// 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 #include #include #include #include #include #include #include "db/db_impl/db_impl.h" #include "monitoring/histogram.h" #include "port/port.h" #include "rocksdb/advanced_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."); DEFINE_string(secondary_cache_uri, "", "Full URI for creating a custom secondary cache object"); static class std::shared_ptr secondary_cache; 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); } }; Cache::ObjectPtr 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(Cache::ObjectPtr /*obj*/) { return FLAGS_value_bytes; } Status SaveToFn(Cache::ObjectPtr from_obj, size_t /*from_offset*/, size_t length, char* out) { memcpy(out, from_obj, length); return Status::OK(); } Status CreateFn(const Slice& data, Cache::CreateContext* /*context*/, MemoryAllocator* /*allocator*/, Cache::ObjectPtr* out_obj, size_t* out_charge) { *out_obj = new char[data.size()]; memcpy(*out_obj, data.data(), data.size()); *out_charge = data.size(); return Status::OK(); }; void DeleteFn(Cache::ObjectPtr value, MemoryAllocator* /*alloc*/) { delete[] static_cast(value); } Cache::CacheItemHelper helper1(CacheEntryRole::kDataBlock, DeleteFn, SizeFn, SaveToFn, CreateFn); Cache::CacheItemHelper helper2(CacheEntryRole::kIndexBlock, DeleteFn, SizeFn, SaveToFn, CreateFn); Cache::CacheItemHelper helper3(CacheEntryRole::kFilterBlock, DeleteFn, SizeFn, SaveToFn, CreateFn); } // namespace class CacheBench { static constexpr uint64_t kHundredthUint64 = std::numeric_limits::max() / 100U; public: CacheBench() : max_key_(static_cast(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(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 == "lru_cache") { LRUCacheOptions opts(FLAGS_cache_size, FLAGS_num_shard_bits, false /* strict_capacity_limit */, 0.5 /* high_pri_pool_ratio */); 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; } 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 > 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(end_time - start_time) * 1e-6; uint32_t ops_per_sec = static_cast( 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(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_; 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 helpers; 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( 1.0 * total_charge / total_entry_count)) << "\n" << "Unique helpers: " << helpers.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; helpers.clear(); auto fn = [&](const Slice& key, Cache::ObjectPtr /*value*/, size_t charge, const Cache::CacheItemHelper* helper) { total_key_size += key.size(); total_charge += charge; ++total_entry_count; // Something slightly more expensive as in stats by category helpers.insert(helper); }; 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(); timer.Start(); if (random_op < lookup_insert_threshold_) { if (handle) { cache_->Release(handle); handle = nullptr; } // do lookup handle = cache_->Lookup(key, &helper2, /*context*/ nullptr, Cache::Priority::LOW, true); if (handle) { if (!FLAGS_lean) { // do something with the data result += NPHash64(static_cast(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, /*context*/ nullptr, Cache::Priority::LOW, true); if (handle) { if (!FLAGS_lean) { // do something with the data result += NPHash64(static_cast(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(&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 dbs_; std::unique_ptr 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