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rocksdb/util/ribbon_test.cc
Peter Dillinger 22161b7547 Upgrade xxhash, add Hash128 (#8634) 
Summary:
With expected use for a 128-bit hash, xxhash library is
upgraded to current dev (2c611a76f914828bed675f0f342d6c4199ffee1e)
as of Aug 6 so that we can use production version of XXH3_128bits
as new Hash128 function (added in hash128.h).

To make this work, however, we have to carve out the "preview" version
of XXH3 that is used in new SST Bloom and Ribbon filters, since that
will not get maintenance in xxhash releases. I have consolidated all the
relevant code into xxph3.h and made it "inline only" (no .cc file). The
working name for this hash function is changed from XXH3p to XXPH3
(XX Preview Hash) because the latter is easier to get working with no
symbol name conflicts between the headers.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/8634

Test Plan:
no expected change in existing functionality. For Hash128,
added some unit tests based on those for Hash64 to ensure some basic
properties and that the values do not change accidentally.

Reviewed By: zhichao-cao

Differential Revision: D30173490

Pulled By: pdillinger

fbshipit-source-id: 06aa542a7a28b353bc2c865b9b2f8bdfe44158e4
2021-08-20 18:41:51 -07:00

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// Copyright (c) Facebook, Inc. and its affiliates. 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).
#include "rocksdb/system_clock.h"
#include "test_util/testharness.h"
#include "util/bloom_impl.h"
#include "util/coding.h"
#include "util/hash.h"
#include "util/ribbon_config.h"
#include "util/ribbon_impl.h"
#include "util/stop_watch.h"
#include "util/string_util.h"
#ifndef GFLAGS
uint32_t FLAGS_thoroughness = 5;
uint32_t FLAGS_max_add = 0;
uint32_t FLAGS_min_check = 4000;
uint32_t FLAGS_max_check = 100000;
bool FLAGS_verbose = false;
bool FLAGS_find_occ = false;
bool FLAGS_find_slot_occ = false;
double FLAGS_find_next_factor = 1.618;
uint32_t FLAGS_find_iters = 10000;
uint32_t FLAGS_find_min_slots = 128;
uint32_t FLAGS_find_max_slots = 1000000;
bool FLAGS_optimize_homog = false;
uint32_t FLAGS_optimize_homog_slots = 30000000;
uint32_t FLAGS_optimize_homog_check = 200000;
double FLAGS_optimize_homog_granularity = 0.002;
#else
#include "util/gflags_compat.h"
using GFLAGS_NAMESPACE::ParseCommandLineFlags;
// Using 500 is a good test when you have time to be thorough.
// Default is for general RocksDB regression test runs.
DEFINE_uint32(thoroughness, 5, "iterations per configuration");
DEFINE_uint32(max_add, 0,
"Add up to this number of entries to a single filter in "
"CompactnessAndBacktrackAndFpRate; 0 == reasonable default");
DEFINE_uint32(min_check, 4000,
"Minimum number of novel entries for testing FP rate");
DEFINE_uint32(max_check, 10000,
"Maximum number of novel entries for testing FP rate");
DEFINE_bool(verbose, false, "Print extra details");
// Options for FindOccupancy, which is more of a tool than a test.
DEFINE_bool(find_occ, false, "whether to run the FindOccupancy tool");
DEFINE_bool(find_slot_occ, false,
"whether to show individual slot occupancies with "
"FindOccupancy tool");
DEFINE_double(find_next_factor, 1.618,
"factor to next num_slots for FindOccupancy");
DEFINE_uint32(find_iters, 10000, "number of samples for FindOccupancy");
DEFINE_uint32(find_min_slots, 128, "number of slots for FindOccupancy");
DEFINE_uint32(find_max_slots, 1000000, "number of slots for FindOccupancy");
// Options for OptimizeHomogAtScale, which is more of a tool than a test.
DEFINE_bool(optimize_homog, false,
"whether to run the OptimizeHomogAtScale tool");
DEFINE_uint32(optimize_homog_slots, 30000000,
"number of slots for OptimizeHomogAtScale");
DEFINE_uint32(optimize_homog_check, 200000,
"number of queries for checking FP rate in OptimizeHomogAtScale");
DEFINE_double(
optimize_homog_granularity, 0.002,
"overhead change between FP rate checking in OptimizeHomogAtScale");
#endif // GFLAGS
template <typename TypesAndSettings>
class RibbonTypeParamTest : public ::testing::Test {};
class RibbonTest : public ::testing::Test {};
namespace {
// Different ways of generating keys for testing
// Generate semi-sequential keys
struct StandardKeyGen {
StandardKeyGen(const std::string& prefix, uint64_t id)
: id_(id), str_(prefix) {
ROCKSDB_NAMESPACE::PutFixed64(&str_, /*placeholder*/ 0);
}
// Prefix (only one required)
StandardKeyGen& operator++() {
++id_;
return *this;
}
StandardKeyGen& operator+=(uint64_t i) {
id_ += i;
return *this;
}
const std::string& operator*() {
// Use multiplication to mix things up a little in the key
ROCKSDB_NAMESPACE::EncodeFixed64(&str_[str_.size() - 8],
id_ * uint64_t{0x1500000001});
return str_;
}
bool operator==(const StandardKeyGen& other) {
// Same prefix is assumed
return id_ == other.id_;
}
bool operator!=(const StandardKeyGen& other) {
// Same prefix is assumed
return id_ != other.id_;
}
uint64_t id_;
std::string str_;
};
// Generate small sequential keys, that can misbehave with sequential seeds
// as in https://github.com/Cyan4973/xxHash/issues/469.
// These keys are only heuristically unique, but that's OK with 64 bits,
// for testing purposes.
struct SmallKeyGen {
SmallKeyGen(const std::string& prefix, uint64_t id) : id_(id) {
// Hash the prefix for a heuristically unique offset
id_ += ROCKSDB_NAMESPACE::GetSliceHash64(prefix);
ROCKSDB_NAMESPACE::PutFixed64(&str_, id_);
}
// Prefix (only one required)
SmallKeyGen& operator++() {
++id_;
return *this;
}
SmallKeyGen& operator+=(uint64_t i) {
id_ += i;
return *this;
}
const std::string& operator*() {
ROCKSDB_NAMESPACE::EncodeFixed64(&str_[str_.size() - 8], id_);
return str_;
}
bool operator==(const SmallKeyGen& other) { return id_ == other.id_; }
bool operator!=(const SmallKeyGen& other) { return id_ != other.id_; }
uint64_t id_;
std::string str_;
};
template <typename KeyGen>
struct Hash32KeyGenWrapper : public KeyGen {
Hash32KeyGenWrapper(const std::string& prefix, uint64_t id)
: KeyGen(prefix, id) {}
uint32_t operator*() {
auto& key = *static_cast<KeyGen&>(*this);
// unseeded
return ROCKSDB_NAMESPACE::GetSliceHash(key);
}
};
template <typename KeyGen>
struct Hash64KeyGenWrapper : public KeyGen {
Hash64KeyGenWrapper(const std::string& prefix, uint64_t id)
: KeyGen(prefix, id) {}
uint64_t operator*() {
auto& key = *static_cast<KeyGen&>(*this);
// unseeded
return ROCKSDB_NAMESPACE::GetSliceHash64(key);
}
};
using ROCKSDB_NAMESPACE::ribbon::ConstructionFailureChance;
const std::vector<ConstructionFailureChance> kFailureOnly50Pct = {
ROCKSDB_NAMESPACE::ribbon::kOneIn2};
const std::vector<ConstructionFailureChance> kFailureOnlyRare = {
ROCKSDB_NAMESPACE::ribbon::kOneIn1000};
const std::vector<ConstructionFailureChance> kFailureAll = {
ROCKSDB_NAMESPACE::ribbon::kOneIn2, ROCKSDB_NAMESPACE::ribbon::kOneIn20,
ROCKSDB_NAMESPACE::ribbon::kOneIn1000};
} // namespace
using ROCKSDB_NAMESPACE::ribbon::ExpectedCollisionFpRate;
using ROCKSDB_NAMESPACE::ribbon::StandardHasher;
using ROCKSDB_NAMESPACE::ribbon::StandardRehasherAdapter;
struct DefaultTypesAndSettings {
using CoeffRow = ROCKSDB_NAMESPACE::Unsigned128;
using ResultRow = uint8_t;
using Index = uint32_t;
using Hash = uint64_t;
using Seed = uint32_t;
using Key = ROCKSDB_NAMESPACE::Slice;
static constexpr bool kIsFilter = true;
static constexpr bool kHomogeneous = false;
static constexpr bool kFirstCoeffAlwaysOne = true;
static constexpr bool kUseSmash = false;
static constexpr bool kAllowZeroStarts = false;
static Hash HashFn(const Key& key, uint64_t raw_seed) {
// This version 0.7.2 preview of XXH3 (a.k.a. XXPH3) function does
// not pass SmallKeyGen tests below without some seed premixing from
// StandardHasher. See https://github.com/Cyan4973/xxHash/issues/469
return ROCKSDB_NAMESPACE::Hash64(key.data(), key.size(), raw_seed);
}
// For testing
using KeyGen = StandardKeyGen;
static const std::vector<ConstructionFailureChance>& FailureChanceToTest() {
return kFailureAll;
}
};
using TypesAndSettings_Coeff128 = DefaultTypesAndSettings;
struct TypesAndSettings_Coeff128Smash : public DefaultTypesAndSettings {
static constexpr bool kUseSmash = true;
};
struct TypesAndSettings_Coeff64 : public DefaultTypesAndSettings {
using CoeffRow = uint64_t;
};
struct TypesAndSettings_Coeff64Smash : public TypesAndSettings_Coeff64 {
static constexpr bool kUseSmash = true;
};
struct TypesAndSettings_Coeff64Smash0 : public TypesAndSettings_Coeff64Smash {
static constexpr bool kFirstCoeffAlwaysOne = false;
};
// Homogeneous Ribbon configurations
struct TypesAndSettings_Coeff128_Homog : public DefaultTypesAndSettings {
static constexpr bool kHomogeneous = true;
// Since our best construction success setting still has 1/1000 failure
// rate, the best FP rate we test is 1/256
using ResultRow = uint8_t;
// Homogeneous only makes sense with sufficient slots for equivalent of
// almost sure construction success
static const std::vector<ConstructionFailureChance>& FailureChanceToTest() {
return kFailureOnlyRare;
}
};
struct TypesAndSettings_Coeff128Smash_Homog
: public TypesAndSettings_Coeff128_Homog {
// Smash (extra time to save space) + Homog (extra space to save time)
// doesn't make much sense in practice, but we minimally test it
static constexpr bool kUseSmash = true;
};
struct TypesAndSettings_Coeff64_Homog : public TypesAndSettings_Coeff128_Homog {
using CoeffRow = uint64_t;
};
struct TypesAndSettings_Coeff64Smash_Homog
: public TypesAndSettings_Coeff64_Homog {
// Smash (extra time to save space) + Homog (extra space to save time)
// doesn't make much sense in practice, but we minimally test it
static constexpr bool kUseSmash = true;
};
// Less exhaustive mix of coverage, but still covering the most stressful case
// (only 50% construction success)
struct AbridgedTypesAndSettings : public DefaultTypesAndSettings {
static const std::vector<ConstructionFailureChance>& FailureChanceToTest() {
return kFailureOnly50Pct;
}
};
struct TypesAndSettings_Result16 : public AbridgedTypesAndSettings {
using ResultRow = uint16_t;
};
struct TypesAndSettings_Result32 : public AbridgedTypesAndSettings {
using ResultRow = uint32_t;
};
struct TypesAndSettings_IndexSizeT : public AbridgedTypesAndSettings {
using Index = size_t;
};
struct TypesAndSettings_Hash32 : public AbridgedTypesAndSettings {
using Hash = uint32_t;
static Hash HashFn(const Key& key, Hash raw_seed) {
// This MurmurHash1 function does not pass tests below without the
// seed premixing from StandardHasher. In fact, it needs more than
// just a multiplication mixer on the ordinal seed.
return ROCKSDB_NAMESPACE::Hash(key.data(), key.size(), raw_seed);
}
};
struct TypesAndSettings_Hash32_Result16 : public AbridgedTypesAndSettings {
using ResultRow = uint16_t;
};
struct TypesAndSettings_KeyString : public AbridgedTypesAndSettings {
using Key = std::string;
};
struct TypesAndSettings_Seed8 : public AbridgedTypesAndSettings {
// This is not a generally recommended configuration. With the configured
// hash function, it would fail with SmallKeyGen due to insufficient
// independence among the seeds.
using Seed = uint8_t;
};
struct TypesAndSettings_NoAlwaysOne : public AbridgedTypesAndSettings {
static constexpr bool kFirstCoeffAlwaysOne = false;
};
struct TypesAndSettings_AllowZeroStarts : public AbridgedTypesAndSettings {
static constexpr bool kAllowZeroStarts = true;
};
struct TypesAndSettings_Seed64 : public AbridgedTypesAndSettings {
using Seed = uint64_t;
};
struct TypesAndSettings_Rehasher
: public StandardRehasherAdapter<AbridgedTypesAndSettings> {
using KeyGen = Hash64KeyGenWrapper<StandardKeyGen>;
};
struct TypesAndSettings_Rehasher_Result16 : public TypesAndSettings_Rehasher {
using ResultRow = uint16_t;
};
struct TypesAndSettings_Rehasher_Result32 : public TypesAndSettings_Rehasher {
using ResultRow = uint32_t;
};
struct TypesAndSettings_Rehasher_Seed64
: public StandardRehasherAdapter<TypesAndSettings_Seed64> {
using KeyGen = Hash64KeyGenWrapper<StandardKeyGen>;
// Note: 64-bit seed with Rehasher gives slightly better average reseeds
};
struct TypesAndSettings_Rehasher32
: public StandardRehasherAdapter<TypesAndSettings_Hash32> {
using KeyGen = Hash32KeyGenWrapper<StandardKeyGen>;
};
struct TypesAndSettings_Rehasher32_Coeff64
: public TypesAndSettings_Rehasher32 {
using CoeffRow = uint64_t;
};
struct TypesAndSettings_SmallKeyGen : public AbridgedTypesAndSettings {
// SmallKeyGen stresses the independence of different hash seeds
using KeyGen = SmallKeyGen;
};
struct TypesAndSettings_Hash32_SmallKeyGen : public TypesAndSettings_Hash32 {
// SmallKeyGen stresses the independence of different hash seeds
using KeyGen = SmallKeyGen;
};
struct TypesAndSettings_Coeff32 : public DefaultTypesAndSettings {
using CoeffRow = uint32_t;
};
struct TypesAndSettings_Coeff32Smash : public TypesAndSettings_Coeff32 {
static constexpr bool kUseSmash = true;
};
struct TypesAndSettings_Coeff16 : public DefaultTypesAndSettings {
using CoeffRow = uint16_t;
};
struct TypesAndSettings_Coeff16Smash : public TypesAndSettings_Coeff16 {
static constexpr bool kUseSmash = true;
};
using TestTypesAndSettings = ::testing::Types<
TypesAndSettings_Coeff128, TypesAndSettings_Coeff128Smash,
TypesAndSettings_Coeff64, TypesAndSettings_Coeff64Smash,
TypesAndSettings_Coeff64Smash0, TypesAndSettings_Coeff128_Homog,
TypesAndSettings_Coeff128Smash_Homog, TypesAndSettings_Coeff64_Homog,
TypesAndSettings_Coeff64Smash_Homog, TypesAndSettings_Result16,
TypesAndSettings_Result32, TypesAndSettings_IndexSizeT,
TypesAndSettings_Hash32, TypesAndSettings_Hash32_Result16,
TypesAndSettings_KeyString, TypesAndSettings_Seed8,
TypesAndSettings_NoAlwaysOne, TypesAndSettings_AllowZeroStarts,
TypesAndSettings_Seed64, TypesAndSettings_Rehasher,
TypesAndSettings_Rehasher_Result16, TypesAndSettings_Rehasher_Result32,
TypesAndSettings_Rehasher_Seed64, TypesAndSettings_Rehasher32,
TypesAndSettings_Rehasher32_Coeff64, TypesAndSettings_SmallKeyGen,
TypesAndSettings_Hash32_SmallKeyGen, TypesAndSettings_Coeff32,
TypesAndSettings_Coeff32Smash, TypesAndSettings_Coeff16,
TypesAndSettings_Coeff16Smash>;
TYPED_TEST_CASE(RibbonTypeParamTest, TestTypesAndSettings);
namespace {
// For testing Poisson-distributed (or similar) statistics, get value for
// `stddevs_allowed` standard deviations above expected mean
// `expected_count`.
// (Poisson approximates Binomial only if probability of a trial being
// in the count is low.)
uint64_t PoissonUpperBound(double expected_count, double stddevs_allowed) {
return static_cast<uint64_t>(
expected_count + stddevs_allowed * std::sqrt(expected_count) + 1.0);
}
uint64_t PoissonLowerBound(double expected_count, double stddevs_allowed) {
return static_cast<uint64_t>(std::max(
0.0, expected_count - stddevs_allowed * std::sqrt(expected_count)));
}
uint64_t FrequentPoissonUpperBound(double expected_count) {
// Allow up to 5.0 standard deviations for frequently checked statistics
return PoissonUpperBound(expected_count, 5.0);
}
uint64_t FrequentPoissonLowerBound(double expected_count) {
return PoissonLowerBound(expected_count, 5.0);
}
uint64_t InfrequentPoissonUpperBound(double expected_count) {
// Allow up to 3 standard deviations for infrequently checked statistics
return PoissonUpperBound(expected_count, 3.0);
}
uint64_t InfrequentPoissonLowerBound(double expected_count) {
return PoissonLowerBound(expected_count, 3.0);
}
} // namespace
TYPED_TEST(RibbonTypeParamTest, CompactnessAndBacktrackAndFpRate) {
IMPORT_RIBBON_TYPES_AND_SETTINGS(TypeParam);
IMPORT_RIBBON_IMPL_TYPES(TypeParam);
using KeyGen = typename TypeParam::KeyGen;
using ConfigHelper =
ROCKSDB_NAMESPACE::ribbon::BandingConfigHelper<TypeParam>;
if (sizeof(CoeffRow) < 8) {
ROCKSDB_GTEST_BYPASS("Not fully supported");
return;
}
const auto log2_thoroughness =
static_cast<uint32_t>(ROCKSDB_NAMESPACE::FloorLog2(FLAGS_thoroughness));
// We are going to choose num_to_add using an exponential distribution,
// so that we have good representation of small-to-medium filters.
// Here we just pick some reasonable, practical upper bound based on
// kCoeffBits or option.
const double log_max_add = std::log(
FLAGS_max_add > 0 ? FLAGS_max_add
: static_cast<uint32_t>(kCoeffBits * kCoeffBits) *
std::max(FLAGS_thoroughness, uint32_t{32}));
// This needs to be enough below the minimum number of slots to get a
// reasonable number of samples with the minimum number of slots.
const double log_min_add = std::log(0.66 * SimpleSoln::RoundUpNumSlots(1));
ASSERT_GT(log_max_add, log_min_add);
const double diff_log_add = log_max_add - log_min_add;
for (ConstructionFailureChance cs : TypeParam::FailureChanceToTest()) {
double expected_reseeds;
switch (cs) {
default:
assert(false);
FALLTHROUGH_INTENDED;
case ROCKSDB_NAMESPACE::ribbon::kOneIn2:
fprintf(stderr, "== Failure: 50 percent\n");
expected_reseeds = 1.0;
break;
case ROCKSDB_NAMESPACE::ribbon::kOneIn20:
fprintf(stderr, "== Failure: 95 percent\n");
expected_reseeds = 0.053;
break;
case ROCKSDB_NAMESPACE::ribbon::kOneIn1000:
fprintf(stderr, "== Failure: 1/1000\n");
expected_reseeds = 0.001;
break;
}
uint64_t total_reseeds = 0;
uint64_t total_singles = 0;
uint64_t total_single_failures = 0;
uint64_t total_batch = 0;
uint64_t total_batch_successes = 0;
uint64_t total_fp_count = 0;
uint64_t total_added = 0;
uint64_t total_expand_trials = 0;
uint64_t total_expand_failures = 0;
double total_expand_overhead = 0.0;
uint64_t soln_query_nanos = 0;
uint64_t soln_query_count = 0;
uint64_t bloom_query_nanos = 0;
uint64_t isoln_query_nanos = 0;
uint64_t isoln_query_count = 0;
// Take different samples if you change thoroughness
ROCKSDB_NAMESPACE::Random32 rnd(FLAGS_thoroughness);
for (uint32_t i = 0; i < FLAGS_thoroughness; ++i) {
// We are going to choose num_to_add using an exponential distribution
// as noted above, but instead of randomly choosing them, we generate
// samples linearly using the golden ratio, which ensures a nice spread
// even for a small number of samples, and starting with the minimum
// number of slots to ensure it is tested.
double log_add =
std::fmod(0.6180339887498948482 * diff_log_add * i, diff_log_add) +
log_min_add;
uint32_t num_to_add = static_cast<uint32_t>(std::exp(log_add));
// Most of the time, test the Interleaved solution storage, but when
// we do we have to make num_slots a multiple of kCoeffBits. So
// sometimes we want to test without that limitation.
bool test_interleaved = (i % 7) != 6;
// Compute num_slots, and re-adjust num_to_add to get as close as possible
// to next num_slots, to stress that num_slots in terms of construction
// success. Ensure at least one iteration:
Index num_slots = Index{0} - 1;
--num_to_add;
for (;;) {
Index next_num_slots = SimpleSoln::RoundUpNumSlots(
ConfigHelper::GetNumSlots(num_to_add + 1, cs));
if (test_interleaved) {
next_num_slots = InterleavedSoln::RoundUpNumSlots(next_num_slots);
// assert idempotent
EXPECT_EQ(next_num_slots,
InterleavedSoln::RoundUpNumSlots(next_num_slots));
}
// assert idempotent with InterleavedSoln::RoundUpNumSlots
EXPECT_EQ(next_num_slots, SimpleSoln::RoundUpNumSlots(next_num_slots));
if (next_num_slots > num_slots) {
break;
}
num_slots = next_num_slots;
++num_to_add;
}
assert(num_slots < Index{0} - 1);
total_added += num_to_add;
std::string prefix;
ROCKSDB_NAMESPACE::PutFixed32(&prefix, rnd.Next());
// Batch that must be added
std::string added_str = prefix + "added";
KeyGen keys_begin(added_str, 0);
KeyGen keys_end(added_str, num_to_add);
// A couple more that will probably be added
KeyGen one_more(prefix + "more", 1);
KeyGen two_more(prefix + "more", 2);
// Batch that may or may not be added
uint32_t batch_size =
static_cast<uint32_t>(2.0 * std::sqrt(num_slots - num_to_add));
if (batch_size < 10U) {
batch_size = 0;
}
std::string batch_str = prefix + "batch";
KeyGen batch_begin(batch_str, 0);
KeyGen batch_end(batch_str, batch_size);
// Batch never (successfully) added, but used for querying FP rate
std::string not_str = prefix + "not";
KeyGen other_keys_begin(not_str, 0);
KeyGen other_keys_end(not_str, FLAGS_max_check);
double overhead_ratio = 1.0 * num_slots / num_to_add;
if (FLAGS_verbose) {
fprintf(stderr, "Adding(%s) %u / %u Overhead: %g Batch size: %u\n",
test_interleaved ? "i" : "s", (unsigned)num_to_add,
(unsigned)num_slots, overhead_ratio, (unsigned)batch_size);
}
// Vary bytes for InterleavedSoln to use number of solution columns
// from 0 to max allowed by ResultRow type (and used by SimpleSoln).
// Specifically include 0 and max, and otherwise skew toward max.
uint32_t max_ibytes =
static_cast<uint32_t>(sizeof(ResultRow) * num_slots);
size_t ibytes;
if (i == 0) {
ibytes = 0;
} else if (i == 1) {
ibytes = max_ibytes;
} else {
// Skewed
ibytes =
std::max(rnd.Uniformish(max_ibytes), rnd.Uniformish(max_ibytes));
}
std::unique_ptr<char[]> idata(new char[ibytes]);
InterleavedSoln isoln(idata.get(), ibytes);
SimpleSoln soln;
Hasher hasher;
bool first_single;
bool second_single;
bool batch_success;
{
Banding banding;
// Traditional solve for a fixed set.
ASSERT_TRUE(
banding.ResetAndFindSeedToSolve(num_slots, keys_begin, keys_end));
Index occupied_count = banding.GetOccupiedCount();
Index more_added = 0;
if (TypeParam::kHomogeneous || overhead_ratio < 1.01 ||
batch_size == 0) {
// Homogeneous not compatible with backtracking because add
// doesn't fail. Small overhead ratio too packed to expect more
first_single = false;
second_single = false;
batch_success = false;
} else {
// Now to test backtracking, starting with guaranteed fail. By using
// the keys that will be used to test FP rate, we are then doing an
// extra check that after backtracking there are no remnants (e.g. in
// result side of banding) of these entries.
KeyGen other_keys_too_big_end = other_keys_begin;
other_keys_too_big_end += num_to_add;
banding.EnsureBacktrackSize(std::max(num_to_add, batch_size));
EXPECT_FALSE(banding.AddRangeOrRollBack(other_keys_begin,
other_keys_too_big_end));
EXPECT_EQ(occupied_count, banding.GetOccupiedCount());
// Check that we still have a good chance of adding a couple more
// individually
first_single = banding.Add(*one_more);
second_single = banding.Add(*two_more);
more_added += (first_single ? 1 : 0) + (second_single ? 1 : 0);
total_singles += 2U;
total_single_failures += 2U - more_added;
// Or as a batch
batch_success = banding.AddRangeOrRollBack(batch_begin, batch_end);
++total_batch;
if (batch_success) {
more_added += batch_size;
++total_batch_successes;
}
EXPECT_LE(banding.GetOccupiedCount(), occupied_count + more_added);
}
// Also verify that redundant adds are OK (no effect)
ASSERT_TRUE(
banding.AddRange(keys_begin, KeyGen(added_str, num_to_add / 8)));
EXPECT_LE(banding.GetOccupiedCount(), occupied_count + more_added);
// Now back-substitution
soln.BackSubstFrom(banding);
if (test_interleaved) {
isoln.BackSubstFrom(banding);
}
Seed reseeds = banding.GetOrdinalSeed();
total_reseeds += reseeds;
EXPECT_LE(reseeds, 8 + log2_thoroughness);
if (reseeds > log2_thoroughness + 1) {
fprintf(
stderr, "%s high reseeds at %u, %u/%u: %u\n",
reseeds > log2_thoroughness + 8 ? "ERROR Extremely" : "Somewhat",
static_cast<unsigned>(i), static_cast<unsigned>(num_to_add),
static_cast<unsigned>(num_slots), static_cast<unsigned>(reseeds));
}
if (reseeds > 0) {
// "Expand" test: given a failed construction, how likely is it to
// pass with same seed and more slots. At each step, we increase
// enough to ensure there is at least one shift within each coeff
// block.
++total_expand_trials;
Index expand_count = 0;
Index ex_slots = num_slots;
banding.SetOrdinalSeed(0);
for (;; ++expand_count) {
ASSERT_LE(expand_count, log2_thoroughness);
ex_slots += ex_slots / kCoeffBits;
if (test_interleaved) {
ex_slots = InterleavedSoln::RoundUpNumSlots(ex_slots);
}
banding.Reset(ex_slots);
bool success = banding.AddRange(keys_begin, keys_end);
if (success) {
break;
}
}
total_expand_failures += expand_count;
total_expand_overhead += 1.0 * (ex_slots - num_slots) / num_slots;
}
hasher.SetOrdinalSeed(reseeds);
}
// soln and hasher now independent of Banding object
// Verify keys added
KeyGen cur = keys_begin;
while (cur != keys_end) {
ASSERT_TRUE(soln.FilterQuery(*cur, hasher));
ASSERT_TRUE(!test_interleaved || isoln.FilterQuery(*cur, hasher));
++cur;
}
// We (maybe) snuck these in!
if (first_single) {
ASSERT_TRUE(soln.FilterQuery(*one_more, hasher));
ASSERT_TRUE(!test_interleaved || isoln.FilterQuery(*one_more, hasher));
}
if (second_single) {
ASSERT_TRUE(soln.FilterQuery(*two_more, hasher));
ASSERT_TRUE(!test_interleaved || isoln.FilterQuery(*two_more, hasher));
}
if (batch_success) {
cur = batch_begin;
while (cur != batch_end) {
ASSERT_TRUE(soln.FilterQuery(*cur, hasher));
ASSERT_TRUE(!test_interleaved || isoln.FilterQuery(*cur, hasher));
++cur;
}
}
// Check FP rate (depends only on number of result bits == solution
// columns)
Index fp_count = 0;
cur = other_keys_begin;
{
ROCKSDB_NAMESPACE::StopWatchNano timer(
ROCKSDB_NAMESPACE::SystemClock::Default().get(), true);
while (cur != other_keys_end) {
bool fp = soln.FilterQuery(*cur, hasher);
fp_count += fp ? 1 : 0;
++cur;
}
soln_query_nanos += timer.ElapsedNanos();
soln_query_count += FLAGS_max_check;
}
{
double expected_fp_count = soln.ExpectedFpRate() * FLAGS_max_check;
// For expected FP rate, also include false positives due to collisions
// in Hash value. (Negligible for 64-bit, can matter for 32-bit.)
double correction =
FLAGS_max_check * ExpectedCollisionFpRate(hasher, num_to_add);
// NOTE: rare violations expected with kHomogeneous
EXPECT_LE(fp_count,
FrequentPoissonUpperBound(expected_fp_count + correction));
EXPECT_GE(fp_count,
FrequentPoissonLowerBound(expected_fp_count + correction));
}
total_fp_count += fp_count;
// And also check FP rate for isoln
if (test_interleaved) {
Index ifp_count = 0;
cur = other_keys_begin;
ROCKSDB_NAMESPACE::StopWatchNano timer(
ROCKSDB_NAMESPACE::SystemClock::Default().get(), true);
while (cur != other_keys_end) {
ifp_count += isoln.FilterQuery(*cur, hasher) ? 1 : 0;
++cur;
}
isoln_query_nanos += timer.ElapsedNanos();
isoln_query_count += FLAGS_max_check;
{
double expected_fp_count = isoln.ExpectedFpRate() * FLAGS_max_check;
// For expected FP rate, also include false positives due to
// collisions in Hash value. (Negligible for 64-bit, can matter for
// 32-bit.)
double correction =
FLAGS_max_check * ExpectedCollisionFpRate(hasher, num_to_add);
// NOTE: rare violations expected with kHomogeneous
EXPECT_LE(ifp_count,
FrequentPoissonUpperBound(expected_fp_count + correction));
// FIXME: why sometimes can we slightly "beat the odds"?
// (0.95 factor should not be needed)
EXPECT_GE(ifp_count, FrequentPoissonLowerBound(
0.95 * expected_fp_count + correction));
}
// Since the bits used in isoln are a subset of the bits used in soln,
// it cannot have fewer FPs
EXPECT_GE(ifp_count, fp_count);
}
// And compare to Bloom time, for fun
if (ibytes >= /* minimum Bloom impl bytes*/ 64) {
Index bfp_count = 0;
cur = other_keys_begin;
ROCKSDB_NAMESPACE::StopWatchNano timer(
ROCKSDB_NAMESPACE::SystemClock::Default().get(), true);
while (cur != other_keys_end) {
uint64_t h = hasher.GetHash(*cur);
uint32_t h1 = ROCKSDB_NAMESPACE::Lower32of64(h);
uint32_t h2 = sizeof(Hash) >= 8 ? ROCKSDB_NAMESPACE::Upper32of64(h)
: h1 * 0x9e3779b9;
bfp_count +=
ROCKSDB_NAMESPACE::FastLocalBloomImpl::HashMayMatch(
h1, h2, static_cast<uint32_t>(ibytes), 6, idata.get())
? 1
: 0;
++cur;
}
bloom_query_nanos += timer.ElapsedNanos();
// ensure bfp_count is used
ASSERT_LT(bfp_count, FLAGS_max_check);
}
}
// "outside" == key not in original set so either negative or false positive
fprintf(stderr,
"Simple outside query, hot, incl hashing, ns/key: %g\n",
1.0 * soln_query_nanos / soln_query_count);
fprintf(stderr,
"Interleaved outside query, hot, incl hashing, ns/key: %g\n",
1.0 * isoln_query_nanos / isoln_query_count);
fprintf(stderr,
"Bloom outside query, hot, incl hashing, ns/key: %g\n",
1.0 * bloom_query_nanos / soln_query_count);
if (TypeParam::kHomogeneous) {
EXPECT_EQ(total_reseeds, 0U);
} else {
double average_reseeds = 1.0 * total_reseeds / FLAGS_thoroughness;
fprintf(stderr, "Average re-seeds: %g\n", average_reseeds);
// Values above were chosen to target around 50% chance of encoding
// success rate (average of 1.0 re-seeds) or slightly better. But 1.15 is
// also close enough.
EXPECT_LE(total_reseeds,
InfrequentPoissonUpperBound(1.15 * expected_reseeds *
FLAGS_thoroughness));
// Would use 0.85 here instead of 0.75, but
// TypesAndSettings_Hash32_SmallKeyGen can "beat the odds" because of
// sequential keys with a small, cheap hash function. We accept that
// there are surely inputs that are somewhat bad for this setup, but
// these somewhat good inputs are probably more likely.
EXPECT_GE(total_reseeds,
InfrequentPoissonLowerBound(0.75 * expected_reseeds *
FLAGS_thoroughness));
}
if (total_expand_trials > 0) {
double average_expand_failures =
1.0 * total_expand_failures / total_expand_trials;
fprintf(stderr, "Average expand failures, and overhead: %g, %g\n",
average_expand_failures,
total_expand_overhead / total_expand_trials);
// Seems to be a generous allowance
EXPECT_LE(total_expand_failures,
InfrequentPoissonUpperBound(1.0 * total_expand_trials));
} else {
fprintf(stderr, "Average expand failures: N/A\n");
}
if (total_singles > 0) {
double single_failure_rate = 1.0 * total_single_failures / total_singles;
fprintf(stderr, "Add'l single, failure rate: %g\n", single_failure_rate);
// A rough bound (one sided) based on nothing in particular
double expected_single_failures =
1.0 * total_singles /
(sizeof(CoeffRow) == 16 ? 128 : TypeParam::kUseSmash ? 64 : 32);
EXPECT_LE(total_single_failures,
InfrequentPoissonUpperBound(expected_single_failures));
}
if (total_batch > 0) {
// Counting successes here for Poisson to approximate the Binomial
// distribution.
// A rough bound (one sided) based on nothing in particular.
double expected_batch_successes = 1.0 * total_batch / 2;
uint64_t lower_bound =
InfrequentPoissonLowerBound(expected_batch_successes);
fprintf(stderr, "Add'l batch, success rate: %g (>= %g)\n",
1.0 * total_batch_successes / total_batch,
1.0 * lower_bound / total_batch);
EXPECT_GE(total_batch_successes, lower_bound);
}
{
uint64_t total_checked = uint64_t{FLAGS_max_check} * FLAGS_thoroughness;
double expected_total_fp_count =
total_checked * std::pow(0.5, 8U * sizeof(ResultRow));
// For expected FP rate, also include false positives due to collisions
// in Hash value. (Negligible for 64-bit, can matter for 32-bit.)
double average_added = 1.0 * total_added / FLAGS_thoroughness;
expected_total_fp_count +=
total_checked * ExpectedCollisionFpRate(Hasher(), average_added);
uint64_t upper_bound =
InfrequentPoissonUpperBound(expected_total_fp_count);
uint64_t lower_bound =
InfrequentPoissonLowerBound(expected_total_fp_count);
fprintf(stderr, "Average FP rate: %g (~= %g, <= %g, >= %g)\n",
1.0 * total_fp_count / total_checked,
expected_total_fp_count / total_checked,
1.0 * upper_bound / total_checked,
1.0 * lower_bound / total_checked);
EXPECT_LE(total_fp_count, upper_bound);
EXPECT_GE(total_fp_count, lower_bound);
}
}
}
TYPED_TEST(RibbonTypeParamTest, Extremes) {
IMPORT_RIBBON_TYPES_AND_SETTINGS(TypeParam);
IMPORT_RIBBON_IMPL_TYPES(TypeParam);
using KeyGen = typename TypeParam::KeyGen;
size_t bytes = 128 * 1024;
std::unique_ptr<char[]> buf(new char[bytes]);
InterleavedSoln isoln(buf.get(), bytes);
SimpleSoln soln;
Hasher hasher;
Banding banding;
// ########################################
// Add zero keys to minimal number of slots
KeyGen begin_and_end("foo", 123);
ASSERT_TRUE(banding.ResetAndFindSeedToSolve(
/*slots*/ kCoeffBits, begin_and_end, begin_and_end, /*first seed*/ 0,
/* seed mask*/ 0));
soln.BackSubstFrom(banding);
isoln.BackSubstFrom(banding);
// Because there's plenty of memory, we expect the interleaved solution to
// use maximum supported columns (same as simple solution)
ASSERT_EQ(isoln.GetUpperNumColumns(), 8U * sizeof(ResultRow));
ASSERT_EQ(isoln.GetUpperStartBlock(), 0U);
// Somewhat oddly, we expect same FP rate as if we had essentially filled
// up the slots.
KeyGen other_keys_begin("not", 0);
KeyGen other_keys_end("not", FLAGS_max_check);
Index fp_count = 0;
KeyGen cur = other_keys_begin;
while (cur != other_keys_end) {
bool isoln_query_result = isoln.FilterQuery(*cur, hasher);
bool soln_query_result = soln.FilterQuery(*cur, hasher);
// Solutions are equivalent
ASSERT_EQ(isoln_query_result, soln_query_result);
if (!TypeParam::kHomogeneous) {
// And in fact we only expect an FP when ResultRow is 0
// (except Homogeneous)
ASSERT_EQ(soln_query_result, hasher.GetResultRowFromHash(
hasher.GetHash(*cur)) == ResultRow{0});
}
fp_count += soln_query_result ? 1 : 0;
++cur;
}
{
ASSERT_EQ(isoln.ExpectedFpRate(), soln.ExpectedFpRate());
double expected_fp_count = isoln.ExpectedFpRate() * FLAGS_max_check;
EXPECT_LE(fp_count, InfrequentPoissonUpperBound(expected_fp_count));
if (TypeParam::kHomogeneous) {
// Pseudorandom garbage in Homogeneous filter can "beat the odds" if
// nothing added
} else {
EXPECT_GE(fp_count, InfrequentPoissonLowerBound(expected_fp_count));
}
}
// ######################################################
// Use zero bytes for interleaved solution (key(s) added)
// Add one key
KeyGen key_begin("added", 0);
KeyGen key_end("added", 1);
ASSERT_TRUE(banding.ResetAndFindSeedToSolve(
/*slots*/ kCoeffBits, key_begin, key_end, /*first seed*/ 0,
/* seed mask*/ 0));
InterleavedSoln isoln2(nullptr, /*bytes*/ 0);
isoln2.BackSubstFrom(banding);
ASSERT_EQ(isoln2.GetUpperNumColumns(), 0U);
ASSERT_EQ(isoln2.GetUpperStartBlock(), 0U);
// All queries return true
ASSERT_TRUE(isoln2.FilterQuery(*other_keys_begin, hasher));
ASSERT_EQ(isoln2.ExpectedFpRate(), 1.0);
}
TEST(RibbonTest, AllowZeroStarts) {
IMPORT_RIBBON_TYPES_AND_SETTINGS(TypesAndSettings_AllowZeroStarts);
IMPORT_RIBBON_IMPL_TYPES(TypesAndSettings_AllowZeroStarts);
using KeyGen = StandardKeyGen;
InterleavedSoln isoln(nullptr, /*bytes*/ 0);
SimpleSoln soln;
Hasher hasher;
Banding banding;
KeyGen begin("foo", 0);
KeyGen end("foo", 1);
// Can't add 1 entry
ASSERT_FALSE(banding.ResetAndFindSeedToSolve(/*slots*/ 0, begin, end));
KeyGen begin_and_end("foo", 123);
// Can add 0 entries
ASSERT_TRUE(banding.ResetAndFindSeedToSolve(/*slots*/ 0, begin_and_end,
begin_and_end));
Seed reseeds = banding.GetOrdinalSeed();
ASSERT_EQ(reseeds, 0U);
hasher.SetOrdinalSeed(reseeds);
// Can construct 0-slot solutions
isoln.BackSubstFrom(banding);
soln.BackSubstFrom(banding);
// Should always return false
ASSERT_FALSE(isoln.FilterQuery(*begin, hasher));
ASSERT_FALSE(soln.FilterQuery(*begin, hasher));
// And report that in FP rate
ASSERT_EQ(isoln.ExpectedFpRate(), 0.0);
ASSERT_EQ(soln.ExpectedFpRate(), 0.0);
}
TEST(RibbonTest, RawAndOrdinalSeeds) {
StandardHasher<TypesAndSettings_Seed64> hasher64;
StandardHasher<DefaultTypesAndSettings> hasher64_32;
StandardHasher<TypesAndSettings_Hash32> hasher32;
StandardHasher<TypesAndSettings_Seed8> hasher8;
for (uint32_t limit : {0xffU, 0xffffU}) {
std::vector<bool> seen(limit + 1);
for (uint32_t i = 0; i < limit; ++i) {
hasher64.SetOrdinalSeed(i);
auto raw64 = hasher64.GetRawSeed();
hasher32.SetOrdinalSeed(i);
auto raw32 = hasher32.GetRawSeed();
hasher8.SetOrdinalSeed(static_cast<uint8_t>(i));
auto raw8 = hasher8.GetRawSeed();
{
hasher64_32.SetOrdinalSeed(i);
auto raw64_32 = hasher64_32.GetRawSeed();
ASSERT_EQ(raw64_32, raw32); // Same size seed
}
if (i == 0) {
// Documented that ordinal seed 0 == raw seed 0
ASSERT_EQ(raw64, 0U);
ASSERT_EQ(raw32, 0U);
ASSERT_EQ(raw8, 0U);
} else {
// Extremely likely that upper bits are set
ASSERT_GT(raw64, raw32);
ASSERT_GT(raw32, raw8);
}
// Hashers agree on lower bits
ASSERT_EQ(static_cast<uint32_t>(raw64), raw32);
ASSERT_EQ(static_cast<uint8_t>(raw32), raw8);
// The translation is one-to-one for this size prefix
uint32_t v = static_cast<uint32_t>(raw32 & limit);
ASSERT_EQ(raw64 & limit, v);
ASSERT_FALSE(seen[v]);
seen[v] = true;
}
}
}
namespace {
struct PhsfInputGen {
PhsfInputGen(const std::string& prefix, uint64_t id) : id_(id) {
val_.first = prefix;
ROCKSDB_NAMESPACE::PutFixed64(&val_.first, /*placeholder*/ 0);
}
// Prefix (only one required)
PhsfInputGen& operator++() {
++id_;
return *this;
}
const std::pair<std::string, uint8_t>& operator*() {
// Use multiplication to mix things up a little in the key
ROCKSDB_NAMESPACE::EncodeFixed64(&val_.first[val_.first.size() - 8],
id_ * uint64_t{0x1500000001});
// Occasionally repeat values etc.
val_.second = static_cast<uint8_t>(id_ * 7 / 8);
return val_;
}
const std::pair<std::string, uint8_t>* operator->() { return &**this; }
bool operator==(const PhsfInputGen& other) {
// Same prefix is assumed
return id_ == other.id_;
}
bool operator!=(const PhsfInputGen& other) {
// Same prefix is assumed
return id_ != other.id_;
}
uint64_t id_;
std::pair<std::string, uint8_t> val_;
};
struct PhsfTypesAndSettings : public DefaultTypesAndSettings {
static constexpr bool kIsFilter = false;
};
} // namespace
TEST(RibbonTest, PhsfBasic) {
IMPORT_RIBBON_TYPES_AND_SETTINGS(PhsfTypesAndSettings);
IMPORT_RIBBON_IMPL_TYPES(PhsfTypesAndSettings);
Index num_slots = 12800;
Index num_to_add = static_cast<Index>(num_slots / 1.02);
PhsfInputGen begin("in", 0);
PhsfInputGen end("in", num_to_add);
std::unique_ptr<char[]> idata(new char[/*bytes*/ num_slots]);
InterleavedSoln isoln(idata.get(), /*bytes*/ num_slots);
SimpleSoln soln;
Hasher hasher;
{
Banding banding;
ASSERT_TRUE(banding.ResetAndFindSeedToSolve(num_slots, begin, end));
soln.BackSubstFrom(banding);
isoln.BackSubstFrom(banding);
hasher.SetOrdinalSeed(banding.GetOrdinalSeed());
}
for (PhsfInputGen cur = begin; cur != end; ++cur) {
ASSERT_EQ(cur->second, soln.PhsfQuery(cur->first, hasher));
ASSERT_EQ(cur->second, isoln.PhsfQuery(cur->first, hasher));
}
}
// Not a real test, but a tool used to build APIs in ribbon_config.h
TYPED_TEST(RibbonTypeParamTest, FindOccupancy) {
IMPORT_RIBBON_TYPES_AND_SETTINGS(TypeParam);
IMPORT_RIBBON_IMPL_TYPES(TypeParam);
using KeyGen = typename TypeParam::KeyGen;
if (!FLAGS_find_occ) {
ROCKSDB_GTEST_BYPASS("Tool disabled during unit test runs");
return;
}
KeyGen cur(ROCKSDB_NAMESPACE::ToString(
testing::UnitTest::GetInstance()->random_seed()),
0);
Banding banding;
Index num_slots = InterleavedSoln::RoundUpNumSlots(FLAGS_find_min_slots);
Index max_slots = InterleavedSoln::RoundUpNumSlots(FLAGS_find_max_slots);
while (num_slots <= max_slots) {
std::map<int32_t, uint32_t> rem_histogram;
std::map<Index, uint32_t> slot_histogram;
if (FLAGS_find_slot_occ) {
for (Index i = 0; i < kCoeffBits; ++i) {
slot_histogram[i] = 0;
slot_histogram[num_slots - 1 - i] = 0;
slot_histogram[num_slots / 2 - kCoeffBits / 2 + i] = 0;
}
}
uint64_t total_added = 0;
for (uint32_t i = 0; i < FLAGS_find_iters; ++i) {
banding.Reset(num_slots);
uint32_t j = 0;
KeyGen end = cur;
end += num_slots + num_slots / 10;
for (; cur != end; ++cur) {
if (banding.Add(*cur)) {
++j;
} else {
break;
}
}
total_added += j;
for (auto& slot : slot_histogram) {
slot.second += banding.IsOccupied(slot.first);
}
int32_t bucket =
static_cast<int32_t>(num_slots) - static_cast<int32_t>(j);
rem_histogram[bucket]++;
if (FLAGS_verbose) {
fprintf(stderr, "num_slots: %u i: %u / %u avg_overhead: %g\r",
static_cast<unsigned>(num_slots), static_cast<unsigned>(i),
static_cast<unsigned>(FLAGS_find_iters),
1.0 * (i + 1) * num_slots / total_added);
}
}
if (FLAGS_verbose) {
fprintf(stderr, "\n");
}
uint32_t cumulative = 0;
double p50_rem = 0;
double p95_rem = 0;
double p99_9_rem = 0;
for (auto& h : rem_histogram) {
double before = 1.0 * cumulative / FLAGS_find_iters;
double not_after = 1.0 * (cumulative + h.second) / FLAGS_find_iters;
if (FLAGS_verbose) {
fprintf(stderr, "overhead: %g before: %g not_after: %g\n",
1.0 * num_slots / (num_slots - h.first), before, not_after);
}
cumulative += h.second;
if (before < 0.5 && 0.5 <= not_after) {
// fake it with linear interpolation
double portion = (0.5 - before) / (not_after - before);
p50_rem = h.first + portion;
} else if (before < 0.95 && 0.95 <= not_after) {
// fake it with linear interpolation
double portion = (0.95 - before) / (not_after - before);
p95_rem = h.first + portion;
} else if (before < 0.999 && 0.999 <= not_after) {
// fake it with linear interpolation
double portion = (0.999 - before) / (not_after - before);
p99_9_rem = h.first + portion;
}
}
for (auto& slot : slot_histogram) {
fprintf(stderr, "slot[%u] occupied: %g\n", (unsigned)slot.first,
1.0 * slot.second / FLAGS_find_iters);
}
double mean_rem =
(1.0 * FLAGS_find_iters * num_slots - total_added) / FLAGS_find_iters;
fprintf(
stderr,
"num_slots: %u iters: %u mean_ovr: %g p50_ovr: %g p95_ovr: %g "
"p99.9_ovr: %g mean_rem: %g p50_rem: %g p95_rem: %g p99.9_rem: %g\n",
static_cast<unsigned>(num_slots),
static_cast<unsigned>(FLAGS_find_iters),
1.0 * num_slots / (num_slots - mean_rem),
1.0 * num_slots / (num_slots - p50_rem),
1.0 * num_slots / (num_slots - p95_rem),
1.0 * num_slots / (num_slots - p99_9_rem), mean_rem, p50_rem, p95_rem,
p99_9_rem);
num_slots = std::max(
num_slots + 1, static_cast<Index>(num_slots * FLAGS_find_next_factor));
num_slots = InterleavedSoln::RoundUpNumSlots(num_slots);
}
}
// Not a real test, but a tool to understand Homogeneous Ribbon
// behavior (TODO: configuration APIs & tests)
TYPED_TEST(RibbonTypeParamTest, OptimizeHomogAtScale) {
IMPORT_RIBBON_TYPES_AND_SETTINGS(TypeParam);
IMPORT_RIBBON_IMPL_TYPES(TypeParam);
using KeyGen = typename TypeParam::KeyGen;
if (!FLAGS_optimize_homog) {
ROCKSDB_GTEST_BYPASS("Tool disabled during unit test runs");
return;
}
if (!TypeParam::kHomogeneous) {
ROCKSDB_GTEST_BYPASS("Only for Homogeneous Ribbon");
return;
}
KeyGen cur(ROCKSDB_NAMESPACE::ToString(
testing::UnitTest::GetInstance()->random_seed()),
0);
Banding banding;
Index num_slots = SimpleSoln::RoundUpNumSlots(FLAGS_optimize_homog_slots);
banding.Reset(num_slots);
// This and "band_ovr" is the "allocated overhead", or slots over added.
// It does not take into account FP rates.
double target_overhead = 1.20;
uint32_t num_added = 0;
do {
do {
(void)banding.Add(*cur);
++cur;
++num_added;
} while (1.0 * num_slots / num_added > target_overhead);
SimpleSoln soln;
soln.BackSubstFrom(banding);
std::array<uint32_t, 8U * sizeof(ResultRow)> fp_counts_by_cols;
fp_counts_by_cols.fill(0U);
for (uint32_t i = 0; i < FLAGS_optimize_homog_check; ++i) {
ResultRow r = soln.PhsfQuery(*cur, banding);
++cur;
for (size_t j = 0; j < fp_counts_by_cols.size(); ++j) {
if ((r & 1) == 1) {
break;
}
fp_counts_by_cols[j]++;
r /= 2;
}
}
fprintf(stderr, "band_ovr: %g ", 1.0 * num_slots / num_added);
for (unsigned j = 0; j < fp_counts_by_cols.size(); ++j) {
double inv_fp_rate =
1.0 * FLAGS_optimize_homog_check / fp_counts_by_cols[j];
double equiv_cols = std::log(inv_fp_rate) * 1.4426950409;
// Overhead vs. information-theoretic minimum based on observed
// FP rate (subject to sampling error, especially for low FP rates)
double actual_overhead =
1.0 * (j + 1) * num_slots / (equiv_cols * num_added);
fprintf(stderr, "ovr_%u: %g ", j + 1, actual_overhead);
}
fprintf(stderr, "\n");
target_overhead -= FLAGS_optimize_homog_granularity;
} while (target_overhead > 1.0);
}
int main(int argc, char** argv) {
::testing::InitGoogleTest(&argc, argv);
#ifdef GFLAGS
ParseCommandLineFlags(&argc, &argv, true);
#endif // GFLAGS
return RUN_ALL_TESTS();
}
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