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rocksdb/cache/cache_bench_tool.cc
Peter Dillinger 0f91c72adc Call experimental new clock cache HyperClockCache (#10684) 
Summary:
This change establishes a distinctive name for the experimental new lock-free clock cache (originally developed by guidotag and revamped in PR https://github.com/facebook/rocksdb/issues/10626). A few reasons:
* We want to make it clear that this is a fundamentally different implementation vs. the old clock cache, to avoid people saying "I already tried clock cache."
* We want to highlight the key feature: it's fast (especially under parallel load)
* Because it requires an estimated charge per entry, it is not drop-in API compatible with old clock cache. This estimate might always be required for highest performance, and giving it a distinct name should reduce confusion about the distinct API requirements.
* We might develop a variant requiring the same estimate parameter but with LRU eviction. In that case, using the name HyperLRUCache should make things more clear. (FastLRUCache is just a prototype that might soon be removed.)

Some API detail:
* To reduce copy-pasting parameter lists, etc. as in LRUCache construction, I have a `MakeSharedCache()` function on `HyperClockCacheOptions` instead of `NewHyperClockCache()`.
* Changes -cache_type=clock_cache to -cache_type=hyper_clock_cache for applicable tools. I think this is more consistent / sustainable for reasons already stated.

For performance tests see https://github.com/facebook/rocksdb/pull/10626

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10684

Test Plan: no interesting functional changes; tests updated

Reviewed By: anand1976

Differential Revision: D39547800

Pulled By: pdillinger

fbshipit-source-id: 5c0fe1b5cf3cb680ab369b928c8569682b9795bf
2022-09-16 12:47:29 -07:00

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// 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).
#include "cache_key.h"
#ifdef GFLAGS
#include <cinttypes>
#include <cstddef>
#include <cstdio>
#include <limits>
#include <memory>
#include <set>
#include <sstream>
#include "cache/fast_lru_cache.h"
#include "db/db_impl/db_impl.h"
#include "monitoring/histogram.h"
#include "port/port.h"
#include "rocksdb/cache.h"
#include "rocksdb/convenience.h"
#include "rocksdb/db.h"
#include "rocksdb/env.h"
#include "rocksdb/secondary_cache.h"
#include "rocksdb/system_clock.h"
#include "rocksdb/table_properties.h"
#include "table/block_based/block_based_table_reader.h"
#include "table/block_based/cachable_entry.h"
#include "util/coding.h"
#include "util/distributed_mutex.h"
#include "util/gflags_compat.h"
#include "util/hash.h"
#include "util/mutexlock.h"
#include "util/random.h"
#include "util/stop_watch.h"
#include "util/string_util.h"
using GFLAGS_NAMESPACE::ParseCommandLineFlags;
static constexpr uint32_t KiB = uint32_t{1} << 10;
static constexpr uint32_t MiB = KiB << 10;
static constexpr uint64_t GiB = MiB << 10;
DEFINE_uint32(threads, 16, "Number of concurrent threads to run.");
DEFINE_uint64(cache_size, 1 * GiB,
"Number of bytes to use as a cache of uncompressed data.");
DEFINE_uint32(num_shard_bits, 6, "shard_bits.");
DEFINE_double(resident_ratio, 0.25,
"Ratio of keys fitting in cache to keyspace.");
DEFINE_uint64(ops_per_thread, 2000000U, "Number of operations per thread.");
DEFINE_uint32(value_bytes, 8 * KiB, "Size of each value added.");
DEFINE_uint32(skew, 5, "Degree of skew in key selection");
DEFINE_bool(populate_cache, true, "Populate cache before operations");
DEFINE_uint32(lookup_insert_percent, 87,
"Ratio of lookup (+ insert on not found) to total workload "
"(expressed as a percentage)");
DEFINE_uint32(insert_percent, 2,
"Ratio of insert to total workload (expressed as a percentage)");
DEFINE_uint32(lookup_percent, 10,
"Ratio of lookup to total workload (expressed as a percentage)");
DEFINE_uint32(erase_percent, 1,
"Ratio of erase to total workload (expressed as a percentage)");
DEFINE_bool(gather_stats, false,
"Whether to periodically simulate gathering block cache stats, "
"using one more thread.");
DEFINE_uint32(
gather_stats_sleep_ms, 1000,
"How many milliseconds to sleep between each gathering of stats.");
DEFINE_uint32(gather_stats_entries_per_lock, 256,
"For Cache::ApplyToAllEntries");
DEFINE_bool(skewed, false, "If true, skew the key access distribution");
DEFINE_bool(lean, false,
"If true, no additional computation is performed besides cache "
"operations.");
#ifndef ROCKSDB_LITE
DEFINE_string(secondary_cache_uri, "",
"Full URI for creating a custom secondary cache object");
static class std::shared_ptr<ROCKSDB_NAMESPACE::SecondaryCache> secondary_cache;
#endif // ROCKSDB_LITE
DEFINE_string(cache_type, "lru_cache", "Type of block cache.");
// ## BEGIN stress_cache_key sub-tool options ##
// See class StressCacheKey below.
DEFINE_bool(stress_cache_key, false,
"If true, run cache key stress test instead");
DEFINE_uint32(
sck_files_per_day, 2500000,
"(-stress_cache_key) Simulated files generated per simulated day");
// NOTE: Giving each run a specified lifetime, rather than e.g. "until
// first collision" ensures equal skew from start-up, when collisions are
// less likely.
DEFINE_uint32(sck_days_per_run, 90,
"(-stress_cache_key) Number of days to simulate in each run");
// NOTE: The number of observed collisions directly affects the relative
// accuracy of the predicted probabilities. 15 observations should be well
// within factor-of-2 accuracy.
DEFINE_uint32(
sck_min_collision, 15,
"(-stress_cache_key) Keep running until this many collisions seen");
// sck_file_size_mb can be thought of as average file size. The simulation is
// not precise enough to care about the distribution of file sizes; other
// simulations (https://github.com/pdillinger/unique_id/tree/main/monte_carlo)
// indicate the distribution only makes a small difference (e.g. < 2x factor)
DEFINE_uint32(
sck_file_size_mb, 32,
"(-stress_cache_key) Simulated file size in MiB, for accounting purposes");
DEFINE_uint32(sck_reopen_nfiles, 100,
"(-stress_cache_key) Simulate DB re-open average every n files");
DEFINE_uint32(sck_newdb_nreopen, 1000,
"(-stress_cache_key) Simulate new DB average every n re-opens");
DEFINE_uint32(sck_restarts_per_day, 24,
"(-stress_cache_key) Average simulated process restarts per day "
"(across DBs)");
DEFINE_uint32(
sck_db_count, 100,
"(-stress_cache_key) Parallel DBs in simulation sharing a block cache");
DEFINE_uint32(
sck_table_bits, 20,
"(-stress_cache_key) Log2 number of tracked (live) files (across DBs)");
// sck_keep_bits being well below full 128 bits amplifies the collision
// probability so that the true probability can be estimated through observed
// collisions. (More explanation below.)
DEFINE_uint32(
sck_keep_bits, 50,
"(-stress_cache_key) Number of bits to keep from each cache key (<= 64)");
// sck_randomize is used to validate whether cache key is performing "better
// than random." Even with this setting, file offsets are not randomized.
DEFINE_bool(sck_randomize, false,
"(-stress_cache_key) Randomize (hash) cache key");
// See https://github.com/facebook/rocksdb/pull/9058
DEFINE_bool(sck_footer_unique_id, false,
"(-stress_cache_key) Simulate using proposed footer unique id");
// ## END stress_cache_key sub-tool options ##
namespace ROCKSDB_NAMESPACE {
class CacheBench;
namespace {
// State shared by all concurrent executions of the same benchmark.
class SharedState {
public:
explicit SharedState(CacheBench* cache_bench)
: cv_(&mu_),
num_initialized_(0),
start_(false),
num_done_(0),
cache_bench_(cache_bench) {}
~SharedState() {}
port::Mutex* GetMutex() { return &mu_; }
port::CondVar* GetCondVar() { return &cv_; }
CacheBench* GetCacheBench() const { return cache_bench_; }
void IncInitialized() { num_initialized_++; }
void IncDone() { num_done_++; }
bool AllInitialized() const { return num_initialized_ >= FLAGS_threads; }
bool AllDone() const { return num_done_ >= FLAGS_threads; }
void SetStart() { start_ = true; }
bool Started() const { return start_; }
private:
port::Mutex mu_;
port::CondVar cv_;
uint64_t num_initialized_;
bool start_;
uint64_t num_done_;
CacheBench* cache_bench_;
};
// Per-thread state for concurrent executions of the same benchmark.
struct ThreadState {
uint32_t tid;
Random64 rnd;
SharedState* shared;
HistogramImpl latency_ns_hist;
uint64_t duration_us = 0;
ThreadState(uint32_t index, SharedState* _shared)
: tid(index), rnd(1000 + index), shared(_shared) {}
};
struct KeyGen {
char key_data[27];
Slice GetRand(Random64& rnd, uint64_t max_key, int max_log) {
uint64_t key = 0;
if (!FLAGS_skewed) {
uint64_t raw = rnd.Next();
// Skew according to setting
for (uint32_t i = 0; i < FLAGS_skew; ++i) {
raw = std::min(raw, rnd.Next());
}
key = FastRange64(raw, max_key);
} else {
key = rnd.Skewed(max_log);
if (key > max_key) {
key -= max_key;
}
}
// Variable size and alignment
size_t off = key % 8;
key_data[0] = char{42};
EncodeFixed64(key_data + 1, key);
key_data[9] = char{11};
EncodeFixed64(key_data + 10, key);
key_data[18] = char{4};
EncodeFixed64(key_data + 19, key);
assert(27 >= kCacheKeySize);
return Slice(&key_data[off], kCacheKeySize);
}
};
char* createValue(Random64& rnd) {
char* rv = new char[FLAGS_value_bytes];
// Fill with some filler data, and take some CPU time
for (uint32_t i = 0; i < FLAGS_value_bytes; i += 8) {
EncodeFixed64(rv + i, rnd.Next());
}
return rv;
}
// Callbacks for secondary cache
size_t SizeFn(void* /*obj*/) { return FLAGS_value_bytes; }
Status SaveToFn(void* obj, size_t /*offset*/, size_t size, void* out) {
memcpy(out, obj, size);
return Status::OK();
}
// Different deleters to simulate using deleter to gather
// stats on the code origin and kind of cache entries.
void deleter1(const Slice& /*key*/, void* value) {
delete[] static_cast<char*>(value);
}
void deleter2(const Slice& /*key*/, void* value) {
delete[] static_cast<char*>(value);
}
void deleter3(const Slice& /*key*/, void* value) {
delete[] static_cast<char*>(value);
}
Cache::CacheItemHelper helper1(SizeFn, SaveToFn, deleter1);
Cache::CacheItemHelper helper2(SizeFn, SaveToFn, deleter2);
Cache::CacheItemHelper helper3(SizeFn, SaveToFn, deleter3);
} // namespace
class CacheBench {
static constexpr uint64_t kHundredthUint64 =
std::numeric_limits<uint64_t>::max() / 100U;
public:
CacheBench()
: max_key_(static_cast<uint64_t>(FLAGS_cache_size / FLAGS_resident_ratio /
FLAGS_value_bytes)),
lookup_insert_threshold_(kHundredthUint64 *
FLAGS_lookup_insert_percent),
insert_threshold_(lookup_insert_threshold_ +
kHundredthUint64 * FLAGS_insert_percent),
lookup_threshold_(insert_threshold_ +
kHundredthUint64 * FLAGS_lookup_percent),
erase_threshold_(lookup_threshold_ +
kHundredthUint64 * FLAGS_erase_percent),
skewed_(FLAGS_skewed) {
if (erase_threshold_ != 100U * kHundredthUint64) {
fprintf(stderr, "Percentages must add to 100.\n");
exit(1);
}
max_log_ = 0;
if (skewed_) {
uint64_t max_key = max_key_;
while (max_key >>= 1) max_log_++;
if (max_key > (static_cast<uint64_t>(1) << max_log_)) max_log_++;
}
if (FLAGS_cache_type == "clock_cache") {
fprintf(stderr, "Old clock cache implementation has been removed.\n");
exit(1);
} else if (FLAGS_cache_type == "hyper_clock_cache") {
cache_ = HyperClockCacheOptions(FLAGS_cache_size, FLAGS_value_bytes,
FLAGS_num_shard_bits)
.MakeSharedCache();
} else if (FLAGS_cache_type == "fast_lru_cache") {
cache_ = NewFastLRUCache(
FLAGS_cache_size, FLAGS_value_bytes, FLAGS_num_shard_bits,
false /*strict_capacity_limit*/, kDefaultCacheMetadataChargePolicy);
} else if (FLAGS_cache_type == "lru_cache") {
LRUCacheOptions opts(FLAGS_cache_size, FLAGS_num_shard_bits,
false /* strict_capacity_limit */,
0.5 /* high_pri_pool_ratio */);
#ifndef ROCKSDB_LITE
if (!FLAGS_secondary_cache_uri.empty()) {
Status s = SecondaryCache::CreateFromString(
ConfigOptions(), FLAGS_secondary_cache_uri, &secondary_cache);
if (secondary_cache == nullptr) {
fprintf(
stderr,
"No secondary cache registered matching string: %s status=%s\n",
FLAGS_secondary_cache_uri.c_str(), s.ToString().c_str());
exit(1);
}
opts.secondary_cache = secondary_cache;
}
#endif // ROCKSDB_LITE
cache_ = NewLRUCache(opts);
} else {
fprintf(stderr, "Cache type not supported.");
exit(1);
}
}
~CacheBench() {}
void PopulateCache() {
Random64 rnd(1);
KeyGen keygen;
for (uint64_t i = 0; i < 2 * FLAGS_cache_size; i += FLAGS_value_bytes) {
Status s = cache_->Insert(keygen.GetRand(rnd, max_key_, max_log_),
createValue(rnd), &helper1, FLAGS_value_bytes);
assert(s.ok());
}
}
bool Run() {
const auto clock = SystemClock::Default().get();
PrintEnv();
SharedState shared(this);
std::vector<std::unique_ptr<ThreadState> > threads(FLAGS_threads);
for (uint32_t i = 0; i < FLAGS_threads; i++) {
threads[i].reset(new ThreadState(i, &shared));
std::thread(ThreadBody, threads[i].get()).detach();
}
HistogramImpl stats_hist;
std::string stats_report;
std::thread stats_thread(StatsBody, &shared, &stats_hist, &stats_report);
uint64_t start_time;
{
MutexLock l(shared.GetMutex());
while (!shared.AllInitialized()) {
shared.GetCondVar()->Wait();
}
// Record start time
start_time = clock->NowMicros();
// Start all threads
shared.SetStart();
shared.GetCondVar()->SignalAll();
// Wait threads to complete
while (!shared.AllDone()) {
shared.GetCondVar()->Wait();
}
}
// Stats gathering is considered background work. This time measurement
// is for foreground work, and not really ideal for that. See below.
uint64_t end_time = clock->NowMicros();
stats_thread.join();
// Wall clock time - includes idle time if threads
// finish at different times (not ideal).
double elapsed_secs = static_cast<double>(end_time - start_time) * 1e-6;
uint32_t ops_per_sec = static_cast<uint32_t>(
1.0 * FLAGS_threads * FLAGS_ops_per_thread / elapsed_secs);
printf("Complete in %.3f s; Rough parallel ops/sec = %u\n", elapsed_secs,
ops_per_sec);
// Total time in each thread (more accurate throughput measure)
elapsed_secs = 0;
for (uint32_t i = 0; i < FLAGS_threads; i++) {
elapsed_secs += threads[i]->duration_us * 1e-6;
}
ops_per_sec = static_cast<uint32_t>(1.0 * FLAGS_threads *
FLAGS_ops_per_thread / elapsed_secs);
printf("Thread ops/sec = %u\n", ops_per_sec);
printf("\nOperation latency (ns):\n");
HistogramImpl combined;
for (uint32_t i = 0; i < FLAGS_threads; i++) {
combined.Merge(threads[i]->latency_ns_hist);
}
printf("%s", combined.ToString().c_str());
if (FLAGS_gather_stats) {
printf("\nGather stats latency (us):\n");
printf("%s", stats_hist.ToString().c_str());
}
printf("\n%s", stats_report.c_str());
return true;
}
private:
std::shared_ptr<Cache> cache_;
const uint64_t max_key_;
// Cumulative thresholds in the space of a random uint64_t
const uint64_t lookup_insert_threshold_;
const uint64_t insert_threshold_;
const uint64_t lookup_threshold_;
const uint64_t erase_threshold_;
const bool skewed_;
int max_log_;
// A benchmark version of gathering stats on an active block cache by
// iterating over it. The primary purpose is to measure the impact of
// gathering stats with ApplyToAllEntries on throughput- and
// latency-sensitive Cache users. Performance of stats gathering is
// also reported. The last set of gathered stats is also reported, for
// manual sanity checking for logical errors or other unexpected
// behavior of cache_bench or the underlying Cache.
static void StatsBody(SharedState* shared, HistogramImpl* stats_hist,
std::string* stats_report) {
if (!FLAGS_gather_stats) {
return;
}
const auto clock = SystemClock::Default().get();
uint64_t total_key_size = 0;
uint64_t total_charge = 0;
uint64_t total_entry_count = 0;
uint64_t table_occupancy = 0;
uint64_t table_size = 0;
std::set<Cache::DeleterFn> deleters;
StopWatchNano timer(clock);
for (;;) {
uint64_t time;
time = clock->NowMicros();
uint64_t deadline = time + uint64_t{FLAGS_gather_stats_sleep_ms} * 1000;
{
MutexLock l(shared->GetMutex());
for (;;) {
if (shared->AllDone()) {
std::ostringstream ostr;
ostr << "Most recent cache entry stats:\n"
<< "Number of entries: " << total_entry_count << "\n"
<< "Table occupancy: " << table_occupancy << " / "
<< table_size << " = "
<< (100.0 * table_occupancy / table_size) << "%\n"
<< "Total charge: " << BytesToHumanString(total_charge) << "\n"
<< "Average key size: "
<< (1.0 * total_key_size / total_entry_count) << "\n"
<< "Average charge: "
<< BytesToHumanString(static_cast<uint64_t>(
1.0 * total_charge / total_entry_count))
<< "\n"
<< "Unique deleters: " << deleters.size() << "\n";
*stats_report = ostr.str();
return;
}
if (clock->NowMicros() >= deadline) {
break;
}
uint64_t diff = deadline - std::min(clock->NowMicros(), deadline);
shared->GetCondVar()->TimedWait(diff + 1);
}
}
// Now gather stats, outside of mutex
total_key_size = 0;
total_charge = 0;
total_entry_count = 0;
deleters.clear();
auto fn = [&](const Slice& key, void* /*value*/, size_t charge,
Cache::DeleterFn deleter) {
total_key_size += key.size();
total_charge += charge;
++total_entry_count;
// Something slightly more expensive as in (future) stats by category
deleters.insert(deleter);
};
timer.Start();
Cache::ApplyToAllEntriesOptions opts;
opts.average_entries_per_lock = FLAGS_gather_stats_entries_per_lock;
shared->GetCacheBench()->cache_->ApplyToAllEntries(fn, opts);
table_occupancy = shared->GetCacheBench()->cache_->GetOccupancyCount();
table_size = shared->GetCacheBench()->cache_->GetTableAddressCount();
stats_hist->Add(timer.ElapsedNanos() / 1000);
}
}
static void ThreadBody(ThreadState* thread) {
SharedState* shared = thread->shared;
{
MutexLock l(shared->GetMutex());
shared->IncInitialized();
if (shared->AllInitialized()) {
shared->GetCondVar()->SignalAll();
}
while (!shared->Started()) {
shared->GetCondVar()->Wait();
}
}
thread->shared->GetCacheBench()->OperateCache(thread);
{
MutexLock l(shared->GetMutex());
shared->IncDone();
if (shared->AllDone()) {
shared->GetCondVar()->SignalAll();
}
}
}
void OperateCache(ThreadState* thread) {
// To use looked-up values
uint64_t result = 0;
// To hold handles for a non-trivial amount of time
Cache::Handle* handle = nullptr;
KeyGen gen;
const auto clock = SystemClock::Default().get();
uint64_t start_time = clock->NowMicros();
StopWatchNano timer(clock);
for (uint64_t i = 0; i < FLAGS_ops_per_thread; i++) {
Slice key = gen.GetRand(thread->rnd, max_key_, max_log_);
uint64_t random_op = thread->rnd.Next();
Cache::CreateCallback create_cb = [](const void* buf, size_t size,
void** out_obj,
size_t* charge) -> Status {
*out_obj = reinterpret_cast<void*>(new char[size]);
memcpy(*out_obj, buf, size);
*charge = size;
return Status::OK();
};
timer.Start();
if (random_op < lookup_insert_threshold_) {
if (handle) {
cache_->Release(handle);
handle = nullptr;
}
// do lookup
handle = cache_->Lookup(key, &helper2, create_cb, Cache::Priority::LOW,
true);
if (handle) {
if (!FLAGS_lean) {
// do something with the data
result += NPHash64(static_cast<char*>(cache_->Value(handle)),
FLAGS_value_bytes);
}
} else {
// do insert
Status s = cache_->Insert(key, createValue(thread->rnd), &helper2,
FLAGS_value_bytes, &handle);
assert(s.ok());
}
} else if (random_op < insert_threshold_) {
if (handle) {
cache_->Release(handle);
handle = nullptr;
}
// do insert
Status s = cache_->Insert(key, createValue(thread->rnd), &helper3,
FLAGS_value_bytes, &handle);
assert(s.ok());
} else if (random_op < lookup_threshold_) {
if (handle) {
cache_->Release(handle);
handle = nullptr;
}
// do lookup
handle = cache_->Lookup(key, &helper2, create_cb, Cache::Priority::LOW,
true);
if (handle) {
if (!FLAGS_lean) {
// do something with the data
result += NPHash64(static_cast<char*>(cache_->Value(handle)),
FLAGS_value_bytes);
}
}
} else if (random_op < erase_threshold_) {
// do erase
cache_->Erase(key);
} else {
// Should be extremely unlikely (noop)
assert(random_op >= kHundredthUint64 * 100U);
}
thread->latency_ns_hist.Add(timer.ElapsedNanos());
}
if (handle) {
cache_->Release(handle);
handle = nullptr;
}
// Ensure computations on `result` are not optimized away.
if (result == 1) {
printf("You are extremely unlucky(2). Try again.\n");
exit(1);
}
thread->duration_us = clock->NowMicros() - start_time;
}
void PrintEnv() const {
#if defined(__GNUC__) && !defined(__OPTIMIZE__)
printf(
"WARNING: Optimization is disabled: benchmarks unnecessarily slow\n");
#endif
#ifndef NDEBUG
printf("WARNING: Assertions are enabled; benchmarks unnecessarily slow\n");
#endif
printf("RocksDB version : %d.%d\n", kMajorVersion, kMinorVersion);
printf("DMutex impl name : %s\n", DMutex::kName());
printf("Number of threads : %u\n", FLAGS_threads);
printf("Ops per thread : %" PRIu64 "\n", FLAGS_ops_per_thread);
printf("Cache size : %s\n",
BytesToHumanString(FLAGS_cache_size).c_str());
printf("Num shard bits : %u\n", FLAGS_num_shard_bits);
printf("Max key : %" PRIu64 "\n", max_key_);
printf("Resident ratio : %g\n", FLAGS_resident_ratio);
printf("Skew degree : %u\n", FLAGS_skew);
printf("Populate cache : %d\n", int{FLAGS_populate_cache});
printf("Lookup+Insert pct : %u%%\n", FLAGS_lookup_insert_percent);
printf("Insert percentage : %u%%\n", FLAGS_insert_percent);
printf("Lookup percentage : %u%%\n", FLAGS_lookup_percent);
printf("Erase percentage : %u%%\n", FLAGS_erase_percent);
std::ostringstream stats;
if (FLAGS_gather_stats) {
stats << "enabled (" << FLAGS_gather_stats_sleep_ms << "ms, "
<< FLAGS_gather_stats_entries_per_lock << "/lock)";
} else {
stats << "disabled";
}
printf("Gather stats : %s\n", stats.str().c_str());
printf("----------------------------\n");
}
};
// cache_bench -stress_cache_key is an independent embedded tool for
// estimating the probability of CacheKey collisions through simulation.
// At a high level, it simulates generating SST files over many months,
// keeping them in the DB and/or cache for some lifetime while staying
// under resource caps, and checking for any cache key collisions that
// arise among the set of live files. For efficient simulation, we make
// some simplifying "pessimistic" assumptions (that only increase the
// chance of the simulation reporting a collision relative to the chance
// of collision in practice):
// * Every generated file has a cache entry for every byte offset in the
// file (contiguous range of cache keys)
// * All of every file is cached for its entire lifetime. (Here "lifetime"
// is technically the union of DB and Cache lifetime, though we only
// model a generous DB lifetime, where space usage is always maximized.
// In a effective Cache, lifetime in cache can only substantially exceed
// lifetime in DB if there is little cache activity; cache activity is
// required to hit cache key collisions.)
//
// It would be possible to track an exact set of cache key ranges for the
// set of live files, but we would have no hope of observing collisions
// (overlap in live files) in our simulation. We need to employ some way
// of amplifying collision probability that allows us to predict the real
// collision probability by extrapolation from observed collisions. Our
// basic approach is to reduce each cache key range down to some smaller
// number of bits, and limiting to bits that are shared over the whole
// range. Now we can observe collisions using a set of smaller stripped-down
// (reduced) cache keys. Let's do some case analysis to understand why this
// works:
// * No collision in reduced key - because the reduction is a pure function
// this implies no collision in the full keys
// * Collision detected between two reduced keys - either
// * The reduction has dropped some structured uniqueness info (from one of
// session counter or file number; file offsets are never materialized here).
// This can only artificially inflate the observed and extrapolated collision
// probabilities. We only have to worry about this in designing the reduction.
// * The reduction has preserved all the structured uniqueness in the cache
// key, which means either
// * REJECTED: We have a uniqueness bug in generating cache keys, where
// structured uniqueness info should have been different but isn't. In such a
// case, increasing by 1 the number of bits kept after reduction would not
// reduce observed probabilities by half. (In our observations, the
// probabilities are reduced approximately by half.)
// * ACCEPTED: The lost unstructured uniqueness in the key determines the
// probability that an observed collision would imply an overlap in ranges.
// In short, dropping n bits from key would increase collision probability by
// 2**n, assuming those n bits have full entropy in unstructured uniqueness.
//
// But we also have to account for the key ranges based on file size. If file
// sizes are roughly 2**b offsets, using XOR in 128-bit cache keys for
// "ranges", we know from other simulations (see
// https://github.com/pdillinger/unique_id/) that that's roughly equivalent to
// (less than 2x higher collision probability) using a cache key of size
// 128 - b bits for the whole file. (This is the only place we make an
// "optimistic" assumption, which is more than offset by the real
// implementation stripping off 2 lower bits from block byte offsets for cache
// keys. The simulation assumes byte offsets, which is net pessimistic.)
//
// So to accept the extrapolation as valid, we need to be confident that all
// "lost" bits, excluding those covered by file offset, are full entropy.
// Recall that we have assumed (verifiably, safely) that other structured data
// (file number and session counter) are kept, not lost. Based on the
// implementation comments for OffsetableCacheKey, the only potential hole here
// is that we only have ~103 bits of entropy in "all new" session IDs, and in
// extreme cases, there might be only 1 DB ID. However, because the upper ~39
// bits of session ID are hashed, the combination of file number and file
// offset only has to add to 25 bits (or more) to ensure full entropy in
// unstructured uniqueness lost in the reduction. Typical file size of 32MB
// suffices (at least for simulation purposes where we assume each file offset
// occupies a cache key).
//
// Example results in comments on OffsetableCacheKey.
class StressCacheKey {
public:
void Run() {
if (FLAGS_sck_footer_unique_id) {
// Proposed footer unique IDs are DB-independent and session-independent
// (but process-dependent) which is most easily simulated here by
// assuming 1 DB and (later below) no session resets without process
// reset.
FLAGS_sck_db_count = 1;
}
// Describe the simulated workload
uint64_t mb_per_day =
uint64_t{FLAGS_sck_files_per_day} * FLAGS_sck_file_size_mb;
printf("Total cache or DBs size: %gTiB Writing %g MiB/s or %gTiB/day\n",
FLAGS_sck_file_size_mb / 1024.0 / 1024.0 *
std::pow(2.0, FLAGS_sck_table_bits),
mb_per_day / 86400.0, mb_per_day / 1024.0 / 1024.0);
// For extrapolating probability of any collisions from a number of
// observed collisions
multiplier_ = std::pow(2.0, 128 - FLAGS_sck_keep_bits) /
(FLAGS_sck_file_size_mb * 1024.0 * 1024.0);
printf(
"Multiply by %g to correct for simulation losses (but still assume "
"whole file cached)\n",
multiplier_);
restart_nfiles_ = FLAGS_sck_files_per_day / FLAGS_sck_restarts_per_day;
double without_ejection =
std::pow(1.414214, FLAGS_sck_keep_bits) / FLAGS_sck_files_per_day;
// This should be a lower bound for -sck_randomize, usually a terribly
// rough lower bound.
// If observation is worse than this, then something has gone wrong.
printf(
"Without ejection, expect random collision after %g days (%g "
"corrected)\n",
without_ejection, without_ejection * multiplier_);
double with_full_table =
std::pow(2.0, FLAGS_sck_keep_bits - FLAGS_sck_table_bits) /
FLAGS_sck_files_per_day;
// This is an alternate lower bound for -sck_randomize, usually pretty
// accurate. Our cache keys should usually perform "better than random"
// but always no worse. (If observation is substantially worse than this,
// then something has gone wrong.)
printf(
"With ejection and full table, expect random collision after %g "
"days (%g corrected)\n",
with_full_table, with_full_table * multiplier_);
collisions_ = 0;
// Run until sufficient number of observed collisions.
for (int i = 1; collisions_ < FLAGS_sck_min_collision; i++) {
RunOnce();
if (collisions_ == 0) {
printf(
"No collisions after %d x %u days "
" \n",
i, FLAGS_sck_days_per_run);
} else {
double est = 1.0 * i * FLAGS_sck_days_per_run / collisions_;
printf("%" PRIu64
" collisions after %d x %u days, est %g days between (%g "
"corrected) \n",
collisions_, i, FLAGS_sck_days_per_run, est, est * multiplier_);
}
}
}
void RunOnce() {
// Re-initialized simulated state
const size_t db_count = std::max(size_t{FLAGS_sck_db_count}, size_t{1});
dbs_.reset(new TableProperties[db_count]{});
const size_t table_mask = (size_t{1} << FLAGS_sck_table_bits) - 1;
table_.reset(new uint64_t[table_mask + 1]{});
if (FLAGS_sck_keep_bits > 64) {
FLAGS_sck_keep_bits = 64;
}
// Details of which bits are dropped in reduction
uint32_t shift_away = 64 - FLAGS_sck_keep_bits;
// Shift away fewer potential file number bits (b) than potential
// session counter bits (a).
uint32_t shift_away_b = shift_away / 3;
uint32_t shift_away_a = shift_away - shift_away_b;
process_count_ = 0;
session_count_ = 0;
newdb_count_ = 0;
ResetProcess(/*newdbs*/ true);
Random64 r{std::random_device{}()};
uint64_t max_file_count =
uint64_t{FLAGS_sck_files_per_day} * FLAGS_sck_days_per_run;
uint32_t report_count = 0;
uint32_t collisions_this_run = 0;
size_t db_i = 0;
for (uint64_t file_count = 1; file_count <= max_file_count;
++file_count, ++db_i) {
// Round-robin through DBs (this faster than %)
if (db_i >= db_count) {
db_i = 0;
}
// Any other periodic actions before simulating next file
if (!FLAGS_sck_footer_unique_id && r.OneIn(FLAGS_sck_reopen_nfiles)) {
ResetSession(db_i, /*newdb*/ r.OneIn(FLAGS_sck_newdb_nreopen));
} else if (r.OneIn(restart_nfiles_)) {
ResetProcess(/*newdbs*/ false);
}
// Simulate next file
OffsetableCacheKey ock;
dbs_[db_i].orig_file_number += 1;
// skip some file numbers for other file kinds, except in footer unique
// ID, orig_file_number here tracks process-wide generated SST file
// count.
if (!FLAGS_sck_footer_unique_id) {
dbs_[db_i].orig_file_number += (r.Next() & 3);
}
bool is_stable;
BlockBasedTable::SetupBaseCacheKey(&dbs_[db_i], /* ignored */ "",
/* ignored */ 42, &ock, &is_stable);
assert(is_stable);
// Get a representative cache key, which later we analytically generalize
// to a range.
CacheKey ck = ock.WithOffset(0);
uint64_t reduced_key;
if (FLAGS_sck_randomize) {
reduced_key = GetSliceHash64(ck.AsSlice()) >> shift_away;
} else if (FLAGS_sck_footer_unique_id) {
// Special case: keep only file number, not session counter
reduced_key = DecodeFixed64(ck.AsSlice().data()) >> shift_away;
} else {
// Try to keep file number and session counter (shift away other bits)
uint32_t a = DecodeFixed32(ck.AsSlice().data()) << shift_away_a;
uint32_t b = DecodeFixed32(ck.AsSlice().data() + 4) >> shift_away_b;
reduced_key = (uint64_t{a} << 32) + b;
}
if (reduced_key == 0) {
// Unlikely, but we need to exclude tracking this value because we
// use it to mean "empty" in table. This case is OK as long as we
// don't hit it often.
printf("Hit Zero! \n");
file_count--;
continue;
}
uint64_t h =
NPHash64(reinterpret_cast<char*>(&reduced_key), sizeof(reduced_key));
// Skew expected lifetimes, for high variance (super-Poisson) variance
// in actual lifetimes.
size_t pos =
std::min(Lower32of64(h) & table_mask, Upper32of64(h) & table_mask);
if (table_[pos] == reduced_key) {
collisions_this_run++;
// Our goal is to predict probability of no collisions, not expected
// number of collisions. To make the distinction, we have to get rid
// of observing correlated collisions, which this takes care of:
ResetProcess(/*newdbs*/ false);
} else {
// Replace (end of lifetime for file that was in this slot)
table_[pos] = reduced_key;
}
if (++report_count == FLAGS_sck_files_per_day) {
report_count = 0;
// Estimate fill %
size_t incr = table_mask / 1000;
size_t sampled_count = 0;
for (size_t i = 0; i <= table_mask; i += incr) {
if (table_[i] != 0) {
sampled_count++;
}
}
// Report
printf(
"%" PRIu64 " days, %" PRIu64 " proc, %" PRIu64 " sess, %" PRIu64
" newdb, %u coll, occ %g%%, ejected %g%% \r",
file_count / FLAGS_sck_files_per_day, process_count_,
session_count_, newdb_count_ - FLAGS_sck_db_count,
collisions_this_run, 100.0 * sampled_count / 1000.0,
100.0 * (1.0 - sampled_count / 1000.0 * table_mask / file_count));
fflush(stdout);
}
}
collisions_ += collisions_this_run;
}
void ResetSession(size_t i, bool newdb) {
dbs_[i].db_session_id = DBImpl::GenerateDbSessionId(nullptr);
if (newdb) {
++newdb_count_;
if (FLAGS_sck_footer_unique_id) {
// Simulate how footer id would behave
dbs_[i].db_id = "none";
} else {
// db_id might be ignored, depending on the implementation details
dbs_[i].db_id = std::to_string(newdb_count_);
dbs_[i].orig_file_number = 0;
}
}
session_count_++;
}
void ResetProcess(bool newdbs) {
process_count_++;
DBImpl::TEST_ResetDbSessionIdGen();
for (size_t i = 0; i < FLAGS_sck_db_count; ++i) {
ResetSession(i, newdbs);
}
if (FLAGS_sck_footer_unique_id) {
// For footer unique ID, this tracks process-wide generated SST file
// count.
dbs_[0].orig_file_number = 0;
}
}
private:
// Use db_session_id and orig_file_number from TableProperties
std::unique_ptr<TableProperties[]> dbs_;
std::unique_ptr<uint64_t[]> table_;
uint64_t process_count_ = 0;
uint64_t session_count_ = 0;
uint64_t newdb_count_ = 0;
uint64_t collisions_ = 0;
uint32_t restart_nfiles_ = 0;
double multiplier_ = 0.0;
};
int cache_bench_tool(int argc, char** argv) {
ParseCommandLineFlags(&argc, &argv, true);
if (FLAGS_stress_cache_key) {
// Alternate tool
StressCacheKey().Run();
return 0;
}
if (FLAGS_threads <= 0) {
fprintf(stderr, "threads number <= 0\n");
exit(1);
}
ROCKSDB_NAMESPACE::CacheBench bench;
if (FLAGS_populate_cache) {
bench.PopulateCache();
printf("Population complete\n");
printf("----------------------------\n");
}
if (bench.Run()) {
return 0;
} else {
return 1;
}
} // namespace ROCKSDB_NAMESPACE
} // namespace ROCKSDB_NAMESPACE
#endif // GFLAGS
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