hash function and number of...
Improve Cuckoo Table Reader performance. Inlined hash function and number of buckets a power of two. Summary: Use inlined hash functions instead of function pointer. Make number of buckets a power of two and use bitwise and instead of mod. After these changes, we get almost 50% improvement in performance. Results: With 120000000 items, utilization is 89.41%, number of hash functions: 2. Time taken per op is 0.231us (4.3 Mqps) with batch size of 0 Time taken per op is 0.229us (4.4 Mqps) with batch size of 0 Time taken per op is 0.185us (5.4 Mqps) with batch size of 0 With 120000000 items, utilization is 89.41%, number of hash functions: 2. Time taken per op is 0.108us (9.3 Mqps) with batch size of 10 Time taken per op is 0.100us (10.0 Mqps) with batch size of 10 Time taken per op is 0.103us (9.7 Mqps) with batch size of 10 With 120000000 items, utilization is 89.41%, number of hash functions: 2. Time taken per op is 0.101us (9.9 Mqps) with batch size of 25 Time taken per op is 0.098us (10.2 Mqps) with batch size of 25 Time taken per op is 0.097us (10.3 Mqps) with batch size of 25 With 120000000 items, utilization is 89.41%, number of hash functions: 2. Time taken per op is 0.100us (10.0 Mqps) with batch size of 50 Time taken per op is 0.097us (10.3 Mqps) with batch size of 50 Time taken per op is 0.097us (10.3 Mqps) with batch size of 50 With 120000000 items, utilization is 89.41%, number of hash functions: 2. Time taken per op is 0.102us (9.8 Mqps) with batch size of 100 Time taken per op is 0.098us (10.2 Mqps) with batch size of 100 Time taken per op is 0.115us (8.7 Mqps) with batch size of 100 With 100000000 items, utilization is 74.51%, number of hash functions: 2. Time taken per op is 0.201us (5.0 Mqps) with batch size of 0 Time taken per op is 0.155us (6.5 Mqps) with batch size of 0 Time taken per op is 0.152us (6.6 Mqps) with batch size of 0 With 100000000 items, utilization is 74.51%, number of hash functions: 2. Time taken per op is 0.089us (11.3 Mqps) with batch size of 10 Time taken per op is 0.084us (11.9 Mqps) with batch size of 10 Time taken per op is 0.086us (11.6 Mqps) with batch size of 10 With 100000000 items, utilization is 74.51%, number of hash functions: 2. Time taken per op is 0.087us (11.5 Mqps) with batch size of 25 Time taken per op is 0.085us (11.7 Mqps) with batch size of 25 Time taken per op is 0.093us (10.8 Mqps) with batch size of 25 With 100000000 items, utilization is 74.51%, number of hash functions: 2. Time taken per op is 0.094us (10.6 Mqps) with batch size of 50 Time taken per op is 0.094us (10.7 Mqps) with batch size of 50 Time taken per op is 0.093us (10.8 Mqps) with batch size of 50 With 100000000 items, utilization is 74.51%, number of hash functions: 2. Time taken per op is 0.092us (10.9 Mqps) with batch size of 100 Time taken per op is 0.089us (11.2 Mqps) with batch size of 100 Time taken per op is 0.088us (11.3 Mqps) with batch size of 100 With 80000000 items, utilization is 59.60%, number of hash functions: 2. Time taken per op is 0.154us (6.5 Mqps) with batch size of 0 Time taken per op is 0.168us (6.0 Mqps) with batch size of 0 Time taken per op is 0.190us (5.3 Mqps) with batch size of 0 With 80000000 items, utilization is 59.60%, number of hash functions: 2. Time taken per op is 0.081us (12.4 Mqps) with batch size of 10 Time taken per op is 0.077us (13.0 Mqps) with batch size of 10 Time taken per op is 0.083us (12.1 Mqps) with batch size of 10 With 80000000 items, utilization is 59.60%, number of hash functions: 2. Time taken per op is 0.077us (13.0 Mqps) with batch size of 25 Time taken per op is 0.073us (13.7 Mqps) with batch size of 25 Time taken per op is 0.073us (13.7 Mqps) with batch size of 25 With 80000000 items, utilization is 59.60%, number of hash functions: 2. Time taken per op is 0.076us (13.1 Mqps) with batch size of 50 Time taken per op is 0.072us (13.8 Mqps) with batch size of 50 Time taken per op is 0.072us (13.8 Mqps) with batch size of 50 With 80000000 items, utilization is 59.60%, number of hash functions: 2. Time taken per op is 0.077us (13.0 Mqps) with batch size of 100 Time taken per op is 0.074us (13.6 Mqps) with batch size of 100 Time taken per op is 0.073us (13.6 Mqps) with batch size of 100 With 70000000 items, utilization is 52.15%, number of hash functions: 2. Time taken per op is 0.190us (5.3 Mqps) with batch size of 0 Time taken per op is 0.186us (5.4 Mqps) with batch size of 0 Time taken per op is 0.184us (5.4 Mqps) with batch size of 0 With 70000000 items, utilization is 52.15%, number of hash functions: 2. Time taken per op is 0.079us (12.7 Mqps) with batch size of 10 Time taken per op is 0.070us (14.2 Mqps) with batch size of 10 Time taken per op is 0.072us (14.0 Mqps) with batch size of 10 With 70000000 items, utilization is 52.15%, number of hash functions: 2. Time taken per op is 0.080us (12.5 Mqps) with batch size of 25 Time taken per op is 0.072us (14.0 Mqps) with batch size of 25 Time taken per op is 0.071us (14.1 Mqps) with batch size of 25 With 70000000 items, utilization is 52.15%, number of hash functions: 2. Time taken per op is 0.082us (12.1 Mqps) with batch size of 50 Time taken per op is 0.071us (14.1 Mqps) with batch size of 50 Time taken per op is 0.073us (13.6 Mqps) with batch size of 50 With 70000000 items, utilization is 52.15%, number of hash functions: 2. Time taken per op is 0.080us (12.5 Mqps) with batch size of 100 Time taken per op is 0.077us (13.0 Mqps) with batch size of 100 Time taken per op is 0.078us (12.8 Mqps) with batch size of 100 Test Plan: make check all make valgrind_check make asan_check Reviewers: sdong, ljin Reviewed By: ljin Subscribers: leveldb Differential Revision: https://reviews.facebook.net/D22539
d20b8cfa · Radheshyam Balasundaram · 0f9c43ea · d20b8cfa · d20b8cfa · d20b8cfa
8 changed file
--- a/table/cuckoo_table_builder.cc
+++ b/table/cuckoo_table_builder.cc
@@ -16,6 +16,7 @@
 #include "rocksdb/env.h"
 #include "rocksdb/table.h"
 #include "table/block_builder.h"
+#include "table/cuckoo_table_factory.h"
 #include "table/format.h"
 #include "table/meta_blocks.h"
 #include "util/autovector.h"
@@ -39,16 +40,17 @@ const std::string CuckooTablePropertyNames::kCuckooBlockSize =
 extern const uint64_t kCuckooTableMagicNumber = 0x926789d0c5f17873ull;

 CuckooTableBuilder::CuckooTableBuilder(
-    WritableFile* file, double hash_table_ratio,
+    WritableFile* file, double max_hash_table_ratio,
    uint32_t max_num_hash_table, uint32_t max_search_depth,
    const Comparator* user_comparator, uint32_t cuckoo_block_size,
    uint64_t (*get_slice_hash)(const Slice&, uint32_t, uint64_t))
    : num_hash_func_(2),
      file_(file),
-      hash_table_ratio_(hash_table_ratio),
+      max_hash_table_ratio_(max_hash_table_ratio),
      max_num_hash_func_(max_num_hash_table),
      max_search_depth_(max_search_depth),
      cuckoo_block_size_(std::max(1U, cuckoo_block_size)),
+      hash_table_size_(2),
      is_last_level_file_(false),
      has_seen_first_key_(false),
      ucomp_(user_comparator),
@@ -89,7 +91,6 @@ void CuckooTableBuilder::Add(const Slice& key, const Slice& value) {
  } else {
    kvs_.emplace_back(std::make_pair(key.ToString(), value.ToString()));
  }
-  properties_.num_entries++;

  // In order to fill the empty buckets in the hash table, we identify a
  // key which is not used so far (unused_user_key). We determine this by
@@ -101,11 +102,14 @@ void CuckooTableBuilder::Add(const Slice& key, const Slice& value) {
  } else if (ikey.user_key.compare(largest_user_key_) > 0) {
    largest_user_key_.assign(ikey.user_key.data(), ikey.user_key.size());
  }
+  if (hash_table_size_ < kvs_.size() / max_hash_table_ratio_) {
+    hash_table_size_ *= 2;
+  }
 }

 Status CuckooTableBuilder::MakeHashTable(std::vector<CuckooBucket>* buckets) {
-  uint64_t hash_table_size = kvs_.size() / hash_table_ratio_;
-  buckets->resize(hash_table_size + cuckoo_block_size_ - 1);
+  uint64_t hash_table_size_minus_one = hash_table_size_ - 1;
+  buckets->resize(hash_table_size_minus_one + cuckoo_block_size_);
  uint64_t make_space_for_key_call_id = 0;
  for (uint32_t vector_idx = 0; vector_idx < kvs_.size(); vector_idx++) {
    uint64_t bucket_id;
@@ -115,7 +119,8 @@ Status CuckooTableBuilder::MakeHashTable(std::vector<CuckooBucket>* buckets) {
      ExtractUserKey(kvs_[vector_idx].first);
    for (uint32_t hash_cnt = 0; hash_cnt < num_hash_func_ && !bucket_found;
        ++hash_cnt) {
-      uint64_t hash_val = get_slice_hash_(user_key, hash_cnt, hash_table_size);
+      uint64_t hash_val = CuckooHash(user_key, hash_cnt,
+          hash_table_size_minus_one, get_slice_hash_);
      // If there is a collision, check next cuckoo_block_size_ locations for
      // empty locations. While checking, if we reach end of the hash table,
      // stop searching and proceed for next hash function.
@@ -137,15 +142,15 @@ Status CuckooTableBuilder::MakeHashTable(std::vector<CuckooBucket>* buckets) {
      }
    }
    while (!bucket_found && !MakeSpaceForKey(hash_vals,
-          hash_table_size, ++make_space_for_key_call_id, buckets, &bucket_id)) {
+          ++make_space_for_key_call_id, buckets, &bucket_id)) {
      // Rehash by increashing number of hash tables.
      if (num_hash_func_ >= max_num_hash_func_) {
        return Status::NotSupported("Too many collisions. Unable to hash.");
      }
      // We don't really need to rehash the entire table because old hashes are
      // still valid and we only increased the number of hash functions.
-      uint64_t hash_val = get_slice_hash_(user_key,
-          num_hash_func_, hash_table_size);
+      uint64_t hash_val = CuckooHash(user_key, num_hash_func_,
+          hash_table_size_minus_one, get_slice_hash_);
      ++num_hash_func_;
      for (uint32_t block_idx = 0; block_idx < cuckoo_block_size_;
          ++block_idx, ++hash_val) {
@@ -167,13 +172,14 @@ Status CuckooTableBuilder::Finish() {
  assert(!closed_);
  closed_ = true;
  std::vector<CuckooBucket> buckets;
-  Status s = MakeHashTable(&buckets);
-  if (!s.ok()) {
-    return s;
-  }
-  // Determine unused_user_key to fill empty buckets.
+  Status s;
  std::string unused_bucket;
  if (!kvs_.empty()) {
+    s = MakeHashTable(&buckets);
+    if (!s.ok()) {
+      return s;
+    }
+    // Determine unused_user_key to fill empty buckets.
    std::string unused_user_key = smallest_user_key_;
    int curr_pos = unused_user_key.size() - 1;
    while (curr_pos >= 0) {
@@ -205,6 +211,7 @@ Status CuckooTableBuilder::Finish() {
      AppendInternalKey(&unused_bucket, ikey);
    }
  }
+  properties_.num_entries = kvs_.size();
  properties_.fixed_key_len = unused_bucket.size();
  uint32_t value_length = kvs_.empty() ? 0 : kvs_[0].second.size();
  uint32_t bucket_size = value_length + properties_.fixed_key_len;
@@ -298,7 +305,7 @@ void CuckooTableBuilder::Abandon() {
 }

 uint64_t CuckooTableBuilder::NumEntries() const {
-  return properties_.num_entries;
+  return kvs_.size();
 }

 uint64_t CuckooTableBuilder::FileSize() const {
@@ -307,11 +314,17 @@ uint64_t CuckooTableBuilder::FileSize() const {
  } else if (properties_.num_entries == 0) {
    return 0;
  }
-  // This is not the actual size of the file as we need to account for
-  // hash table ratio. This returns the size of filled buckets in the table
-  // scaled up by a factor of 1/hash_table_ratio.
-  return ((kvs_[0].first.size() + kvs_[0].second.size()) *
-      properties_.num_entries) / hash_table_ratio_;
+
+  // Account for buckets being a power of two.
+  // As elements are added, file size remains constant for a while and doubles
+  // its size. Since compaction algorithm stops adding elements only after it
+  // exceeds the file limit, we account for the extra element being added here.
+  uint64_t expected_hash_table_size = hash_table_size_;
+  if (expected_hash_table_size < (kvs_.size() + 1) / max_hash_table_ratio_) {
+    expected_hash_table_size *= 2;
+  }
+  return (kvs_[0].first.size() + kvs_[0].second.size()) *
+    expected_hash_table_size;
 }

 // This method is invoked when there is no place to insert the target key.
@@ -326,7 +339,6 @@ uint64_t CuckooTableBuilder::FileSize() const {
 // If tree depth exceedes max depth, we return false indicating failure.
 bool CuckooTableBuilder::MakeSpaceForKey(
    const autovector<uint64_t>& hash_vals,
-    const uint64_t hash_table_size,
    const uint64_t make_space_for_key_call_id,
    std::vector<CuckooBucket>* buckets,
    uint64_t* bucket_id) {
@@ -354,6 +366,7 @@ bool CuckooTableBuilder::MakeSpaceForKey(
      make_space_for_key_call_id;
    tree.push_back(CuckooNode(bucket_id, 0, 0));
  }
+  uint64_t hash_table_size_minus_one = hash_table_size_ - 1;
  bool null_found = false;
  uint32_t curr_pos = 0;
  while (!null_found && curr_pos < tree.size()) {
@@ -365,10 +378,11 @@ bool CuckooTableBuilder::MakeSpaceForKey(
    CuckooBucket& curr_bucket = (*buckets)[curr_node.bucket_id];
    for (uint32_t hash_cnt = 0;
        hash_cnt < num_hash_func_ && !null_found; ++hash_cnt) {
-      uint64_t child_bucket_id = get_slice_hash_(
-          is_last_level_file_ ? kvs_[curr_bucket.vector_idx].first
-          : ExtractUserKey(Slice(kvs_[curr_bucket.vector_idx].first)),
-          hash_cnt, hash_table_size);
+      uint64_t child_bucket_id = CuckooHash(
+          (is_last_level_file_ ? kvs_[curr_bucket.vector_idx].first :
+           ExtractUserKey(Slice(kvs_[curr_bucket.vector_idx].first))),
+          hash_cnt, hash_table_size_minus_one, get_slice_hash_);
+      // Iterate inside Cuckoo Block.
      for (uint32_t block_idx = 0; block_idx < cuckoo_block_size_;
          ++block_idx, ++child_bucket_id) {
        if ((*buckets)[child_bucket_id].make_space_for_key_call_id ==

--- a/table/cuckoo_table_builder.h
+++ b/table/cuckoo_table_builder.h
@@ -21,9 +21,9 @@ namespace rocksdb {
 class CuckooTableBuilder: public TableBuilder {
 public:
  CuckooTableBuilder(
-      WritableFile* file, double hash_table_ratio, uint32_t max_num_hash_table,
-      uint32_t max_search_depth, const Comparator* user_comparator,
-      uint32_t cuckoo_block_size,
+      WritableFile* file, double max_hash_table_ratio,
+      uint32_t max_num_hash_func, uint32_t max_search_depth,
+      const Comparator* user_comparator, uint32_t cuckoo_block_size,
      uint64_t (*get_slice_hash)(const Slice&, uint32_t, uint64_t));

  // REQUIRES: Either Finish() or Abandon() has been called.
@@ -69,7 +69,6 @@ class CuckooTableBuilder: public TableBuilder {

  bool MakeSpaceForKey(
      const autovector<uint64_t>& hash_vals,
-      const uint64_t hash_table_size,
      const uint64_t call_id,
      std::vector<CuckooBucket>* buckets,
      uint64_t* bucket_id);
@@ -77,10 +76,11 @@ class CuckooTableBuilder: public TableBuilder {

  uint32_t num_hash_func_;
  WritableFile* file_;
-  const double hash_table_ratio_;
+  const double max_hash_table_ratio_;
  const uint32_t max_num_hash_func_;
  const uint32_t max_search_depth_;
  const uint32_t cuckoo_block_size_;
+  uint64_t hash_table_size_;
  bool is_last_level_file_;
  Status status_;
  std::vector<std::pair<std::string, std::string>> kvs_;

--- a/table/cuckoo_table_builder_test.cc
+++ b/table/cuckoo_table_builder_test.cc
@@ -114,6 +114,14 @@ class CuckooBuilderTest {
    return ikey.GetKey().ToString();
  }

+  uint64_t NextPowOf2(uint64_t num) {
+    uint64_t n = 2;
+    while (n <= num) {
+      n *= 2;
+    }
+    return n;
+  }
+
  Env* env_;
  EnvOptions env_options_;
  std::string fname;
@@ -122,7 +130,7 @@ class CuckooBuilderTest {

 TEST(CuckooBuilderTest, SuccessWithEmptyFile) {
  unique_ptr<WritableFile> writable_file;
-  fname = test::TmpDir() + "/NoCollisionFullKey";
+  fname = test::TmpDir() + "/EmptyFile";
  ASSERT_OK(env_->NewWritableFile(fname, &writable_file, env_options_));
  CuckooTableBuilder builder(writable_file.get(), kHashTableRatio,
      4, 100, BytewiseComparator(), 1, GetSliceHash);
@@ -162,7 +170,7 @@ TEST(CuckooBuilderTest, WriteSuccessNoCollisionFullKey) {
  ASSERT_OK(builder.Finish());
  ASSERT_OK(writable_file->Close());

-  uint32_t expected_table_size = keys.size() / kHashTableRatio;
+  uint32_t expected_table_size = NextPowOf2(keys.size() / kHashTableRatio);
  std::string expected_unused_bucket = GetInternalKey("key00", true);
  expected_unused_bucket += std::string(values[0].size(), 'a');
  CheckFileContents(keys, values, expected_locations,
@@ -199,7 +207,7 @@ TEST(CuckooBuilderTest, WriteSuccessWithCollisionFullKey) {
  ASSERT_OK(builder.Finish());
  ASSERT_OK(writable_file->Close());

-  uint32_t expected_table_size = keys.size() / kHashTableRatio;
+  uint32_t expected_table_size = NextPowOf2(keys.size() / kHashTableRatio);
  std::string expected_unused_bucket = GetInternalKey("key00", true);
  expected_unused_bucket += std::string(values[0].size(), 'a');
  CheckFileContents(keys, values, expected_locations,
@@ -237,7 +245,7 @@ TEST(CuckooBuilderTest, WriteSuccessWithCollisionAndCuckooBlock) {
  ASSERT_OK(builder.Finish());
  ASSERT_OK(writable_file->Close());

-  uint32_t expected_table_size = keys.size() / kHashTableRatio;
+  uint32_t expected_table_size = NextPowOf2(keys.size() / kHashTableRatio);
  std::string expected_unused_bucket = GetInternalKey("key00", true);
  expected_unused_bucket += std::string(values[0].size(), 'a');
  CheckFileContents(keys, values, expected_locations,
@@ -279,7 +287,7 @@ TEST(CuckooBuilderTest, WithCollisionPathFullKey) {
  ASSERT_OK(builder.Finish());
  ASSERT_OK(writable_file->Close());

-  uint32_t expected_table_size = keys.size() / kHashTableRatio;
+  uint32_t expected_table_size = NextPowOf2(keys.size() / kHashTableRatio);
  std::string expected_unused_bucket = GetInternalKey("key00", true);
  expected_unused_bucket += std::string(values[0].size(), 'a');
  CheckFileContents(keys, values, expected_locations,
@@ -318,7 +326,7 @@ TEST(CuckooBuilderTest, WithCollisionPathFullKeyAndCuckooBlock) {
  ASSERT_OK(builder.Finish());
  ASSERT_OK(writable_file->Close());

-  uint32_t expected_table_size = keys.size() / kHashTableRatio;
+  uint32_t expected_table_size = NextPowOf2(keys.size() / kHashTableRatio);
  std::string expected_unused_bucket = GetInternalKey("key00", true);
  expected_unused_bucket += std::string(values[0].size(), 'a');
  CheckFileContents(keys, values, expected_locations,
@@ -351,7 +359,7 @@ TEST(CuckooBuilderTest, WriteSuccessNoCollisionUserKey) {
  ASSERT_OK(builder.Finish());
  ASSERT_OK(writable_file->Close());

-  uint32_t expected_table_size = user_keys.size() / kHashTableRatio;
+  uint32_t expected_table_size = NextPowOf2(user_keys.size() / kHashTableRatio);
  std::string expected_unused_bucket = "key00";
  expected_unused_bucket += std::string(values[0].size(), 'a');
  CheckFileContents(user_keys, values, expected_locations,
@@ -384,7 +392,7 @@ TEST(CuckooBuilderTest, WriteSuccessWithCollisionUserKey) {
  ASSERT_OK(builder.Finish());
  ASSERT_OK(writable_file->Close());

-  uint32_t expected_table_size = user_keys.size() / kHashTableRatio;
+  uint32_t expected_table_size = NextPowOf2(user_keys.size() / kHashTableRatio);
  std::string expected_unused_bucket = "key00";
  expected_unused_bucket += std::string(values[0].size(), 'a');
  CheckFileContents(user_keys, values, expected_locations,
@@ -419,7 +427,7 @@ TEST(CuckooBuilderTest, WithCollisionPathUserKey) {
  ASSERT_OK(builder.Finish());
  ASSERT_OK(writable_file->Close());

-  uint32_t expected_table_size = user_keys.size() / kHashTableRatio;
+  uint32_t expected_table_size = NextPowOf2(user_keys.size() / kHashTableRatio);
  std::string expected_unused_bucket = "key00";
  expected_unused_bucket += std::string(values[0].size(), 'a');
  CheckFileContents(user_keys, values, expected_locations,

--- a/table/cuckoo_table_factory.cc
+++ b/table/cuckoo_table_factory.cc
@@ -9,34 +9,14 @@
 #include "db/dbformat.h"
 #include "table/cuckoo_table_builder.h"
 #include "table/cuckoo_table_reader.h"
-#include "util/murmurhash.h"

 namespace rocksdb {
-extern const uint32_t kMaxNumHashTable = 64;
-
-extern uint64_t GetSliceMurmurHash(const Slice& s, uint32_t index,
-    uint64_t max_num_buckets) {
-  static constexpr uint32_t seeds[kMaxNumHashTable] = {
-    816922183, 506425713, 949485004, 22513986, 421427259, 500437285,
-    888981693, 847587269, 511007211, 722295391, 934013645, 566947683,
-    193618736, 428277388, 770956674, 819994962, 755946528, 40807421,
-    263144466, 241420041, 444294464, 731606396, 304158902, 563235655,
-    968740453, 336996831, 462831574, 407970157, 985877240, 637708754,
-    736932700, 205026023, 755371467, 729648411, 807744117, 46482135,
-    847092855, 620960699, 102476362, 314094354, 625838942, 550889395,
-    639071379, 834567510, 397667304, 151945969, 443634243, 196618243,
-    421986347, 407218337, 964502417, 327741231, 493359459, 452453139,
-    692216398, 108161624, 816246924, 234779764, 618949448, 496133787,
-    156374056, 316589799, 982915425, 553105889 };
-  return MurmurHash(s.data(), s.size(), seeds[index]) % max_num_buckets;
-}
-
 Status CuckooTableFactory::NewTableReader(const Options& options,
    const EnvOptions& soptions, const InternalKeyComparator& icomp,
    std::unique_ptr<RandomAccessFile>&& file, uint64_t file_size,
    std::unique_ptr<TableReader>* table) const {
  std::unique_ptr<CuckooTableReader> new_reader(new CuckooTableReader(options,
-      std::move(file), file_size, icomp.user_comparator(), GetSliceMurmurHash));
+      std::move(file), file_size, icomp.user_comparator(), nullptr));
  Status s = new_reader->status();
  if (s.ok()) {
    *table = std::move(new_reader);
@@ -47,9 +27,8 @@ Status CuckooTableFactory::NewTableReader(const Options& options,
 TableBuilder* CuckooTableFactory::NewTableBuilder(
    const Options& options, const InternalKeyComparator& internal_comparator,
    WritableFile* file, CompressionType compression_type) const {
-  return new CuckooTableBuilder(file, hash_table_ratio_, kMaxNumHashTable,
-      max_search_depth_, internal_comparator.user_comparator(),
-      cuckoo_block_size_, GetSliceMurmurHash);
+  return new CuckooTableBuilder(file, hash_table_ratio_, 64, max_search_depth_,
+      internal_comparator.user_comparator(), cuckoo_block_size_, nullptr);
 }

 std::string CuckooTableFactory::GetPrintableTableOptions() const {
@@ -64,6 +43,9 @@ std::string CuckooTableFactory::GetPrintableTableOptions() const {
  snprintf(buffer, kBufferSize, "  max_search_depth: %u\n",
           max_search_depth_);
  ret.append(buffer);
+  snprintf(buffer, kBufferSize, "  cuckoo_block_size: %u\n",
+           cuckoo_block_size_);
+  ret.append(buffer);
  return ret;
 }


--- a/table/cuckoo_table_factory.h
+++ b/table/cuckoo_table_factory.h
@@ -8,11 +8,23 @@

 #include <string>
 #include "rocksdb/table.h"
+#include "util/murmurhash.h"

 namespace rocksdb {

-extern uint64_t GetSliceMurmurHash(const Slice& s, uint32_t index,
-    uint64_t max_num_buckets);
+const uint32_t kCuckooMurmurSeedMultiplier = 816922183;
+static inline uint64_t CuckooHash(
+    const Slice& user_key, uint32_t hash_cnt, uint64_t table_size_minus_one,
+    uint64_t (*get_slice_hash)(const Slice&, uint32_t, uint64_t)) {
+#ifndef NDEBUG
+  // This part is used only in unit tests.
+  if (get_slice_hash != nullptr) {
+    return get_slice_hash(user_key, hash_cnt, table_size_minus_one + 1);
+  }
+#endif
+  return MurmurHash(user_key.data(), user_key.size(),
+      kCuckooMurmurSeedMultiplier * hash_cnt) & table_size_minus_one;
+}

 // Cuckoo Table is designed for applications that require fast point lookups
 // but not fast range scans.

--- a/table/cuckoo_table_reader.cc
+++ b/table/cuckoo_table_reader.cc
@@ -17,12 +17,13 @@
 #include <vector>
 #include "rocksdb/iterator.h"
 #include "table/meta_blocks.h"
+#include "table/cuckoo_table_factory.h"
 #include "util/arena.h"
 #include "util/coding.h"

 namespace rocksdb {
 namespace {
-  static const uint64_t CACHE_LINE_MASK = ~(CACHE_LINE_SIZE - 1);
+  static const uint64_t CACHE_LINE_MASK = ~((uint64_t)CACHE_LINE_SIZE - 1);
 }

 extern const uint64_t kCuckooTableMagicNumber;
@@ -76,8 +77,8 @@ CuckooTableReader::CuckooTableReader(
    status_ = Status::InvalidArgument("Hash table size not found");
    return;
  }
-  hash_table_size_ = *reinterpret_cast<const uint64_t*>(
-      hash_table_size->second.data());
+  table_size_minus_one_ = *reinterpret_cast<const uint64_t*>(
+      hash_table_size->second.data()) - 1;
  auto is_last_level = user_props.find(CuckooTablePropertyNames::kIsLastLevel);
  if (is_last_level == user_props.end()) {
    status_ = Status::InvalidArgument("Is last level not found");
@@ -104,11 +105,11 @@ Status CuckooTableReader::Get(
  assert(key.size() == key_length_ + (is_last_level_ ? 8 : 0));
  Slice user_key = ExtractUserKey(key);
  for (uint32_t hash_cnt = 0; hash_cnt < num_hash_func_; ++hash_cnt) {
-    uint64_t hash_val = get_slice_hash_(user_key, hash_cnt, hash_table_size_);
-    assert(hash_val < hash_table_size_);
+    uint64_t offset = bucket_length_ * CuckooHash(
+        user_key, hash_cnt, table_size_minus_one_, get_slice_hash_);
+    const char* bucket = &file_data_.data()[offset];
    for (uint32_t block_idx = 0; block_idx < cuckoo_block_size_;
-        ++block_idx, ++hash_val) {
-      const char* bucket = &file_data_.data()[hash_val * bucket_length_];
+        ++block_idx, bucket += bucket_length_) {
      if (ucomp_->Compare(Slice(unused_key_.data(), user_key.size()),
            Slice(bucket, user_key.size())) == 0) {
        return Status::OK();
@@ -137,8 +138,9 @@ Status CuckooTableReader::Get(

 void CuckooTableReader::Prepare(const Slice& key) {
  // Prefetch the first Cuckoo Block.
-  uint64_t addr = reinterpret_cast<uint64_t>(file_data_.data()) + bucket_length_
-    * get_slice_hash_(ExtractUserKey(key), 0, hash_table_size_);
+  Slice user_key = ExtractUserKey(key);
+  uint64_t addr = reinterpret_cast<uint64_t>(file_data_.data()) +
+    bucket_length_ * CuckooHash(user_key, 0, table_size_minus_one_, nullptr);
  uint64_t end_addr = addr + cuckoo_block_bytes_minus_one_;
  for (addr &= CACHE_LINE_MASK; addr < end_addr; addr += CACHE_LINE_SIZE) {
    PREFETCH(reinterpret_cast<const char*>(addr), 0, 3);
@@ -205,8 +207,8 @@ CuckooTableIterator::CuckooTableIterator(CuckooTableReader* reader)

 void CuckooTableIterator::LoadKeysFromReader() {
  key_to_bucket_id_.reserve(reader_->GetTableProperties()->num_entries);
-  uint64_t num_buckets = reader_->hash_table_size_ +
-    reader_->cuckoo_block_size_ - 1;
+  uint64_t num_buckets = reader_->table_size_minus_one_ +
+    reader_->cuckoo_block_size_;
  for (uint32_t bucket_id = 0; bucket_id < num_buckets; bucket_id++) {
    Slice read_key;
    status_ = reader_->file_->Read(bucket_id * reader_->bucket_length_,

--- a/table/cuckoo_table_reader.h
+++ b/table/cuckoo_table_reader.h
@@ -72,7 +72,7 @@ class CuckooTableReader: public TableReader {
  uint32_t bucket_length_;
  uint32_t cuckoo_block_size_;
  uint32_t cuckoo_block_bytes_minus_one_;
-  uint64_t hash_table_size_;
+  uint64_t table_size_minus_one_;
  const Comparator* ucomp_;
  uint64_t (*get_slice_hash_)(const Slice& s, uint32_t index,
      uint64_t max_num_buckets);

--- a/table/cuckoo_table_reader_test.cc
+++ b/table/cuckoo_table_reader_test.cc
@@ -38,9 +38,6 @@ DEFINE_bool(write, false,

 namespace rocksdb {

-extern const uint64_t kCuckooTableMagicNumber;
-extern const uint64_t kMaxNumHashTable;
-
 namespace {
 const uint32_t kNumHashFunc = 10;
 // Methods, variables related to Hash functions.
@@ -397,13 +394,12 @@ void GetKeys(uint64_t num, std::vector<std::string>* keys) {
  }
 }

-std::string GetFileName(uint64_t num, double hash_ratio) {
+std::string GetFileName(uint64_t num) {
  if (FLAGS_file_dir.empty()) {
    FLAGS_file_dir = test::TmpDir();
  }
  return FLAGS_file_dir + "/cuckoo_read_benchmark" +
-    std::to_string(num/1000000) + "Mratio" +
-    std::to_string(static_cast<int>(100*hash_ratio));
+    std::to_string(num/1000000) + "Mkeys";
 }

 // Create last level file as we are interested in measuring performance of
@@ -414,13 +410,13 @@ void WriteFile(const std::vector<std::string>& keys,
  options.allow_mmap_reads = true;
  Env* env = options.env;
  EnvOptions env_options = EnvOptions(options);
-  std::string fname = GetFileName(num, hash_ratio);
+  std::string fname = GetFileName(num);

  std::unique_ptr<WritableFile> writable_file;
  ASSERT_OK(env->NewWritableFile(fname, &writable_file, env_options));
  CuckooTableBuilder builder(
      writable_file.get(), hash_ratio,
-      kMaxNumHashTable, 1000, test::Uint64Comparator(), 5, GetSliceMurmurHash);
+      64, 1000, test::Uint64Comparator(), 5, nullptr);
  ASSERT_OK(builder.status());
  for (uint64_t key_idx = 0; key_idx < num; ++key_idx) {
    // Value is just a part of key.
@@ -439,27 +435,25 @@ void WriteFile(const std::vector<std::string>& keys,

  CuckooTableReader reader(
      options, std::move(read_file), file_size,
-      test::Uint64Comparator(), GetSliceMurmurHash);
+      test::Uint64Comparator(), nullptr);
  ASSERT_OK(reader.status());
  ReadOptions r_options;
-  for (const auto& key : keys) {
+  for (uint64_t i = 0; i < num; ++i) {
    int cnt = 0;
-    ASSERT_OK(reader.Get(r_options, Slice(key), &cnt, CheckValue, nullptr));
+    ASSERT_OK(reader.Get(r_options, Slice(keys[i]), &cnt, CheckValue, nullptr));
    if (cnt != 1) {
-      fprintf(stderr, "%" PRIu64 " not found.\n",
-          *reinterpret_cast<const uint64_t*>(key.data()));
+      fprintf(stderr, "%" PRIu64 " not found.\n", i);
      ASSERT_EQ(1, cnt);
    }
  }
 }

-void ReadKeys(const std::vector<std::string>& keys, uint64_t num,
-    double hash_ratio, uint32_t batch_size) {
+void ReadKeys(uint64_t num, uint32_t batch_size) {
  Options options;
  options.allow_mmap_reads = true;
  Env* env = options.env;
  EnvOptions env_options = EnvOptions(options);
-  std::string fname = GetFileName(num, hash_ratio);
+  std::string fname = GetFileName(num);

  uint64_t file_size;
  env->GetFileSize(fname, &file_size);
@@ -468,29 +462,33 @@ void ReadKeys(const std::vector<std::string>& keys, uint64_t num,

  CuckooTableReader reader(
      options, std::move(read_file), file_size, test::Uint64Comparator(),
-      GetSliceMurmurHash);
+      nullptr);
  ASSERT_OK(reader.status());
  const UserCollectedProperties user_props =
    reader.GetTableProperties()->user_collected_properties;
  const uint32_t num_hash_fun = *reinterpret_cast<const uint32_t*>(
      user_props.at(CuckooTablePropertyNames::kNumHashFunc).data());
-  fprintf(stderr, "With %" PRIu64 " items and hash table ratio %f, number of"
-      " hash functions used: %u.\n", num, hash_ratio, num_hash_fun);
+  const uint64_t table_size = *reinterpret_cast<const uint64_t*>(
+      user_props.at(CuckooTablePropertyNames::kHashTableSize).data());
+  fprintf(stderr, "With %" PRIu64 " items, utilization is %.2f%%, number of"
+      " hash functions: %u.\n", num, num * 100.0 / (table_size), num_hash_fun);
  ReadOptions r_options;

  uint64_t start_time = env->NowMicros();
  if (batch_size > 0) {
    for (uint64_t i = 0; i < num; i += batch_size) {
      for (uint64_t j = i; j < i+batch_size && j < num; ++j) {
-        reader.Prepare(Slice(keys[j]));
+        reader.Prepare(Slice(reinterpret_cast<char*>(&j), 16));
      }
      for (uint64_t j = i; j < i+batch_size && j < num; ++j) {
-        reader.Get(r_options, Slice(keys[j]), nullptr, DoNothing, nullptr);
+        reader.Get(r_options, Slice(reinterpret_cast<char*>(&j), 16),
+            nullptr, DoNothing, nullptr);
      }
    }
  } else {
    for (uint64_t i = 0; i < num; i++) {
-      reader.Get(r_options, Slice(keys[i]), nullptr, DoNothing, nullptr);
+      reader.Get(r_options, Slice(reinterpret_cast<char*>(&i), 16), nullptr,
+          DoNothing, nullptr);
    }
  }
  float time_per_op = (env->NowMicros() - start_time) * 1.0 / num;
@@ -501,26 +499,30 @@ void ReadKeys(const std::vector<std::string>& keys, uint64_t num,
 }  // namespace.

 TEST(CuckooReaderTest, TestReadPerformance) {
-  uint64_t num = 1000*1000*100;
  if (!FLAGS_enable_perf) {
    return;
  }
+  double hash_ratio = 0.95;
+  // These numbers are chosen to have a hash utilizaiton % close to
+  // 0.9, 0.75, 0.6 and 0.5 respectively.
+  // They all create 128 M buckets.
+  std::vector<uint64_t> nums = {120*1000*1000, 100*1000*1000, 80*1000*1000,
+    70*1000*1000};
 #ifndef NDEBUG
  fprintf(stdout,
      "WARNING: Not compiled with DNDEBUG. Performance tests may be slow.\n");
 #endif
  std::vector<std::string> keys;
-  GetKeys(num, &keys);
-  for (double hash_ratio : std::vector<double>({0.5, 0.6, 0.75, 0.9})) {
-    if (FLAGS_write || !Env::Default()->FileExists(
-          GetFileName(num, hash_ratio))) {
+  GetKeys(*std::max_element(nums.begin(), nums.end()), &keys);
+  for (uint64_t num : nums) {
+    if (FLAGS_write || !Env::Default()->FileExists(GetFileName(num))) {
      WriteFile(keys, num, hash_ratio);
    }
-    ReadKeys(keys, num, hash_ratio, 0);
-    ReadKeys(keys, num, hash_ratio, 10);
-    ReadKeys(keys, num, hash_ratio, 25);
-    ReadKeys(keys, num, hash_ratio, 50);
-    ReadKeys(keys, num, hash_ratio, 100);
+    ReadKeys(num, 0);
+    ReadKeys(num, 10);
+    ReadKeys(num, 25);
+    ReadKeys(num, 50);
+    ReadKeys(num, 100);
    fprintf(stderr, "\n");
  }
 }