rocksdb/utilities/simulator_cache/sim_cache.cc

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add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
// 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).
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
#include "rocksdb/utilities/sim_cache.h"
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
#include <atomic>
#include <iomanip>
#include "file/writable_file_writer.h"
#include "monitoring/statistics_impl.h"
#include "port/port.h"
#include "rocksdb/env.h"
#include "rocksdb/file_system.h"
#include "util/mutexlock.h"
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
namespace ROCKSDB_NAMESPACE {
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
namespace {
class CacheActivityLogger {
public:
CacheActivityLogger()
: activity_logging_enabled_(false), max_logging_size_(0) {}
~CacheActivityLogger() {
MutexLock l(&mutex_);
StopLoggingInternal();
bg_status_.PermitUncheckedError();
}
Status StartLogging(const std::string& activity_log_file, Env* env,
uint64_t max_logging_size = 0) {
assert(activity_log_file != "");
assert(env != nullptr);
Status status;
FileOptions file_opts;
MutexLock l(&mutex_);
// Stop existing logging if any
StopLoggingInternal();
// Open log file
status = WritableFileWriter::Create(env->GetFileSystem(), activity_log_file,
file_opts, &file_writer_, nullptr);
if (!status.ok()) {
return status;
}
max_logging_size_ = max_logging_size;
activity_logging_enabled_.store(true);
return status;
}
void StopLogging() {
MutexLock l(&mutex_);
StopLoggingInternal();
}
void ReportLookup(const Slice& key) {
if (activity_logging_enabled_.load() == false) {
return;
}
std::ostringstream oss;
// line format: "LOOKUP - <KEY>"
oss << "LOOKUP - " << key.ToString(true) << std::endl;
MutexLock l(&mutex_);
Group SST write in flush, compaction and db open with new stats (#11910) Summary: ## Context/Summary Similar to https://github.com/facebook/rocksdb/pull/11288, https://github.com/facebook/rocksdb/pull/11444, categorizing SST/blob file write according to different io activities allows more insight into the activity. For that, this PR does the following: - Tag different write IOs by passing down and converting WriteOptions to IOOptions - Add new SST_WRITE_MICROS histogram in WritableFileWriter::Append() and breakdown FILE_WRITE_{FLUSH|COMPACTION|DB_OPEN}_MICROS Some related code refactory to make implementation cleaner: - Blob stats - Replace high-level write measurement with low-level WritableFileWriter::Append() measurement for BLOB_DB_BLOB_FILE_WRITE_MICROS. This is to make FILE_WRITE_{FLUSH|COMPACTION|DB_OPEN}_MICROS include blob file. As a consequence, this introduces some behavioral changes on it, see HISTORY and db bench test plan below for more info. - Fix bugs where BLOB_DB_BLOB_FILE_SYNCED/BLOB_DB_BLOB_FILE_BYTES_WRITTEN include file failed to sync and bytes failed to write. - Refactor WriteOptions constructor for easier construction with io_activity and rate_limiter_priority - Refactor DBImpl::~DBImpl()/BlobDBImpl::Close() to bypass thread op verification - Build table - TableBuilderOptions now includes Read/WriteOpitons so BuildTable() do not need to take these two variables - Replace the io_priority passed into BuildTable() with TableBuilderOptions::WriteOpitons::rate_limiter_priority. Similar for BlobFileBuilder. This parameter is used for dynamically changing file io priority for flush, see https://github.com/facebook/rocksdb/pull/9988?fbclid=IwAR1DtKel6c-bRJAdesGo0jsbztRtciByNlvokbxkV6h_L-AE9MACzqRTT5s for more - Update ThreadStatus::FLUSH_BYTES_WRITTEN to use io_activity to track flush IO in flush job and db open instead of io_priority ## Test ### db bench Flush ``` ./db_bench --statistics=1 --benchmarks=fillseq --num=100000 --write_buffer_size=100 rocksdb.sst.write.micros P50 : 1.830863 P95 : 4.094720 P99 : 6.578947 P100 : 26.000000 COUNT : 7875 SUM : 20377 rocksdb.file.write.flush.micros P50 : 1.830863 P95 : 4.094720 P99 : 6.578947 P100 : 26.000000 COUNT : 7875 SUM : 20377 rocksdb.file.write.compaction.micros P50 : 0.000000 P95 : 0.000000 P99 : 0.000000 P100 : 0.000000 COUNT : 0 SUM : 0 rocksdb.file.write.db.open.micros P50 : 0.000000 P95 : 0.000000 P99 : 0.000000 P100 : 0.000000 COUNT : 0 SUM : 0 ``` compaction, db oopen ``` Setup: ./db_bench --statistics=1 --benchmarks=fillseq --num=10000 --disable_auto_compactions=1 -write_buffer_size=100 --db=../db_bench Run:./db_bench --statistics=1 --benchmarks=compact --db=../db_bench --use_existing_db=1 rocksdb.sst.write.micros P50 : 2.675325 P95 : 9.578788 P99 : 18.780000 P100 : 314.000000 COUNT : 638 SUM : 3279 rocksdb.file.write.flush.micros P50 : 0.000000 P95 : 0.000000 P99 : 0.000000 P100 : 0.000000 COUNT : 0 SUM : 0 rocksdb.file.write.compaction.micros P50 : 2.757353 P95 : 9.610687 P99 : 19.316667 P100 : 314.000000 COUNT : 615 SUM : 3213 rocksdb.file.write.db.open.micros P50 : 2.055556 P95 : 3.925000 P99 : 9.000000 P100 : 9.000000 COUNT : 23 SUM : 66 ``` blob stats - just to make sure they aren't broken by this PR ``` Integrated Blob DB Setup: ./db_bench --enable_blob_files=1 --statistics=1 --benchmarks=fillseq --num=10000 --disable_auto_compactions=1 -write_buffer_size=100 --db=../db_bench Run:./db_bench --enable_blob_files=1 --statistics=1 --benchmarks=compact --db=../db_bench --use_existing_db=1 pre-PR: rocksdb.blobdb.blob.file.write.micros P50 : 7.298246 P95 : 9.771930 P99 : 9.991813 P100 : 16.000000 COUNT : 235 SUM : 1600 rocksdb.blobdb.blob.file.synced COUNT : 1 rocksdb.blobdb.blob.file.bytes.written COUNT : 34842 post-PR: rocksdb.blobdb.blob.file.write.micros P50 : 2.000000 P95 : 2.829360 P99 : 2.993779 P100 : 9.000000 COUNT : 707 SUM : 1614 - COUNT is higher and values are smaller as it includes header and footer write - COUNT is 3X higher due to each Append() count as one post-PR, while in pre-PR, 3 Append()s counts as one. See https://github.com/facebook/rocksdb/pull/11910/files#diff-32b811c0a1c000768cfb2532052b44dc0b3bf82253f3eab078e15ff201a0dabfL157-L164 rocksdb.blobdb.blob.file.synced COUNT : 1 (stay the same) rocksdb.blobdb.blob.file.bytes.written COUNT : 34842 (stay the same) ``` ``` Stacked Blob DB Run: ./db_bench --use_blob_db=1 --statistics=1 --benchmarks=fillseq --num=10000 --disable_auto_compactions=1 -write_buffer_size=100 --db=../db_bench pre-PR: rocksdb.blobdb.blob.file.write.micros P50 : 12.808042 P95 : 19.674497 P99 : 28.539683 P100 : 51.000000 COUNT : 10000 SUM : 140876 rocksdb.blobdb.blob.file.synced COUNT : 8 rocksdb.blobdb.blob.file.bytes.written COUNT : 1043445 post-PR: rocksdb.blobdb.blob.file.write.micros P50 : 1.657370 P95 : 2.952175 P99 : 3.877519 P100 : 24.000000 COUNT : 30001 SUM : 67924 - COUNT is higher and values are smaller as it includes header and footer write - COUNT is 3X higher due to each Append() count as one post-PR, while in pre-PR, 3 Append()s counts as one. See https://github.com/facebook/rocksdb/pull/11910/files#diff-32b811c0a1c000768cfb2532052b44dc0b3bf82253f3eab078e15ff201a0dabfL157-L164 rocksdb.blobdb.blob.file.synced COUNT : 8 (stay the same) rocksdb.blobdb.blob.file.bytes.written COUNT : 1043445 (stay the same) ``` ### Rehearsal CI stress test Trigger 3 full runs of all our CI stress tests ### Performance Flush ``` TEST_TMPDIR=/dev/shm ./db_basic_bench_pre_pr --benchmark_filter=ManualFlush/key_num:524288/per_key_size:256 --benchmark_repetitions=1000 -- default: 1 thread is used to run benchmark; enable_statistics = true Pre-pr: avg 507515519.3 ns 497686074,499444327,500862543,501389862,502994471,503744435,504142123,504224056,505724198,506610393,506837742,506955122,507695561,507929036,508307733,508312691,508999120,509963561,510142147,510698091,510743096,510769317,510957074,511053311,511371367,511409911,511432960,511642385,511691964,511730908, Post-pr: avg 511971266.5 ns, regressed 0.88% 502744835,506502498,507735420,507929724,508313335,509548582,509994942,510107257,510715603,511046955,511352639,511458478,512117521,512317380,512766303,512972652,513059586,513804934,513808980,514059409,514187369,514389494,514447762,514616464,514622882,514641763,514666265,514716377,514990179,515502408, ``` Compaction ``` TEST_TMPDIR=/dev/shm ./db_basic_bench_{pre|post}_pr --benchmark_filter=ManualCompaction/comp_style:0/max_data:134217728/per_key_size:256/enable_statistics:1 --benchmark_repetitions=1000 -- default: 1 thread is used to run benchmark Pre-pr: avg 495346098.30 ns 492118301,493203526,494201411,494336607,495269217,495404950,496402598,497012157,497358370,498153846 Post-pr: avg 504528077.20, regressed 1.85%. "ManualCompaction" include flush so the isolated regression for compaction should be around 1.85-0.88 = 0.97% 502465338,502485945,502541789,502909283,503438601,504143885,506113087,506629423,507160414,507393007 ``` Put with WAL (in case passing WriteOptions slows down this path even without collecting SST write stats) ``` TEST_TMPDIR=/dev/shm ./db_basic_bench_pre_pr --benchmark_filter=DBPut/comp_style:0/max_data:107374182400/per_key_size:256/enable_statistics:1/wal:1 --benchmark_repetitions=1000 -- default: 1 thread is used to run benchmark Pre-pr: avg 3848.10 ns 3814,3838,3839,3848,3854,3854,3854,3860,3860,3860 Post-pr: avg 3874.20 ns, regressed 0.68% 3863,3867,3871,3874,3875,3877,3877,3877,3880,3881 ``` Pull Request resolved: https://github.com/facebook/rocksdb/pull/11910 Reviewed By: ajkr Differential Revision: D49788060 Pulled By: hx235 fbshipit-source-id: 79e73699cda5be3b66461687e5147c2484fc5eff
2023-12-29 23:29:23 +00:00
Status s = file_writer_->Append(IOOptions(), oss.str());
if (!s.ok() && bg_status_.ok()) {
bg_status_ = s;
}
if (MaxLoggingSizeReached() || !bg_status_.ok()) {
// Stop logging if we have reached the max file size or
// encountered an error
StopLoggingInternal();
}
}
void ReportAdd(const Slice& key, size_t size) {
if (activity_logging_enabled_.load() == false) {
return;
}
std::ostringstream oss;
// line format: "ADD - <KEY> - <KEY-SIZE>"
oss << "ADD - " << key.ToString(true) << " - " << size << std::endl;
MutexLock l(&mutex_);
Group SST write in flush, compaction and db open with new stats (#11910) Summary: ## Context/Summary Similar to https://github.com/facebook/rocksdb/pull/11288, https://github.com/facebook/rocksdb/pull/11444, categorizing SST/blob file write according to different io activities allows more insight into the activity. For that, this PR does the following: - Tag different write IOs by passing down and converting WriteOptions to IOOptions - Add new SST_WRITE_MICROS histogram in WritableFileWriter::Append() and breakdown FILE_WRITE_{FLUSH|COMPACTION|DB_OPEN}_MICROS Some related code refactory to make implementation cleaner: - Blob stats - Replace high-level write measurement with low-level WritableFileWriter::Append() measurement for BLOB_DB_BLOB_FILE_WRITE_MICROS. This is to make FILE_WRITE_{FLUSH|COMPACTION|DB_OPEN}_MICROS include blob file. As a consequence, this introduces some behavioral changes on it, see HISTORY and db bench test plan below for more info. - Fix bugs where BLOB_DB_BLOB_FILE_SYNCED/BLOB_DB_BLOB_FILE_BYTES_WRITTEN include file failed to sync and bytes failed to write. - Refactor WriteOptions constructor for easier construction with io_activity and rate_limiter_priority - Refactor DBImpl::~DBImpl()/BlobDBImpl::Close() to bypass thread op verification - Build table - TableBuilderOptions now includes Read/WriteOpitons so BuildTable() do not need to take these two variables - Replace the io_priority passed into BuildTable() with TableBuilderOptions::WriteOpitons::rate_limiter_priority. Similar for BlobFileBuilder. This parameter is used for dynamically changing file io priority for flush, see https://github.com/facebook/rocksdb/pull/9988?fbclid=IwAR1DtKel6c-bRJAdesGo0jsbztRtciByNlvokbxkV6h_L-AE9MACzqRTT5s for more - Update ThreadStatus::FLUSH_BYTES_WRITTEN to use io_activity to track flush IO in flush job and db open instead of io_priority ## Test ### db bench Flush ``` ./db_bench --statistics=1 --benchmarks=fillseq --num=100000 --write_buffer_size=100 rocksdb.sst.write.micros P50 : 1.830863 P95 : 4.094720 P99 : 6.578947 P100 : 26.000000 COUNT : 7875 SUM : 20377 rocksdb.file.write.flush.micros P50 : 1.830863 P95 : 4.094720 P99 : 6.578947 P100 : 26.000000 COUNT : 7875 SUM : 20377 rocksdb.file.write.compaction.micros P50 : 0.000000 P95 : 0.000000 P99 : 0.000000 P100 : 0.000000 COUNT : 0 SUM : 0 rocksdb.file.write.db.open.micros P50 : 0.000000 P95 : 0.000000 P99 : 0.000000 P100 : 0.000000 COUNT : 0 SUM : 0 ``` compaction, db oopen ``` Setup: ./db_bench --statistics=1 --benchmarks=fillseq --num=10000 --disable_auto_compactions=1 -write_buffer_size=100 --db=../db_bench Run:./db_bench --statistics=1 --benchmarks=compact --db=../db_bench --use_existing_db=1 rocksdb.sst.write.micros P50 : 2.675325 P95 : 9.578788 P99 : 18.780000 P100 : 314.000000 COUNT : 638 SUM : 3279 rocksdb.file.write.flush.micros P50 : 0.000000 P95 : 0.000000 P99 : 0.000000 P100 : 0.000000 COUNT : 0 SUM : 0 rocksdb.file.write.compaction.micros P50 : 2.757353 P95 : 9.610687 P99 : 19.316667 P100 : 314.000000 COUNT : 615 SUM : 3213 rocksdb.file.write.db.open.micros P50 : 2.055556 P95 : 3.925000 P99 : 9.000000 P100 : 9.000000 COUNT : 23 SUM : 66 ``` blob stats - just to make sure they aren't broken by this PR ``` Integrated Blob DB Setup: ./db_bench --enable_blob_files=1 --statistics=1 --benchmarks=fillseq --num=10000 --disable_auto_compactions=1 -write_buffer_size=100 --db=../db_bench Run:./db_bench --enable_blob_files=1 --statistics=1 --benchmarks=compact --db=../db_bench --use_existing_db=1 pre-PR: rocksdb.blobdb.blob.file.write.micros P50 : 7.298246 P95 : 9.771930 P99 : 9.991813 P100 : 16.000000 COUNT : 235 SUM : 1600 rocksdb.blobdb.blob.file.synced COUNT : 1 rocksdb.blobdb.blob.file.bytes.written COUNT : 34842 post-PR: rocksdb.blobdb.blob.file.write.micros P50 : 2.000000 P95 : 2.829360 P99 : 2.993779 P100 : 9.000000 COUNT : 707 SUM : 1614 - COUNT is higher and values are smaller as it includes header and footer write - COUNT is 3X higher due to each Append() count as one post-PR, while in pre-PR, 3 Append()s counts as one. See https://github.com/facebook/rocksdb/pull/11910/files#diff-32b811c0a1c000768cfb2532052b44dc0b3bf82253f3eab078e15ff201a0dabfL157-L164 rocksdb.blobdb.blob.file.synced COUNT : 1 (stay the same) rocksdb.blobdb.blob.file.bytes.written COUNT : 34842 (stay the same) ``` ``` Stacked Blob DB Run: ./db_bench --use_blob_db=1 --statistics=1 --benchmarks=fillseq --num=10000 --disable_auto_compactions=1 -write_buffer_size=100 --db=../db_bench pre-PR: rocksdb.blobdb.blob.file.write.micros P50 : 12.808042 P95 : 19.674497 P99 : 28.539683 P100 : 51.000000 COUNT : 10000 SUM : 140876 rocksdb.blobdb.blob.file.synced COUNT : 8 rocksdb.blobdb.blob.file.bytes.written COUNT : 1043445 post-PR: rocksdb.blobdb.blob.file.write.micros P50 : 1.657370 P95 : 2.952175 P99 : 3.877519 P100 : 24.000000 COUNT : 30001 SUM : 67924 - COUNT is higher and values are smaller as it includes header and footer write - COUNT is 3X higher due to each Append() count as one post-PR, while in pre-PR, 3 Append()s counts as one. See https://github.com/facebook/rocksdb/pull/11910/files#diff-32b811c0a1c000768cfb2532052b44dc0b3bf82253f3eab078e15ff201a0dabfL157-L164 rocksdb.blobdb.blob.file.synced COUNT : 8 (stay the same) rocksdb.blobdb.blob.file.bytes.written COUNT : 1043445 (stay the same) ``` ### Rehearsal CI stress test Trigger 3 full runs of all our CI stress tests ### Performance Flush ``` TEST_TMPDIR=/dev/shm ./db_basic_bench_pre_pr --benchmark_filter=ManualFlush/key_num:524288/per_key_size:256 --benchmark_repetitions=1000 -- default: 1 thread is used to run benchmark; enable_statistics = true Pre-pr: avg 507515519.3 ns 497686074,499444327,500862543,501389862,502994471,503744435,504142123,504224056,505724198,506610393,506837742,506955122,507695561,507929036,508307733,508312691,508999120,509963561,510142147,510698091,510743096,510769317,510957074,511053311,511371367,511409911,511432960,511642385,511691964,511730908, Post-pr: avg 511971266.5 ns, regressed 0.88% 502744835,506502498,507735420,507929724,508313335,509548582,509994942,510107257,510715603,511046955,511352639,511458478,512117521,512317380,512766303,512972652,513059586,513804934,513808980,514059409,514187369,514389494,514447762,514616464,514622882,514641763,514666265,514716377,514990179,515502408, ``` Compaction ``` TEST_TMPDIR=/dev/shm ./db_basic_bench_{pre|post}_pr --benchmark_filter=ManualCompaction/comp_style:0/max_data:134217728/per_key_size:256/enable_statistics:1 --benchmark_repetitions=1000 -- default: 1 thread is used to run benchmark Pre-pr: avg 495346098.30 ns 492118301,493203526,494201411,494336607,495269217,495404950,496402598,497012157,497358370,498153846 Post-pr: avg 504528077.20, regressed 1.85%. "ManualCompaction" include flush so the isolated regression for compaction should be around 1.85-0.88 = 0.97% 502465338,502485945,502541789,502909283,503438601,504143885,506113087,506629423,507160414,507393007 ``` Put with WAL (in case passing WriteOptions slows down this path even without collecting SST write stats) ``` TEST_TMPDIR=/dev/shm ./db_basic_bench_pre_pr --benchmark_filter=DBPut/comp_style:0/max_data:107374182400/per_key_size:256/enable_statistics:1/wal:1 --benchmark_repetitions=1000 -- default: 1 thread is used to run benchmark Pre-pr: avg 3848.10 ns 3814,3838,3839,3848,3854,3854,3854,3860,3860,3860 Post-pr: avg 3874.20 ns, regressed 0.68% 3863,3867,3871,3874,3875,3877,3877,3877,3880,3881 ``` Pull Request resolved: https://github.com/facebook/rocksdb/pull/11910 Reviewed By: ajkr Differential Revision: D49788060 Pulled By: hx235 fbshipit-source-id: 79e73699cda5be3b66461687e5147c2484fc5eff
2023-12-29 23:29:23 +00:00
Status s = file_writer_->Append(IOOptions(), oss.str());
if (!s.ok() && bg_status_.ok()) {
bg_status_ = s;
}
if (MaxLoggingSizeReached() || !bg_status_.ok()) {
// Stop logging if we have reached the max file size or
// encountered an error
StopLoggingInternal();
}
}
Status& bg_status() {
MutexLock l(&mutex_);
return bg_status_;
}
private:
bool MaxLoggingSizeReached() {
mutex_.AssertHeld();
return (max_logging_size_ > 0 &&
file_writer_->GetFileSize() >= max_logging_size_);
}
void StopLoggingInternal() {
mutex_.AssertHeld();
if (!activity_logging_enabled_) {
return;
}
activity_logging_enabled_.store(false);
Group SST write in flush, compaction and db open with new stats (#11910) Summary: ## Context/Summary Similar to https://github.com/facebook/rocksdb/pull/11288, https://github.com/facebook/rocksdb/pull/11444, categorizing SST/blob file write according to different io activities allows more insight into the activity. For that, this PR does the following: - Tag different write IOs by passing down and converting WriteOptions to IOOptions - Add new SST_WRITE_MICROS histogram in WritableFileWriter::Append() and breakdown FILE_WRITE_{FLUSH|COMPACTION|DB_OPEN}_MICROS Some related code refactory to make implementation cleaner: - Blob stats - Replace high-level write measurement with low-level WritableFileWriter::Append() measurement for BLOB_DB_BLOB_FILE_WRITE_MICROS. This is to make FILE_WRITE_{FLUSH|COMPACTION|DB_OPEN}_MICROS include blob file. As a consequence, this introduces some behavioral changes on it, see HISTORY and db bench test plan below for more info. - Fix bugs where BLOB_DB_BLOB_FILE_SYNCED/BLOB_DB_BLOB_FILE_BYTES_WRITTEN include file failed to sync and bytes failed to write. - Refactor WriteOptions constructor for easier construction with io_activity and rate_limiter_priority - Refactor DBImpl::~DBImpl()/BlobDBImpl::Close() to bypass thread op verification - Build table - TableBuilderOptions now includes Read/WriteOpitons so BuildTable() do not need to take these two variables - Replace the io_priority passed into BuildTable() with TableBuilderOptions::WriteOpitons::rate_limiter_priority. Similar for BlobFileBuilder. This parameter is used for dynamically changing file io priority for flush, see https://github.com/facebook/rocksdb/pull/9988?fbclid=IwAR1DtKel6c-bRJAdesGo0jsbztRtciByNlvokbxkV6h_L-AE9MACzqRTT5s for more - Update ThreadStatus::FLUSH_BYTES_WRITTEN to use io_activity to track flush IO in flush job and db open instead of io_priority ## Test ### db bench Flush ``` ./db_bench --statistics=1 --benchmarks=fillseq --num=100000 --write_buffer_size=100 rocksdb.sst.write.micros P50 : 1.830863 P95 : 4.094720 P99 : 6.578947 P100 : 26.000000 COUNT : 7875 SUM : 20377 rocksdb.file.write.flush.micros P50 : 1.830863 P95 : 4.094720 P99 : 6.578947 P100 : 26.000000 COUNT : 7875 SUM : 20377 rocksdb.file.write.compaction.micros P50 : 0.000000 P95 : 0.000000 P99 : 0.000000 P100 : 0.000000 COUNT : 0 SUM : 0 rocksdb.file.write.db.open.micros P50 : 0.000000 P95 : 0.000000 P99 : 0.000000 P100 : 0.000000 COUNT : 0 SUM : 0 ``` compaction, db oopen ``` Setup: ./db_bench --statistics=1 --benchmarks=fillseq --num=10000 --disable_auto_compactions=1 -write_buffer_size=100 --db=../db_bench Run:./db_bench --statistics=1 --benchmarks=compact --db=../db_bench --use_existing_db=1 rocksdb.sst.write.micros P50 : 2.675325 P95 : 9.578788 P99 : 18.780000 P100 : 314.000000 COUNT : 638 SUM : 3279 rocksdb.file.write.flush.micros P50 : 0.000000 P95 : 0.000000 P99 : 0.000000 P100 : 0.000000 COUNT : 0 SUM : 0 rocksdb.file.write.compaction.micros P50 : 2.757353 P95 : 9.610687 P99 : 19.316667 P100 : 314.000000 COUNT : 615 SUM : 3213 rocksdb.file.write.db.open.micros P50 : 2.055556 P95 : 3.925000 P99 : 9.000000 P100 : 9.000000 COUNT : 23 SUM : 66 ``` blob stats - just to make sure they aren't broken by this PR ``` Integrated Blob DB Setup: ./db_bench --enable_blob_files=1 --statistics=1 --benchmarks=fillseq --num=10000 --disable_auto_compactions=1 -write_buffer_size=100 --db=../db_bench Run:./db_bench --enable_blob_files=1 --statistics=1 --benchmarks=compact --db=../db_bench --use_existing_db=1 pre-PR: rocksdb.blobdb.blob.file.write.micros P50 : 7.298246 P95 : 9.771930 P99 : 9.991813 P100 : 16.000000 COUNT : 235 SUM : 1600 rocksdb.blobdb.blob.file.synced COUNT : 1 rocksdb.blobdb.blob.file.bytes.written COUNT : 34842 post-PR: rocksdb.blobdb.blob.file.write.micros P50 : 2.000000 P95 : 2.829360 P99 : 2.993779 P100 : 9.000000 COUNT : 707 SUM : 1614 - COUNT is higher and values are smaller as it includes header and footer write - COUNT is 3X higher due to each Append() count as one post-PR, while in pre-PR, 3 Append()s counts as one. See https://github.com/facebook/rocksdb/pull/11910/files#diff-32b811c0a1c000768cfb2532052b44dc0b3bf82253f3eab078e15ff201a0dabfL157-L164 rocksdb.blobdb.blob.file.synced COUNT : 1 (stay the same) rocksdb.blobdb.blob.file.bytes.written COUNT : 34842 (stay the same) ``` ``` Stacked Blob DB Run: ./db_bench --use_blob_db=1 --statistics=1 --benchmarks=fillseq --num=10000 --disable_auto_compactions=1 -write_buffer_size=100 --db=../db_bench pre-PR: rocksdb.blobdb.blob.file.write.micros P50 : 12.808042 P95 : 19.674497 P99 : 28.539683 P100 : 51.000000 COUNT : 10000 SUM : 140876 rocksdb.blobdb.blob.file.synced COUNT : 8 rocksdb.blobdb.blob.file.bytes.written COUNT : 1043445 post-PR: rocksdb.blobdb.blob.file.write.micros P50 : 1.657370 P95 : 2.952175 P99 : 3.877519 P100 : 24.000000 COUNT : 30001 SUM : 67924 - COUNT is higher and values are smaller as it includes header and footer write - COUNT is 3X higher due to each Append() count as one post-PR, while in pre-PR, 3 Append()s counts as one. See https://github.com/facebook/rocksdb/pull/11910/files#diff-32b811c0a1c000768cfb2532052b44dc0b3bf82253f3eab078e15ff201a0dabfL157-L164 rocksdb.blobdb.blob.file.synced COUNT : 8 (stay the same) rocksdb.blobdb.blob.file.bytes.written COUNT : 1043445 (stay the same) ``` ### Rehearsal CI stress test Trigger 3 full runs of all our CI stress tests ### Performance Flush ``` TEST_TMPDIR=/dev/shm ./db_basic_bench_pre_pr --benchmark_filter=ManualFlush/key_num:524288/per_key_size:256 --benchmark_repetitions=1000 -- default: 1 thread is used to run benchmark; enable_statistics = true Pre-pr: avg 507515519.3 ns 497686074,499444327,500862543,501389862,502994471,503744435,504142123,504224056,505724198,506610393,506837742,506955122,507695561,507929036,508307733,508312691,508999120,509963561,510142147,510698091,510743096,510769317,510957074,511053311,511371367,511409911,511432960,511642385,511691964,511730908, Post-pr: avg 511971266.5 ns, regressed 0.88% 502744835,506502498,507735420,507929724,508313335,509548582,509994942,510107257,510715603,511046955,511352639,511458478,512117521,512317380,512766303,512972652,513059586,513804934,513808980,514059409,514187369,514389494,514447762,514616464,514622882,514641763,514666265,514716377,514990179,515502408, ``` Compaction ``` TEST_TMPDIR=/dev/shm ./db_basic_bench_{pre|post}_pr --benchmark_filter=ManualCompaction/comp_style:0/max_data:134217728/per_key_size:256/enable_statistics:1 --benchmark_repetitions=1000 -- default: 1 thread is used to run benchmark Pre-pr: avg 495346098.30 ns 492118301,493203526,494201411,494336607,495269217,495404950,496402598,497012157,497358370,498153846 Post-pr: avg 504528077.20, regressed 1.85%. "ManualCompaction" include flush so the isolated regression for compaction should be around 1.85-0.88 = 0.97% 502465338,502485945,502541789,502909283,503438601,504143885,506113087,506629423,507160414,507393007 ``` Put with WAL (in case passing WriteOptions slows down this path even without collecting SST write stats) ``` TEST_TMPDIR=/dev/shm ./db_basic_bench_pre_pr --benchmark_filter=DBPut/comp_style:0/max_data:107374182400/per_key_size:256/enable_statistics:1/wal:1 --benchmark_repetitions=1000 -- default: 1 thread is used to run benchmark Pre-pr: avg 3848.10 ns 3814,3838,3839,3848,3854,3854,3854,3860,3860,3860 Post-pr: avg 3874.20 ns, regressed 0.68% 3863,3867,3871,3874,3875,3877,3877,3877,3880,3881 ``` Pull Request resolved: https://github.com/facebook/rocksdb/pull/11910 Reviewed By: ajkr Differential Revision: D49788060 Pulled By: hx235 fbshipit-source-id: 79e73699cda5be3b66461687e5147c2484fc5eff
2023-12-29 23:29:23 +00:00
Status s = file_writer_->Close(IOOptions());
if (!s.ok() && bg_status_.ok()) {
bg_status_ = s;
}
}
// Mutex to sync writes to file_writer, and all following
// class data members
port::Mutex mutex_;
// Indicates if logging is currently enabled
// atomic to allow reads without mutex
std::atomic<bool> activity_logging_enabled_;
// When reached, we will stop logging and close the file
// Value of 0 means unlimited
uint64_t max_logging_size_;
std::unique_ptr<WritableFileWriter> file_writer_;
Status bg_status_;
};
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
// SimCacheImpl definition
class SimCacheImpl : public SimCache {
public:
// capacity for real cache (ShardedLRUCache)
// test_capacity for key only cache
SimCacheImpl(std::shared_ptr<Cache> sim_cache, std::shared_ptr<Cache> cache)
: SimCache(cache),
key_only_cache_(sim_cache),
miss_times_(0),
utilities: Fix coverity issues Summary: ``` utilities/persistent_cache/block_cache_tier_file.cc 64struct CacheRecordHeader { 2. uninit_member: Non-static class member magic_ is not initialized in this constructor nor in any functions that it calls. 4. uninit_member: Non-static class member crc_ is not initialized in this constructor nor in any functions that it calls. 6. uninit_member: Non-static class member key_size_ is not initialized in this constructor nor in any functions that it calls. CID 1396161 (#1 of 1): Uninitialized scalar field (UNINIT_CTOR) 8. uninit_member: Non-static class member val_size_ is not initialized in this constructor nor in any functions that it calls. 65 CacheRecordHeader() {} 66 CacheRecordHeader(const uint32_t magic, const uint32_t key_size, 67 const uint32_t val_size) 68 : magic_(magic), crc_(0), key_size_(key_size), val_size_(val_size) {} 69 1. member_decl: Class member declaration for magic_. 70 uint32_t magic_; 3. member_decl: Class member declaration for crc_. 71 uint32_t crc_; 5. member_decl: Class member declaration for key_size_. 72 uint32_t key_size_; 7. member_decl: Class member declaration for val_size_. 73 uint32_t val_size_; 74}; utilities/simulator_cache/sim_cache.cc: 157 miss_times_(0), CID 1396124 (#1 of 1): Uninitialized pointer field (UNINIT_CTOR) 2. uninit_member: Non-static class member stats_ is not initialized in this constructor nor in any functions that it calls. 158 hit_times_(0) {} 159 ``` Closes https://github.com/facebook/rocksdb/pull/3155 Differential Revision: D6427237 Pulled By: sagar0 fbshipit-source-id: 97e493da5fc043c5b9a3e0d33103442cffb75aad
2017-11-28 21:15:20 +00:00
hit_times_(0),
stats_(nullptr) {}
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
~SimCacheImpl() override = default;
const char* Name() const override { return "SimCache"; }
void SetCapacity(size_t capacity) override { target_->SetCapacity(capacity); }
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
void SetStrictCapacityLimit(bool strict_capacity_limit) override {
target_->SetStrictCapacityLimit(strict_capacity_limit);
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
}
Major Cache refactoring, CPU efficiency improvement (#10975) Summary: This is several refactorings bundled into one to avoid having to incrementally re-modify uses of Cache several times. Overall, there are breaking changes to Cache class, and it becomes more of low-level interface for implementing caches, especially block cache. New internal APIs make using Cache cleaner than before, and more insulated from block cache evolution. Hopefully, this is the last really big block cache refactoring, because of rather effectively decoupling the implementations from the uses. This change also removes the EXPERIMENTAL designation on the SecondaryCache support in Cache. It seems reasonably mature at this point but still subject to change/evolution (as I warn in the API docs for Cache). The high-level motivation for this refactoring is to minimize code duplication / compounding complexity in adding SecondaryCache support to HyperClockCache (in a later PR). Other benefits listed below. * static_cast lines of code +29 -35 (net removed 6) * reinterpret_cast lines of code +6 -32 (net removed 26) ## cache.h and secondary_cache.h * Always use CacheItemHelper with entries instead of just a Deleter. There are several motivations / justifications: * Simpler for implementations to deal with just one Insert and one Lookup. * Simpler and more efficient implementation because we don't have to track which entries are using helpers and which are using deleters * Gets rid of hack to classify cache entries by their deleter. Instead, the CacheItemHelper includes a CacheEntryRole. This simplifies a lot of code (cache_entry_roles.h almost eliminated). Fixes https://github.com/facebook/rocksdb/issues/9428. * Makes it trivial to adjust SecondaryCache behavior based on kind of block (e.g. don't re-compress filter blocks). * It is arguably less convenient for many direct users of Cache, but direct users of Cache are now rare with introduction of typed_cache.h (below). * I considered and rejected an alternative approach in which we reduce customizability by assuming each secondary cache compatible value starts with a Slice referencing the uncompressed block contents (already true or mostly true), but we apparently intend to stack secondary caches. Saving an entry from a compressed secondary to a lower tier requires custom handling offered by SaveToCallback, etc. * Make CreateCallback part of the helper and introduce CreateContext to work with it (alternative to https://github.com/facebook/rocksdb/issues/10562). This cleans up the interface while still allowing context to be provided for loading/parsing values into primary cache. This model works for async lookup in BlockBasedTable reader (reader owns a CreateContext) under the assumption that it always waits on secondary cache operations to finish. (Otherwise, the CreateContext could be destroyed while async operation depending on it continues.) This likely contributes most to the observed performance improvement because it saves an std::function backed by a heap allocation. * Use char* for serialized data, e.g. in SaveToCallback, where void* was confusingly used. (We use `char*` for serialized byte data all over RocksDB, with many advantages over `void*`. `memcpy` etc. are legacy APIs that should not be mimicked.) * Add a type alias Cache::ObjectPtr = void*, so that we can better indicate the intent of the void* when it is to be the object associated with a Cache entry. Related: started (but did not complete) a refactoring to move away from "value" of a cache entry toward "object" or "obj". (It is confusing to call Cache a key-value store (like DB) when it is really storing arbitrary in-memory objects, not byte strings.) * Remove unnecessary key param from DeleterFn. This is good for efficiency in HyperClockCache, which does not directly store the cache key in memory. (Alternative to https://github.com/facebook/rocksdb/issues/10774) * Add allocator to Cache DeleterFn. This is a kind of future-proofing change in case we get more serious about using the Cache allocator for memory tracked by the Cache. Right now, only the uncompressed block contents are allocated using the allocator, and a pointer to that allocator is saved as part of the cached object so that the deleter can use it. (See CacheAllocationPtr.) If in the future we are able to "flatten out" our Cache objects some more, it would be good not to have to track the allocator as part of each object. * Removes legacy `ApplyToAllCacheEntries` and changes `ApplyToAllEntries` signature for Deleter->CacheItemHelper change. ## typed_cache.h Adds various "typed" interfaces to the Cache as internal APIs, so that most uses of Cache can use simple type safe code without casting and without explicit deleters, etc. Almost all of the non-test, non-glue code uses of Cache have been migrated. (Follow-up work: CompressedSecondaryCache deserves deeper attention to migrate.) This change expands RocksDB's internal usage of metaprogramming and SFINAE (https://en.cppreference.com/w/cpp/language/sfinae). The existing usages of Cache are divided up at a high level into these new interfaces. See updated existing uses of Cache for examples of how these are used. * PlaceholderCacheInterface - Used for making cache reservations, with entries that have a charge but no value. * BasicTypedCacheInterface<TValue> - Used for primary cache storage of objects of type TValue, which can be cleaned up with std::default_delete<TValue>. The role is provided by TValue::kCacheEntryRole or given in an optional template parameter. * FullTypedCacheInterface<TValue, TCreateContext> - Used for secondary cache compatible storage of objects of type TValue. In addition to BasicTypedCacheInterface constraints, we require TValue::ContentSlice() to return persistable data. This simplifies usage for the normal case of simple secondary cache compatibility (can give you a Slice to the data already in memory). In addition to TCreateContext performing the role of Cache::CreateContext, it is also expected to provide a factory function for creating TValue. * For each of these, there's a "Shared" version (e.g. FullTypedSharedCacheInterface) that holds a shared_ptr to the Cache, rather than assuming external ownership by holding only a raw `Cache*`. These interfaces introduce specific handle types for each interface instantiation, so that it's easy to see what kind of object is controlled by a handle. (Ultimately, this might not be worth the extra complexity, but it seems OK so far.) Note: I attempted to make the cache 'charge' automatically inferred from the cache object type, such as by expecting an ApproximateMemoryUsage() function, but this is not so clean because there are cases where we need to compute the charge ahead of time and don't want to re-compute it. ## block_cache.h This header is essentially the replacement for the old block_like_traits.h. It includes various things to support block cache access with typed_cache.h for block-based table. ## block_based_table_reader.cc Before this change, accessing the block cache here was an awkward mix of static polymorphism (template TBlocklike) and switch-case on a dynamic BlockType value. This change mostly unifies on static polymorphism, relying on minor hacks in block_cache.h to distinguish variants of Block. We still check BlockType in some places (especially for stats, which could be improved in follow-up work) but at least the BlockType is a static constant from the template parameter. (No more awkward partial redundancy between static and dynamic info.) This likely contributes to the overall performance improvement, but hasn't been tested in isolation. The other key source of simplification here is a more unified system of creating block cache objects: for directly populating from primary cache and for promotion from secondary cache. Both use BlockCreateContext, for context and for factory functions. ## block_based_table_builder.cc, cache_dump_load_impl.cc Before this change, warming caches was super ugly code. Both of these source files had switch statements to basically transition from the dynamic BlockType world to the static TBlocklike world. None of that mess is needed anymore as there's a new, untyped WarmInCache function that handles all the details just as promotion from SecondaryCache would. (Fixes `TODO akanksha: Dedup below code` in block_based_table_builder.cc.) ## Everything else Mostly just updating Cache users to use new typed APIs when reasonably possible, or changed Cache APIs when not. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10975 Test Plan: tests updated Performance test setup similar to https://github.com/facebook/rocksdb/issues/10626 (by cache size, LRUCache when not "hyper" for HyperClockCache): 34MB 1thread base.hyper -> kops/s: 0.745 io_bytes/op: 2.52504e+06 miss_ratio: 0.140906 max_rss_mb: 76.4844 34MB 1thread new.hyper -> kops/s: 0.751 io_bytes/op: 2.5123e+06 miss_ratio: 0.140161 max_rss_mb: 79.3594 34MB 1thread base -> kops/s: 0.254 io_bytes/op: 1.36073e+07 miss_ratio: 0.918818 max_rss_mb: 45.9297 34MB 1thread new -> kops/s: 0.252 io_bytes/op: 1.36157e+07 miss_ratio: 0.918999 max_rss_mb: 44.1523 34MB 32thread base.hyper -> kops/s: 7.272 io_bytes/op: 2.88323e+06 miss_ratio: 0.162532 max_rss_mb: 516.602 34MB 32thread new.hyper -> kops/s: 7.214 io_bytes/op: 2.99046e+06 miss_ratio: 0.168818 max_rss_mb: 518.293 34MB 32thread base -> kops/s: 3.528 io_bytes/op: 1.35722e+07 miss_ratio: 0.914691 max_rss_mb: 264.926 34MB 32thread new -> kops/s: 3.604 io_bytes/op: 1.35744e+07 miss_ratio: 0.915054 max_rss_mb: 264.488 233MB 1thread base.hyper -> kops/s: 53.909 io_bytes/op: 2552.35 miss_ratio: 0.0440566 max_rss_mb: 241.984 233MB 1thread new.hyper -> kops/s: 62.792 io_bytes/op: 2549.79 miss_ratio: 0.044043 max_rss_mb: 241.922 233MB 1thread base -> kops/s: 1.197 io_bytes/op: 2.75173e+06 miss_ratio: 0.103093 max_rss_mb: 241.559 233MB 1thread new -> kops/s: 1.199 io_bytes/op: 2.73723e+06 miss_ratio: 0.10305 max_rss_mb: 240.93 233MB 32thread base.hyper -> kops/s: 1298.69 io_bytes/op: 2539.12 miss_ratio: 0.0440307 max_rss_mb: 371.418 233MB 32thread new.hyper -> kops/s: 1421.35 io_bytes/op: 2538.75 miss_ratio: 0.0440307 max_rss_mb: 347.273 233MB 32thread base -> kops/s: 9.693 io_bytes/op: 2.77304e+06 miss_ratio: 0.103745 max_rss_mb: 569.691 233MB 32thread new -> kops/s: 9.75 io_bytes/op: 2.77559e+06 miss_ratio: 0.103798 max_rss_mb: 552.82 1597MB 1thread base.hyper -> kops/s: 58.607 io_bytes/op: 1449.14 miss_ratio: 0.0249324 max_rss_mb: 1583.55 1597MB 1thread new.hyper -> kops/s: 69.6 io_bytes/op: 1434.89 miss_ratio: 0.0247167 max_rss_mb: 1584.02 1597MB 1thread base -> kops/s: 60.478 io_bytes/op: 1421.28 miss_ratio: 0.024452 max_rss_mb: 1589.45 1597MB 1thread new -> kops/s: 63.973 io_bytes/op: 1416.07 miss_ratio: 0.0243766 max_rss_mb: 1589.24 1597MB 32thread base.hyper -> kops/s: 1436.2 io_bytes/op: 1357.93 miss_ratio: 0.0235353 max_rss_mb: 1692.92 1597MB 32thread new.hyper -> kops/s: 1605.03 io_bytes/op: 1358.04 miss_ratio: 0.023538 max_rss_mb: 1702.78 1597MB 32thread base -> kops/s: 280.059 io_bytes/op: 1350.34 miss_ratio: 0.023289 max_rss_mb: 1675.36 1597MB 32thread new -> kops/s: 283.125 io_bytes/op: 1351.05 miss_ratio: 0.0232797 max_rss_mb: 1703.83 Almost uniformly improving over base revision, especially for hot paths with HyperClockCache, up to 12% higher throughput seen (1597MB, 32thread, hyper). The improvement for that is likely coming from much simplified code for providing context for secondary cache promotion (CreateCallback/CreateContext), and possibly from less branching in block_based_table_reader. And likely a small improvement from not reconstituting key for DeleterFn. Reviewed By: anand1976 Differential Revision: D42417818 Pulled By: pdillinger fbshipit-source-id: f86bfdd584dce27c028b151ba56818ad14f7a432
2023-01-11 22:20:40 +00:00
Status Insert(const Slice& key, Cache::ObjectPtr value,
const CacheItemHelper* helper, size_t charge, Handle** handle,
Support compressed and local flash secondary cache stacking (#11812) Summary: This PR implements support for a three tier cache - primary block cache, compressed secondary cache, and a nvm (local flash) secondary cache. This allows more effective utilization of the nvm cache, and minimizes the number of reads from local flash by caching compressed blocks in the compressed secondary cache. The basic design is as follows - 1. A new secondary cache implementation, ```TieredSecondaryCache```, is introduced. It keeps the compressed and nvm secondary caches and manages the movement of blocks between them and the primary block cache. To setup a three tier cache, we allocate a ```CacheWithSecondaryAdapter```, with a ```TieredSecondaryCache``` instance as the secondary cache. 2. The table reader passes both the uncompressed and compressed block to ```FullTypedCacheInterface::InsertFull```, allowing the block cache to optionally store the compressed block. 3. When there's a miss, the block object is constructed and inserted in the primary cache, and the compressed block is inserted into the nvm cache by calling ```InsertSaved```. This avoids the overhead of recompressing the block, as well as avoiding putting more memory pressure on the compressed secondary cache. 4. When there's a hit in the nvm cache, we attempt to insert the block in the compressed secondary cache and the primary cache, subject to the admission policy of those caches (i.e admit on second access). Blocks/items evicted from any tier are simply discarded. We can easily implement additional admission policies if desired. Todo (In a subsequent PR): 1. Add to db_bench and run benchmarks 2. Add to db_stress Pull Request resolved: https://github.com/facebook/rocksdb/pull/11812 Reviewed By: pdillinger Differential Revision: D49461842 Pulled By: anand1976 fbshipit-source-id: b40ac1330ef7cd8c12efa0a3ca75128e602e3a0b
2023-09-22 03:30:53 +00:00
Priority priority, const Slice& compressed = {},
CompressionType type = kNoCompression) override {
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
// The handle and value passed in are for real cache, so we pass nullptr
// to key_only_cache_ for both instead. Also, the deleter function pointer
// will be called by user to perform some external operation which should
// be applied only once. Thus key_only_cache accepts an empty function.
// *Lambda function without capture can be assgined to a function pointer
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
Handle* h = key_only_cache_->Lookup(key);
if (h == nullptr) {
// TODO: Check for error here?
Support compressed and local flash secondary cache stacking (#11812) Summary: This PR implements support for a three tier cache - primary block cache, compressed secondary cache, and a nvm (local flash) secondary cache. This allows more effective utilization of the nvm cache, and minimizes the number of reads from local flash by caching compressed blocks in the compressed secondary cache. The basic design is as follows - 1. A new secondary cache implementation, ```TieredSecondaryCache```, is introduced. It keeps the compressed and nvm secondary caches and manages the movement of blocks between them and the primary block cache. To setup a three tier cache, we allocate a ```CacheWithSecondaryAdapter```, with a ```TieredSecondaryCache``` instance as the secondary cache. 2. The table reader passes both the uncompressed and compressed block to ```FullTypedCacheInterface::InsertFull```, allowing the block cache to optionally store the compressed block. 3. When there's a miss, the block object is constructed and inserted in the primary cache, and the compressed block is inserted into the nvm cache by calling ```InsertSaved```. This avoids the overhead of recompressing the block, as well as avoiding putting more memory pressure on the compressed secondary cache. 4. When there's a hit in the nvm cache, we attempt to insert the block in the compressed secondary cache and the primary cache, subject to the admission policy of those caches (i.e admit on second access). Blocks/items evicted from any tier are simply discarded. We can easily implement additional admission policies if desired. Todo (In a subsequent PR): 1. Add to db_bench and run benchmarks 2. Add to db_stress Pull Request resolved: https://github.com/facebook/rocksdb/pull/11812 Reviewed By: pdillinger Differential Revision: D49461842 Pulled By: anand1976 fbshipit-source-id: b40ac1330ef7cd8c12efa0a3ca75128e602e3a0b
2023-09-22 03:30:53 +00:00
auto s =
key_only_cache_->Insert(key, nullptr, &kNoopCacheItemHelper, charge,
nullptr, priority, compressed, type);
s.PermitUncheckedError();
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
} else {
key_only_cache_->Release(h);
}
cache_activity_logger_.ReportAdd(key, charge);
if (!target_) {
return Status::OK();
}
Support compressed and local flash secondary cache stacking (#11812) Summary: This PR implements support for a three tier cache - primary block cache, compressed secondary cache, and a nvm (local flash) secondary cache. This allows more effective utilization of the nvm cache, and minimizes the number of reads from local flash by caching compressed blocks in the compressed secondary cache. The basic design is as follows - 1. A new secondary cache implementation, ```TieredSecondaryCache```, is introduced. It keeps the compressed and nvm secondary caches and manages the movement of blocks between them and the primary block cache. To setup a three tier cache, we allocate a ```CacheWithSecondaryAdapter```, with a ```TieredSecondaryCache``` instance as the secondary cache. 2. The table reader passes both the uncompressed and compressed block to ```FullTypedCacheInterface::InsertFull```, allowing the block cache to optionally store the compressed block. 3. When there's a miss, the block object is constructed and inserted in the primary cache, and the compressed block is inserted into the nvm cache by calling ```InsertSaved```. This avoids the overhead of recompressing the block, as well as avoiding putting more memory pressure on the compressed secondary cache. 4. When there's a hit in the nvm cache, we attempt to insert the block in the compressed secondary cache and the primary cache, subject to the admission policy of those caches (i.e admit on second access). Blocks/items evicted from any tier are simply discarded. We can easily implement additional admission policies if desired. Todo (In a subsequent PR): 1. Add to db_bench and run benchmarks 2. Add to db_stress Pull Request resolved: https://github.com/facebook/rocksdb/pull/11812 Reviewed By: pdillinger Differential Revision: D49461842 Pulled By: anand1976 fbshipit-source-id: b40ac1330ef7cd8c12efa0a3ca75128e602e3a0b
2023-09-22 03:30:53 +00:00
return target_->Insert(key, value, helper, charge, handle, priority,
compressed, type);
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
}
Major Cache refactoring, CPU efficiency improvement (#10975) Summary: This is several refactorings bundled into one to avoid having to incrementally re-modify uses of Cache several times. Overall, there are breaking changes to Cache class, and it becomes more of low-level interface for implementing caches, especially block cache. New internal APIs make using Cache cleaner than before, and more insulated from block cache evolution. Hopefully, this is the last really big block cache refactoring, because of rather effectively decoupling the implementations from the uses. This change also removes the EXPERIMENTAL designation on the SecondaryCache support in Cache. It seems reasonably mature at this point but still subject to change/evolution (as I warn in the API docs for Cache). The high-level motivation for this refactoring is to minimize code duplication / compounding complexity in adding SecondaryCache support to HyperClockCache (in a later PR). Other benefits listed below. * static_cast lines of code +29 -35 (net removed 6) * reinterpret_cast lines of code +6 -32 (net removed 26) ## cache.h and secondary_cache.h * Always use CacheItemHelper with entries instead of just a Deleter. There are several motivations / justifications: * Simpler for implementations to deal with just one Insert and one Lookup. * Simpler and more efficient implementation because we don't have to track which entries are using helpers and which are using deleters * Gets rid of hack to classify cache entries by their deleter. Instead, the CacheItemHelper includes a CacheEntryRole. This simplifies a lot of code (cache_entry_roles.h almost eliminated). Fixes https://github.com/facebook/rocksdb/issues/9428. * Makes it trivial to adjust SecondaryCache behavior based on kind of block (e.g. don't re-compress filter blocks). * It is arguably less convenient for many direct users of Cache, but direct users of Cache are now rare with introduction of typed_cache.h (below). * I considered and rejected an alternative approach in which we reduce customizability by assuming each secondary cache compatible value starts with a Slice referencing the uncompressed block contents (already true or mostly true), but we apparently intend to stack secondary caches. Saving an entry from a compressed secondary to a lower tier requires custom handling offered by SaveToCallback, etc. * Make CreateCallback part of the helper and introduce CreateContext to work with it (alternative to https://github.com/facebook/rocksdb/issues/10562). This cleans up the interface while still allowing context to be provided for loading/parsing values into primary cache. This model works for async lookup in BlockBasedTable reader (reader owns a CreateContext) under the assumption that it always waits on secondary cache operations to finish. (Otherwise, the CreateContext could be destroyed while async operation depending on it continues.) This likely contributes most to the observed performance improvement because it saves an std::function backed by a heap allocation. * Use char* for serialized data, e.g. in SaveToCallback, where void* was confusingly used. (We use `char*` for serialized byte data all over RocksDB, with many advantages over `void*`. `memcpy` etc. are legacy APIs that should not be mimicked.) * Add a type alias Cache::ObjectPtr = void*, so that we can better indicate the intent of the void* when it is to be the object associated with a Cache entry. Related: started (but did not complete) a refactoring to move away from "value" of a cache entry toward "object" or "obj". (It is confusing to call Cache a key-value store (like DB) when it is really storing arbitrary in-memory objects, not byte strings.) * Remove unnecessary key param from DeleterFn. This is good for efficiency in HyperClockCache, which does not directly store the cache key in memory. (Alternative to https://github.com/facebook/rocksdb/issues/10774) * Add allocator to Cache DeleterFn. This is a kind of future-proofing change in case we get more serious about using the Cache allocator for memory tracked by the Cache. Right now, only the uncompressed block contents are allocated using the allocator, and a pointer to that allocator is saved as part of the cached object so that the deleter can use it. (See CacheAllocationPtr.) If in the future we are able to "flatten out" our Cache objects some more, it would be good not to have to track the allocator as part of each object. * Removes legacy `ApplyToAllCacheEntries` and changes `ApplyToAllEntries` signature for Deleter->CacheItemHelper change. ## typed_cache.h Adds various "typed" interfaces to the Cache as internal APIs, so that most uses of Cache can use simple type safe code without casting and without explicit deleters, etc. Almost all of the non-test, non-glue code uses of Cache have been migrated. (Follow-up work: CompressedSecondaryCache deserves deeper attention to migrate.) This change expands RocksDB's internal usage of metaprogramming and SFINAE (https://en.cppreference.com/w/cpp/language/sfinae). The existing usages of Cache are divided up at a high level into these new interfaces. See updated existing uses of Cache for examples of how these are used. * PlaceholderCacheInterface - Used for making cache reservations, with entries that have a charge but no value. * BasicTypedCacheInterface<TValue> - Used for primary cache storage of objects of type TValue, which can be cleaned up with std::default_delete<TValue>. The role is provided by TValue::kCacheEntryRole or given in an optional template parameter. * FullTypedCacheInterface<TValue, TCreateContext> - Used for secondary cache compatible storage of objects of type TValue. In addition to BasicTypedCacheInterface constraints, we require TValue::ContentSlice() to return persistable data. This simplifies usage for the normal case of simple secondary cache compatibility (can give you a Slice to the data already in memory). In addition to TCreateContext performing the role of Cache::CreateContext, it is also expected to provide a factory function for creating TValue. * For each of these, there's a "Shared" version (e.g. FullTypedSharedCacheInterface) that holds a shared_ptr to the Cache, rather than assuming external ownership by holding only a raw `Cache*`. These interfaces introduce specific handle types for each interface instantiation, so that it's easy to see what kind of object is controlled by a handle. (Ultimately, this might not be worth the extra complexity, but it seems OK so far.) Note: I attempted to make the cache 'charge' automatically inferred from the cache object type, such as by expecting an ApproximateMemoryUsage() function, but this is not so clean because there are cases where we need to compute the charge ahead of time and don't want to re-compute it. ## block_cache.h This header is essentially the replacement for the old block_like_traits.h. It includes various things to support block cache access with typed_cache.h for block-based table. ## block_based_table_reader.cc Before this change, accessing the block cache here was an awkward mix of static polymorphism (template TBlocklike) and switch-case on a dynamic BlockType value. This change mostly unifies on static polymorphism, relying on minor hacks in block_cache.h to distinguish variants of Block. We still check BlockType in some places (especially for stats, which could be improved in follow-up work) but at least the BlockType is a static constant from the template parameter. (No more awkward partial redundancy between static and dynamic info.) This likely contributes to the overall performance improvement, but hasn't been tested in isolation. The other key source of simplification here is a more unified system of creating block cache objects: for directly populating from primary cache and for promotion from secondary cache. Both use BlockCreateContext, for context and for factory functions. ## block_based_table_builder.cc, cache_dump_load_impl.cc Before this change, warming caches was super ugly code. Both of these source files had switch statements to basically transition from the dynamic BlockType world to the static TBlocklike world. None of that mess is needed anymore as there's a new, untyped WarmInCache function that handles all the details just as promotion from SecondaryCache would. (Fixes `TODO akanksha: Dedup below code` in block_based_table_builder.cc.) ## Everything else Mostly just updating Cache users to use new typed APIs when reasonably possible, or changed Cache APIs when not. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10975 Test Plan: tests updated Performance test setup similar to https://github.com/facebook/rocksdb/issues/10626 (by cache size, LRUCache when not "hyper" for HyperClockCache): 34MB 1thread base.hyper -> kops/s: 0.745 io_bytes/op: 2.52504e+06 miss_ratio: 0.140906 max_rss_mb: 76.4844 34MB 1thread new.hyper -> kops/s: 0.751 io_bytes/op: 2.5123e+06 miss_ratio: 0.140161 max_rss_mb: 79.3594 34MB 1thread base -> kops/s: 0.254 io_bytes/op: 1.36073e+07 miss_ratio: 0.918818 max_rss_mb: 45.9297 34MB 1thread new -> kops/s: 0.252 io_bytes/op: 1.36157e+07 miss_ratio: 0.918999 max_rss_mb: 44.1523 34MB 32thread base.hyper -> kops/s: 7.272 io_bytes/op: 2.88323e+06 miss_ratio: 0.162532 max_rss_mb: 516.602 34MB 32thread new.hyper -> kops/s: 7.214 io_bytes/op: 2.99046e+06 miss_ratio: 0.168818 max_rss_mb: 518.293 34MB 32thread base -> kops/s: 3.528 io_bytes/op: 1.35722e+07 miss_ratio: 0.914691 max_rss_mb: 264.926 34MB 32thread new -> kops/s: 3.604 io_bytes/op: 1.35744e+07 miss_ratio: 0.915054 max_rss_mb: 264.488 233MB 1thread base.hyper -> kops/s: 53.909 io_bytes/op: 2552.35 miss_ratio: 0.0440566 max_rss_mb: 241.984 233MB 1thread new.hyper -> kops/s: 62.792 io_bytes/op: 2549.79 miss_ratio: 0.044043 max_rss_mb: 241.922 233MB 1thread base -> kops/s: 1.197 io_bytes/op: 2.75173e+06 miss_ratio: 0.103093 max_rss_mb: 241.559 233MB 1thread new -> kops/s: 1.199 io_bytes/op: 2.73723e+06 miss_ratio: 0.10305 max_rss_mb: 240.93 233MB 32thread base.hyper -> kops/s: 1298.69 io_bytes/op: 2539.12 miss_ratio: 0.0440307 max_rss_mb: 371.418 233MB 32thread new.hyper -> kops/s: 1421.35 io_bytes/op: 2538.75 miss_ratio: 0.0440307 max_rss_mb: 347.273 233MB 32thread base -> kops/s: 9.693 io_bytes/op: 2.77304e+06 miss_ratio: 0.103745 max_rss_mb: 569.691 233MB 32thread new -> kops/s: 9.75 io_bytes/op: 2.77559e+06 miss_ratio: 0.103798 max_rss_mb: 552.82 1597MB 1thread base.hyper -> kops/s: 58.607 io_bytes/op: 1449.14 miss_ratio: 0.0249324 max_rss_mb: 1583.55 1597MB 1thread new.hyper -> kops/s: 69.6 io_bytes/op: 1434.89 miss_ratio: 0.0247167 max_rss_mb: 1584.02 1597MB 1thread base -> kops/s: 60.478 io_bytes/op: 1421.28 miss_ratio: 0.024452 max_rss_mb: 1589.45 1597MB 1thread new -> kops/s: 63.973 io_bytes/op: 1416.07 miss_ratio: 0.0243766 max_rss_mb: 1589.24 1597MB 32thread base.hyper -> kops/s: 1436.2 io_bytes/op: 1357.93 miss_ratio: 0.0235353 max_rss_mb: 1692.92 1597MB 32thread new.hyper -> kops/s: 1605.03 io_bytes/op: 1358.04 miss_ratio: 0.023538 max_rss_mb: 1702.78 1597MB 32thread base -> kops/s: 280.059 io_bytes/op: 1350.34 miss_ratio: 0.023289 max_rss_mb: 1675.36 1597MB 32thread new -> kops/s: 283.125 io_bytes/op: 1351.05 miss_ratio: 0.0232797 max_rss_mb: 1703.83 Almost uniformly improving over base revision, especially for hot paths with HyperClockCache, up to 12% higher throughput seen (1597MB, 32thread, hyper). The improvement for that is likely coming from much simplified code for providing context for secondary cache promotion (CreateCallback/CreateContext), and possibly from less branching in block_based_table_reader. And likely a small improvement from not reconstituting key for DeleterFn. Reviewed By: anand1976 Differential Revision: D42417818 Pulled By: pdillinger fbshipit-source-id: f86bfdd584dce27c028b151ba56818ad14f7a432
2023-01-11 22:20:40 +00:00
Handle* Lookup(const Slice& key, const CacheItemHelper* helper,
CreateContext* create_context,
HyperClockCache support for SecondaryCache, with refactoring (#11301) Summary: Internally refactors SecondaryCache integration out of LRUCache specifically and into a wrapper/adapter class that works with various Cache implementations. Notably, this relies on separating the notion of async lookup handles from other cache handles, so that HyperClockCache doesn't have to deal with the problem of allocating handles from the hash table for lookups that might fail anyway, and might be on the same key without support for coalescing. (LRUCache's hash table can incorporate previously allocated handles thanks to its pointer indirection.) Specifically, I'm worried about the case in which hundreds of threads try to access the same block and probing in the hash table degrades to linear search on the pile of entries with the same key. This change is a big step in the direction of supporting stacked SecondaryCaches, but there are obstacles to completing that. Especially, there is no SecondaryCache hook for evictions to pass from one to the next. It has been proposed that evictions be transmitted simply as the persisted data (as in SaveToCallback), but given the current structure provided by the CacheItemHelpers, that would require an extra copy of the block data, because there's intentionally no way to ask for a contiguous Slice of the data (to allow for flexibility in storage). `AsyncLookupHandle` and the re-worked `WaitAll()` should be essentially prepared for stacked SecondaryCaches, but several "TODO with stacked secondaries" issues remain in various places. It could be argued that the stacking instead be done as a SecondaryCache adapter that wraps two (or more) SecondaryCaches, but at least with the current API that would require an extra heap allocation on SecondaryCache Lookup for a wrapper SecondaryCacheResultHandle that can transfer a Lookup between secondaries. We could also consider trying to unify the Cache and SecondaryCache APIs, though that might be difficult if `AsyncLookupHandle` is kept a fixed struct. ## cache.h (public API) Moves `secondary_cache` option from LRUCacheOptions to ShardedCacheOptions so that it is applicable to HyperClockCache. ## advanced_cache.h (advanced public API) * Add `Cache::CreateStandalone()` so that the SecondaryCache support wrapper can use it. * Add `SetEvictionCallback()` / `eviction_callback_` so that the SecondaryCache support wrapper can use it. Only a single callback is supported for efficiency. If there is ever a need for more than one, hopefully that can be handled with a broadcast callback wrapper. These are essentially the two "extra" pieces of `Cache` for pulling out specific SecondaryCache support from the `Cache` implementation. I think it's a good trade-off as these are reasonable, limited, and reusable "cut points" into the `Cache` implementations. * Remove async capability from standard `Lookup()` (getting rid of awkward restrictions on pending Handles) and add `AsyncLookupHandle` and `StartAsyncLookup()`. As noted in the comments, the full struct of `AsyncLookupHandle` is exposed so that it can be stack allocated, for efficiency, though more data is being copied around than before, which could impact performance. (Lookup info -> AsyncLookupHandle -> Handle vs. Lookup info -> Handle) I could foresee a future in which a Cache internally saves a pointer to the AsyncLookupHandle, which means it's dangerous to allow it to be copyable or even movable. It also means it's not compatible with std::vector (which I don't like requiring as an API parameter anyway), so `WaitAll()` expects any contiguous array of AsyncLookupHandles. I believe this is best for common case efficiency, while behaving well in other cases also. For example, `WaitAll()` has no effect on default-constructed AsyncLookupHandles, which look like a completed cache miss. ## cacheable_entry.h A couple of functions are obsolete because Cache::Handle can no longer be pending. ## cache.cc Provides default implementations for new or revamped Cache functions, especially appropriate for non-blocking caches. ## secondary_cache_adapter.{h,cc} The full details of the Cache wrapper adding SecondaryCache support. Essentially replicates the SecondaryCache handling that was in LRUCache, but obviously refactored. There is a bit of logic duplication, where Lookup() is essentially a manually optimized version of StartAsyncLookup() and Wait(), but it's roughly a dozen lines of code. ## sharded_cache.h, typed_cache.h, charged_cache.{h,cc}, sim_cache.cc Simply updated for Cache API changes. ## lru_cache.{h,cc} Carefully remove SecondaryCache logic, implement `CreateStandalone` and eviction handler functionality. ## clock_cache.{h,cc} Expose existing `CreateStandalone` functionality, add eviction handler functionality. Light refactoring. ## block_based_table_reader* Mostly re-worked the only usage of async Lookup, which is in BlockBasedTable::MultiGet. Used arrays in place of autovector in some places for efficiency. Simplified some logic by not trying to process some cache results before they're all ready. Created new function `BlockBasedTable::GetCachePriority()` to reduce some pre-existing code duplication (and avoid making it worse). Fixed at least one small bug from the prior confusing mixture of async and sync Lookups. In MaybeReadBlockAndLoadToCache(), called by RetrieveBlock(), called by MultiGet() with wait=false, is_cache_hit for the block_cache_tracer entry would not be set to true if the handle was pending after Lookup and before Wait. ## Intended follow-up work * Figure out if there are any missing stats or block_cache_tracer work in refactored BlockBasedTable::MultiGet * Stacked secondary caches (see above discussion) * See if we can make up for the small MultiGet performance regression. * Study more performance with SecondaryCache * Items evicted from over-full LRUCache in Release were not being demoted to SecondaryCache, and still aren't to minimize unit test churn. Ideally they would be demoted, but it's an exceptional case so not a big deal. * Use CreateStandalone for cache reservations (save unnecessary hash table operations). Not a big deal, but worthy cleanup. * Somehow I got the contract for SecondaryCache::Insert wrong in #10945. (Doesn't take ownership!) That API comment needs to be fixed, but didn't want to mingle that in here. Pull Request resolved: https://github.com/facebook/rocksdb/pull/11301 Test Plan: ## Unit tests Generally updated to include HCC in SecondaryCache tests, though HyperClockCache has some different, less strict behaviors that leads to some tests not really being set up to work with it. Some of the tests remain disabled with it, but I think we have good coverage without them. ## Crash/stress test Updated to use the new combination. ## Performance First, let's check for regression on caches without secondary cache configured. Adding support for the eviction callback is likely to have a tiny effect, but it shouldn't be worrisome. LRUCache could benefit slightly from less logic around SecondaryCache handling. We can test with cache_bench default settings, built with DEBUG_LEVEL=0 and PORTABLE=0. ``` (while :; do base/cache_bench --cache_type=hyper_clock_cache | grep Rough; done) | awk '{ sum += $9; count++; print $0; print "Average: " int(sum / count) }' ``` **Before** this and #11299 (which could also have a small effect), running for about an hour, before & after running concurrently for each cache type: HyperClockCache: 3168662 (average parallel ops/sec) LRUCache: 2940127 **After** this and #11299, running for about an hour: HyperClockCache: 3164862 (average parallel ops/sec) (0.12% slower) LRUCache: 2940928 (0.03% faster) This is an acceptable difference IMHO. Next, let's consider essentially the worst case of new CPU overhead affecting overall performance. MultiGet uses the async lookup interface regardless of whether SecondaryCache or folly are used. We can configure a benchmark where all block cache queries are for data blocks, and all are hits. Create DB and test (before and after tests running simultaneously): ``` TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=fillrandom -num=30000000 -disable_wal=1 -bloom_bits=16 TEST_TMPDIR=/dev/shm base/db_bench -benchmarks=multireadrandom[-X30] -readonly -multiread_batched -batch_size=32 -num=30000000 -bloom_bits=16 -cache_size=6789000000 -duration 20 -threads=16 ``` **Before**: multireadrandom [AVG 30 runs] : 3444202 (± 57049) ops/sec; 240.9 (± 4.0) MB/sec multireadrandom [MEDIAN 30 runs] : 3514443 ops/sec; 245.8 MB/sec **After**: multireadrandom [AVG 30 runs] : 3291022 (± 58851) ops/sec; 230.2 (± 4.1) MB/sec multireadrandom [MEDIAN 30 runs] : 3366179 ops/sec; 235.4 MB/sec So that's roughly a 3% regression, on kind of a *worst case* test of MultiGet CPU. Similar story with HyperClockCache: **Before**: multireadrandom [AVG 30 runs] : 3933777 (± 41840) ops/sec; 275.1 (± 2.9) MB/sec multireadrandom [MEDIAN 30 runs] : 3970667 ops/sec; 277.7 MB/sec **After**: multireadrandom [AVG 30 runs] : 3755338 (± 30391) ops/sec; 262.6 (± 2.1) MB/sec multireadrandom [MEDIAN 30 runs] : 3785696 ops/sec; 264.8 MB/sec Roughly a 4-5% regression. Not ideal, but not the whole story, fortunately. Let's also look at Get() in db_bench: ``` TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=readrandom[-X30] -readonly -num=30000000 -bloom_bits=16 -cache_size=6789000000 -duration 20 -threads=16 ``` **Before**: readrandom [AVG 30 runs] : 2198685 (± 13412) ops/sec; 153.8 (± 0.9) MB/sec readrandom [MEDIAN 30 runs] : 2209498 ops/sec; 154.5 MB/sec **After**: readrandom [AVG 30 runs] : 2292814 (± 43508) ops/sec; 160.3 (± 3.0) MB/sec readrandom [MEDIAN 30 runs] : 2365181 ops/sec; 165.4 MB/sec That's showing roughly a 4% improvement, perhaps because of the secondary cache code that is no longer part of LRUCache. But weirdly, HyperClockCache is also showing 2-3% improvement: **Before**: readrandom [AVG 30 runs] : 2272333 (± 9992) ops/sec; 158.9 (± 0.7) MB/sec readrandom [MEDIAN 30 runs] : 2273239 ops/sec; 159.0 MB/sec **After**: readrandom [AVG 30 runs] : 2332407 (± 11252) ops/sec; 163.1 (± 0.8) MB/sec readrandom [MEDIAN 30 runs] : 2335329 ops/sec; 163.3 MB/sec Reviewed By: ltamasi Differential Revision: D44177044 Pulled By: pdillinger fbshipit-source-id: e808e48ff3fe2f792a79841ba617be98e48689f5
2023-03-18 03:23:49 +00:00
Priority priority = Priority::LOW,
Major Cache refactoring, CPU efficiency improvement (#10975) Summary: This is several refactorings bundled into one to avoid having to incrementally re-modify uses of Cache several times. Overall, there are breaking changes to Cache class, and it becomes more of low-level interface for implementing caches, especially block cache. New internal APIs make using Cache cleaner than before, and more insulated from block cache evolution. Hopefully, this is the last really big block cache refactoring, because of rather effectively decoupling the implementations from the uses. This change also removes the EXPERIMENTAL designation on the SecondaryCache support in Cache. It seems reasonably mature at this point but still subject to change/evolution (as I warn in the API docs for Cache). The high-level motivation for this refactoring is to minimize code duplication / compounding complexity in adding SecondaryCache support to HyperClockCache (in a later PR). Other benefits listed below. * static_cast lines of code +29 -35 (net removed 6) * reinterpret_cast lines of code +6 -32 (net removed 26) ## cache.h and secondary_cache.h * Always use CacheItemHelper with entries instead of just a Deleter. There are several motivations / justifications: * Simpler for implementations to deal with just one Insert and one Lookup. * Simpler and more efficient implementation because we don't have to track which entries are using helpers and which are using deleters * Gets rid of hack to classify cache entries by their deleter. Instead, the CacheItemHelper includes a CacheEntryRole. This simplifies a lot of code (cache_entry_roles.h almost eliminated). Fixes https://github.com/facebook/rocksdb/issues/9428. * Makes it trivial to adjust SecondaryCache behavior based on kind of block (e.g. don't re-compress filter blocks). * It is arguably less convenient for many direct users of Cache, but direct users of Cache are now rare with introduction of typed_cache.h (below). * I considered and rejected an alternative approach in which we reduce customizability by assuming each secondary cache compatible value starts with a Slice referencing the uncompressed block contents (already true or mostly true), but we apparently intend to stack secondary caches. Saving an entry from a compressed secondary to a lower tier requires custom handling offered by SaveToCallback, etc. * Make CreateCallback part of the helper and introduce CreateContext to work with it (alternative to https://github.com/facebook/rocksdb/issues/10562). This cleans up the interface while still allowing context to be provided for loading/parsing values into primary cache. This model works for async lookup in BlockBasedTable reader (reader owns a CreateContext) under the assumption that it always waits on secondary cache operations to finish. (Otherwise, the CreateContext could be destroyed while async operation depending on it continues.) This likely contributes most to the observed performance improvement because it saves an std::function backed by a heap allocation. * Use char* for serialized data, e.g. in SaveToCallback, where void* was confusingly used. (We use `char*` for serialized byte data all over RocksDB, with many advantages over `void*`. `memcpy` etc. are legacy APIs that should not be mimicked.) * Add a type alias Cache::ObjectPtr = void*, so that we can better indicate the intent of the void* when it is to be the object associated with a Cache entry. Related: started (but did not complete) a refactoring to move away from "value" of a cache entry toward "object" or "obj". (It is confusing to call Cache a key-value store (like DB) when it is really storing arbitrary in-memory objects, not byte strings.) * Remove unnecessary key param from DeleterFn. This is good for efficiency in HyperClockCache, which does not directly store the cache key in memory. (Alternative to https://github.com/facebook/rocksdb/issues/10774) * Add allocator to Cache DeleterFn. This is a kind of future-proofing change in case we get more serious about using the Cache allocator for memory tracked by the Cache. Right now, only the uncompressed block contents are allocated using the allocator, and a pointer to that allocator is saved as part of the cached object so that the deleter can use it. (See CacheAllocationPtr.) If in the future we are able to "flatten out" our Cache objects some more, it would be good not to have to track the allocator as part of each object. * Removes legacy `ApplyToAllCacheEntries` and changes `ApplyToAllEntries` signature for Deleter->CacheItemHelper change. ## typed_cache.h Adds various "typed" interfaces to the Cache as internal APIs, so that most uses of Cache can use simple type safe code without casting and without explicit deleters, etc. Almost all of the non-test, non-glue code uses of Cache have been migrated. (Follow-up work: CompressedSecondaryCache deserves deeper attention to migrate.) This change expands RocksDB's internal usage of metaprogramming and SFINAE (https://en.cppreference.com/w/cpp/language/sfinae). The existing usages of Cache are divided up at a high level into these new interfaces. See updated existing uses of Cache for examples of how these are used. * PlaceholderCacheInterface - Used for making cache reservations, with entries that have a charge but no value. * BasicTypedCacheInterface<TValue> - Used for primary cache storage of objects of type TValue, which can be cleaned up with std::default_delete<TValue>. The role is provided by TValue::kCacheEntryRole or given in an optional template parameter. * FullTypedCacheInterface<TValue, TCreateContext> - Used for secondary cache compatible storage of objects of type TValue. In addition to BasicTypedCacheInterface constraints, we require TValue::ContentSlice() to return persistable data. This simplifies usage for the normal case of simple secondary cache compatibility (can give you a Slice to the data already in memory). In addition to TCreateContext performing the role of Cache::CreateContext, it is also expected to provide a factory function for creating TValue. * For each of these, there's a "Shared" version (e.g. FullTypedSharedCacheInterface) that holds a shared_ptr to the Cache, rather than assuming external ownership by holding only a raw `Cache*`. These interfaces introduce specific handle types for each interface instantiation, so that it's easy to see what kind of object is controlled by a handle. (Ultimately, this might not be worth the extra complexity, but it seems OK so far.) Note: I attempted to make the cache 'charge' automatically inferred from the cache object type, such as by expecting an ApproximateMemoryUsage() function, but this is not so clean because there are cases where we need to compute the charge ahead of time and don't want to re-compute it. ## block_cache.h This header is essentially the replacement for the old block_like_traits.h. It includes various things to support block cache access with typed_cache.h for block-based table. ## block_based_table_reader.cc Before this change, accessing the block cache here was an awkward mix of static polymorphism (template TBlocklike) and switch-case on a dynamic BlockType value. This change mostly unifies on static polymorphism, relying on minor hacks in block_cache.h to distinguish variants of Block. We still check BlockType in some places (especially for stats, which could be improved in follow-up work) but at least the BlockType is a static constant from the template parameter. (No more awkward partial redundancy between static and dynamic info.) This likely contributes to the overall performance improvement, but hasn't been tested in isolation. The other key source of simplification here is a more unified system of creating block cache objects: for directly populating from primary cache and for promotion from secondary cache. Both use BlockCreateContext, for context and for factory functions. ## block_based_table_builder.cc, cache_dump_load_impl.cc Before this change, warming caches was super ugly code. Both of these source files had switch statements to basically transition from the dynamic BlockType world to the static TBlocklike world. None of that mess is needed anymore as there's a new, untyped WarmInCache function that handles all the details just as promotion from SecondaryCache would. (Fixes `TODO akanksha: Dedup below code` in block_based_table_builder.cc.) ## Everything else Mostly just updating Cache users to use new typed APIs when reasonably possible, or changed Cache APIs when not. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10975 Test Plan: tests updated Performance test setup similar to https://github.com/facebook/rocksdb/issues/10626 (by cache size, LRUCache when not "hyper" for HyperClockCache): 34MB 1thread base.hyper -> kops/s: 0.745 io_bytes/op: 2.52504e+06 miss_ratio: 0.140906 max_rss_mb: 76.4844 34MB 1thread new.hyper -> kops/s: 0.751 io_bytes/op: 2.5123e+06 miss_ratio: 0.140161 max_rss_mb: 79.3594 34MB 1thread base -> kops/s: 0.254 io_bytes/op: 1.36073e+07 miss_ratio: 0.918818 max_rss_mb: 45.9297 34MB 1thread new -> kops/s: 0.252 io_bytes/op: 1.36157e+07 miss_ratio: 0.918999 max_rss_mb: 44.1523 34MB 32thread base.hyper -> kops/s: 7.272 io_bytes/op: 2.88323e+06 miss_ratio: 0.162532 max_rss_mb: 516.602 34MB 32thread new.hyper -> kops/s: 7.214 io_bytes/op: 2.99046e+06 miss_ratio: 0.168818 max_rss_mb: 518.293 34MB 32thread base -> kops/s: 3.528 io_bytes/op: 1.35722e+07 miss_ratio: 0.914691 max_rss_mb: 264.926 34MB 32thread new -> kops/s: 3.604 io_bytes/op: 1.35744e+07 miss_ratio: 0.915054 max_rss_mb: 264.488 233MB 1thread base.hyper -> kops/s: 53.909 io_bytes/op: 2552.35 miss_ratio: 0.0440566 max_rss_mb: 241.984 233MB 1thread new.hyper -> kops/s: 62.792 io_bytes/op: 2549.79 miss_ratio: 0.044043 max_rss_mb: 241.922 233MB 1thread base -> kops/s: 1.197 io_bytes/op: 2.75173e+06 miss_ratio: 0.103093 max_rss_mb: 241.559 233MB 1thread new -> kops/s: 1.199 io_bytes/op: 2.73723e+06 miss_ratio: 0.10305 max_rss_mb: 240.93 233MB 32thread base.hyper -> kops/s: 1298.69 io_bytes/op: 2539.12 miss_ratio: 0.0440307 max_rss_mb: 371.418 233MB 32thread new.hyper -> kops/s: 1421.35 io_bytes/op: 2538.75 miss_ratio: 0.0440307 max_rss_mb: 347.273 233MB 32thread base -> kops/s: 9.693 io_bytes/op: 2.77304e+06 miss_ratio: 0.103745 max_rss_mb: 569.691 233MB 32thread new -> kops/s: 9.75 io_bytes/op: 2.77559e+06 miss_ratio: 0.103798 max_rss_mb: 552.82 1597MB 1thread base.hyper -> kops/s: 58.607 io_bytes/op: 1449.14 miss_ratio: 0.0249324 max_rss_mb: 1583.55 1597MB 1thread new.hyper -> kops/s: 69.6 io_bytes/op: 1434.89 miss_ratio: 0.0247167 max_rss_mb: 1584.02 1597MB 1thread base -> kops/s: 60.478 io_bytes/op: 1421.28 miss_ratio: 0.024452 max_rss_mb: 1589.45 1597MB 1thread new -> kops/s: 63.973 io_bytes/op: 1416.07 miss_ratio: 0.0243766 max_rss_mb: 1589.24 1597MB 32thread base.hyper -> kops/s: 1436.2 io_bytes/op: 1357.93 miss_ratio: 0.0235353 max_rss_mb: 1692.92 1597MB 32thread new.hyper -> kops/s: 1605.03 io_bytes/op: 1358.04 miss_ratio: 0.023538 max_rss_mb: 1702.78 1597MB 32thread base -> kops/s: 280.059 io_bytes/op: 1350.34 miss_ratio: 0.023289 max_rss_mb: 1675.36 1597MB 32thread new -> kops/s: 283.125 io_bytes/op: 1351.05 miss_ratio: 0.0232797 max_rss_mb: 1703.83 Almost uniformly improving over base revision, especially for hot paths with HyperClockCache, up to 12% higher throughput seen (1597MB, 32thread, hyper). The improvement for that is likely coming from much simplified code for providing context for secondary cache promotion (CreateCallback/CreateContext), and possibly from less branching in block_based_table_reader. And likely a small improvement from not reconstituting key for DeleterFn. Reviewed By: anand1976 Differential Revision: D42417818 Pulled By: pdillinger fbshipit-source-id: f86bfdd584dce27c028b151ba56818ad14f7a432
2023-01-11 22:20:40 +00:00
Statistics* stats = nullptr) override {
HandleLookup(key, stats);
if (!target_) {
return nullptr;
}
HyperClockCache support for SecondaryCache, with refactoring (#11301) Summary: Internally refactors SecondaryCache integration out of LRUCache specifically and into a wrapper/adapter class that works with various Cache implementations. Notably, this relies on separating the notion of async lookup handles from other cache handles, so that HyperClockCache doesn't have to deal with the problem of allocating handles from the hash table for lookups that might fail anyway, and might be on the same key without support for coalescing. (LRUCache's hash table can incorporate previously allocated handles thanks to its pointer indirection.) Specifically, I'm worried about the case in which hundreds of threads try to access the same block and probing in the hash table degrades to linear search on the pile of entries with the same key. This change is a big step in the direction of supporting stacked SecondaryCaches, but there are obstacles to completing that. Especially, there is no SecondaryCache hook for evictions to pass from one to the next. It has been proposed that evictions be transmitted simply as the persisted data (as in SaveToCallback), but given the current structure provided by the CacheItemHelpers, that would require an extra copy of the block data, because there's intentionally no way to ask for a contiguous Slice of the data (to allow for flexibility in storage). `AsyncLookupHandle` and the re-worked `WaitAll()` should be essentially prepared for stacked SecondaryCaches, but several "TODO with stacked secondaries" issues remain in various places. It could be argued that the stacking instead be done as a SecondaryCache adapter that wraps two (or more) SecondaryCaches, but at least with the current API that would require an extra heap allocation on SecondaryCache Lookup for a wrapper SecondaryCacheResultHandle that can transfer a Lookup between secondaries. We could also consider trying to unify the Cache and SecondaryCache APIs, though that might be difficult if `AsyncLookupHandle` is kept a fixed struct. ## cache.h (public API) Moves `secondary_cache` option from LRUCacheOptions to ShardedCacheOptions so that it is applicable to HyperClockCache. ## advanced_cache.h (advanced public API) * Add `Cache::CreateStandalone()` so that the SecondaryCache support wrapper can use it. * Add `SetEvictionCallback()` / `eviction_callback_` so that the SecondaryCache support wrapper can use it. Only a single callback is supported for efficiency. If there is ever a need for more than one, hopefully that can be handled with a broadcast callback wrapper. These are essentially the two "extra" pieces of `Cache` for pulling out specific SecondaryCache support from the `Cache` implementation. I think it's a good trade-off as these are reasonable, limited, and reusable "cut points" into the `Cache` implementations. * Remove async capability from standard `Lookup()` (getting rid of awkward restrictions on pending Handles) and add `AsyncLookupHandle` and `StartAsyncLookup()`. As noted in the comments, the full struct of `AsyncLookupHandle` is exposed so that it can be stack allocated, for efficiency, though more data is being copied around than before, which could impact performance. (Lookup info -> AsyncLookupHandle -> Handle vs. Lookup info -> Handle) I could foresee a future in which a Cache internally saves a pointer to the AsyncLookupHandle, which means it's dangerous to allow it to be copyable or even movable. It also means it's not compatible with std::vector (which I don't like requiring as an API parameter anyway), so `WaitAll()` expects any contiguous array of AsyncLookupHandles. I believe this is best for common case efficiency, while behaving well in other cases also. For example, `WaitAll()` has no effect on default-constructed AsyncLookupHandles, which look like a completed cache miss. ## cacheable_entry.h A couple of functions are obsolete because Cache::Handle can no longer be pending. ## cache.cc Provides default implementations for new or revamped Cache functions, especially appropriate for non-blocking caches. ## secondary_cache_adapter.{h,cc} The full details of the Cache wrapper adding SecondaryCache support. Essentially replicates the SecondaryCache handling that was in LRUCache, but obviously refactored. There is a bit of logic duplication, where Lookup() is essentially a manually optimized version of StartAsyncLookup() and Wait(), but it's roughly a dozen lines of code. ## sharded_cache.h, typed_cache.h, charged_cache.{h,cc}, sim_cache.cc Simply updated for Cache API changes. ## lru_cache.{h,cc} Carefully remove SecondaryCache logic, implement `CreateStandalone` and eviction handler functionality. ## clock_cache.{h,cc} Expose existing `CreateStandalone` functionality, add eviction handler functionality. Light refactoring. ## block_based_table_reader* Mostly re-worked the only usage of async Lookup, which is in BlockBasedTable::MultiGet. Used arrays in place of autovector in some places for efficiency. Simplified some logic by not trying to process some cache results before they're all ready. Created new function `BlockBasedTable::GetCachePriority()` to reduce some pre-existing code duplication (and avoid making it worse). Fixed at least one small bug from the prior confusing mixture of async and sync Lookups. In MaybeReadBlockAndLoadToCache(), called by RetrieveBlock(), called by MultiGet() with wait=false, is_cache_hit for the block_cache_tracer entry would not be set to true if the handle was pending after Lookup and before Wait. ## Intended follow-up work * Figure out if there are any missing stats or block_cache_tracer work in refactored BlockBasedTable::MultiGet * Stacked secondary caches (see above discussion) * See if we can make up for the small MultiGet performance regression. * Study more performance with SecondaryCache * Items evicted from over-full LRUCache in Release were not being demoted to SecondaryCache, and still aren't to minimize unit test churn. Ideally they would be demoted, but it's an exceptional case so not a big deal. * Use CreateStandalone for cache reservations (save unnecessary hash table operations). Not a big deal, but worthy cleanup. * Somehow I got the contract for SecondaryCache::Insert wrong in #10945. (Doesn't take ownership!) That API comment needs to be fixed, but didn't want to mingle that in here. Pull Request resolved: https://github.com/facebook/rocksdb/pull/11301 Test Plan: ## Unit tests Generally updated to include HCC in SecondaryCache tests, though HyperClockCache has some different, less strict behaviors that leads to some tests not really being set up to work with it. Some of the tests remain disabled with it, but I think we have good coverage without them. ## Crash/stress test Updated to use the new combination. ## Performance First, let's check for regression on caches without secondary cache configured. Adding support for the eviction callback is likely to have a tiny effect, but it shouldn't be worrisome. LRUCache could benefit slightly from less logic around SecondaryCache handling. We can test with cache_bench default settings, built with DEBUG_LEVEL=0 and PORTABLE=0. ``` (while :; do base/cache_bench --cache_type=hyper_clock_cache | grep Rough; done) | awk '{ sum += $9; count++; print $0; print "Average: " int(sum / count) }' ``` **Before** this and #11299 (which could also have a small effect), running for about an hour, before & after running concurrently for each cache type: HyperClockCache: 3168662 (average parallel ops/sec) LRUCache: 2940127 **After** this and #11299, running for about an hour: HyperClockCache: 3164862 (average parallel ops/sec) (0.12% slower) LRUCache: 2940928 (0.03% faster) This is an acceptable difference IMHO. Next, let's consider essentially the worst case of new CPU overhead affecting overall performance. MultiGet uses the async lookup interface regardless of whether SecondaryCache or folly are used. We can configure a benchmark where all block cache queries are for data blocks, and all are hits. Create DB and test (before and after tests running simultaneously): ``` TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=fillrandom -num=30000000 -disable_wal=1 -bloom_bits=16 TEST_TMPDIR=/dev/shm base/db_bench -benchmarks=multireadrandom[-X30] -readonly -multiread_batched -batch_size=32 -num=30000000 -bloom_bits=16 -cache_size=6789000000 -duration 20 -threads=16 ``` **Before**: multireadrandom [AVG 30 runs] : 3444202 (± 57049) ops/sec; 240.9 (± 4.0) MB/sec multireadrandom [MEDIAN 30 runs] : 3514443 ops/sec; 245.8 MB/sec **After**: multireadrandom [AVG 30 runs] : 3291022 (± 58851) ops/sec; 230.2 (± 4.1) MB/sec multireadrandom [MEDIAN 30 runs] : 3366179 ops/sec; 235.4 MB/sec So that's roughly a 3% regression, on kind of a *worst case* test of MultiGet CPU. Similar story with HyperClockCache: **Before**: multireadrandom [AVG 30 runs] : 3933777 (± 41840) ops/sec; 275.1 (± 2.9) MB/sec multireadrandom [MEDIAN 30 runs] : 3970667 ops/sec; 277.7 MB/sec **After**: multireadrandom [AVG 30 runs] : 3755338 (± 30391) ops/sec; 262.6 (± 2.1) MB/sec multireadrandom [MEDIAN 30 runs] : 3785696 ops/sec; 264.8 MB/sec Roughly a 4-5% regression. Not ideal, but not the whole story, fortunately. Let's also look at Get() in db_bench: ``` TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=readrandom[-X30] -readonly -num=30000000 -bloom_bits=16 -cache_size=6789000000 -duration 20 -threads=16 ``` **Before**: readrandom [AVG 30 runs] : 2198685 (± 13412) ops/sec; 153.8 (± 0.9) MB/sec readrandom [MEDIAN 30 runs] : 2209498 ops/sec; 154.5 MB/sec **After**: readrandom [AVG 30 runs] : 2292814 (± 43508) ops/sec; 160.3 (± 3.0) MB/sec readrandom [MEDIAN 30 runs] : 2365181 ops/sec; 165.4 MB/sec That's showing roughly a 4% improvement, perhaps because of the secondary cache code that is no longer part of LRUCache. But weirdly, HyperClockCache is also showing 2-3% improvement: **Before**: readrandom [AVG 30 runs] : 2272333 (± 9992) ops/sec; 158.9 (± 0.7) MB/sec readrandom [MEDIAN 30 runs] : 2273239 ops/sec; 159.0 MB/sec **After**: readrandom [AVG 30 runs] : 2332407 (± 11252) ops/sec; 163.1 (± 0.8) MB/sec readrandom [MEDIAN 30 runs] : 2335329 ops/sec; 163.3 MB/sec Reviewed By: ltamasi Differential Revision: D44177044 Pulled By: pdillinger fbshipit-source-id: e808e48ff3fe2f792a79841ba617be98e48689f5
2023-03-18 03:23:49 +00:00
return target_->Lookup(key, helper, create_context, priority, stats);
}
void StartAsyncLookup(AsyncLookupHandle& async_handle) override {
HandleLookup(async_handle.key, async_handle.stats);
if (target_) {
target_->StartAsyncLookup(async_handle);
}
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
}
bool Ref(Handle* handle) override { return target_->Ref(handle); }
Initial support for secondary cache in LRUCache (#8271) Summary: Defined the abstract interface for a secondary cache in include/rocksdb/secondary_cache.h, and updated LRUCacheOptions to take a std::shared_ptr<SecondaryCache>. An item is initially inserted into the LRU (primary) cache. When it ages out and evicted from memory, its inserted into the secondary cache. On a LRU cache miss and successful lookup in the secondary cache, the item is promoted to the LRU cache. Only support synchronous lookup currently. The secondary cache would be used to implement a persistent (flash cache) or compressed cache. Tests: Results from cache_bench and db_bench don't show any regression due to these changes. cache_bench results before and after this change - Command ```./cache_bench -ops_per_thread=10000000 -threads=1``` Before ```Complete in 40.688 s; QPS = 245774``` ```Complete in 40.486 s; QPS = 246996``` ```Complete in 42.019 s; QPS = 237989``` After ```Complete in 40.672 s; QPS = 245869``` ```Complete in 44.622 s; QPS = 224107``` ```Complete in 42.445 s; QPS = 235599``` db_bench results before this change, and with this change + https://github.com/facebook/rocksdb/issues/8213 and https://github.com/facebook/rocksdb/issues/8191 - Commands ```./db_bench --benchmarks="fillseq,compact" -num=30000000 -key_size=32 -value_size=256 -use_direct_io_for_flush_and_compaction=true -db=/home/anand76/nvm_cache/db -partition_index_and_filters=true``` ```./db_bench -db=/home/anand76/nvm_cache/db -use_existing_db=true -benchmarks=readrandom -num=30000000 -key_size=32 -value_size=256 -use_direct_reads=true -cache_size=1073741824 -cache_numshardbits=6 -cache_index_and_filter_blocks=true -read_random_exp_range=17 -statistics -partition_index_and_filters=true -threads=16 -duration=300``` Before ``` DB path: [/home/anand76/nvm_cache/db] readrandom : 80.702 micros/op 198104 ops/sec; 54.4 MB/s (3708999 of 3708999 found) ``` ``` DB path: [/home/anand76/nvm_cache/db] readrandom : 87.124 micros/op 183625 ops/sec; 50.4 MB/s (3439999 of 3439999 found) ``` After ``` DB path: [/home/anand76/nvm_cache/db] readrandom : 77.653 micros/op 206025 ops/sec; 56.6 MB/s (3866999 of 3866999 found) ``` ``` DB path: [/home/anand76/nvm_cache/db] readrandom : 84.962 micros/op 188299 ops/sec; 51.7 MB/s (3535999 of 3535999 found) ``` Pull Request resolved: https://github.com/facebook/rocksdb/pull/8271 Reviewed By: zhichao-cao Differential Revision: D28357511 Pulled By: anand1976 fbshipit-source-id: d1cfa236f00e649a18c53328be10a8062a4b6da2
2021-05-14 05:57:51 +00:00
using Cache::Release;
bool Release(Handle* handle, bool erase_if_last_ref = false) override {
return target_->Release(handle, erase_if_last_ref);
}
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
void Erase(const Slice& key) override {
target_->Erase(key);
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
key_only_cache_->Erase(key);
}
Major Cache refactoring, CPU efficiency improvement (#10975) Summary: This is several refactorings bundled into one to avoid having to incrementally re-modify uses of Cache several times. Overall, there are breaking changes to Cache class, and it becomes more of low-level interface for implementing caches, especially block cache. New internal APIs make using Cache cleaner than before, and more insulated from block cache evolution. Hopefully, this is the last really big block cache refactoring, because of rather effectively decoupling the implementations from the uses. This change also removes the EXPERIMENTAL designation on the SecondaryCache support in Cache. It seems reasonably mature at this point but still subject to change/evolution (as I warn in the API docs for Cache). The high-level motivation for this refactoring is to minimize code duplication / compounding complexity in adding SecondaryCache support to HyperClockCache (in a later PR). Other benefits listed below. * static_cast lines of code +29 -35 (net removed 6) * reinterpret_cast lines of code +6 -32 (net removed 26) ## cache.h and secondary_cache.h * Always use CacheItemHelper with entries instead of just a Deleter. There are several motivations / justifications: * Simpler for implementations to deal with just one Insert and one Lookup. * Simpler and more efficient implementation because we don't have to track which entries are using helpers and which are using deleters * Gets rid of hack to classify cache entries by their deleter. Instead, the CacheItemHelper includes a CacheEntryRole. This simplifies a lot of code (cache_entry_roles.h almost eliminated). Fixes https://github.com/facebook/rocksdb/issues/9428. * Makes it trivial to adjust SecondaryCache behavior based on kind of block (e.g. don't re-compress filter blocks). * It is arguably less convenient for many direct users of Cache, but direct users of Cache are now rare with introduction of typed_cache.h (below). * I considered and rejected an alternative approach in which we reduce customizability by assuming each secondary cache compatible value starts with a Slice referencing the uncompressed block contents (already true or mostly true), but we apparently intend to stack secondary caches. Saving an entry from a compressed secondary to a lower tier requires custom handling offered by SaveToCallback, etc. * Make CreateCallback part of the helper and introduce CreateContext to work with it (alternative to https://github.com/facebook/rocksdb/issues/10562). This cleans up the interface while still allowing context to be provided for loading/parsing values into primary cache. This model works for async lookup in BlockBasedTable reader (reader owns a CreateContext) under the assumption that it always waits on secondary cache operations to finish. (Otherwise, the CreateContext could be destroyed while async operation depending on it continues.) This likely contributes most to the observed performance improvement because it saves an std::function backed by a heap allocation. * Use char* for serialized data, e.g. in SaveToCallback, where void* was confusingly used. (We use `char*` for serialized byte data all over RocksDB, with many advantages over `void*`. `memcpy` etc. are legacy APIs that should not be mimicked.) * Add a type alias Cache::ObjectPtr = void*, so that we can better indicate the intent of the void* when it is to be the object associated with a Cache entry. Related: started (but did not complete) a refactoring to move away from "value" of a cache entry toward "object" or "obj". (It is confusing to call Cache a key-value store (like DB) when it is really storing arbitrary in-memory objects, not byte strings.) * Remove unnecessary key param from DeleterFn. This is good for efficiency in HyperClockCache, which does not directly store the cache key in memory. (Alternative to https://github.com/facebook/rocksdb/issues/10774) * Add allocator to Cache DeleterFn. This is a kind of future-proofing change in case we get more serious about using the Cache allocator for memory tracked by the Cache. Right now, only the uncompressed block contents are allocated using the allocator, and a pointer to that allocator is saved as part of the cached object so that the deleter can use it. (See CacheAllocationPtr.) If in the future we are able to "flatten out" our Cache objects some more, it would be good not to have to track the allocator as part of each object. * Removes legacy `ApplyToAllCacheEntries` and changes `ApplyToAllEntries` signature for Deleter->CacheItemHelper change. ## typed_cache.h Adds various "typed" interfaces to the Cache as internal APIs, so that most uses of Cache can use simple type safe code without casting and without explicit deleters, etc. Almost all of the non-test, non-glue code uses of Cache have been migrated. (Follow-up work: CompressedSecondaryCache deserves deeper attention to migrate.) This change expands RocksDB's internal usage of metaprogramming and SFINAE (https://en.cppreference.com/w/cpp/language/sfinae). The existing usages of Cache are divided up at a high level into these new interfaces. See updated existing uses of Cache for examples of how these are used. * PlaceholderCacheInterface - Used for making cache reservations, with entries that have a charge but no value. * BasicTypedCacheInterface<TValue> - Used for primary cache storage of objects of type TValue, which can be cleaned up with std::default_delete<TValue>. The role is provided by TValue::kCacheEntryRole or given in an optional template parameter. * FullTypedCacheInterface<TValue, TCreateContext> - Used for secondary cache compatible storage of objects of type TValue. In addition to BasicTypedCacheInterface constraints, we require TValue::ContentSlice() to return persistable data. This simplifies usage for the normal case of simple secondary cache compatibility (can give you a Slice to the data already in memory). In addition to TCreateContext performing the role of Cache::CreateContext, it is also expected to provide a factory function for creating TValue. * For each of these, there's a "Shared" version (e.g. FullTypedSharedCacheInterface) that holds a shared_ptr to the Cache, rather than assuming external ownership by holding only a raw `Cache*`. These interfaces introduce specific handle types for each interface instantiation, so that it's easy to see what kind of object is controlled by a handle. (Ultimately, this might not be worth the extra complexity, but it seems OK so far.) Note: I attempted to make the cache 'charge' automatically inferred from the cache object type, such as by expecting an ApproximateMemoryUsage() function, but this is not so clean because there are cases where we need to compute the charge ahead of time and don't want to re-compute it. ## block_cache.h This header is essentially the replacement for the old block_like_traits.h. It includes various things to support block cache access with typed_cache.h for block-based table. ## block_based_table_reader.cc Before this change, accessing the block cache here was an awkward mix of static polymorphism (template TBlocklike) and switch-case on a dynamic BlockType value. This change mostly unifies on static polymorphism, relying on minor hacks in block_cache.h to distinguish variants of Block. We still check BlockType in some places (especially for stats, which could be improved in follow-up work) but at least the BlockType is a static constant from the template parameter. (No more awkward partial redundancy between static and dynamic info.) This likely contributes to the overall performance improvement, but hasn't been tested in isolation. The other key source of simplification here is a more unified system of creating block cache objects: for directly populating from primary cache and for promotion from secondary cache. Both use BlockCreateContext, for context and for factory functions. ## block_based_table_builder.cc, cache_dump_load_impl.cc Before this change, warming caches was super ugly code. Both of these source files had switch statements to basically transition from the dynamic BlockType world to the static TBlocklike world. None of that mess is needed anymore as there's a new, untyped WarmInCache function that handles all the details just as promotion from SecondaryCache would. (Fixes `TODO akanksha: Dedup below code` in block_based_table_builder.cc.) ## Everything else Mostly just updating Cache users to use new typed APIs when reasonably possible, or changed Cache APIs when not. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10975 Test Plan: tests updated Performance test setup similar to https://github.com/facebook/rocksdb/issues/10626 (by cache size, LRUCache when not "hyper" for HyperClockCache): 34MB 1thread base.hyper -> kops/s: 0.745 io_bytes/op: 2.52504e+06 miss_ratio: 0.140906 max_rss_mb: 76.4844 34MB 1thread new.hyper -> kops/s: 0.751 io_bytes/op: 2.5123e+06 miss_ratio: 0.140161 max_rss_mb: 79.3594 34MB 1thread base -> kops/s: 0.254 io_bytes/op: 1.36073e+07 miss_ratio: 0.918818 max_rss_mb: 45.9297 34MB 1thread new -> kops/s: 0.252 io_bytes/op: 1.36157e+07 miss_ratio: 0.918999 max_rss_mb: 44.1523 34MB 32thread base.hyper -> kops/s: 7.272 io_bytes/op: 2.88323e+06 miss_ratio: 0.162532 max_rss_mb: 516.602 34MB 32thread new.hyper -> kops/s: 7.214 io_bytes/op: 2.99046e+06 miss_ratio: 0.168818 max_rss_mb: 518.293 34MB 32thread base -> kops/s: 3.528 io_bytes/op: 1.35722e+07 miss_ratio: 0.914691 max_rss_mb: 264.926 34MB 32thread new -> kops/s: 3.604 io_bytes/op: 1.35744e+07 miss_ratio: 0.915054 max_rss_mb: 264.488 233MB 1thread base.hyper -> kops/s: 53.909 io_bytes/op: 2552.35 miss_ratio: 0.0440566 max_rss_mb: 241.984 233MB 1thread new.hyper -> kops/s: 62.792 io_bytes/op: 2549.79 miss_ratio: 0.044043 max_rss_mb: 241.922 233MB 1thread base -> kops/s: 1.197 io_bytes/op: 2.75173e+06 miss_ratio: 0.103093 max_rss_mb: 241.559 233MB 1thread new -> kops/s: 1.199 io_bytes/op: 2.73723e+06 miss_ratio: 0.10305 max_rss_mb: 240.93 233MB 32thread base.hyper -> kops/s: 1298.69 io_bytes/op: 2539.12 miss_ratio: 0.0440307 max_rss_mb: 371.418 233MB 32thread new.hyper -> kops/s: 1421.35 io_bytes/op: 2538.75 miss_ratio: 0.0440307 max_rss_mb: 347.273 233MB 32thread base -> kops/s: 9.693 io_bytes/op: 2.77304e+06 miss_ratio: 0.103745 max_rss_mb: 569.691 233MB 32thread new -> kops/s: 9.75 io_bytes/op: 2.77559e+06 miss_ratio: 0.103798 max_rss_mb: 552.82 1597MB 1thread base.hyper -> kops/s: 58.607 io_bytes/op: 1449.14 miss_ratio: 0.0249324 max_rss_mb: 1583.55 1597MB 1thread new.hyper -> kops/s: 69.6 io_bytes/op: 1434.89 miss_ratio: 0.0247167 max_rss_mb: 1584.02 1597MB 1thread base -> kops/s: 60.478 io_bytes/op: 1421.28 miss_ratio: 0.024452 max_rss_mb: 1589.45 1597MB 1thread new -> kops/s: 63.973 io_bytes/op: 1416.07 miss_ratio: 0.0243766 max_rss_mb: 1589.24 1597MB 32thread base.hyper -> kops/s: 1436.2 io_bytes/op: 1357.93 miss_ratio: 0.0235353 max_rss_mb: 1692.92 1597MB 32thread new.hyper -> kops/s: 1605.03 io_bytes/op: 1358.04 miss_ratio: 0.023538 max_rss_mb: 1702.78 1597MB 32thread base -> kops/s: 280.059 io_bytes/op: 1350.34 miss_ratio: 0.023289 max_rss_mb: 1675.36 1597MB 32thread new -> kops/s: 283.125 io_bytes/op: 1351.05 miss_ratio: 0.0232797 max_rss_mb: 1703.83 Almost uniformly improving over base revision, especially for hot paths with HyperClockCache, up to 12% higher throughput seen (1597MB, 32thread, hyper). The improvement for that is likely coming from much simplified code for providing context for secondary cache promotion (CreateCallback/CreateContext), and possibly from less branching in block_based_table_reader. And likely a small improvement from not reconstituting key for DeleterFn. Reviewed By: anand1976 Differential Revision: D42417818 Pulled By: pdillinger fbshipit-source-id: f86bfdd584dce27c028b151ba56818ad14f7a432
2023-01-11 22:20:40 +00:00
Cache::ObjectPtr Value(Handle* handle) override {
return target_->Value(handle);
Major Cache refactoring, CPU efficiency improvement (#10975) Summary: This is several refactorings bundled into one to avoid having to incrementally re-modify uses of Cache several times. Overall, there are breaking changes to Cache class, and it becomes more of low-level interface for implementing caches, especially block cache. New internal APIs make using Cache cleaner than before, and more insulated from block cache evolution. Hopefully, this is the last really big block cache refactoring, because of rather effectively decoupling the implementations from the uses. This change also removes the EXPERIMENTAL designation on the SecondaryCache support in Cache. It seems reasonably mature at this point but still subject to change/evolution (as I warn in the API docs for Cache). The high-level motivation for this refactoring is to minimize code duplication / compounding complexity in adding SecondaryCache support to HyperClockCache (in a later PR). Other benefits listed below. * static_cast lines of code +29 -35 (net removed 6) * reinterpret_cast lines of code +6 -32 (net removed 26) ## cache.h and secondary_cache.h * Always use CacheItemHelper with entries instead of just a Deleter. There are several motivations / justifications: * Simpler for implementations to deal with just one Insert and one Lookup. * Simpler and more efficient implementation because we don't have to track which entries are using helpers and which are using deleters * Gets rid of hack to classify cache entries by their deleter. Instead, the CacheItemHelper includes a CacheEntryRole. This simplifies a lot of code (cache_entry_roles.h almost eliminated). Fixes https://github.com/facebook/rocksdb/issues/9428. * Makes it trivial to adjust SecondaryCache behavior based on kind of block (e.g. don't re-compress filter blocks). * It is arguably less convenient for many direct users of Cache, but direct users of Cache are now rare with introduction of typed_cache.h (below). * I considered and rejected an alternative approach in which we reduce customizability by assuming each secondary cache compatible value starts with a Slice referencing the uncompressed block contents (already true or mostly true), but we apparently intend to stack secondary caches. Saving an entry from a compressed secondary to a lower tier requires custom handling offered by SaveToCallback, etc. * Make CreateCallback part of the helper and introduce CreateContext to work with it (alternative to https://github.com/facebook/rocksdb/issues/10562). This cleans up the interface while still allowing context to be provided for loading/parsing values into primary cache. This model works for async lookup in BlockBasedTable reader (reader owns a CreateContext) under the assumption that it always waits on secondary cache operations to finish. (Otherwise, the CreateContext could be destroyed while async operation depending on it continues.) This likely contributes most to the observed performance improvement because it saves an std::function backed by a heap allocation. * Use char* for serialized data, e.g. in SaveToCallback, where void* was confusingly used. (We use `char*` for serialized byte data all over RocksDB, with many advantages over `void*`. `memcpy` etc. are legacy APIs that should not be mimicked.) * Add a type alias Cache::ObjectPtr = void*, so that we can better indicate the intent of the void* when it is to be the object associated with a Cache entry. Related: started (but did not complete) a refactoring to move away from "value" of a cache entry toward "object" or "obj". (It is confusing to call Cache a key-value store (like DB) when it is really storing arbitrary in-memory objects, not byte strings.) * Remove unnecessary key param from DeleterFn. This is good for efficiency in HyperClockCache, which does not directly store the cache key in memory. (Alternative to https://github.com/facebook/rocksdb/issues/10774) * Add allocator to Cache DeleterFn. This is a kind of future-proofing change in case we get more serious about using the Cache allocator for memory tracked by the Cache. Right now, only the uncompressed block contents are allocated using the allocator, and a pointer to that allocator is saved as part of the cached object so that the deleter can use it. (See CacheAllocationPtr.) If in the future we are able to "flatten out" our Cache objects some more, it would be good not to have to track the allocator as part of each object. * Removes legacy `ApplyToAllCacheEntries` and changes `ApplyToAllEntries` signature for Deleter->CacheItemHelper change. ## typed_cache.h Adds various "typed" interfaces to the Cache as internal APIs, so that most uses of Cache can use simple type safe code without casting and without explicit deleters, etc. Almost all of the non-test, non-glue code uses of Cache have been migrated. (Follow-up work: CompressedSecondaryCache deserves deeper attention to migrate.) This change expands RocksDB's internal usage of metaprogramming and SFINAE (https://en.cppreference.com/w/cpp/language/sfinae). The existing usages of Cache are divided up at a high level into these new interfaces. See updated existing uses of Cache for examples of how these are used. * PlaceholderCacheInterface - Used for making cache reservations, with entries that have a charge but no value. * BasicTypedCacheInterface<TValue> - Used for primary cache storage of objects of type TValue, which can be cleaned up with std::default_delete<TValue>. The role is provided by TValue::kCacheEntryRole or given in an optional template parameter. * FullTypedCacheInterface<TValue, TCreateContext> - Used for secondary cache compatible storage of objects of type TValue. In addition to BasicTypedCacheInterface constraints, we require TValue::ContentSlice() to return persistable data. This simplifies usage for the normal case of simple secondary cache compatibility (can give you a Slice to the data already in memory). In addition to TCreateContext performing the role of Cache::CreateContext, it is also expected to provide a factory function for creating TValue. * For each of these, there's a "Shared" version (e.g. FullTypedSharedCacheInterface) that holds a shared_ptr to the Cache, rather than assuming external ownership by holding only a raw `Cache*`. These interfaces introduce specific handle types for each interface instantiation, so that it's easy to see what kind of object is controlled by a handle. (Ultimately, this might not be worth the extra complexity, but it seems OK so far.) Note: I attempted to make the cache 'charge' automatically inferred from the cache object type, such as by expecting an ApproximateMemoryUsage() function, but this is not so clean because there are cases where we need to compute the charge ahead of time and don't want to re-compute it. ## block_cache.h This header is essentially the replacement for the old block_like_traits.h. It includes various things to support block cache access with typed_cache.h for block-based table. ## block_based_table_reader.cc Before this change, accessing the block cache here was an awkward mix of static polymorphism (template TBlocklike) and switch-case on a dynamic BlockType value. This change mostly unifies on static polymorphism, relying on minor hacks in block_cache.h to distinguish variants of Block. We still check BlockType in some places (especially for stats, which could be improved in follow-up work) but at least the BlockType is a static constant from the template parameter. (No more awkward partial redundancy between static and dynamic info.) This likely contributes to the overall performance improvement, but hasn't been tested in isolation. The other key source of simplification here is a more unified system of creating block cache objects: for directly populating from primary cache and for promotion from secondary cache. Both use BlockCreateContext, for context and for factory functions. ## block_based_table_builder.cc, cache_dump_load_impl.cc Before this change, warming caches was super ugly code. Both of these source files had switch statements to basically transition from the dynamic BlockType world to the static TBlocklike world. None of that mess is needed anymore as there's a new, untyped WarmInCache function that handles all the details just as promotion from SecondaryCache would. (Fixes `TODO akanksha: Dedup below code` in block_based_table_builder.cc.) ## Everything else Mostly just updating Cache users to use new typed APIs when reasonably possible, or changed Cache APIs when not. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10975 Test Plan: tests updated Performance test setup similar to https://github.com/facebook/rocksdb/issues/10626 (by cache size, LRUCache when not "hyper" for HyperClockCache): 34MB 1thread base.hyper -> kops/s: 0.745 io_bytes/op: 2.52504e+06 miss_ratio: 0.140906 max_rss_mb: 76.4844 34MB 1thread new.hyper -> kops/s: 0.751 io_bytes/op: 2.5123e+06 miss_ratio: 0.140161 max_rss_mb: 79.3594 34MB 1thread base -> kops/s: 0.254 io_bytes/op: 1.36073e+07 miss_ratio: 0.918818 max_rss_mb: 45.9297 34MB 1thread new -> kops/s: 0.252 io_bytes/op: 1.36157e+07 miss_ratio: 0.918999 max_rss_mb: 44.1523 34MB 32thread base.hyper -> kops/s: 7.272 io_bytes/op: 2.88323e+06 miss_ratio: 0.162532 max_rss_mb: 516.602 34MB 32thread new.hyper -> kops/s: 7.214 io_bytes/op: 2.99046e+06 miss_ratio: 0.168818 max_rss_mb: 518.293 34MB 32thread base -> kops/s: 3.528 io_bytes/op: 1.35722e+07 miss_ratio: 0.914691 max_rss_mb: 264.926 34MB 32thread new -> kops/s: 3.604 io_bytes/op: 1.35744e+07 miss_ratio: 0.915054 max_rss_mb: 264.488 233MB 1thread base.hyper -> kops/s: 53.909 io_bytes/op: 2552.35 miss_ratio: 0.0440566 max_rss_mb: 241.984 233MB 1thread new.hyper -> kops/s: 62.792 io_bytes/op: 2549.79 miss_ratio: 0.044043 max_rss_mb: 241.922 233MB 1thread base -> kops/s: 1.197 io_bytes/op: 2.75173e+06 miss_ratio: 0.103093 max_rss_mb: 241.559 233MB 1thread new -> kops/s: 1.199 io_bytes/op: 2.73723e+06 miss_ratio: 0.10305 max_rss_mb: 240.93 233MB 32thread base.hyper -> kops/s: 1298.69 io_bytes/op: 2539.12 miss_ratio: 0.0440307 max_rss_mb: 371.418 233MB 32thread new.hyper -> kops/s: 1421.35 io_bytes/op: 2538.75 miss_ratio: 0.0440307 max_rss_mb: 347.273 233MB 32thread base -> kops/s: 9.693 io_bytes/op: 2.77304e+06 miss_ratio: 0.103745 max_rss_mb: 569.691 233MB 32thread new -> kops/s: 9.75 io_bytes/op: 2.77559e+06 miss_ratio: 0.103798 max_rss_mb: 552.82 1597MB 1thread base.hyper -> kops/s: 58.607 io_bytes/op: 1449.14 miss_ratio: 0.0249324 max_rss_mb: 1583.55 1597MB 1thread new.hyper -> kops/s: 69.6 io_bytes/op: 1434.89 miss_ratio: 0.0247167 max_rss_mb: 1584.02 1597MB 1thread base -> kops/s: 60.478 io_bytes/op: 1421.28 miss_ratio: 0.024452 max_rss_mb: 1589.45 1597MB 1thread new -> kops/s: 63.973 io_bytes/op: 1416.07 miss_ratio: 0.0243766 max_rss_mb: 1589.24 1597MB 32thread base.hyper -> kops/s: 1436.2 io_bytes/op: 1357.93 miss_ratio: 0.0235353 max_rss_mb: 1692.92 1597MB 32thread new.hyper -> kops/s: 1605.03 io_bytes/op: 1358.04 miss_ratio: 0.023538 max_rss_mb: 1702.78 1597MB 32thread base -> kops/s: 280.059 io_bytes/op: 1350.34 miss_ratio: 0.023289 max_rss_mb: 1675.36 1597MB 32thread new -> kops/s: 283.125 io_bytes/op: 1351.05 miss_ratio: 0.0232797 max_rss_mb: 1703.83 Almost uniformly improving over base revision, especially for hot paths with HyperClockCache, up to 12% higher throughput seen (1597MB, 32thread, hyper). The improvement for that is likely coming from much simplified code for providing context for secondary cache promotion (CreateCallback/CreateContext), and possibly from less branching in block_based_table_reader. And likely a small improvement from not reconstituting key for DeleterFn. Reviewed By: anand1976 Differential Revision: D42417818 Pulled By: pdillinger fbshipit-source-id: f86bfdd584dce27c028b151ba56818ad14f7a432
2023-01-11 22:20:40 +00:00
}
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
uint64_t NewId() override { return target_->NewId(); }
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
size_t GetCapacity() const override { return target_->GetCapacity(); }
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
bool HasStrictCapacityLimit() const override {
return target_->HasStrictCapacityLimit();
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
}
size_t GetUsage() const override { return target_->GetUsage(); }
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
size_t GetUsage(Handle* handle) const override {
return target_->GetUsage(handle);
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
}
size_t GetCharge(Handle* handle) const override {
return target_->GetCharge(handle);
}
Major Cache refactoring, CPU efficiency improvement (#10975) Summary: This is several refactorings bundled into one to avoid having to incrementally re-modify uses of Cache several times. Overall, there are breaking changes to Cache class, and it becomes more of low-level interface for implementing caches, especially block cache. New internal APIs make using Cache cleaner than before, and more insulated from block cache evolution. Hopefully, this is the last really big block cache refactoring, because of rather effectively decoupling the implementations from the uses. This change also removes the EXPERIMENTAL designation on the SecondaryCache support in Cache. It seems reasonably mature at this point but still subject to change/evolution (as I warn in the API docs for Cache). The high-level motivation for this refactoring is to minimize code duplication / compounding complexity in adding SecondaryCache support to HyperClockCache (in a later PR). Other benefits listed below. * static_cast lines of code +29 -35 (net removed 6) * reinterpret_cast lines of code +6 -32 (net removed 26) ## cache.h and secondary_cache.h * Always use CacheItemHelper with entries instead of just a Deleter. There are several motivations / justifications: * Simpler for implementations to deal with just one Insert and one Lookup. * Simpler and more efficient implementation because we don't have to track which entries are using helpers and which are using deleters * Gets rid of hack to classify cache entries by their deleter. Instead, the CacheItemHelper includes a CacheEntryRole. This simplifies a lot of code (cache_entry_roles.h almost eliminated). Fixes https://github.com/facebook/rocksdb/issues/9428. * Makes it trivial to adjust SecondaryCache behavior based on kind of block (e.g. don't re-compress filter blocks). * It is arguably less convenient for many direct users of Cache, but direct users of Cache are now rare with introduction of typed_cache.h (below). * I considered and rejected an alternative approach in which we reduce customizability by assuming each secondary cache compatible value starts with a Slice referencing the uncompressed block contents (already true or mostly true), but we apparently intend to stack secondary caches. Saving an entry from a compressed secondary to a lower tier requires custom handling offered by SaveToCallback, etc. * Make CreateCallback part of the helper and introduce CreateContext to work with it (alternative to https://github.com/facebook/rocksdb/issues/10562). This cleans up the interface while still allowing context to be provided for loading/parsing values into primary cache. This model works for async lookup in BlockBasedTable reader (reader owns a CreateContext) under the assumption that it always waits on secondary cache operations to finish. (Otherwise, the CreateContext could be destroyed while async operation depending on it continues.) This likely contributes most to the observed performance improvement because it saves an std::function backed by a heap allocation. * Use char* for serialized data, e.g. in SaveToCallback, where void* was confusingly used. (We use `char*` for serialized byte data all over RocksDB, with many advantages over `void*`. `memcpy` etc. are legacy APIs that should not be mimicked.) * Add a type alias Cache::ObjectPtr = void*, so that we can better indicate the intent of the void* when it is to be the object associated with a Cache entry. Related: started (but did not complete) a refactoring to move away from "value" of a cache entry toward "object" or "obj". (It is confusing to call Cache a key-value store (like DB) when it is really storing arbitrary in-memory objects, not byte strings.) * Remove unnecessary key param from DeleterFn. This is good for efficiency in HyperClockCache, which does not directly store the cache key in memory. (Alternative to https://github.com/facebook/rocksdb/issues/10774) * Add allocator to Cache DeleterFn. This is a kind of future-proofing change in case we get more serious about using the Cache allocator for memory tracked by the Cache. Right now, only the uncompressed block contents are allocated using the allocator, and a pointer to that allocator is saved as part of the cached object so that the deleter can use it. (See CacheAllocationPtr.) If in the future we are able to "flatten out" our Cache objects some more, it would be good not to have to track the allocator as part of each object. * Removes legacy `ApplyToAllCacheEntries` and changes `ApplyToAllEntries` signature for Deleter->CacheItemHelper change. ## typed_cache.h Adds various "typed" interfaces to the Cache as internal APIs, so that most uses of Cache can use simple type safe code without casting and without explicit deleters, etc. Almost all of the non-test, non-glue code uses of Cache have been migrated. (Follow-up work: CompressedSecondaryCache deserves deeper attention to migrate.) This change expands RocksDB's internal usage of metaprogramming and SFINAE (https://en.cppreference.com/w/cpp/language/sfinae). The existing usages of Cache are divided up at a high level into these new interfaces. See updated existing uses of Cache for examples of how these are used. * PlaceholderCacheInterface - Used for making cache reservations, with entries that have a charge but no value. * BasicTypedCacheInterface<TValue> - Used for primary cache storage of objects of type TValue, which can be cleaned up with std::default_delete<TValue>. The role is provided by TValue::kCacheEntryRole or given in an optional template parameter. * FullTypedCacheInterface<TValue, TCreateContext> - Used for secondary cache compatible storage of objects of type TValue. In addition to BasicTypedCacheInterface constraints, we require TValue::ContentSlice() to return persistable data. This simplifies usage for the normal case of simple secondary cache compatibility (can give you a Slice to the data already in memory). In addition to TCreateContext performing the role of Cache::CreateContext, it is also expected to provide a factory function for creating TValue. * For each of these, there's a "Shared" version (e.g. FullTypedSharedCacheInterface) that holds a shared_ptr to the Cache, rather than assuming external ownership by holding only a raw `Cache*`. These interfaces introduce specific handle types for each interface instantiation, so that it's easy to see what kind of object is controlled by a handle. (Ultimately, this might not be worth the extra complexity, but it seems OK so far.) Note: I attempted to make the cache 'charge' automatically inferred from the cache object type, such as by expecting an ApproximateMemoryUsage() function, but this is not so clean because there are cases where we need to compute the charge ahead of time and don't want to re-compute it. ## block_cache.h This header is essentially the replacement for the old block_like_traits.h. It includes various things to support block cache access with typed_cache.h for block-based table. ## block_based_table_reader.cc Before this change, accessing the block cache here was an awkward mix of static polymorphism (template TBlocklike) and switch-case on a dynamic BlockType value. This change mostly unifies on static polymorphism, relying on minor hacks in block_cache.h to distinguish variants of Block. We still check BlockType in some places (especially for stats, which could be improved in follow-up work) but at least the BlockType is a static constant from the template parameter. (No more awkward partial redundancy between static and dynamic info.) This likely contributes to the overall performance improvement, but hasn't been tested in isolation. The other key source of simplification here is a more unified system of creating block cache objects: for directly populating from primary cache and for promotion from secondary cache. Both use BlockCreateContext, for context and for factory functions. ## block_based_table_builder.cc, cache_dump_load_impl.cc Before this change, warming caches was super ugly code. Both of these source files had switch statements to basically transition from the dynamic BlockType world to the static TBlocklike world. None of that mess is needed anymore as there's a new, untyped WarmInCache function that handles all the details just as promotion from SecondaryCache would. (Fixes `TODO akanksha: Dedup below code` in block_based_table_builder.cc.) ## Everything else Mostly just updating Cache users to use new typed APIs when reasonably possible, or changed Cache APIs when not. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10975 Test Plan: tests updated Performance test setup similar to https://github.com/facebook/rocksdb/issues/10626 (by cache size, LRUCache when not "hyper" for HyperClockCache): 34MB 1thread base.hyper -> kops/s: 0.745 io_bytes/op: 2.52504e+06 miss_ratio: 0.140906 max_rss_mb: 76.4844 34MB 1thread new.hyper -> kops/s: 0.751 io_bytes/op: 2.5123e+06 miss_ratio: 0.140161 max_rss_mb: 79.3594 34MB 1thread base -> kops/s: 0.254 io_bytes/op: 1.36073e+07 miss_ratio: 0.918818 max_rss_mb: 45.9297 34MB 1thread new -> kops/s: 0.252 io_bytes/op: 1.36157e+07 miss_ratio: 0.918999 max_rss_mb: 44.1523 34MB 32thread base.hyper -> kops/s: 7.272 io_bytes/op: 2.88323e+06 miss_ratio: 0.162532 max_rss_mb: 516.602 34MB 32thread new.hyper -> kops/s: 7.214 io_bytes/op: 2.99046e+06 miss_ratio: 0.168818 max_rss_mb: 518.293 34MB 32thread base -> kops/s: 3.528 io_bytes/op: 1.35722e+07 miss_ratio: 0.914691 max_rss_mb: 264.926 34MB 32thread new -> kops/s: 3.604 io_bytes/op: 1.35744e+07 miss_ratio: 0.915054 max_rss_mb: 264.488 233MB 1thread base.hyper -> kops/s: 53.909 io_bytes/op: 2552.35 miss_ratio: 0.0440566 max_rss_mb: 241.984 233MB 1thread new.hyper -> kops/s: 62.792 io_bytes/op: 2549.79 miss_ratio: 0.044043 max_rss_mb: 241.922 233MB 1thread base -> kops/s: 1.197 io_bytes/op: 2.75173e+06 miss_ratio: 0.103093 max_rss_mb: 241.559 233MB 1thread new -> kops/s: 1.199 io_bytes/op: 2.73723e+06 miss_ratio: 0.10305 max_rss_mb: 240.93 233MB 32thread base.hyper -> kops/s: 1298.69 io_bytes/op: 2539.12 miss_ratio: 0.0440307 max_rss_mb: 371.418 233MB 32thread new.hyper -> kops/s: 1421.35 io_bytes/op: 2538.75 miss_ratio: 0.0440307 max_rss_mb: 347.273 233MB 32thread base -> kops/s: 9.693 io_bytes/op: 2.77304e+06 miss_ratio: 0.103745 max_rss_mb: 569.691 233MB 32thread new -> kops/s: 9.75 io_bytes/op: 2.77559e+06 miss_ratio: 0.103798 max_rss_mb: 552.82 1597MB 1thread base.hyper -> kops/s: 58.607 io_bytes/op: 1449.14 miss_ratio: 0.0249324 max_rss_mb: 1583.55 1597MB 1thread new.hyper -> kops/s: 69.6 io_bytes/op: 1434.89 miss_ratio: 0.0247167 max_rss_mb: 1584.02 1597MB 1thread base -> kops/s: 60.478 io_bytes/op: 1421.28 miss_ratio: 0.024452 max_rss_mb: 1589.45 1597MB 1thread new -> kops/s: 63.973 io_bytes/op: 1416.07 miss_ratio: 0.0243766 max_rss_mb: 1589.24 1597MB 32thread base.hyper -> kops/s: 1436.2 io_bytes/op: 1357.93 miss_ratio: 0.0235353 max_rss_mb: 1692.92 1597MB 32thread new.hyper -> kops/s: 1605.03 io_bytes/op: 1358.04 miss_ratio: 0.023538 max_rss_mb: 1702.78 1597MB 32thread base -> kops/s: 280.059 io_bytes/op: 1350.34 miss_ratio: 0.023289 max_rss_mb: 1675.36 1597MB 32thread new -> kops/s: 283.125 io_bytes/op: 1351.05 miss_ratio: 0.0232797 max_rss_mb: 1703.83 Almost uniformly improving over base revision, especially for hot paths with HyperClockCache, up to 12% higher throughput seen (1597MB, 32thread, hyper). The improvement for that is likely coming from much simplified code for providing context for secondary cache promotion (CreateCallback/CreateContext), and possibly from less branching in block_based_table_reader. And likely a small improvement from not reconstituting key for DeleterFn. Reviewed By: anand1976 Differential Revision: D42417818 Pulled By: pdillinger fbshipit-source-id: f86bfdd584dce27c028b151ba56818ad14f7a432
2023-01-11 22:20:40 +00:00
const CacheItemHelper* GetCacheItemHelper(Handle* handle) const override {
return target_->GetCacheItemHelper(handle);
Use deleters to label cache entries and collect stats (#8297) Summary: This change gathers and publishes statistics about the kinds of items in block cache. This is especially important for profiling relative usage of cache by index vs. filter vs. data blocks. It works by iterating over the cache during periodic stats dump (InternalStats, stats_dump_period_sec) or on demand when DB::Get(Map)Property(kBlockCacheEntryStats), except that for efficiency and sharing among column families, saved data from the last scan is used when the data is not considered too old. The new information can be seen in info LOG, for example: Block cache LRUCache@0x7fca62229330 capacity: 95.37 MB collections: 8 last_copies: 0 last_secs: 0.00178 secs_since: 0 Block cache entry stats(count,size,portion): DataBlock(7092,28.24 MB,29.6136%) FilterBlock(215,867.90 KB,0.888728%) FilterMetaBlock(2,5.31 KB,0.00544%) IndexBlock(217,180.11 KB,0.184432%) WriteBuffer(1,256.00 KB,0.262144%) Misc(1,0.00 KB,0%) And also through DB::GetProperty and GetMapProperty (here using ldb just for demonstration): $ ./ldb --db=/dev/shm/dbbench/ get_property rocksdb.block-cache-entry-stats rocksdb.block-cache-entry-stats.bytes.data-block: 0 rocksdb.block-cache-entry-stats.bytes.deprecated-filter-block: 0 rocksdb.block-cache-entry-stats.bytes.filter-block: 0 rocksdb.block-cache-entry-stats.bytes.filter-meta-block: 0 rocksdb.block-cache-entry-stats.bytes.index-block: 178992 rocksdb.block-cache-entry-stats.bytes.misc: 0 rocksdb.block-cache-entry-stats.bytes.other-block: 0 rocksdb.block-cache-entry-stats.bytes.write-buffer: 0 rocksdb.block-cache-entry-stats.capacity: 8388608 rocksdb.block-cache-entry-stats.count.data-block: 0 rocksdb.block-cache-entry-stats.count.deprecated-filter-block: 0 rocksdb.block-cache-entry-stats.count.filter-block: 0 rocksdb.block-cache-entry-stats.count.filter-meta-block: 0 rocksdb.block-cache-entry-stats.count.index-block: 215 rocksdb.block-cache-entry-stats.count.misc: 1 rocksdb.block-cache-entry-stats.count.other-block: 0 rocksdb.block-cache-entry-stats.count.write-buffer: 0 rocksdb.block-cache-entry-stats.id: LRUCache@0x7f3636661290 rocksdb.block-cache-entry-stats.percent.data-block: 0.000000 rocksdb.block-cache-entry-stats.percent.deprecated-filter-block: 0.000000 rocksdb.block-cache-entry-stats.percent.filter-block: 0.000000 rocksdb.block-cache-entry-stats.percent.filter-meta-block: 0.000000 rocksdb.block-cache-entry-stats.percent.index-block: 2.133751 rocksdb.block-cache-entry-stats.percent.misc: 0.000000 rocksdb.block-cache-entry-stats.percent.other-block: 0.000000 rocksdb.block-cache-entry-stats.percent.write-buffer: 0.000000 rocksdb.block-cache-entry-stats.secs_for_last_collection: 0.000052 rocksdb.block-cache-entry-stats.secs_since_last_collection: 0 Solution detail - We need some way to flag what kind of blocks each entry belongs to, preferably without changing the Cache API. One of the complications is that Cache is a general interface that could have other users that don't adhere to whichever convention we decide on for keys and values. Or we would pay for an extra field in the Handle that would only be used for this purpose. This change uses a back-door approach, the deleter, to indicate the "role" of a Cache entry (in addition to the value type, implicitly). This has the added benefit of ensuring proper code origin whenever we recognize a particular role for a cache entry; if the entry came from some other part of the code, it will use an unrecognized deleter, which we simply attribute to the "Misc" role. An internal API makes for simple instantiation and automatic registration of Cache deleters for a given value type and "role". Another internal API, CacheEntryStatsCollector, solves the problem of caching the results of a scan and sharing them, to ensure scans are neither excessive nor redundant so as not to harm Cache performance. Because code is added to BlocklikeTraits, it is pulled out of block_based_table_reader.cc into its own file. This is a reformulation of https://github.com/facebook/rocksdb/issues/8276, without the type checking option (could still be added), and with actual stat gathering. Pull Request resolved: https://github.com/facebook/rocksdb/pull/8297 Test Plan: manual testing with db_bench, and a couple of basic unit tests Reviewed By: ltamasi Differential Revision: D28488721 Pulled By: pdillinger fbshipit-source-id: 472f524a9691b5afb107934be2d41d84f2b129fb
2021-05-19 23:45:51 +00:00
}
size_t GetPinnedUsage() const override { return target_->GetPinnedUsage(); }
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
void DisownData() override {
target_->DisownData();
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
key_only_cache_->DisownData();
}
New Cache API for gathering statistics (#8225) Summary: Adds a new Cache::ApplyToAllEntries API that we expect to use (in follow-up PRs) for efficiently gathering block cache statistics. Notable features vs. old ApplyToAllCacheEntries: * Includes key and deleter (in addition to value and charge). We could have passed in a Handle but then more virtual function calls would be needed to get the "fields" of each entry. We expect to use the 'deleter' to identify the origin of entries, perhaps even more. * Heavily tuned to minimize latency impact on operating cache. It does this by iterating over small sections of each cache shard while cycling through the shards. * Supports tuning roughly how many entries to operate on for each lock acquire and release, to control the impact on the latency of other operations without excessive lock acquire & release. The right balance can depend on the cost of the callback. Good default seems to be around 256. * There should be no need to disable thread safety. (I would expect uncontended locks to be sufficiently fast.) I have enhanced cache_bench to validate this approach: * Reports a histogram of ns per operation, so we can look at the ditribution of times, not just throughput (average). * Can add a thread for simulated "gather stats" which calls ApplyToAllEntries at a specified interval. We also generate a histogram of time to run ApplyToAllEntries. To make the iteration over some entries of each shard work as cleanly as possible, even with resize between next set of entries, I have re-arranged which hash bits are used for sharding and which for indexing within a shard. Pull Request resolved: https://github.com/facebook/rocksdb/pull/8225 Test Plan: A couple of unit tests are added, but primary validation is manual, as the primary risk is to performance. The primary validation is using cache_bench to ensure that neither the minor hashing changes nor the simulated stats gathering significantly impact QPS or latency distribution. Note that adding op latency histogram seriously impacts the benchmark QPS, so for a fair baseline, we need the cache_bench changes (except remove simulated stat gathering to make it compile). In short, we don't see any reproducible difference in ops/sec or op latency unless we are gathering stats nearly continuously. Test uses 10GB block cache with 8KB values to be somewhat realistic in the number of items to iterate over. Baseline typical output: ``` Complete in 92.017 s; Rough parallel ops/sec = 869401 Thread ops/sec = 54662 Operation latency (ns): Count: 80000000 Average: 11223.9494 StdDev: 29.61 Min: 0 Median: 7759.3973 Max: 9620500 Percentiles: P50: 7759.40 P75: 14190.73 P99: 46922.75 P99.9: 77509.84 P99.99: 217030.58 ------------------------------------------------------ [ 0, 1 ] 68 0.000% 0.000% ( 2900, 4400 ] 89 0.000% 0.000% ( 4400, 6600 ] 33630240 42.038% 42.038% ######## ( 6600, 9900 ] 18129842 22.662% 64.700% ##### ( 9900, 14000 ] 7877533 9.847% 74.547% ## ( 14000, 22000 ] 15193238 18.992% 93.539% #### ( 22000, 33000 ] 3037061 3.796% 97.335% # ( 33000, 50000 ] 1626316 2.033% 99.368% ( 50000, 75000 ] 421532 0.527% 99.895% ( 75000, 110000 ] 56910 0.071% 99.966% ( 110000, 170000 ] 16134 0.020% 99.986% ( 170000, 250000 ] 5166 0.006% 99.993% ( 250000, 380000 ] 3017 0.004% 99.996% ( 380000, 570000 ] 1337 0.002% 99.998% ( 570000, 860000 ] 805 0.001% 99.999% ( 860000, 1200000 ] 319 0.000% 100.000% ( 1200000, 1900000 ] 231 0.000% 100.000% ( 1900000, 2900000 ] 100 0.000% 100.000% ( 2900000, 4300000 ] 39 0.000% 100.000% ( 4300000, 6500000 ] 16 0.000% 100.000% ( 6500000, 9800000 ] 7 0.000% 100.000% ``` New, gather_stats=false. Median thread ops/sec of 5 runs: ``` Complete in 92.030 s; Rough parallel ops/sec = 869285 Thread ops/sec = 54458 Operation latency (ns): Count: 80000000 Average: 11298.1027 StdDev: 42.18 Min: 0 Median: 7722.0822 Max: 6398720 Percentiles: P50: 7722.08 P75: 14294.68 P99: 47522.95 P99.9: 85292.16 P99.99: 228077.78 ------------------------------------------------------ [ 0, 1 ] 109 0.000% 0.000% ( 2900, 4400 ] 793 0.001% 0.001% ( 4400, 6600 ] 34054563 42.568% 42.569% ######### ( 6600, 9900 ] 17482646 21.853% 64.423% #### ( 9900, 14000 ] 7908180 9.885% 74.308% ## ( 14000, 22000 ] 15032072 18.790% 93.098% #### ( 22000, 33000 ] 3237834 4.047% 97.145% # ( 33000, 50000 ] 1736882 2.171% 99.316% ( 50000, 75000 ] 446851 0.559% 99.875% ( 75000, 110000 ] 68251 0.085% 99.960% ( 110000, 170000 ] 18592 0.023% 99.983% ( 170000, 250000 ] 7200 0.009% 99.992% ( 250000, 380000 ] 3334 0.004% 99.997% ( 380000, 570000 ] 1393 0.002% 99.998% ( 570000, 860000 ] 700 0.001% 99.999% ( 860000, 1200000 ] 293 0.000% 100.000% ( 1200000, 1900000 ] 196 0.000% 100.000% ( 1900000, 2900000 ] 69 0.000% 100.000% ( 2900000, 4300000 ] 32 0.000% 100.000% ( 4300000, 6500000 ] 10 0.000% 100.000% ``` New, gather_stats=true, 1 second delay between scans. Scans take about 1 second here so it's spending about 50% time scanning. Still the effect on ops/sec and latency seems to be in the noise. Median thread ops/sec of 5 runs: ``` Complete in 91.890 s; Rough parallel ops/sec = 870608 Thread ops/sec = 54551 Operation latency (ns): Count: 80000000 Average: 11311.2629 StdDev: 45.28 Min: 0 Median: 7686.5458 Max: 10018340 Percentiles: P50: 7686.55 P75: 14481.95 P99: 47232.60 P99.9: 79230.18 P99.99: 232998.86 ------------------------------------------------------ [ 0, 1 ] 71 0.000% 0.000% ( 2900, 4400 ] 291 0.000% 0.000% ( 4400, 6600 ] 34492060 43.115% 43.116% ######### ( 6600, 9900 ] 16727328 20.909% 64.025% #### ( 9900, 14000 ] 7845828 9.807% 73.832% ## ( 14000, 22000 ] 15510654 19.388% 93.220% #### ( 22000, 33000 ] 3216533 4.021% 97.241% # ( 33000, 50000 ] 1680859 2.101% 99.342% ( 50000, 75000 ] 439059 0.549% 99.891% ( 75000, 110000 ] 60540 0.076% 99.967% ( 110000, 170000 ] 14649 0.018% 99.985% ( 170000, 250000 ] 5242 0.007% 99.991% ( 250000, 380000 ] 3260 0.004% 99.995% ( 380000, 570000 ] 1599 0.002% 99.997% ( 570000, 860000 ] 1043 0.001% 99.999% ( 860000, 1200000 ] 471 0.001% 99.999% ( 1200000, 1900000 ] 275 0.000% 100.000% ( 1900000, 2900000 ] 143 0.000% 100.000% ( 2900000, 4300000 ] 60 0.000% 100.000% ( 4300000, 6500000 ] 27 0.000% 100.000% ( 6500000, 9800000 ] 7 0.000% 100.000% ( 9800000, 14000000 ] 1 0.000% 100.000% Gather stats latency (us): Count: 46 Average: 980387.5870 StdDev: 60911.18 Min: 879155 Median: 1033777.7778 Max: 1261431 Percentiles: P50: 1033777.78 P75: 1120666.67 P99: 1261431.00 P99.9: 1261431.00 P99.99: 1261431.00 ------------------------------------------------------ ( 860000, 1200000 ] 45 97.826% 97.826% #################### ( 1200000, 1900000 ] 1 2.174% 100.000% Most recent cache entry stats: Number of entries: 1295133 Total charge: 9.88 GB Average key size: 23.4982 Average charge: 8.00 KB Unique deleters: 3 ``` Reviewed By: mrambacher Differential Revision: D28295742 Pulled By: pdillinger fbshipit-source-id: bbc4a552f91ba0fe10e5cc025c42cef5a81f2b95
2021-05-11 23:16:11 +00:00
void ApplyToAllEntries(
Major Cache refactoring, CPU efficiency improvement (#10975) Summary: This is several refactorings bundled into one to avoid having to incrementally re-modify uses of Cache several times. Overall, there are breaking changes to Cache class, and it becomes more of low-level interface for implementing caches, especially block cache. New internal APIs make using Cache cleaner than before, and more insulated from block cache evolution. Hopefully, this is the last really big block cache refactoring, because of rather effectively decoupling the implementations from the uses. This change also removes the EXPERIMENTAL designation on the SecondaryCache support in Cache. It seems reasonably mature at this point but still subject to change/evolution (as I warn in the API docs for Cache). The high-level motivation for this refactoring is to minimize code duplication / compounding complexity in adding SecondaryCache support to HyperClockCache (in a later PR). Other benefits listed below. * static_cast lines of code +29 -35 (net removed 6) * reinterpret_cast lines of code +6 -32 (net removed 26) ## cache.h and secondary_cache.h * Always use CacheItemHelper with entries instead of just a Deleter. There are several motivations / justifications: * Simpler for implementations to deal with just one Insert and one Lookup. * Simpler and more efficient implementation because we don't have to track which entries are using helpers and which are using deleters * Gets rid of hack to classify cache entries by their deleter. Instead, the CacheItemHelper includes a CacheEntryRole. This simplifies a lot of code (cache_entry_roles.h almost eliminated). Fixes https://github.com/facebook/rocksdb/issues/9428. * Makes it trivial to adjust SecondaryCache behavior based on kind of block (e.g. don't re-compress filter blocks). * It is arguably less convenient for many direct users of Cache, but direct users of Cache are now rare with introduction of typed_cache.h (below). * I considered and rejected an alternative approach in which we reduce customizability by assuming each secondary cache compatible value starts with a Slice referencing the uncompressed block contents (already true or mostly true), but we apparently intend to stack secondary caches. Saving an entry from a compressed secondary to a lower tier requires custom handling offered by SaveToCallback, etc. * Make CreateCallback part of the helper and introduce CreateContext to work with it (alternative to https://github.com/facebook/rocksdb/issues/10562). This cleans up the interface while still allowing context to be provided for loading/parsing values into primary cache. This model works for async lookup in BlockBasedTable reader (reader owns a CreateContext) under the assumption that it always waits on secondary cache operations to finish. (Otherwise, the CreateContext could be destroyed while async operation depending on it continues.) This likely contributes most to the observed performance improvement because it saves an std::function backed by a heap allocation. * Use char* for serialized data, e.g. in SaveToCallback, where void* was confusingly used. (We use `char*` for serialized byte data all over RocksDB, with many advantages over `void*`. `memcpy` etc. are legacy APIs that should not be mimicked.) * Add a type alias Cache::ObjectPtr = void*, so that we can better indicate the intent of the void* when it is to be the object associated with a Cache entry. Related: started (but did not complete) a refactoring to move away from "value" of a cache entry toward "object" or "obj". (It is confusing to call Cache a key-value store (like DB) when it is really storing arbitrary in-memory objects, not byte strings.) * Remove unnecessary key param from DeleterFn. This is good for efficiency in HyperClockCache, which does not directly store the cache key in memory. (Alternative to https://github.com/facebook/rocksdb/issues/10774) * Add allocator to Cache DeleterFn. This is a kind of future-proofing change in case we get more serious about using the Cache allocator for memory tracked by the Cache. Right now, only the uncompressed block contents are allocated using the allocator, and a pointer to that allocator is saved as part of the cached object so that the deleter can use it. (See CacheAllocationPtr.) If in the future we are able to "flatten out" our Cache objects some more, it would be good not to have to track the allocator as part of each object. * Removes legacy `ApplyToAllCacheEntries` and changes `ApplyToAllEntries` signature for Deleter->CacheItemHelper change. ## typed_cache.h Adds various "typed" interfaces to the Cache as internal APIs, so that most uses of Cache can use simple type safe code without casting and without explicit deleters, etc. Almost all of the non-test, non-glue code uses of Cache have been migrated. (Follow-up work: CompressedSecondaryCache deserves deeper attention to migrate.) This change expands RocksDB's internal usage of metaprogramming and SFINAE (https://en.cppreference.com/w/cpp/language/sfinae). The existing usages of Cache are divided up at a high level into these new interfaces. See updated existing uses of Cache for examples of how these are used. * PlaceholderCacheInterface - Used for making cache reservations, with entries that have a charge but no value. * BasicTypedCacheInterface<TValue> - Used for primary cache storage of objects of type TValue, which can be cleaned up with std::default_delete<TValue>. The role is provided by TValue::kCacheEntryRole or given in an optional template parameter. * FullTypedCacheInterface<TValue, TCreateContext> - Used for secondary cache compatible storage of objects of type TValue. In addition to BasicTypedCacheInterface constraints, we require TValue::ContentSlice() to return persistable data. This simplifies usage for the normal case of simple secondary cache compatibility (can give you a Slice to the data already in memory). In addition to TCreateContext performing the role of Cache::CreateContext, it is also expected to provide a factory function for creating TValue. * For each of these, there's a "Shared" version (e.g. FullTypedSharedCacheInterface) that holds a shared_ptr to the Cache, rather than assuming external ownership by holding only a raw `Cache*`. These interfaces introduce specific handle types for each interface instantiation, so that it's easy to see what kind of object is controlled by a handle. (Ultimately, this might not be worth the extra complexity, but it seems OK so far.) Note: I attempted to make the cache 'charge' automatically inferred from the cache object type, such as by expecting an ApproximateMemoryUsage() function, but this is not so clean because there are cases where we need to compute the charge ahead of time and don't want to re-compute it. ## block_cache.h This header is essentially the replacement for the old block_like_traits.h. It includes various things to support block cache access with typed_cache.h for block-based table. ## block_based_table_reader.cc Before this change, accessing the block cache here was an awkward mix of static polymorphism (template TBlocklike) and switch-case on a dynamic BlockType value. This change mostly unifies on static polymorphism, relying on minor hacks in block_cache.h to distinguish variants of Block. We still check BlockType in some places (especially for stats, which could be improved in follow-up work) but at least the BlockType is a static constant from the template parameter. (No more awkward partial redundancy between static and dynamic info.) This likely contributes to the overall performance improvement, but hasn't been tested in isolation. The other key source of simplification here is a more unified system of creating block cache objects: for directly populating from primary cache and for promotion from secondary cache. Both use BlockCreateContext, for context and for factory functions. ## block_based_table_builder.cc, cache_dump_load_impl.cc Before this change, warming caches was super ugly code. Both of these source files had switch statements to basically transition from the dynamic BlockType world to the static TBlocklike world. None of that mess is needed anymore as there's a new, untyped WarmInCache function that handles all the details just as promotion from SecondaryCache would. (Fixes `TODO akanksha: Dedup below code` in block_based_table_builder.cc.) ## Everything else Mostly just updating Cache users to use new typed APIs when reasonably possible, or changed Cache APIs when not. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10975 Test Plan: tests updated Performance test setup similar to https://github.com/facebook/rocksdb/issues/10626 (by cache size, LRUCache when not "hyper" for HyperClockCache): 34MB 1thread base.hyper -> kops/s: 0.745 io_bytes/op: 2.52504e+06 miss_ratio: 0.140906 max_rss_mb: 76.4844 34MB 1thread new.hyper -> kops/s: 0.751 io_bytes/op: 2.5123e+06 miss_ratio: 0.140161 max_rss_mb: 79.3594 34MB 1thread base -> kops/s: 0.254 io_bytes/op: 1.36073e+07 miss_ratio: 0.918818 max_rss_mb: 45.9297 34MB 1thread new -> kops/s: 0.252 io_bytes/op: 1.36157e+07 miss_ratio: 0.918999 max_rss_mb: 44.1523 34MB 32thread base.hyper -> kops/s: 7.272 io_bytes/op: 2.88323e+06 miss_ratio: 0.162532 max_rss_mb: 516.602 34MB 32thread new.hyper -> kops/s: 7.214 io_bytes/op: 2.99046e+06 miss_ratio: 0.168818 max_rss_mb: 518.293 34MB 32thread base -> kops/s: 3.528 io_bytes/op: 1.35722e+07 miss_ratio: 0.914691 max_rss_mb: 264.926 34MB 32thread new -> kops/s: 3.604 io_bytes/op: 1.35744e+07 miss_ratio: 0.915054 max_rss_mb: 264.488 233MB 1thread base.hyper -> kops/s: 53.909 io_bytes/op: 2552.35 miss_ratio: 0.0440566 max_rss_mb: 241.984 233MB 1thread new.hyper -> kops/s: 62.792 io_bytes/op: 2549.79 miss_ratio: 0.044043 max_rss_mb: 241.922 233MB 1thread base -> kops/s: 1.197 io_bytes/op: 2.75173e+06 miss_ratio: 0.103093 max_rss_mb: 241.559 233MB 1thread new -> kops/s: 1.199 io_bytes/op: 2.73723e+06 miss_ratio: 0.10305 max_rss_mb: 240.93 233MB 32thread base.hyper -> kops/s: 1298.69 io_bytes/op: 2539.12 miss_ratio: 0.0440307 max_rss_mb: 371.418 233MB 32thread new.hyper -> kops/s: 1421.35 io_bytes/op: 2538.75 miss_ratio: 0.0440307 max_rss_mb: 347.273 233MB 32thread base -> kops/s: 9.693 io_bytes/op: 2.77304e+06 miss_ratio: 0.103745 max_rss_mb: 569.691 233MB 32thread new -> kops/s: 9.75 io_bytes/op: 2.77559e+06 miss_ratio: 0.103798 max_rss_mb: 552.82 1597MB 1thread base.hyper -> kops/s: 58.607 io_bytes/op: 1449.14 miss_ratio: 0.0249324 max_rss_mb: 1583.55 1597MB 1thread new.hyper -> kops/s: 69.6 io_bytes/op: 1434.89 miss_ratio: 0.0247167 max_rss_mb: 1584.02 1597MB 1thread base -> kops/s: 60.478 io_bytes/op: 1421.28 miss_ratio: 0.024452 max_rss_mb: 1589.45 1597MB 1thread new -> kops/s: 63.973 io_bytes/op: 1416.07 miss_ratio: 0.0243766 max_rss_mb: 1589.24 1597MB 32thread base.hyper -> kops/s: 1436.2 io_bytes/op: 1357.93 miss_ratio: 0.0235353 max_rss_mb: 1692.92 1597MB 32thread new.hyper -> kops/s: 1605.03 io_bytes/op: 1358.04 miss_ratio: 0.023538 max_rss_mb: 1702.78 1597MB 32thread base -> kops/s: 280.059 io_bytes/op: 1350.34 miss_ratio: 0.023289 max_rss_mb: 1675.36 1597MB 32thread new -> kops/s: 283.125 io_bytes/op: 1351.05 miss_ratio: 0.0232797 max_rss_mb: 1703.83 Almost uniformly improving over base revision, especially for hot paths with HyperClockCache, up to 12% higher throughput seen (1597MB, 32thread, hyper). The improvement for that is likely coming from much simplified code for providing context for secondary cache promotion (CreateCallback/CreateContext), and possibly from less branching in block_based_table_reader. And likely a small improvement from not reconstituting key for DeleterFn. Reviewed By: anand1976 Differential Revision: D42417818 Pulled By: pdillinger fbshipit-source-id: f86bfdd584dce27c028b151ba56818ad14f7a432
2023-01-11 22:20:40 +00:00
const std::function<void(const Slice& key, ObjectPtr value, size_t charge,
const CacheItemHelper* helper)>& callback,
New Cache API for gathering statistics (#8225) Summary: Adds a new Cache::ApplyToAllEntries API that we expect to use (in follow-up PRs) for efficiently gathering block cache statistics. Notable features vs. old ApplyToAllCacheEntries: * Includes key and deleter (in addition to value and charge). We could have passed in a Handle but then more virtual function calls would be needed to get the "fields" of each entry. We expect to use the 'deleter' to identify the origin of entries, perhaps even more. * Heavily tuned to minimize latency impact on operating cache. It does this by iterating over small sections of each cache shard while cycling through the shards. * Supports tuning roughly how many entries to operate on for each lock acquire and release, to control the impact on the latency of other operations without excessive lock acquire & release. The right balance can depend on the cost of the callback. Good default seems to be around 256. * There should be no need to disable thread safety. (I would expect uncontended locks to be sufficiently fast.) I have enhanced cache_bench to validate this approach: * Reports a histogram of ns per operation, so we can look at the ditribution of times, not just throughput (average). * Can add a thread for simulated "gather stats" which calls ApplyToAllEntries at a specified interval. We also generate a histogram of time to run ApplyToAllEntries. To make the iteration over some entries of each shard work as cleanly as possible, even with resize between next set of entries, I have re-arranged which hash bits are used for sharding and which for indexing within a shard. Pull Request resolved: https://github.com/facebook/rocksdb/pull/8225 Test Plan: A couple of unit tests are added, but primary validation is manual, as the primary risk is to performance. The primary validation is using cache_bench to ensure that neither the minor hashing changes nor the simulated stats gathering significantly impact QPS or latency distribution. Note that adding op latency histogram seriously impacts the benchmark QPS, so for a fair baseline, we need the cache_bench changes (except remove simulated stat gathering to make it compile). In short, we don't see any reproducible difference in ops/sec or op latency unless we are gathering stats nearly continuously. Test uses 10GB block cache with 8KB values to be somewhat realistic in the number of items to iterate over. Baseline typical output: ``` Complete in 92.017 s; Rough parallel ops/sec = 869401 Thread ops/sec = 54662 Operation latency (ns): Count: 80000000 Average: 11223.9494 StdDev: 29.61 Min: 0 Median: 7759.3973 Max: 9620500 Percentiles: P50: 7759.40 P75: 14190.73 P99: 46922.75 P99.9: 77509.84 P99.99: 217030.58 ------------------------------------------------------ [ 0, 1 ] 68 0.000% 0.000% ( 2900, 4400 ] 89 0.000% 0.000% ( 4400, 6600 ] 33630240 42.038% 42.038% ######## ( 6600, 9900 ] 18129842 22.662% 64.700% ##### ( 9900, 14000 ] 7877533 9.847% 74.547% ## ( 14000, 22000 ] 15193238 18.992% 93.539% #### ( 22000, 33000 ] 3037061 3.796% 97.335% # ( 33000, 50000 ] 1626316 2.033% 99.368% ( 50000, 75000 ] 421532 0.527% 99.895% ( 75000, 110000 ] 56910 0.071% 99.966% ( 110000, 170000 ] 16134 0.020% 99.986% ( 170000, 250000 ] 5166 0.006% 99.993% ( 250000, 380000 ] 3017 0.004% 99.996% ( 380000, 570000 ] 1337 0.002% 99.998% ( 570000, 860000 ] 805 0.001% 99.999% ( 860000, 1200000 ] 319 0.000% 100.000% ( 1200000, 1900000 ] 231 0.000% 100.000% ( 1900000, 2900000 ] 100 0.000% 100.000% ( 2900000, 4300000 ] 39 0.000% 100.000% ( 4300000, 6500000 ] 16 0.000% 100.000% ( 6500000, 9800000 ] 7 0.000% 100.000% ``` New, gather_stats=false. Median thread ops/sec of 5 runs: ``` Complete in 92.030 s; Rough parallel ops/sec = 869285 Thread ops/sec = 54458 Operation latency (ns): Count: 80000000 Average: 11298.1027 StdDev: 42.18 Min: 0 Median: 7722.0822 Max: 6398720 Percentiles: P50: 7722.08 P75: 14294.68 P99: 47522.95 P99.9: 85292.16 P99.99: 228077.78 ------------------------------------------------------ [ 0, 1 ] 109 0.000% 0.000% ( 2900, 4400 ] 793 0.001% 0.001% ( 4400, 6600 ] 34054563 42.568% 42.569% ######### ( 6600, 9900 ] 17482646 21.853% 64.423% #### ( 9900, 14000 ] 7908180 9.885% 74.308% ## ( 14000, 22000 ] 15032072 18.790% 93.098% #### ( 22000, 33000 ] 3237834 4.047% 97.145% # ( 33000, 50000 ] 1736882 2.171% 99.316% ( 50000, 75000 ] 446851 0.559% 99.875% ( 75000, 110000 ] 68251 0.085% 99.960% ( 110000, 170000 ] 18592 0.023% 99.983% ( 170000, 250000 ] 7200 0.009% 99.992% ( 250000, 380000 ] 3334 0.004% 99.997% ( 380000, 570000 ] 1393 0.002% 99.998% ( 570000, 860000 ] 700 0.001% 99.999% ( 860000, 1200000 ] 293 0.000% 100.000% ( 1200000, 1900000 ] 196 0.000% 100.000% ( 1900000, 2900000 ] 69 0.000% 100.000% ( 2900000, 4300000 ] 32 0.000% 100.000% ( 4300000, 6500000 ] 10 0.000% 100.000% ``` New, gather_stats=true, 1 second delay between scans. Scans take about 1 second here so it's spending about 50% time scanning. Still the effect on ops/sec and latency seems to be in the noise. Median thread ops/sec of 5 runs: ``` Complete in 91.890 s; Rough parallel ops/sec = 870608 Thread ops/sec = 54551 Operation latency (ns): Count: 80000000 Average: 11311.2629 StdDev: 45.28 Min: 0 Median: 7686.5458 Max: 10018340 Percentiles: P50: 7686.55 P75: 14481.95 P99: 47232.60 P99.9: 79230.18 P99.99: 232998.86 ------------------------------------------------------ [ 0, 1 ] 71 0.000% 0.000% ( 2900, 4400 ] 291 0.000% 0.000% ( 4400, 6600 ] 34492060 43.115% 43.116% ######### ( 6600, 9900 ] 16727328 20.909% 64.025% #### ( 9900, 14000 ] 7845828 9.807% 73.832% ## ( 14000, 22000 ] 15510654 19.388% 93.220% #### ( 22000, 33000 ] 3216533 4.021% 97.241% # ( 33000, 50000 ] 1680859 2.101% 99.342% ( 50000, 75000 ] 439059 0.549% 99.891% ( 75000, 110000 ] 60540 0.076% 99.967% ( 110000, 170000 ] 14649 0.018% 99.985% ( 170000, 250000 ] 5242 0.007% 99.991% ( 250000, 380000 ] 3260 0.004% 99.995% ( 380000, 570000 ] 1599 0.002% 99.997% ( 570000, 860000 ] 1043 0.001% 99.999% ( 860000, 1200000 ] 471 0.001% 99.999% ( 1200000, 1900000 ] 275 0.000% 100.000% ( 1900000, 2900000 ] 143 0.000% 100.000% ( 2900000, 4300000 ] 60 0.000% 100.000% ( 4300000, 6500000 ] 27 0.000% 100.000% ( 6500000, 9800000 ] 7 0.000% 100.000% ( 9800000, 14000000 ] 1 0.000% 100.000% Gather stats latency (us): Count: 46 Average: 980387.5870 StdDev: 60911.18 Min: 879155 Median: 1033777.7778 Max: 1261431 Percentiles: P50: 1033777.78 P75: 1120666.67 P99: 1261431.00 P99.9: 1261431.00 P99.99: 1261431.00 ------------------------------------------------------ ( 860000, 1200000 ] 45 97.826% 97.826% #################### ( 1200000, 1900000 ] 1 2.174% 100.000% Most recent cache entry stats: Number of entries: 1295133 Total charge: 9.88 GB Average key size: 23.4982 Average charge: 8.00 KB Unique deleters: 3 ``` Reviewed By: mrambacher Differential Revision: D28295742 Pulled By: pdillinger fbshipit-source-id: bbc4a552f91ba0fe10e5cc025c42cef5a81f2b95
2021-05-11 23:16:11 +00:00
const ApplyToAllEntriesOptions& opts) override {
target_->ApplyToAllEntries(callback, opts);
New Cache API for gathering statistics (#8225) Summary: Adds a new Cache::ApplyToAllEntries API that we expect to use (in follow-up PRs) for efficiently gathering block cache statistics. Notable features vs. old ApplyToAllCacheEntries: * Includes key and deleter (in addition to value and charge). We could have passed in a Handle but then more virtual function calls would be needed to get the "fields" of each entry. We expect to use the 'deleter' to identify the origin of entries, perhaps even more. * Heavily tuned to minimize latency impact on operating cache. It does this by iterating over small sections of each cache shard while cycling through the shards. * Supports tuning roughly how many entries to operate on for each lock acquire and release, to control the impact on the latency of other operations without excessive lock acquire & release. The right balance can depend on the cost of the callback. Good default seems to be around 256. * There should be no need to disable thread safety. (I would expect uncontended locks to be sufficiently fast.) I have enhanced cache_bench to validate this approach: * Reports a histogram of ns per operation, so we can look at the ditribution of times, not just throughput (average). * Can add a thread for simulated "gather stats" which calls ApplyToAllEntries at a specified interval. We also generate a histogram of time to run ApplyToAllEntries. To make the iteration over some entries of each shard work as cleanly as possible, even with resize between next set of entries, I have re-arranged which hash bits are used for sharding and which for indexing within a shard. Pull Request resolved: https://github.com/facebook/rocksdb/pull/8225 Test Plan: A couple of unit tests are added, but primary validation is manual, as the primary risk is to performance. The primary validation is using cache_bench to ensure that neither the minor hashing changes nor the simulated stats gathering significantly impact QPS or latency distribution. Note that adding op latency histogram seriously impacts the benchmark QPS, so for a fair baseline, we need the cache_bench changes (except remove simulated stat gathering to make it compile). In short, we don't see any reproducible difference in ops/sec or op latency unless we are gathering stats nearly continuously. Test uses 10GB block cache with 8KB values to be somewhat realistic in the number of items to iterate over. Baseline typical output: ``` Complete in 92.017 s; Rough parallel ops/sec = 869401 Thread ops/sec = 54662 Operation latency (ns): Count: 80000000 Average: 11223.9494 StdDev: 29.61 Min: 0 Median: 7759.3973 Max: 9620500 Percentiles: P50: 7759.40 P75: 14190.73 P99: 46922.75 P99.9: 77509.84 P99.99: 217030.58 ------------------------------------------------------ [ 0, 1 ] 68 0.000% 0.000% ( 2900, 4400 ] 89 0.000% 0.000% ( 4400, 6600 ] 33630240 42.038% 42.038% ######## ( 6600, 9900 ] 18129842 22.662% 64.700% ##### ( 9900, 14000 ] 7877533 9.847% 74.547% ## ( 14000, 22000 ] 15193238 18.992% 93.539% #### ( 22000, 33000 ] 3037061 3.796% 97.335% # ( 33000, 50000 ] 1626316 2.033% 99.368% ( 50000, 75000 ] 421532 0.527% 99.895% ( 75000, 110000 ] 56910 0.071% 99.966% ( 110000, 170000 ] 16134 0.020% 99.986% ( 170000, 250000 ] 5166 0.006% 99.993% ( 250000, 380000 ] 3017 0.004% 99.996% ( 380000, 570000 ] 1337 0.002% 99.998% ( 570000, 860000 ] 805 0.001% 99.999% ( 860000, 1200000 ] 319 0.000% 100.000% ( 1200000, 1900000 ] 231 0.000% 100.000% ( 1900000, 2900000 ] 100 0.000% 100.000% ( 2900000, 4300000 ] 39 0.000% 100.000% ( 4300000, 6500000 ] 16 0.000% 100.000% ( 6500000, 9800000 ] 7 0.000% 100.000% ``` New, gather_stats=false. Median thread ops/sec of 5 runs: ``` Complete in 92.030 s; Rough parallel ops/sec = 869285 Thread ops/sec = 54458 Operation latency (ns): Count: 80000000 Average: 11298.1027 StdDev: 42.18 Min: 0 Median: 7722.0822 Max: 6398720 Percentiles: P50: 7722.08 P75: 14294.68 P99: 47522.95 P99.9: 85292.16 P99.99: 228077.78 ------------------------------------------------------ [ 0, 1 ] 109 0.000% 0.000% ( 2900, 4400 ] 793 0.001% 0.001% ( 4400, 6600 ] 34054563 42.568% 42.569% ######### ( 6600, 9900 ] 17482646 21.853% 64.423% #### ( 9900, 14000 ] 7908180 9.885% 74.308% ## ( 14000, 22000 ] 15032072 18.790% 93.098% #### ( 22000, 33000 ] 3237834 4.047% 97.145% # ( 33000, 50000 ] 1736882 2.171% 99.316% ( 50000, 75000 ] 446851 0.559% 99.875% ( 75000, 110000 ] 68251 0.085% 99.960% ( 110000, 170000 ] 18592 0.023% 99.983% ( 170000, 250000 ] 7200 0.009% 99.992% ( 250000, 380000 ] 3334 0.004% 99.997% ( 380000, 570000 ] 1393 0.002% 99.998% ( 570000, 860000 ] 700 0.001% 99.999% ( 860000, 1200000 ] 293 0.000% 100.000% ( 1200000, 1900000 ] 196 0.000% 100.000% ( 1900000, 2900000 ] 69 0.000% 100.000% ( 2900000, 4300000 ] 32 0.000% 100.000% ( 4300000, 6500000 ] 10 0.000% 100.000% ``` New, gather_stats=true, 1 second delay between scans. Scans take about 1 second here so it's spending about 50% time scanning. Still the effect on ops/sec and latency seems to be in the noise. Median thread ops/sec of 5 runs: ``` Complete in 91.890 s; Rough parallel ops/sec = 870608 Thread ops/sec = 54551 Operation latency (ns): Count: 80000000 Average: 11311.2629 StdDev: 45.28 Min: 0 Median: 7686.5458 Max: 10018340 Percentiles: P50: 7686.55 P75: 14481.95 P99: 47232.60 P99.9: 79230.18 P99.99: 232998.86 ------------------------------------------------------ [ 0, 1 ] 71 0.000% 0.000% ( 2900, 4400 ] 291 0.000% 0.000% ( 4400, 6600 ] 34492060 43.115% 43.116% ######### ( 6600, 9900 ] 16727328 20.909% 64.025% #### ( 9900, 14000 ] 7845828 9.807% 73.832% ## ( 14000, 22000 ] 15510654 19.388% 93.220% #### ( 22000, 33000 ] 3216533 4.021% 97.241% # ( 33000, 50000 ] 1680859 2.101% 99.342% ( 50000, 75000 ] 439059 0.549% 99.891% ( 75000, 110000 ] 60540 0.076% 99.967% ( 110000, 170000 ] 14649 0.018% 99.985% ( 170000, 250000 ] 5242 0.007% 99.991% ( 250000, 380000 ] 3260 0.004% 99.995% ( 380000, 570000 ] 1599 0.002% 99.997% ( 570000, 860000 ] 1043 0.001% 99.999% ( 860000, 1200000 ] 471 0.001% 99.999% ( 1200000, 1900000 ] 275 0.000% 100.000% ( 1900000, 2900000 ] 143 0.000% 100.000% ( 2900000, 4300000 ] 60 0.000% 100.000% ( 4300000, 6500000 ] 27 0.000% 100.000% ( 6500000, 9800000 ] 7 0.000% 100.000% ( 9800000, 14000000 ] 1 0.000% 100.000% Gather stats latency (us): Count: 46 Average: 980387.5870 StdDev: 60911.18 Min: 879155 Median: 1033777.7778 Max: 1261431 Percentiles: P50: 1033777.78 P75: 1120666.67 P99: 1261431.00 P99.9: 1261431.00 P99.99: 1261431.00 ------------------------------------------------------ ( 860000, 1200000 ] 45 97.826% 97.826% #################### ( 1200000, 1900000 ] 1 2.174% 100.000% Most recent cache entry stats: Number of entries: 1295133 Total charge: 9.88 GB Average key size: 23.4982 Average charge: 8.00 KB Unique deleters: 3 ``` Reviewed By: mrambacher Differential Revision: D28295742 Pulled By: pdillinger fbshipit-source-id: bbc4a552f91ba0fe10e5cc025c42cef5a81f2b95
2021-05-11 23:16:11 +00:00
}
void EraseUnRefEntries() override {
target_->EraseUnRefEntries();
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
key_only_cache_->EraseUnRefEntries();
}
size_t GetSimCapacity() const override {
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
return key_only_cache_->GetCapacity();
}
size_t GetSimUsage() const override { return key_only_cache_->GetUsage(); }
void SetSimCapacity(size_t capacity) override {
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
key_only_cache_->SetCapacity(capacity);
}
uint64_t get_miss_counter() const override {
return miss_times_.load(std::memory_order_relaxed);
}
uint64_t get_hit_counter() const override {
return hit_times_.load(std::memory_order_relaxed);
}
void reset_counter() override {
miss_times_.store(0, std::memory_order_relaxed);
hit_times_.store(0, std::memory_order_relaxed);
SetTickerCount(stats_, SIM_BLOCK_CACHE_HIT, 0);
SetTickerCount(stats_, SIM_BLOCK_CACHE_MISS, 0);
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
}
std::string ToString() const override {
std::ostringstream oss;
oss << "SimCache MISSes: " << get_miss_counter() << std::endl;
oss << "SimCache HITs: " << get_hit_counter() << std::endl;
auto lookups = get_miss_counter() + get_hit_counter();
oss << "SimCache HITRATE: " << std::fixed << std::setprecision(2)
<< (lookups == 0 ? 0 : get_hit_counter() * 100.0f / lookups)
<< std::endl;
return oss.str();
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
}
std::string GetPrintableOptions() const override {
std::ostringstream oss;
oss << " cache_options:" << std::endl;
oss << target_->GetPrintableOptions();
oss << " sim_cache_options:" << std::endl;
oss << key_only_cache_->GetPrintableOptions();
return oss.str();
}
Status StartActivityLogging(const std::string& activity_log_file, Env* env,
uint64_t max_logging_size = 0) override {
return cache_activity_logger_.StartLogging(activity_log_file, env,
max_logging_size);
}
void StopActivityLogging() override { cache_activity_logger_.StopLogging(); }
Status GetActivityLoggingStatus() override {
return cache_activity_logger_.bg_status();
}
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
private:
std::shared_ptr<Cache> key_only_cache_;
std::atomic<uint64_t> miss_times_;
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
std::atomic<uint64_t> hit_times_;
Statistics* stats_;
CacheActivityLogger cache_activity_logger_;
void inc_miss_counter() {
miss_times_.fetch_add(1, std::memory_order_relaxed);
}
void inc_hit_counter() { hit_times_.fetch_add(1, std::memory_order_relaxed); }
Major Cache refactoring, CPU efficiency improvement (#10975) Summary: This is several refactorings bundled into one to avoid having to incrementally re-modify uses of Cache several times. Overall, there are breaking changes to Cache class, and it becomes more of low-level interface for implementing caches, especially block cache. New internal APIs make using Cache cleaner than before, and more insulated from block cache evolution. Hopefully, this is the last really big block cache refactoring, because of rather effectively decoupling the implementations from the uses. This change also removes the EXPERIMENTAL designation on the SecondaryCache support in Cache. It seems reasonably mature at this point but still subject to change/evolution (as I warn in the API docs for Cache). The high-level motivation for this refactoring is to minimize code duplication / compounding complexity in adding SecondaryCache support to HyperClockCache (in a later PR). Other benefits listed below. * static_cast lines of code +29 -35 (net removed 6) * reinterpret_cast lines of code +6 -32 (net removed 26) ## cache.h and secondary_cache.h * Always use CacheItemHelper with entries instead of just a Deleter. There are several motivations / justifications: * Simpler for implementations to deal with just one Insert and one Lookup. * Simpler and more efficient implementation because we don't have to track which entries are using helpers and which are using deleters * Gets rid of hack to classify cache entries by their deleter. Instead, the CacheItemHelper includes a CacheEntryRole. This simplifies a lot of code (cache_entry_roles.h almost eliminated). Fixes https://github.com/facebook/rocksdb/issues/9428. * Makes it trivial to adjust SecondaryCache behavior based on kind of block (e.g. don't re-compress filter blocks). * It is arguably less convenient for many direct users of Cache, but direct users of Cache are now rare with introduction of typed_cache.h (below). * I considered and rejected an alternative approach in which we reduce customizability by assuming each secondary cache compatible value starts with a Slice referencing the uncompressed block contents (already true or mostly true), but we apparently intend to stack secondary caches. Saving an entry from a compressed secondary to a lower tier requires custom handling offered by SaveToCallback, etc. * Make CreateCallback part of the helper and introduce CreateContext to work with it (alternative to https://github.com/facebook/rocksdb/issues/10562). This cleans up the interface while still allowing context to be provided for loading/parsing values into primary cache. This model works for async lookup in BlockBasedTable reader (reader owns a CreateContext) under the assumption that it always waits on secondary cache operations to finish. (Otherwise, the CreateContext could be destroyed while async operation depending on it continues.) This likely contributes most to the observed performance improvement because it saves an std::function backed by a heap allocation. * Use char* for serialized data, e.g. in SaveToCallback, where void* was confusingly used. (We use `char*` for serialized byte data all over RocksDB, with many advantages over `void*`. `memcpy` etc. are legacy APIs that should not be mimicked.) * Add a type alias Cache::ObjectPtr = void*, so that we can better indicate the intent of the void* when it is to be the object associated with a Cache entry. Related: started (but did not complete) a refactoring to move away from "value" of a cache entry toward "object" or "obj". (It is confusing to call Cache a key-value store (like DB) when it is really storing arbitrary in-memory objects, not byte strings.) * Remove unnecessary key param from DeleterFn. This is good for efficiency in HyperClockCache, which does not directly store the cache key in memory. (Alternative to https://github.com/facebook/rocksdb/issues/10774) * Add allocator to Cache DeleterFn. This is a kind of future-proofing change in case we get more serious about using the Cache allocator for memory tracked by the Cache. Right now, only the uncompressed block contents are allocated using the allocator, and a pointer to that allocator is saved as part of the cached object so that the deleter can use it. (See CacheAllocationPtr.) If in the future we are able to "flatten out" our Cache objects some more, it would be good not to have to track the allocator as part of each object. * Removes legacy `ApplyToAllCacheEntries` and changes `ApplyToAllEntries` signature for Deleter->CacheItemHelper change. ## typed_cache.h Adds various "typed" interfaces to the Cache as internal APIs, so that most uses of Cache can use simple type safe code without casting and without explicit deleters, etc. Almost all of the non-test, non-glue code uses of Cache have been migrated. (Follow-up work: CompressedSecondaryCache deserves deeper attention to migrate.) This change expands RocksDB's internal usage of metaprogramming and SFINAE (https://en.cppreference.com/w/cpp/language/sfinae). The existing usages of Cache are divided up at a high level into these new interfaces. See updated existing uses of Cache for examples of how these are used. * PlaceholderCacheInterface - Used for making cache reservations, with entries that have a charge but no value. * BasicTypedCacheInterface<TValue> - Used for primary cache storage of objects of type TValue, which can be cleaned up with std::default_delete<TValue>. The role is provided by TValue::kCacheEntryRole or given in an optional template parameter. * FullTypedCacheInterface<TValue, TCreateContext> - Used for secondary cache compatible storage of objects of type TValue. In addition to BasicTypedCacheInterface constraints, we require TValue::ContentSlice() to return persistable data. This simplifies usage for the normal case of simple secondary cache compatibility (can give you a Slice to the data already in memory). In addition to TCreateContext performing the role of Cache::CreateContext, it is also expected to provide a factory function for creating TValue. * For each of these, there's a "Shared" version (e.g. FullTypedSharedCacheInterface) that holds a shared_ptr to the Cache, rather than assuming external ownership by holding only a raw `Cache*`. These interfaces introduce specific handle types for each interface instantiation, so that it's easy to see what kind of object is controlled by a handle. (Ultimately, this might not be worth the extra complexity, but it seems OK so far.) Note: I attempted to make the cache 'charge' automatically inferred from the cache object type, such as by expecting an ApproximateMemoryUsage() function, but this is not so clean because there are cases where we need to compute the charge ahead of time and don't want to re-compute it. ## block_cache.h This header is essentially the replacement for the old block_like_traits.h. It includes various things to support block cache access with typed_cache.h for block-based table. ## block_based_table_reader.cc Before this change, accessing the block cache here was an awkward mix of static polymorphism (template TBlocklike) and switch-case on a dynamic BlockType value. This change mostly unifies on static polymorphism, relying on minor hacks in block_cache.h to distinguish variants of Block. We still check BlockType in some places (especially for stats, which could be improved in follow-up work) but at least the BlockType is a static constant from the template parameter. (No more awkward partial redundancy between static and dynamic info.) This likely contributes to the overall performance improvement, but hasn't been tested in isolation. The other key source of simplification here is a more unified system of creating block cache objects: for directly populating from primary cache and for promotion from secondary cache. Both use BlockCreateContext, for context and for factory functions. ## block_based_table_builder.cc, cache_dump_load_impl.cc Before this change, warming caches was super ugly code. Both of these source files had switch statements to basically transition from the dynamic BlockType world to the static TBlocklike world. None of that mess is needed anymore as there's a new, untyped WarmInCache function that handles all the details just as promotion from SecondaryCache would. (Fixes `TODO akanksha: Dedup below code` in block_based_table_builder.cc.) ## Everything else Mostly just updating Cache users to use new typed APIs when reasonably possible, or changed Cache APIs when not. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10975 Test Plan: tests updated Performance test setup similar to https://github.com/facebook/rocksdb/issues/10626 (by cache size, LRUCache when not "hyper" for HyperClockCache): 34MB 1thread base.hyper -> kops/s: 0.745 io_bytes/op: 2.52504e+06 miss_ratio: 0.140906 max_rss_mb: 76.4844 34MB 1thread new.hyper -> kops/s: 0.751 io_bytes/op: 2.5123e+06 miss_ratio: 0.140161 max_rss_mb: 79.3594 34MB 1thread base -> kops/s: 0.254 io_bytes/op: 1.36073e+07 miss_ratio: 0.918818 max_rss_mb: 45.9297 34MB 1thread new -> kops/s: 0.252 io_bytes/op: 1.36157e+07 miss_ratio: 0.918999 max_rss_mb: 44.1523 34MB 32thread base.hyper -> kops/s: 7.272 io_bytes/op: 2.88323e+06 miss_ratio: 0.162532 max_rss_mb: 516.602 34MB 32thread new.hyper -> kops/s: 7.214 io_bytes/op: 2.99046e+06 miss_ratio: 0.168818 max_rss_mb: 518.293 34MB 32thread base -> kops/s: 3.528 io_bytes/op: 1.35722e+07 miss_ratio: 0.914691 max_rss_mb: 264.926 34MB 32thread new -> kops/s: 3.604 io_bytes/op: 1.35744e+07 miss_ratio: 0.915054 max_rss_mb: 264.488 233MB 1thread base.hyper -> kops/s: 53.909 io_bytes/op: 2552.35 miss_ratio: 0.0440566 max_rss_mb: 241.984 233MB 1thread new.hyper -> kops/s: 62.792 io_bytes/op: 2549.79 miss_ratio: 0.044043 max_rss_mb: 241.922 233MB 1thread base -> kops/s: 1.197 io_bytes/op: 2.75173e+06 miss_ratio: 0.103093 max_rss_mb: 241.559 233MB 1thread new -> kops/s: 1.199 io_bytes/op: 2.73723e+06 miss_ratio: 0.10305 max_rss_mb: 240.93 233MB 32thread base.hyper -> kops/s: 1298.69 io_bytes/op: 2539.12 miss_ratio: 0.0440307 max_rss_mb: 371.418 233MB 32thread new.hyper -> kops/s: 1421.35 io_bytes/op: 2538.75 miss_ratio: 0.0440307 max_rss_mb: 347.273 233MB 32thread base -> kops/s: 9.693 io_bytes/op: 2.77304e+06 miss_ratio: 0.103745 max_rss_mb: 569.691 233MB 32thread new -> kops/s: 9.75 io_bytes/op: 2.77559e+06 miss_ratio: 0.103798 max_rss_mb: 552.82 1597MB 1thread base.hyper -> kops/s: 58.607 io_bytes/op: 1449.14 miss_ratio: 0.0249324 max_rss_mb: 1583.55 1597MB 1thread new.hyper -> kops/s: 69.6 io_bytes/op: 1434.89 miss_ratio: 0.0247167 max_rss_mb: 1584.02 1597MB 1thread base -> kops/s: 60.478 io_bytes/op: 1421.28 miss_ratio: 0.024452 max_rss_mb: 1589.45 1597MB 1thread new -> kops/s: 63.973 io_bytes/op: 1416.07 miss_ratio: 0.0243766 max_rss_mb: 1589.24 1597MB 32thread base.hyper -> kops/s: 1436.2 io_bytes/op: 1357.93 miss_ratio: 0.0235353 max_rss_mb: 1692.92 1597MB 32thread new.hyper -> kops/s: 1605.03 io_bytes/op: 1358.04 miss_ratio: 0.023538 max_rss_mb: 1702.78 1597MB 32thread base -> kops/s: 280.059 io_bytes/op: 1350.34 miss_ratio: 0.023289 max_rss_mb: 1675.36 1597MB 32thread new -> kops/s: 283.125 io_bytes/op: 1351.05 miss_ratio: 0.0232797 max_rss_mb: 1703.83 Almost uniformly improving over base revision, especially for hot paths with HyperClockCache, up to 12% higher throughput seen (1597MB, 32thread, hyper). The improvement for that is likely coming from much simplified code for providing context for secondary cache promotion (CreateCallback/CreateContext), and possibly from less branching in block_based_table_reader. And likely a small improvement from not reconstituting key for DeleterFn. Reviewed By: anand1976 Differential Revision: D42417818 Pulled By: pdillinger fbshipit-source-id: f86bfdd584dce27c028b151ba56818ad14f7a432
2023-01-11 22:20:40 +00:00
void HandleLookup(const Slice& key, Statistics* stats) {
Handle* h = key_only_cache_->Lookup(key);
if (h != nullptr) {
key_only_cache_->Release(h);
inc_hit_counter();
RecordTick(stats, SIM_BLOCK_CACHE_HIT);
} else {
inc_miss_counter();
RecordTick(stats, SIM_BLOCK_CACHE_MISS);
}
cache_activity_logger_.ReportLookup(key);
}
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
};
} // end anonymous namespace
// For instrumentation purpose, use NewSimCache instead
std::shared_ptr<SimCache> NewSimCache(std::shared_ptr<Cache> cache,
size_t sim_capacity, int num_shard_bits) {
LRUCacheOptions co;
co.capacity = sim_capacity;
co.num_shard_bits = num_shard_bits;
co.metadata_charge_policy = kDontChargeCacheMetadata;
return NewSimCache(NewLRUCache(co), cache, num_shard_bits);
}
std::shared_ptr<SimCache> NewSimCache(std::shared_ptr<Cache> sim_cache,
std::shared_ptr<Cache> cache,
int num_shard_bits) {
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
if (num_shard_bits >= 20) {
return nullptr; // the cache cannot be sharded into too many fine pieces
}
return std::make_shared<SimCacheImpl>(sim_cache, cache);
add simulator Cache as class SimCache/SimLRUCache(with test) Summary: add class SimCache(base class with instrumentation api) and SimLRUCache(derived class with detailed implementation) which is used as an instrumented block cache that can predict hit rate for different cache size Test Plan: Add a test case in `db_block_cache_test.cc` called `SimCacheTest` to test basic logic of SimCache. Also add option `-simcache_size` in db_bench. if set with a value other than -1, then the benchmark will use this value as the size of the simulator cache and finally output the simulation result. ``` [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 1000000 RocksDB: version 4.8 Date: Tue May 17 16:56:16 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 6.809 micros/op 146874 ops/sec; 16.2 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.343 micros/op 157665 ops/sec; 17.4 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 986559 SimCache HITs: 264760 SimCache HITRATE: 26.84% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 10000000 RocksDB: version 4.8 Date: Tue May 17 16:57:10 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.066 micros/op 197394 ops/sec; 21.8 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.457 micros/op 154870 ops/sec; 17.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1059764 SimCache HITs: 374501 SimCache HITRATE: 35.34% [gzh@dev9927.prn1 ~/local/rocksdb] ./db_bench -benchmarks "fillseq,readrandom" -cache_size 1000000 -simcache_size 100000000 RocksDB: version 4.8 Date: Tue May 17 16:57:32 2016 CPU: 32 * Intel(R) Xeon(R) CPU E5-2660 0 @ 2.20GHz CPUCache: 20480 KB Keys: 16 bytes each Values: 100 bytes each (50 bytes after compression) Entries: 1000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 110.6 MB (estimated) FileSize: 62.9 MB (estimated) Write rate: 0 bytes/second Compression: Snappy Memtablerep: skip_list Perf Level: 0 WARNING: Assertions are enabled; benchmarks unnecessarily slow ------------------------------------------------ DB path: [/tmp/rocksdbtest-112628/dbbench] fillseq : 5.632 micros/op 177572 ops/sec; 19.6 MB/s DB path: [/tmp/rocksdbtest-112628/dbbench] readrandom : 6.892 micros/op 145094 ops/sec; 16.1 MB/s (1000000 of 1000000 found) SIMULATOR CACHE STATISTICS: SimCache LOOKUPs: 1150767 SimCache HITs: 1034535 SimCache HITRATE: 89.90% ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: MarkCallaghan, andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D57999
2016-05-24 06:35:23 +00:00
}
} // namespace ROCKSDB_NAMESPACE