|
|
|
// Copyright (c) 2013, Facebook, Inc. All rights reserved.
|
|
|
|
// This source code is licensed under the BSD-style license found in the
|
|
|
|
// LICENSE file in the root directory of this source tree. An additional grant
|
|
|
|
// of patent rights can be found in the PATENTS file in the same directory.
|
|
|
|
//
|
|
|
|
// Copyright (c) 2011 The LevelDB Authors. All rights reserved.
|
|
|
|
// Use of this source code is governed by a BSD-style license that can be
|
|
|
|
// found in the LICENSE file. See the AUTHORS file for names of contributors.
|
|
|
|
|
|
|
|
#ifndef __STDC_FORMAT_MACROS
|
|
|
|
#define __STDC_FORMAT_MACROS
|
|
|
|
#endif
|
|
|
|
|
|
|
|
#ifndef GFLAGS
|
|
|
|
#include <cstdio>
|
|
|
|
int main() {
|
|
|
|
fprintf(stderr, "Please install gflags to run rocksdb tools\n");
|
|
|
|
return 1;
|
|
|
|
}
|
|
|
|
#else
|
|
|
|
|
|
|
|
#ifdef NUMA
|
|
|
|
#include <numa.h>
|
|
|
|
#include <numaif.h>
|
|
|
|
#endif
|
|
|
|
|
|
|
|
#include <inttypes.h>
|
|
|
|
#include <cstddef>
|
|
|
|
#include <sys/types.h>
|
|
|
|
#include <stdio.h>
|
|
|
|
#include <stdlib.h>
|
|
|
|
#include <gflags/gflags.h>
|
|
|
|
#include "db/db_impl.h"
|
|
|
|
#include "db/version_set.h"
|
|
|
|
#include "rocksdb/options.h"
|
|
|
|
#include "rocksdb/cache.h"
|
|
|
|
#include "rocksdb/db.h"
|
|
|
|
#include "rocksdb/env.h"
|
|
|
|
#include "rocksdb/memtablerep.h"
|
|
|
|
#include "rocksdb/write_batch.h"
|
|
|
|
#include "rocksdb/slice.h"
|
|
|
|
#include "rocksdb/filter_policy.h"
|
|
|
|
#include "rocksdb/slice_transform.h"
|
|
|
|
#include "rocksdb/perf_context.h"
|
|
|
|
#include "port/port.h"
|
|
|
|
#include "port/stack_trace.h"
|
|
|
|
#include "util/crc32c.h"
|
|
|
|
#include "util/compression.h"
|
|
|
|
#include "util/histogram.h"
|
|
|
|
#include "util/mutexlock.h"
|
|
|
|
#include "util/random.h"
|
|
|
|
#include "util/string_util.h"
|
|
|
|
#include "util/statistics.h"
|
|
|
|
#include "util/testutil.h"
|
|
|
|
#include "util/xxhash.h"
|
|
|
|
#include "hdfs/env_hdfs.h"
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
#include "utilities/merge_operators.h"
|
|
|
|
|
|
|
|
using GFLAGS::ParseCommandLineFlags;
|
|
|
|
using GFLAGS::RegisterFlagValidator;
|
|
|
|
using GFLAGS::SetUsageMessage;
|
|
|
|
|
|
|
|
DEFINE_string(benchmarks,
|
|
|
|
"fillseq,"
|
|
|
|
"fillsync,"
|
|
|
|
"fillrandom,"
|
|
|
|
"overwrite,"
|
|
|
|
"readrandom,"
|
|
|
|
"newiterator,"
|
|
|
|
"newiteratorwhilewriting,"
|
|
|
|
"seekrandom,"
|
|
|
|
"seekrandomwhilewriting,"
|
|
|
|
"readseq,"
|
|
|
|
"readreverse,"
|
|
|
|
"compact,"
|
|
|
|
"readrandom,"
|
|
|
|
"multireadrandom,"
|
|
|
|
"readseq,"
|
|
|
|
"readtocache,"
|
|
|
|
"readreverse,"
|
|
|
|
"readwhilewriting,"
|
|
|
|
"readwhilemerging,"
|
|
|
|
"readrandomwriterandom,"
|
|
|
|
"updaterandom,"
|
|
|
|
"randomwithverify,"
|
|
|
|
"fill100K,"
|
|
|
|
"crc32c,"
|
|
|
|
"xxhash,"
|
|
|
|
"compress,"
|
|
|
|
"uncompress,"
|
SkipListRep::LookaheadIterator
Summary:
This diff introduces the `lookahead` argument to `SkipListFactory()`. This is an
optimization for the tailing use case which includes many seeks. E.g. consider
the following operations on a skip list iterator:
Seek(x), Next(), Next(), Seek(x+2), Next(), Seek(x+3), Next(), Next(), ...
If `lookahead` is positive, `SkipListRep` will return an iterator which also
keeps track of the previously visited node. Seek() then first does a linear
search starting from that node (up to `lookahead` steps). As in the tailing
example above, this may require fewer than ~log(n) comparisons as with regular
skip list search.
Test Plan:
Added a new benchmark (`fillseekseq`) which simulates the usage pattern. It
first writes N records (with consecutive keys), then measures how much time it
takes to read them by calling `Seek()` and `Next()`.
$ time ./db_bench -num 10000000 -benchmarks fillseekseq -prefix_size 1 \
-key_size 8 -write_buffer_size $[1024*1024*1024] -value_size 50 \
-seekseq_next 2 -skip_list_lookahead=0
[...]
DB path: [/dev/shm/rocksdbtest/dbbench]
fillseekseq : 0.389 micros/op 2569047 ops/sec;
real 0m21.806s
user 0m12.106s
sys 0m9.672s
$ time ./db_bench [...] -skip_list_lookahead=2
[...]
DB path: [/dev/shm/rocksdbtest/dbbench]
fillseekseq : 0.153 micros/op 6540684 ops/sec;
real 0m19.469s
user 0m10.192s
sys 0m9.252s
Reviewers: ljin, sdong, igor
Reviewed By: igor
Subscribers: dhruba, leveldb, march, lovro
Differential Revision: https://reviews.facebook.net/D23997
10 years ago
|
|
|
"acquireload,"
|
|
|
|
"fillseekseq,",
|
|
|
|
|
|
|
|
"Comma-separated list of operations to run in the specified order"
|
|
|
|
"Actual benchmarks:\n"
|
|
|
|
"\tfillseq -- write N values in sequential key"
|
|
|
|
" order in async mode\n"
|
|
|
|
"\tfillrandom -- write N values in random key order in async"
|
|
|
|
" mode\n"
|
|
|
|
"\toverwrite -- overwrite N values in random key order in"
|
|
|
|
" async mode\n"
|
|
|
|
"\tfillsync -- write N/100 values in random key order in "
|
|
|
|
"sync mode\n"
|
|
|
|
"\tfill100K -- write N/1000 100K values in random order in"
|
|
|
|
" async mode\n"
|
|
|
|
"\tdeleteseq -- delete N keys in sequential order\n"
|
|
|
|
"\tdeleterandom -- delete N keys in random order\n"
|
|
|
|
"\treadseq -- read N times sequentially\n"
|
|
|
|
"\treadtocache -- 1 thread reading database sequentially\n"
|
|
|
|
"\treadreverse -- read N times in reverse order\n"
|
|
|
|
"\treadrandom -- read N times in random order\n"
|
|
|
|
"\treadmissing -- read N missing keys in random order\n"
|
|
|
|
"\treadhot -- read N times in random order from 1% section "
|
|
|
|
"of DB\n"
|
|
|
|
"\treadwhilewriting -- 1 writer, N threads doing random "
|
|
|
|
"reads\n"
|
|
|
|
"\treadwhilemerging -- 1 merger, N threads doing random "
|
|
|
|
"reads\n"
|
|
|
|
"\treadrandomwriterandom -- N threads doing random-read, "
|
|
|
|
"random-write\n"
|
|
|
|
"\tprefixscanrandom -- prefix scan N times in random order\n"
|
|
|
|
"\tupdaterandom -- N threads doing read-modify-write for random "
|
|
|
|
"keys\n"
|
|
|
|
"\tappendrandom -- N threads doing read-modify-write with "
|
|
|
|
"growing values\n"
|
|
|
|
"\tmergerandom -- same as updaterandom/appendrandom using merge"
|
|
|
|
" operator. "
|
|
|
|
"Must be used with merge_operator\n"
|
|
|
|
"\treadrandommergerandom -- perform N random read-or-merge "
|
|
|
|
"operations. Must be used with merge_operator\n"
|
|
|
|
"\tnewiterator -- repeated iterator creation\n"
|
|
|
|
"\tseekrandom -- N random seeks\n"
|
|
|
|
"\tseekrandom -- 1 writer, N threads doing random seeks\n"
|
|
|
|
"\tcrc32c -- repeated crc32c of 4K of data\n"
|
|
|
|
"\txxhash -- repeated xxHash of 4K of data\n"
|
|
|
|
"\tacquireload -- load N*1000 times\n"
|
SkipListRep::LookaheadIterator
Summary:
This diff introduces the `lookahead` argument to `SkipListFactory()`. This is an
optimization for the tailing use case which includes many seeks. E.g. consider
the following operations on a skip list iterator:
Seek(x), Next(), Next(), Seek(x+2), Next(), Seek(x+3), Next(), Next(), ...
If `lookahead` is positive, `SkipListRep` will return an iterator which also
keeps track of the previously visited node. Seek() then first does a linear
search starting from that node (up to `lookahead` steps). As in the tailing
example above, this may require fewer than ~log(n) comparisons as with regular
skip list search.
Test Plan:
Added a new benchmark (`fillseekseq`) which simulates the usage pattern. It
first writes N records (with consecutive keys), then measures how much time it
takes to read them by calling `Seek()` and `Next()`.
$ time ./db_bench -num 10000000 -benchmarks fillseekseq -prefix_size 1 \
-key_size 8 -write_buffer_size $[1024*1024*1024] -value_size 50 \
-seekseq_next 2 -skip_list_lookahead=0
[...]
DB path: [/dev/shm/rocksdbtest/dbbench]
fillseekseq : 0.389 micros/op 2569047 ops/sec;
real 0m21.806s
user 0m12.106s
sys 0m9.672s
$ time ./db_bench [...] -skip_list_lookahead=2
[...]
DB path: [/dev/shm/rocksdbtest/dbbench]
fillseekseq : 0.153 micros/op 6540684 ops/sec;
real 0m19.469s
user 0m10.192s
sys 0m9.252s
Reviewers: ljin, sdong, igor
Reviewed By: igor
Subscribers: dhruba, leveldb, march, lovro
Differential Revision: https://reviews.facebook.net/D23997
10 years ago
|
|
|
"\tfillseekseq -- write N values in sequential key, then read "
|
|
|
|
"them by seeking to each key\n"
|
|
|
|
"Meta operations:\n"
|
|
|
|
"\tcompact -- Compact the entire DB\n"
|
|
|
|
"\tstats -- Print DB stats\n"
|
|
|
|
"\tlevelstats -- Print the number of files and bytes per level\n"
|
|
|
|
"\tsstables -- Print sstable info\n"
|
|
|
|
"\theapprofile -- Dump a heap profile (if supported by this"
|
|
|
|
" port)\n");
|
|
|
|
|
|
|
|
DEFINE_int64(num, 1000000, "Number of key/values to place in database");
|
|
|
|
|
|
|
|
DEFINE_int64(numdistinct, 1000,
|
|
|
|
"Number of distinct keys to use. Used in RandomWithVerify to "
|
|
|
|
"read/write on fewer keys so that gets are more likely to find the"
|
|
|
|
" key and puts are more likely to update the same key");
|
|
|
|
|
|
|
|
DEFINE_int64(merge_keys, -1,
|
|
|
|
"Number of distinct keys to use for MergeRandom and "
|
|
|
|
"ReadRandomMergeRandom. "
|
|
|
|
"If negative, there will be FLAGS_num keys.");
|
|
|
|
DEFINE_int32(num_column_families, 1, "Number of Column Families to use.");
|
|
|
|
|
|
|
|
DEFINE_int32(
|
|
|
|
num_hot_column_families, 0,
|
|
|
|
"Number of Hot Column Families. If more than 0, only write to this "
|
|
|
|
"number of column families. After finishing all the writes to them, "
|
|
|
|
"create new set of column families and insert to them. Only used "
|
|
|
|
"when num_column_families > 1.");
|
|
|
|
|
|
|
|
DEFINE_int64(reads, -1, "Number of read operations to do. "
|
|
|
|
"If negative, do FLAGS_num reads.");
|
|
|
|
|
|
|
|
DEFINE_int32(bloom_locality, 0, "Control bloom filter probes locality");
|
|
|
|
|
|
|
|
DEFINE_int64(seed, 0, "Seed base for random number generators. "
|
|
|
|
"When 0 it is deterministic.");
|
|
|
|
|
|
|
|
DEFINE_int32(threads, 1, "Number of concurrent threads to run.");
|
|
|
|
|
|
|
|
DEFINE_int32(duration, 0, "Time in seconds for the random-ops tests to run."
|
|
|
|
" When 0 then num & reads determine the test duration");
|
|
|
|
|
|
|
|
DEFINE_int32(value_size, 100, "Size of each value");
|
|
|
|
|
|
|
|
DEFINE_int32(seek_nexts, 0,
|
|
|
|
"How many times to call Next() after Seek() in "
|
|
|
|
"fillseekseq and seekrandom");
|
SkipListRep::LookaheadIterator
Summary:
This diff introduces the `lookahead` argument to `SkipListFactory()`. This is an
optimization for the tailing use case which includes many seeks. E.g. consider
the following operations on a skip list iterator:
Seek(x), Next(), Next(), Seek(x+2), Next(), Seek(x+3), Next(), Next(), ...
If `lookahead` is positive, `SkipListRep` will return an iterator which also
keeps track of the previously visited node. Seek() then first does a linear
search starting from that node (up to `lookahead` steps). As in the tailing
example above, this may require fewer than ~log(n) comparisons as with regular
skip list search.
Test Plan:
Added a new benchmark (`fillseekseq`) which simulates the usage pattern. It
first writes N records (with consecutive keys), then measures how much time it
takes to read them by calling `Seek()` and `Next()`.
$ time ./db_bench -num 10000000 -benchmarks fillseekseq -prefix_size 1 \
-key_size 8 -write_buffer_size $[1024*1024*1024] -value_size 50 \
-seekseq_next 2 -skip_list_lookahead=0
[...]
DB path: [/dev/shm/rocksdbtest/dbbench]
fillseekseq : 0.389 micros/op 2569047 ops/sec;
real 0m21.806s
user 0m12.106s
sys 0m9.672s
$ time ./db_bench [...] -skip_list_lookahead=2
[...]
DB path: [/dev/shm/rocksdbtest/dbbench]
fillseekseq : 0.153 micros/op 6540684 ops/sec;
real 0m19.469s
user 0m10.192s
sys 0m9.252s
Reviewers: ljin, sdong, igor
Reviewed By: igor
Subscribers: dhruba, leveldb, march, lovro
Differential Revision: https://reviews.facebook.net/D23997
10 years ago
|
|
|
|
|
|
|
DEFINE_bool(reverse_iterator, false,
|
|
|
|
"When true use Prev rather than Next for iterators that do "
|
|
|
|
"Seek and then Next");
|
|
|
|
|
|
|
|
DEFINE_bool(use_uint64_comparator, false, "use Uint64 user comparator");
|
|
|
|
|
|
|
|
DEFINE_int64(batch_size, 1, "Batch size");
|
|
|
|
|
|
|
|
static bool ValidateKeySize(const char* flagname, int32_t value) {
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
|
|
|
|
DEFINE_int32(key_size, 16, "size of each key");
|
|
|
|
|
|
|
|
DEFINE_int32(num_multi_db, 0,
|
|
|
|
"Number of DBs used in the benchmark. 0 means single DB.");
|
|
|
|
|
|
|
|
DEFINE_double(compression_ratio, 0.5, "Arrange to generate values that shrink"
|
|
|
|
" to this fraction of their original size after compression");
|
|
|
|
|
|
|
|
DEFINE_double(read_random_exp_range, 0.0,
|
|
|
|
"Read random's key will be generated using distribution of "
|
|
|
|
"num * exp(r) where r is uniform number from 0 to this value. "
|
|
|
|
"The larger the number is, the more skewed the reads are. "
|
|
|
|
"Only used in readrandom and multireadrandom benchmarks.");
|
|
|
|
|
|
|
|
DEFINE_bool(histogram, false, "Print histogram of operation timings");
|
|
|
|
|
|
|
|
DEFINE_bool(enable_numa, false,
|
|
|
|
"Make operations aware of NUMA architecture and bind memory "
|
|
|
|
"and cpus corresponding to nodes together. In NUMA, memory "
|
|
|
|
"in same node as CPUs are closer when compared to memory in "
|
|
|
|
"other nodes. Reads can be faster when the process is bound to "
|
|
|
|
"CPU and memory of same node. Use \"$numactl --hardware\" command "
|
|
|
|
"to see NUMA memory architecture.");
|
|
|
|
|
|
|
|
DEFINE_int64(db_write_buffer_size, rocksdb::Options().db_write_buffer_size,
|
|
|
|
"Number of bytes to buffer in all memtables before compacting");
|
|
|
|
|
Add monitoring for universal compaction and add counters for compaction IO
Summary:
Adds these counters
{ WAL_FILE_SYNCED, "rocksdb.wal.synced" }
number of writes that request a WAL sync
{ WAL_FILE_BYTES, "rocksdb.wal.bytes" },
number of bytes written to the WAL
{ WRITE_DONE_BY_SELF, "rocksdb.write.self" },
number of writes processed by the calling thread
{ WRITE_DONE_BY_OTHER, "rocksdb.write.other" },
number of writes not processed by the calling thread. Instead these were
processed by the current holder of the write lock
{ WRITE_WITH_WAL, "rocksdb.write.wal" },
number of writes that request WAL logging
{ COMPACT_READ_BYTES, "rocksdb.compact.read.bytes" },
number of bytes read during compaction
{ COMPACT_WRITE_BYTES, "rocksdb.compact.write.bytes" },
number of bytes written during compaction
Per-interval stats output was updated with WAL stats and correct stats for universal compaction
including a correct value for write-amplification. It now looks like:
Compactions
Level Files Size(MB) Score Time(sec) Read(MB) Write(MB) Rn(MB) Rnp1(MB) Wnew(MB) RW-Amplify Read(MB/s) Write(MB/s) Rn Rnp1 Wnp1 NewW Count Ln-stall Stall-cnt
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
0 7 464 46.4 281 3411 3875 3411 0 3875 2.1 12.1 13.8 621 0 240 240 628 0.0 0
Uptime(secs): 310.8 total, 2.0 interval
Writes cumulative: 9999999 total, 9999999 batches, 1.0 per batch, 1.22 ingest GB
WAL cumulative: 9999999 WAL writes, 9999999 WAL syncs, 1.00 writes per sync, 1.22 GB written
Compaction IO cumulative (GB): 1.22 new, 3.33 read, 3.78 write, 7.12 read+write
Compaction IO cumulative (MB/sec): 4.0 new, 11.0 read, 12.5 write, 23.4 read+write
Amplification cumulative: 4.1 write, 6.8 compaction
Writes interval: 100000 total, 100000 batches, 1.0 per batch, 12.5 ingest MB
WAL interval: 100000 WAL writes, 100000 WAL syncs, 1.00 writes per sync, 0.01 MB written
Compaction IO interval (MB): 12.49 new, 14.98 read, 21.50 write, 36.48 read+write
Compaction IO interval (MB/sec): 6.4 new, 7.6 read, 11.0 write, 18.6 read+write
Amplification interval: 101.7 write, 102.9 compaction
Stalls(secs): 142.924 level0_slowdown, 0.000 level0_numfiles, 0.805 memtable_compaction, 0.000 leveln_slowdown
Stalls(count): 132461 level0_slowdown, 0 level0_numfiles, 3 memtable_compaction, 0 leveln_slowdown
Task ID: #3329644, #3301695
Blame Rev:
Test Plan:
Revert Plan:
Database Impact:
Memcache Impact:
Other Notes:
EImportant:
- begin *PUBLIC* platform impact section -
Bugzilla: #
- end platform impact -
Reviewers: dhruba
CC: leveldb
Differential Revision: https://reviews.facebook.net/D14583
11 years ago
|
|
|
DEFINE_int64(write_buffer_size, rocksdb::Options().write_buffer_size,
|
|
|
|
"Number of bytes to buffer in memtable before compacting");
|
|
|
|
|
|
|
|
DEFINE_int32(max_write_buffer_number,
|
|
|
|
rocksdb::Options().max_write_buffer_number,
|
|
|
|
"The number of in-memory memtables. Each memtable is of size"
|
|
|
|
"write_buffer_size.");
|
|
|
|
|
|
|
|
DEFINE_int32(min_write_buffer_number_to_merge,
|
|
|
|
rocksdb::Options().min_write_buffer_number_to_merge,
|
|
|
|
"The minimum number of write buffers that will be merged together"
|
|
|
|
"before writing to storage. This is cheap because it is an"
|
|
|
|
"in-memory merge. If this feature is not enabled, then all these"
|
|
|
|
"write buffers are flushed to L0 as separate files and this "
|
|
|
|
"increases read amplification because a get request has to check"
|
|
|
|
" in all of these files. Also, an in-memory merge may result in"
|
|
|
|
" writing less data to storage if there are duplicate records "
|
|
|
|
" in each of these individual write buffers.");
|
|
|
|
|
|
|
|
DEFINE_int32(max_background_compactions,
|
|
|
|
rocksdb::Options().max_background_compactions,
|
|
|
|
"The maximum number of concurrent background compactions"
|
|
|
|
" that can occur in parallel.");
|
|
|
|
|
|
|
|
DEFINE_int32(max_background_flushes,
|
|
|
|
rocksdb::Options().max_background_flushes,
|
|
|
|
"The maximum number of concurrent background flushes"
|
|
|
|
" that can occur in parallel.");
|
|
|
|
|
|
|
|
static rocksdb::CompactionStyle FLAGS_compaction_style_e;
|
|
|
|
DEFINE_int32(compaction_style, (int32_t) rocksdb::Options().compaction_style,
|
|
|
|
"style of compaction: level-based vs universal");
|
|
|
|
|
|
|
|
DEFINE_int32(universal_size_ratio, 0,
|
|
|
|
"Percentage flexibility while comparing file size"
|
|
|
|
" (for universal compaction only).");
|
|
|
|
|
|
|
|
DEFINE_int32(universal_min_merge_width, 0, "The minimum number of files in a"
|
|
|
|
" single compaction run (for universal compaction only).");
|
|
|
|
|
|
|
|
DEFINE_int32(universal_max_merge_width, 0, "The max number of files to compact"
|
|
|
|
" in universal style compaction");
|
|
|
|
|
|
|
|
DEFINE_int32(universal_max_size_amplification_percent, 0,
|
|
|
|
"The max size amplification for universal style compaction");
|
|
|
|
|
|
|
|
DEFINE_int32(universal_compression_size_percent, -1,
|
|
|
|
"The percentage of the database to compress for universal "
|
|
|
|
"compaction. -1 means compress everything.");
|
|
|
|
|
|
|
|
DEFINE_int64(cache_size, -1, "Number of bytes to use as a cache of uncompressed"
|
|
|
|
"data. Negative means use default settings.");
|
|
|
|
|
|
|
|
DEFINE_int32(block_size,
|
|
|
|
static_cast<int32_t>(rocksdb::BlockBasedTableOptions().block_size),
|
|
|
|
"Number of bytes in a block.");
|
|
|
|
|
|
|
|
DEFINE_int32(block_restart_interval,
|
|
|
|
rocksdb::BlockBasedTableOptions().block_restart_interval,
|
|
|
|
"Number of keys between restart points "
|
|
|
|
"for delta encoding of keys.");
|
|
|
|
|
|
|
|
DEFINE_int64(compressed_cache_size, -1,
|
|
|
|
"Number of bytes to use as a cache of compressed data.");
|
|
|
|
|
|
|
|
DEFINE_int32(open_files, rocksdb::Options().max_open_files,
|
|
|
|
"Maximum number of files to keep open at the same time"
|
|
|
|
" (use default if == 0)");
|
|
|
|
|
|
|
|
DEFINE_int32(bloom_bits, -1, "Bloom filter bits per key. Negative means"
|
|
|
|
" use default settings.");
|
|
|
|
DEFINE_int32(memtable_bloom_bits, 0, "Bloom filter bits per key for memtable. "
|
|
|
|
"Negative means no bloom filter.");
|
|
|
|
|
|
|
|
DEFINE_bool(use_existing_db, false, "If true, do not destroy the existing"
|
|
|
|
" database. If you set this flag and also specify a benchmark that"
|
|
|
|
" wants a fresh database, that benchmark will fail.");
|
|
|
|
|
|
|
|
DEFINE_string(db, "", "Use the db with the following name.");
|
|
|
|
|
|
|
|
static bool ValidateCacheNumshardbits(const char* flagname, int32_t value) {
|
|
|
|
if (value >= 20) {
|
|
|
|
fprintf(stderr, "Invalid value for --%s: %d, must be < 20\n",
|
|
|
|
flagname, value);
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
DEFINE_int32(cache_numshardbits, -1, "Number of shards for the block cache"
|
|
|
|
" is 2 ** cache_numshardbits. Negative means use default settings."
|
|
|
|
" This is applied only if FLAGS_cache_size is non-negative.");
|
|
|
|
|
|
|
|
DEFINE_bool(verify_checksum, false, "Verify checksum for every block read"
|
|
|
|
" from storage");
|
|
|
|
|
|
|
|
DEFINE_bool(statistics, false, "Database statistics");
|
|
|
|
static class std::shared_ptr<rocksdb::Statistics> dbstats;
|
|
|
|
|
|
|
|
DEFINE_int64(writes, -1, "Number of write operations to do. If negative, do"
|
|
|
|
" --num reads.");
|
|
|
|
|
|
|
|
DEFINE_int32(writes_per_second, 0, "Per-thread rate limit on writes and merges "
|
|
|
|
" per second. No limit when <= 0. Only for the readwhilewriting "
|
|
|
|
" and readwhilemerging tests.");
|
|
|
|
|
|
|
|
DEFINE_bool(sync, false, "Sync all writes to disk");
|
|
|
|
|
|
|
|
DEFINE_bool(disable_data_sync, false, "If true, do not wait until data is"
|
|
|
|
" synced to disk.");
|
|
|
|
|
|
|
|
DEFINE_bool(use_fsync, false, "If true, issue fsync instead of fdatasync");
|
|
|
|
|
|
|
|
DEFINE_bool(disable_wal, false, "If true, do not write WAL for write.");
|
|
|
|
|
|
|
|
DEFINE_string(wal_dir, "", "If not empty, use the given dir for WAL");
|
|
|
|
|
|
|
|
DEFINE_int32(num_levels, 7, "The total number of levels");
|
|
|
|
|
|
|
|
DEFINE_int64(target_file_size_base, 2 * 1048576, "Target file size at level-1");
|
|
|
|
|
|
|
|
DEFINE_int32(target_file_size_multiplier, 1,
|
|
|
|
"A multiplier to compute target level-N file size (N >= 2)");
|
|
|
|
|
|
|
|
DEFINE_uint64(max_bytes_for_level_base, 10 * 1048576, "Max bytes for level-1");
|
|
|
|
|
options.level_compaction_dynamic_level_bytes to allow RocksDB to pick size bases of levels dynamically.
Summary:
When having fixed max_bytes_for_level_base, the ratio of size of largest level and the second one can range from 0 to the multiplier. This makes LSM tree frequently irregular and unpredictable. It can also cause poor space amplification in some cases.
In this improvement (proposed by Igor Kabiljo), we introduce a parameter option.level_compaction_use_dynamic_max_bytes. When turning it on, RocksDB is free to pick a level base in the range of (options.max_bytes_for_level_base/options.max_bytes_for_level_multiplier, options.max_bytes_for_level_base] so that real level ratios are close to options.max_bytes_for_level_multiplier.
Test Plan: New unit tests and pass tests suites including valgrind.
Reviewers: MarkCallaghan, rven, yhchiang, igor, ikabiljo
Reviewed By: ikabiljo
Subscribers: yoshinorim, ikabiljo, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D31437
10 years ago
|
|
|
DEFINE_bool(level_compaction_dynamic_level_bytes, false,
|
|
|
|
"Whether level size base is dynamic");
|
|
|
|
|
|
|
|
DEFINE_int32(max_bytes_for_level_multiplier, 10,
|
|
|
|
"A multiplier to compute max bytes for level-N (N >= 2)");
|
|
|
|
|
|
|
|
static std::vector<int> FLAGS_max_bytes_for_level_multiplier_additional_v;
|
|
|
|
DEFINE_string(max_bytes_for_level_multiplier_additional, "",
|
|
|
|
"A vector that specifies additional fanout per level");
|
|
|
|
|
|
|
|
DEFINE_int32(level0_stop_writes_trigger, 12, "Number of files in level-0"
|
|
|
|
" that will trigger put stop.");
|
|
|
|
|
|
|
|
DEFINE_int32(level0_slowdown_writes_trigger, 8, "Number of files in level-0"
|
|
|
|
" that will slow down writes.");
|
|
|
|
|
|
|
|
DEFINE_int32(level0_file_num_compaction_trigger, 4, "Number of files in level-0"
|
|
|
|
" when compactions start");
|
|
|
|
|
|
|
|
static bool ValidateInt32Percent(const char* flagname, int32_t value) {
|
|
|
|
if (value <= 0 || value>=100) {
|
|
|
|
fprintf(stderr, "Invalid value for --%s: %d, 0< pct <100 \n",
|
|
|
|
flagname, value);
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
DEFINE_int32(readwritepercent, 90, "Ratio of reads to reads/writes (expressed"
|
|
|
|
" as percentage) for the ReadRandomWriteRandom workload. The "
|
|
|
|
"default value 90 means 90% operations out of all reads and writes"
|
|
|
|
" operations are reads. In other words, 9 gets for every 1 put.");
|
|
|
|
|
|
|
|
DEFINE_int32(mergereadpercent, 70, "Ratio of merges to merges&reads (expressed"
|
|
|
|
" as percentage) for the ReadRandomMergeRandom workload. The"
|
|
|
|
" default value 70 means 70% out of all read and merge operations"
|
|
|
|
" are merges. In other words, 7 merges for every 3 gets.");
|
|
|
|
|
|
|
|
DEFINE_int32(deletepercent, 2, "Percentage of deletes out of reads/writes/"
|
|
|
|
"deletes (used in RandomWithVerify only). RandomWithVerify "
|
|
|
|
"calculates writepercent as (100 - FLAGS_readwritepercent - "
|
|
|
|
"deletepercent), so deletepercent must be smaller than (100 - "
|
|
|
|
"FLAGS_readwritepercent)");
|
|
|
|
|
|
|
|
DEFINE_uint64(delete_obsolete_files_period_micros, 0,
|
|
|
|
"Ignored. Left here for backward compatibility");
|
|
|
|
|
|
|
|
namespace {
|
|
|
|
enum rocksdb::CompressionType StringToCompressionType(const char* ctype) {
|
|
|
|
assert(ctype);
|
|
|
|
|
|
|
|
if (!strcasecmp(ctype, "none"))
|
|
|
|
return rocksdb::kNoCompression;
|
|
|
|
else if (!strcasecmp(ctype, "snappy"))
|
|
|
|
return rocksdb::kSnappyCompression;
|
|
|
|
else if (!strcasecmp(ctype, "zlib"))
|
|
|
|
return rocksdb::kZlibCompression;
|
|
|
|
else if (!strcasecmp(ctype, "bzip2"))
|
|
|
|
return rocksdb::kBZip2Compression;
|
|
|
|
else if (!strcasecmp(ctype, "lz4"))
|
|
|
|
return rocksdb::kLZ4Compression;
|
|
|
|
else if (!strcasecmp(ctype, "lz4hc"))
|
|
|
|
return rocksdb::kLZ4HCCompression;
|
|
|
|
|
|
|
|
fprintf(stdout, "Cannot parse compression type '%s'\n", ctype);
|
|
|
|
return rocksdb::kSnappyCompression; //default value
|
|
|
|
}
|
|
|
|
|
|
|
|
std::string ColumnFamilyName(size_t i) {
|
|
|
|
if (i == 0) {
|
|
|
|
return rocksdb::kDefaultColumnFamilyName;
|
|
|
|
} else {
|
|
|
|
char name[100];
|
|
|
|
snprintf(name, sizeof(name), "column_family_name_%06zu", i);
|
|
|
|
return std::string(name);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
} // namespace
|
|
|
|
|
|
|
|
DEFINE_string(compression_type, "snappy",
|
|
|
|
"Algorithm to use to compress the database");
|
|
|
|
static enum rocksdb::CompressionType FLAGS_compression_type_e =
|
|
|
|
rocksdb::kSnappyCompression;
|
|
|
|
|
|
|
|
DEFINE_int32(compression_level, -1,
|
|
|
|
"Compression level. For zlib this should be -1 for the "
|
|
|
|
"default level, or between 0 and 9.");
|
|
|
|
|
|
|
|
static bool ValidateCompressionLevel(const char* flagname, int32_t value) {
|
|
|
|
if (value < -1 || value > 9) {
|
|
|
|
fprintf(stderr, "Invalid value for --%s: %d, must be between -1 and 9\n",
|
|
|
|
flagname, value);
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
|
|
|
|
static const bool FLAGS_compression_level_dummy __attribute__((unused)) =
|
|
|
|
RegisterFlagValidator(&FLAGS_compression_level, &ValidateCompressionLevel);
|
|
|
|
|
|
|
|
DEFINE_int32(min_level_to_compress, -1, "If non-negative, compression starts"
|
|
|
|
" from this level. Levels with number < min_level_to_compress are"
|
|
|
|
" not compressed. Otherwise, apply compression_type to "
|
|
|
|
"all levels.");
|
|
|
|
|
|
|
|
static bool ValidateTableCacheNumshardbits(const char* flagname,
|
|
|
|
int32_t value) {
|
|
|
|
if (0 >= value || value > 20) {
|
|
|
|
fprintf(stderr, "Invalid value for --%s: %d, must be 0 < val <= 20\n",
|
|
|
|
flagname, value);
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
DEFINE_int32(table_cache_numshardbits, 4, "");
|
|
|
|
|
|
|
|
DEFINE_string(hdfs, "", "Name of hdfs environment");
|
|
|
|
// posix or hdfs environment
|
|
|
|
static rocksdb::Env* FLAGS_env = rocksdb::Env::Default();
|
|
|
|
|
|
|
|
DEFINE_int64(stats_interval, 0, "Stats are reported every N operations when "
|
|
|
|
"this is greater than zero. When 0 the interval grows over time.");
|
|
|
|
|
|
|
|
DEFINE_int32(stats_per_interval, 0, "Reports additional stats per interval when"
|
|
|
|
" this is greater than 0.");
|
|
|
|
|
|
|
|
DEFINE_int32(thread_status_per_interval, 0,
|
|
|
|
"Takes and report a snapshot of the current status of each thread"
|
|
|
|
" when this is greater than 0.");
|
|
|
|
|
|
|
|
DEFINE_int32(perf_level, 0, "Level of perf collection");
|
|
|
|
|
|
|
|
static bool ValidateRateLimit(const char* flagname, double value) {
|
|
|
|
static constexpr double EPSILON = 1e-10;
|
|
|
|
if ( value < -EPSILON ) {
|
|
|
|
fprintf(stderr, "Invalid value for --%s: %12.6f, must be >= 0.0\n",
|
|
|
|
flagname, value);
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
DEFINE_double(soft_rate_limit, 0.0, "");
|
|
|
|
|
|
|
|
DEFINE_double(hard_rate_limit, 0.0, "When not equal to 0 this make threads "
|
|
|
|
"sleep at each stats reporting interval until the compaction"
|
|
|
|
" score for all levels is less than or equal to this value.");
|
|
|
|
|
|
|
|
DEFINE_int32(rate_limit_delay_max_milliseconds, 1000,
|
|
|
|
"When hard_rate_limit is set then this is the max time a put will"
|
|
|
|
" be stalled.");
|
|
|
|
|
|
|
|
DEFINE_int32(max_grandparent_overlap_factor, 10, "Control maximum bytes of "
|
|
|
|
"overlaps in grandparent (i.e., level+2) before we stop building a"
|
|
|
|
" single file in a level->level+1 compaction.");
|
|
|
|
|
|
|
|
DEFINE_bool(readonly, false, "Run read only benchmarks.");
|
|
|
|
|
|
|
|
DEFINE_bool(disable_auto_compactions, false, "Do not auto trigger compactions");
|
|
|
|
|
|
|
|
DEFINE_int32(source_compaction_factor, 1, "Cap the size of data in level-K for"
|
|
|
|
" a compaction run that compacts Level-K with Level-(K+1) (for"
|
|
|
|
" K >= 1)");
|
|
|
|
|
|
|
|
DEFINE_uint64(wal_ttl_seconds, 0, "Set the TTL for the WAL Files in seconds.");
|
|
|
|
DEFINE_uint64(wal_size_limit_MB, 0, "Set the size limit for the WAL Files"
|
|
|
|
" in MB.");
|
|
|
|
DEFINE_uint64(max_total_wal_size, 0, "Set total max WAL size");
|
|
|
|
|
|
|
|
DEFINE_bool(bufferedio, rocksdb::EnvOptions().use_os_buffer,
|
|
|
|
"Allow buffered io using OS buffers");
|
|
|
|
|
|
|
|
DEFINE_bool(mmap_read, rocksdb::EnvOptions().use_mmap_reads,
|
|
|
|
"Allow reads to occur via mmap-ing files");
|
|
|
|
|
|
|
|
DEFINE_bool(mmap_write, rocksdb::EnvOptions().use_mmap_writes,
|
|
|
|
"Allow writes to occur via mmap-ing files");
|
|
|
|
|
|
|
|
DEFINE_bool(advise_random_on_open, rocksdb::Options().advise_random_on_open,
|
|
|
|
"Advise random access on table file open");
|
|
|
|
|
|
|
|
DEFINE_string(compaction_fadvice, "NORMAL",
|
|
|
|
"Access pattern advice when a file is compacted");
|
|
|
|
static auto FLAGS_compaction_fadvice_e =
|
|
|
|
rocksdb::Options().access_hint_on_compaction_start;
|
|
|
|
|
|
|
|
DEFINE_bool(use_tailing_iterator, false,
|
|
|
|
"Use tailing iterator to access a series of keys instead of get");
|
|
|
|
DEFINE_int64(iter_refresh_interval_us, -1,
|
|
|
|
"How often to refresh iterators. Disable refresh when -1");
|
|
|
|
|
|
|
|
DEFINE_bool(use_adaptive_mutex, rocksdb::Options().use_adaptive_mutex,
|
|
|
|
"Use adaptive mutex");
|
|
|
|
|
|
|
|
DEFINE_uint64(bytes_per_sync, rocksdb::Options().bytes_per_sync,
|
|
|
|
"Allows OS to incrementally sync files to disk while they are"
|
|
|
|
" being written, in the background. Issue one request for every"
|
|
|
|
" bytes_per_sync written. 0 turns it off.");
|
|
|
|
DEFINE_bool(filter_deletes, false, " On true, deletes use bloom-filter and drop"
|
|
|
|
" the delete if key not present");
|
|
|
|
|
|
|
|
DEFINE_int32(max_successive_merges, 0, "Maximum number of successive merge"
|
|
|
|
" operations on a key in the memtable");
|
|
|
|
|
|
|
|
static bool ValidatePrefixSize(const char* flagname, int32_t value) {
|
|
|
|
if (value < 0 || value>=2000000000) {
|
|
|
|
fprintf(stderr, "Invalid value for --%s: %d. 0<= PrefixSize <=2000000000\n",
|
|
|
|
flagname, value);
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
DEFINE_int32(prefix_size, 0, "control the prefix size for HashSkipList and "
|
|
|
|
"plain table");
|
|
|
|
DEFINE_int64(keys_per_prefix, 0, "control average number of keys generated "
|
|
|
|
"per prefix, 0 means no special handling of the prefix, "
|
|
|
|
"i.e. use the prefix comes with the generated random number.");
|
|
|
|
DEFINE_bool(enable_io_prio, false, "Lower the background flush/compaction "
|
|
|
|
"threads' IO priority");
|
CuckooTable: add one option to allow identity function for the first hash function
Summary:
MurmurHash becomes expensive when we do millions Get() a second in one
thread. Add this option to allow the first hash function to use identity
function as hash function. It results in QPS increase from 3.7M/s to
~4.3M/s. I did not observe improvement for end to end RocksDB
performance. This may be caused by other bottlenecks that I will address
in a separate diff.
Test Plan:
```
[ljin@dev1964 rocksdb] ./cuckoo_table_reader_test --enable_perf --file_dir=/dev/shm --write --identity_as_first_hash=0
==== Test CuckooReaderTest.WhenKeyExists
==== Test CuckooReaderTest.WhenKeyExistsWithUint64Comparator
==== Test CuckooReaderTest.CheckIterator
==== Test CuckooReaderTest.CheckIteratorUint64
==== Test CuckooReaderTest.WhenKeyNotFound
==== Test CuckooReaderTest.TestReadPerformance
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.272us (3.7 Mqps) with batch size of 0, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.138us (7.2 Mqps) with batch size of 10, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.142us (7.1 Mqps) with batch size of 25, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.142us (7.0 Mqps) with batch size of 50, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.144us (6.9 Mqps) with batch size of 100, # of found keys 125829120
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.201us (5.0 Mqps) with batch size of 0, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.121us (8.3 Mqps) with batch size of 10, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.123us (8.1 Mqps) with batch size of 25, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.121us (8.3 Mqps) with batch size of 50, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.112us (8.9 Mqps) with batch size of 100, # of found keys 104857600
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.251us (4.0 Mqps) with batch size of 0, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.107us (9.4 Mqps) with batch size of 10, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.099us (10.1 Mqps) with batch size of 25, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.100us (10.0 Mqps) with batch size of 50, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.116us (8.6 Mqps) with batch size of 100, # of found keys 83886080
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.189us (5.3 Mqps) with batch size of 0, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.095us (10.5 Mqps) with batch size of 10, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.096us (10.4 Mqps) with batch size of 25, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.098us (10.2 Mqps) with batch size of 50, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.105us (9.5 Mqps) with batch size of 100, # of found keys 73400320
[ljin@dev1964 rocksdb] ./cuckoo_table_reader_test --enable_perf --file_dir=/dev/shm --write --identity_as_first_hash=1
==== Test CuckooReaderTest.WhenKeyExists
==== Test CuckooReaderTest.WhenKeyExistsWithUint64Comparator
==== Test CuckooReaderTest.CheckIterator
==== Test CuckooReaderTest.CheckIteratorUint64
==== Test CuckooReaderTest.WhenKeyNotFound
==== Test CuckooReaderTest.TestReadPerformance
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.230us (4.3 Mqps) with batch size of 0, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.086us (11.7 Mqps) with batch size of 10, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.088us (11.3 Mqps) with batch size of 25, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.083us (12.1 Mqps) with batch size of 50, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.083us (12.1 Mqps) with batch size of 100, # of found keys 125829120
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.159us (6.3 Mqps) with batch size of 0, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.078us (12.8 Mqps) with batch size of 10, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.080us (12.6 Mqps) with batch size of 25, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.080us (12.5 Mqps) with batch size of 50, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.082us (12.2 Mqps) with batch size of 100, # of found keys 104857600
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.154us (6.5 Mqps) with batch size of 0, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.077us (13.0 Mqps) with batch size of 10, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.077us (12.9 Mqps) with batch size of 25, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.078us (12.8 Mqps) with batch size of 50, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.079us (12.6 Mqps) with batch size of 100, # of found keys 83886080
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.218us (4.6 Mqps) with batch size of 0, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.083us (12.0 Mqps) with batch size of 10, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.085us (11.7 Mqps) with batch size of 25, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.086us (11.6 Mqps) with batch size of 50, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.078us (12.8 Mqps) with batch size of 100, # of found keys 73400320
```
Reviewers: sdong, igor, yhchiang
Reviewed By: igor
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D23451
10 years ago
|
|
|
DEFINE_bool(identity_as_first_hash, false, "the first hash function of cuckoo "
|
|
|
|
"table becomes an identity function. This is only valid when key "
|
|
|
|
"is 8 bytes");
|
|
|
|
|
|
|
|
enum PutOrMerge {
|
|
|
|
kPut,
|
|
|
|
kMerge
|
|
|
|
};
|
|
|
|
|
|
|
|
enum RepFactory {
|
|
|
|
kSkipList,
|
|
|
|
kPrefixHash,
|
|
|
|
kVectorRep,
|
Add a new mem-table representation based on cuckoo hash.
Summary:
= Major Changes =
* Add a new mem-table representation, HashCuckooRep, which is based cuckoo hash.
Cuckoo hash uses multiple hash functions. This allows each key to have multiple
possible locations in the mem-table.
- Put: When insert a key, it will try to find whether one of its possible
locations is vacant and store the key. If none of its possible
locations are available, then it will kick out a victim key and
store at that location. The kicked-out victim key will then be
stored at a vacant space of its possible locations or kick-out
another victim. In this diff, the kick-out path (known as
cuckoo-path) is found using BFS, which guarantees to be the shortest.
- Get: Simply tries all possible locations of a key --- this guarantees
worst-case constant time complexity.
- Time complexity: O(1) for Get, and average O(1) for Put if the
fullness of the mem-table is below 80%.
- Default using two hash functions, the number of hash functions used
by the cuckoo-hash may dynamically increase if it fails to find a
short-enough kick-out path.
- Currently, HashCuckooRep does not support iteration and snapshots,
as our current main purpose of this is to optimize point access.
= Minor Changes =
* Add IsSnapshotSupported() to DB to indicate whether the current DB
supports snapshots. If it returns false, then DB::GetSnapshot() will
always return nullptr.
Test Plan:
Run existing tests. Will develop a test specifically for cuckoo hash in
the next diff.
Reviewers: sdong, haobo
Reviewed By: sdong
CC: leveldb, dhruba, igor
Differential Revision: https://reviews.facebook.net/D16155
11 years ago
|
|
|
kHashLinkedList,
|
|
|
|
kCuckoo
|
|
|
|
};
|
|
|
|
|
|
|
|
namespace {
|
|
|
|
enum RepFactory StringToRepFactory(const char* ctype) {
|
|
|
|
assert(ctype);
|
|
|
|
|
|
|
|
if (!strcasecmp(ctype, "skip_list"))
|
|
|
|
return kSkipList;
|
|
|
|
else if (!strcasecmp(ctype, "prefix_hash"))
|
|
|
|
return kPrefixHash;
|
|
|
|
else if (!strcasecmp(ctype, "vector"))
|
|
|
|
return kVectorRep;
|
|
|
|
else if (!strcasecmp(ctype, "hash_linkedlist"))
|
|
|
|
return kHashLinkedList;
|
Add a new mem-table representation based on cuckoo hash.
Summary:
= Major Changes =
* Add a new mem-table representation, HashCuckooRep, which is based cuckoo hash.
Cuckoo hash uses multiple hash functions. This allows each key to have multiple
possible locations in the mem-table.
- Put: When insert a key, it will try to find whether one of its possible
locations is vacant and store the key. If none of its possible
locations are available, then it will kick out a victim key and
store at that location. The kicked-out victim key will then be
stored at a vacant space of its possible locations or kick-out
another victim. In this diff, the kick-out path (known as
cuckoo-path) is found using BFS, which guarantees to be the shortest.
- Get: Simply tries all possible locations of a key --- this guarantees
worst-case constant time complexity.
- Time complexity: O(1) for Get, and average O(1) for Put if the
fullness of the mem-table is below 80%.
- Default using two hash functions, the number of hash functions used
by the cuckoo-hash may dynamically increase if it fails to find a
short-enough kick-out path.
- Currently, HashCuckooRep does not support iteration and snapshots,
as our current main purpose of this is to optimize point access.
= Minor Changes =
* Add IsSnapshotSupported() to DB to indicate whether the current DB
supports snapshots. If it returns false, then DB::GetSnapshot() will
always return nullptr.
Test Plan:
Run existing tests. Will develop a test specifically for cuckoo hash in
the next diff.
Reviewers: sdong, haobo
Reviewed By: sdong
CC: leveldb, dhruba, igor
Differential Revision: https://reviews.facebook.net/D16155
11 years ago
|
|
|
else if (!strcasecmp(ctype, "cuckoo"))
|
|
|
|
return kCuckoo;
|
|
|
|
|
|
|
|
fprintf(stdout, "Cannot parse memreptable %s\n", ctype);
|
|
|
|
return kSkipList;
|
|
|
|
}
|
|
|
|
} // namespace
|
|
|
|
|
|
|
|
static enum RepFactory FLAGS_rep_factory;
|
|
|
|
DEFINE_string(memtablerep, "skip_list", "");
|
|
|
|
DEFINE_int64(hash_bucket_count, 1024 * 1024, "hash bucket count");
|
|
|
|
DEFINE_bool(use_plain_table, false, "if use plain table "
|
|
|
|
"instead of block-based table format");
|
|
|
|
DEFINE_bool(use_cuckoo_table, false, "if use cuckoo table format");
|
|
|
|
DEFINE_double(cuckoo_hash_ratio, 0.9, "Hash ratio for Cuckoo SST table.");
|
|
|
|
DEFINE_bool(use_hash_search, false, "if use kHashSearch "
|
|
|
|
"instead of kBinarySearch. "
|
|
|
|
"This is valid if only we use BlockTable");
|
|
|
|
DEFINE_bool(use_block_based_filter, false, "if use kBlockBasedFilter "
|
|
|
|
"instead of kFullFilter for filter block. "
|
|
|
|
"This is valid if only we use BlockTable");
|
|
|
|
DEFINE_string(merge_operator, "", "The merge operator to use with the database."
|
|
|
|
"If a new merge operator is specified, be sure to use fresh"
|
|
|
|
" database The possible merge operators are defined in"
|
|
|
|
" utilities/merge_operators.h");
|
SkipListRep::LookaheadIterator
Summary:
This diff introduces the `lookahead` argument to `SkipListFactory()`. This is an
optimization for the tailing use case which includes many seeks. E.g. consider
the following operations on a skip list iterator:
Seek(x), Next(), Next(), Seek(x+2), Next(), Seek(x+3), Next(), Next(), ...
If `lookahead` is positive, `SkipListRep` will return an iterator which also
keeps track of the previously visited node. Seek() then first does a linear
search starting from that node (up to `lookahead` steps). As in the tailing
example above, this may require fewer than ~log(n) comparisons as with regular
skip list search.
Test Plan:
Added a new benchmark (`fillseekseq`) which simulates the usage pattern. It
first writes N records (with consecutive keys), then measures how much time it
takes to read them by calling `Seek()` and `Next()`.
$ time ./db_bench -num 10000000 -benchmarks fillseekseq -prefix_size 1 \
-key_size 8 -write_buffer_size $[1024*1024*1024] -value_size 50 \
-seekseq_next 2 -skip_list_lookahead=0
[...]
DB path: [/dev/shm/rocksdbtest/dbbench]
fillseekseq : 0.389 micros/op 2569047 ops/sec;
real 0m21.806s
user 0m12.106s
sys 0m9.672s
$ time ./db_bench [...] -skip_list_lookahead=2
[...]
DB path: [/dev/shm/rocksdbtest/dbbench]
fillseekseq : 0.153 micros/op 6540684 ops/sec;
real 0m19.469s
user 0m10.192s
sys 0m9.252s
Reviewers: ljin, sdong, igor
Reviewed By: igor
Subscribers: dhruba, leveldb, march, lovro
Differential Revision: https://reviews.facebook.net/D23997
10 years ago
|
|
|
DEFINE_int32(skip_list_lookahead, 0, "Used with skip_list memtablerep; try "
|
|
|
|
"linear search first for this many steps from the previous "
|
|
|
|
"position");
|
|
|
|
DEFINE_bool(report_file_operations, false, "if report number of file "
|
|
|
|
"operations");
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
|
|
|
|
static const bool FLAGS_soft_rate_limit_dummy __attribute__((unused)) =
|
|
|
|
RegisterFlagValidator(&FLAGS_soft_rate_limit, &ValidateRateLimit);
|
|
|
|
|
|
|
|
static const bool FLAGS_hard_rate_limit_dummy __attribute__((unused)) =
|
|
|
|
RegisterFlagValidator(&FLAGS_hard_rate_limit, &ValidateRateLimit);
|
|
|
|
|
|
|
|
static const bool FLAGS_prefix_size_dummy __attribute__((unused)) =
|
|
|
|
RegisterFlagValidator(&FLAGS_prefix_size, &ValidatePrefixSize);
|
|
|
|
|
|
|
|
static const bool FLAGS_key_size_dummy __attribute__((unused)) =
|
|
|
|
RegisterFlagValidator(&FLAGS_key_size, &ValidateKeySize);
|
|
|
|
|
|
|
|
static const bool FLAGS_cache_numshardbits_dummy __attribute__((unused)) =
|
|
|
|
RegisterFlagValidator(&FLAGS_cache_numshardbits,
|
|
|
|
&ValidateCacheNumshardbits);
|
|
|
|
|
|
|
|
static const bool FLAGS_readwritepercent_dummy __attribute__((unused)) =
|
|
|
|
RegisterFlagValidator(&FLAGS_readwritepercent, &ValidateInt32Percent);
|
|
|
|
|
|
|
|
DEFINE_int32(disable_seek_compaction, false,
|
|
|
|
"Not used, left here for backwards compatibility");
|
|
|
|
|
|
|
|
static const bool FLAGS_deletepercent_dummy __attribute__((unused)) =
|
|
|
|
RegisterFlagValidator(&FLAGS_deletepercent, &ValidateInt32Percent);
|
|
|
|
static const bool FLAGS_table_cache_numshardbits_dummy __attribute__((unused)) =
|
|
|
|
RegisterFlagValidator(&FLAGS_table_cache_numshardbits,
|
|
|
|
&ValidateTableCacheNumshardbits);
|
|
|
|
|
|
|
|
namespace rocksdb {
|
|
|
|
|
|
|
|
namespace {
|
|
|
|
struct ReportFileOpCounters {
|
|
|
|
std::atomic<int> open_counter_;
|
|
|
|
std::atomic<int> read_counter_;
|
|
|
|
std::atomic<int> append_counter_;
|
|
|
|
std::atomic<uint64_t> bytes_read_;
|
|
|
|
std::atomic<uint64_t> bytes_written_;
|
|
|
|
};
|
|
|
|
|
|
|
|
// A special Env to records and report file operations in db_bench
|
|
|
|
class ReportFileOpEnv : public EnvWrapper {
|
|
|
|
public:
|
|
|
|
explicit ReportFileOpEnv(Env* base) : EnvWrapper(base) { reset(); }
|
|
|
|
|
|
|
|
void reset() {
|
|
|
|
counters_.open_counter_ = 0;
|
|
|
|
counters_.read_counter_ = 0;
|
|
|
|
counters_.append_counter_ = 0;
|
|
|
|
counters_.bytes_read_ = 0;
|
|
|
|
counters_.bytes_written_ = 0;
|
|
|
|
}
|
|
|
|
|
|
|
|
Status NewSequentialFile(const std::string& f, unique_ptr<SequentialFile>* r,
|
|
|
|
const EnvOptions& soptions) override {
|
|
|
|
class CountingFile : public SequentialFile {
|
|
|
|
private:
|
|
|
|
unique_ptr<SequentialFile> target_;
|
|
|
|
ReportFileOpCounters* counters_;
|
|
|
|
|
|
|
|
public:
|
|
|
|
CountingFile(unique_ptr<SequentialFile>&& target,
|
|
|
|
ReportFileOpCounters* counters)
|
|
|
|
: target_(std::move(target)), counters_(counters) {}
|
|
|
|
|
|
|
|
virtual Status Read(size_t n, Slice* result, char* scratch) override {
|
|
|
|
counters_->read_counter_.fetch_add(1, std::memory_order_relaxed);
|
|
|
|
Status rv = target_->Read(n, result, scratch);
|
|
|
|
counters_->bytes_read_.fetch_add(result->size(),
|
|
|
|
std::memory_order_relaxed);
|
|
|
|
return rv;
|
|
|
|
}
|
|
|
|
|
|
|
|
virtual Status Skip(uint64_t n) override { return target_->Skip(n); }
|
|
|
|
};
|
|
|
|
|
|
|
|
Status s = target()->NewSequentialFile(f, r, soptions);
|
|
|
|
if (s.ok()) {
|
|
|
|
counters()->open_counter_.fetch_add(1, std::memory_order_relaxed);
|
|
|
|
r->reset(new CountingFile(std::move(*r), counters()));
|
|
|
|
}
|
|
|
|
return s;
|
|
|
|
}
|
|
|
|
|
|
|
|
Status NewRandomAccessFile(const std::string& f,
|
|
|
|
unique_ptr<RandomAccessFile>* r,
|
|
|
|
const EnvOptions& soptions) override {
|
|
|
|
class CountingFile : public RandomAccessFile {
|
|
|
|
private:
|
|
|
|
unique_ptr<RandomAccessFile> target_;
|
|
|
|
ReportFileOpCounters* counters_;
|
|
|
|
|
|
|
|
public:
|
|
|
|
CountingFile(unique_ptr<RandomAccessFile>&& target,
|
|
|
|
ReportFileOpCounters* counters)
|
|
|
|
: target_(std::move(target)), counters_(counters) {}
|
|
|
|
virtual Status Read(uint64_t offset, size_t n, Slice* result,
|
|
|
|
char* scratch) const override {
|
|
|
|
counters_->read_counter_.fetch_add(1, std::memory_order_relaxed);
|
|
|
|
Status rv = target_->Read(offset, n, result, scratch);
|
|
|
|
counters_->bytes_read_.fetch_add(result->size(),
|
|
|
|
std::memory_order_relaxed);
|
|
|
|
return rv;
|
|
|
|
}
|
|
|
|
};
|
|
|
|
|
|
|
|
Status s = target()->NewRandomAccessFile(f, r, soptions);
|
|
|
|
if (s.ok()) {
|
|
|
|
counters()->open_counter_.fetch_add(1, std::memory_order_relaxed);
|
|
|
|
r->reset(new CountingFile(std::move(*r), counters()));
|
|
|
|
}
|
|
|
|
return s;
|
|
|
|
}
|
|
|
|
|
|
|
|
Status NewWritableFile(const std::string& f, unique_ptr<WritableFile>* r,
|
|
|
|
const EnvOptions& soptions) override {
|
|
|
|
class CountingFile : public WritableFile {
|
|
|
|
private:
|
|
|
|
unique_ptr<WritableFile> target_;
|
|
|
|
ReportFileOpCounters* counters_;
|
|
|
|
|
|
|
|
public:
|
|
|
|
CountingFile(unique_ptr<WritableFile>&& target,
|
|
|
|
ReportFileOpCounters* counters)
|
|
|
|
: target_(std::move(target)), counters_(counters) {}
|
|
|
|
|
|
|
|
Status Append(const Slice& data) override {
|
|
|
|
counters_->append_counter_.fetch_add(1, std::memory_order_relaxed);
|
|
|
|
Status rv = target_->Append(data);
|
|
|
|
counters_->bytes_written_.fetch_add(data.size(),
|
|
|
|
std::memory_order_relaxed);
|
|
|
|
return rv;
|
|
|
|
}
|
|
|
|
|
|
|
|
Status Close() override { return target_->Close(); }
|
|
|
|
Status Flush() override { return target_->Flush(); }
|
|
|
|
Status Sync() override { return target_->Sync(); }
|
|
|
|
};
|
|
|
|
|
|
|
|
Status s = target()->NewWritableFile(f, r, soptions);
|
|
|
|
if (s.ok()) {
|
|
|
|
counters()->open_counter_.fetch_add(1, std::memory_order_relaxed);
|
|
|
|
r->reset(new CountingFile(std::move(*r), counters()));
|
|
|
|
}
|
|
|
|
return s;
|
|
|
|
}
|
|
|
|
|
|
|
|
// getter
|
|
|
|
ReportFileOpCounters* counters() { return &counters_; }
|
|
|
|
|
|
|
|
private:
|
|
|
|
ReportFileOpCounters counters_;
|
|
|
|
};
|
|
|
|
|
|
|
|
} // namespace
|
|
|
|
|
|
|
|
// Helper for quickly generating random data.
|
|
|
|
class RandomGenerator {
|
|
|
|
private:
|
|
|
|
std::string data_;
|
|
|
|
unsigned int pos_;
|
|
|
|
|
|
|
|
public:
|
|
|
|
RandomGenerator() {
|
|
|
|
// We use a limited amount of data over and over again and ensure
|
|
|
|
// that it is larger than the compression window (32KB), and also
|
|
|
|
// large enough to serve all typical value sizes we want to write.
|
|
|
|
Random rnd(301);
|
|
|
|
std::string piece;
|
|
|
|
while (data_.size() < (unsigned)std::max(1048576, FLAGS_value_size)) {
|
|
|
|
// Add a short fragment that is as compressible as specified
|
|
|
|
// by FLAGS_compression_ratio.
|
|
|
|
test::CompressibleString(&rnd, FLAGS_compression_ratio, 100, &piece);
|
|
|
|
data_.append(piece);
|
|
|
|
}
|
|
|
|
pos_ = 0;
|
|
|
|
}
|
|
|
|
|
|
|
|
Slice Generate(unsigned int len) {
|
|
|
|
assert(len <= data_.size());
|
|
|
|
if (pos_ + len > data_.size()) {
|
|
|
|
pos_ = 0;
|
|
|
|
}
|
|
|
|
pos_ += len;
|
|
|
|
return Slice(data_.data() + pos_ - len, len);
|
|
|
|
}
|
|
|
|
};
|
|
|
|
|
|
|
|
static void AppendWithSpace(std::string* str, Slice msg) {
|
|
|
|
if (msg.empty()) return;
|
|
|
|
if (!str->empty()) {
|
|
|
|
str->push_back(' ');
|
|
|
|
}
|
|
|
|
str->append(msg.data(), msg.size());
|
|
|
|
}
|
|
|
|
|
|
|
|
struct DBWithColumnFamilies {
|
|
|
|
std::vector<ColumnFamilyHandle*> cfh;
|
|
|
|
DB* db;
|
|
|
|
std::atomic<size_t> num_created; // Need to be updated after all the
|
|
|
|
// new entries in cfh are set.
|
|
|
|
size_t num_hot; // Number of column families to be queried at each moment.
|
|
|
|
// After each CreateNewCf(), another num_hot number of new
|
|
|
|
// Column families will be created and used to be queried.
|
|
|
|
port::Mutex create_cf_mutex; // Only one thread can execute CreateNewCf()
|
|
|
|
|
|
|
|
DBWithColumnFamilies() : db(nullptr) {
|
|
|
|
cfh.clear();
|
|
|
|
num_created = 0;
|
|
|
|
num_hot = 0;
|
|
|
|
}
|
|
|
|
|
|
|
|
DBWithColumnFamilies(const DBWithColumnFamilies& other)
|
|
|
|
: cfh(other.cfh),
|
|
|
|
db(other.db),
|
|
|
|
num_created(other.num_created.load()),
|
|
|
|
num_hot(other.num_hot) {}
|
|
|
|
|
|
|
|
ColumnFamilyHandle* GetCfh(int64_t rand_num) {
|
|
|
|
assert(num_hot > 0);
|
|
|
|
return cfh[num_created.load(std::memory_order_acquire) - num_hot +
|
|
|
|
rand_num % num_hot];
|
|
|
|
}
|
|
|
|
|
|
|
|
// stage: assume CF from 0 to stage * num_hot has be created. Need to create
|
|
|
|
// stage * num_hot + 1 to stage * (num_hot + 1).
|
|
|
|
void CreateNewCf(ColumnFamilyOptions options, int64_t stage) {
|
|
|
|
MutexLock l(&create_cf_mutex);
|
|
|
|
if ((stage + 1) * num_hot <= num_created) {
|
|
|
|
// Already created.
|
|
|
|
return;
|
|
|
|
}
|
|
|
|
auto new_num_created = num_created + num_hot;
|
|
|
|
assert(new_num_created <= cfh.size());
|
|
|
|
for (size_t i = num_created; i < new_num_created; i++) {
|
|
|
|
Status s =
|
|
|
|
db->CreateColumnFamily(options, ColumnFamilyName(i), &(cfh[i]));
|
|
|
|
if (!s.ok()) {
|
|
|
|
fprintf(stderr, "create column family error: %s\n",
|
|
|
|
s.ToString().c_str());
|
|
|
|
abort();
|
|
|
|
}
|
|
|
|
}
|
|
|
|
num_created.store(new_num_created, std::memory_order_release);
|
|
|
|
}
|
|
|
|
};
|
|
|
|
|
|
|
|
class Stats {
|
|
|
|
private:
|
|
|
|
int id_;
|
|
|
|
double start_;
|
|
|
|
double finish_;
|
|
|
|
double seconds_;
|
|
|
|
int64_t done_;
|
|
|
|
int64_t last_report_done_;
|
|
|
|
int64_t next_report_;
|
|
|
|
int64_t bytes_;
|
|
|
|
double last_op_finish_;
|
|
|
|
double last_report_finish_;
|
|
|
|
HistogramImpl hist_;
|
|
|
|
std::string message_;
|
|
|
|
bool exclude_from_merge_;
|
|
|
|
|
|
|
|
public:
|
|
|
|
Stats() { Start(-1); }
|
|
|
|
|
|
|
|
void Start(int id) {
|
|
|
|
id_ = id;
|
|
|
|
next_report_ = FLAGS_stats_interval ? FLAGS_stats_interval : 100;
|
|
|
|
last_op_finish_ = start_;
|
|
|
|
hist_.Clear();
|
|
|
|
done_ = 0;
|
|
|
|
last_report_done_ = 0;
|
|
|
|
bytes_ = 0;
|
|
|
|
seconds_ = 0;
|
|
|
|
start_ = FLAGS_env->NowMicros();
|
|
|
|
finish_ = start_;
|
|
|
|
last_report_finish_ = start_;
|
|
|
|
message_.clear();
|
|
|
|
// When set, stats from this thread won't be merged with others.
|
|
|
|
exclude_from_merge_ = false;
|
|
|
|
}
|
|
|
|
|
|
|
|
void Merge(const Stats& other) {
|
|
|
|
if (other.exclude_from_merge_)
|
|
|
|
return;
|
|
|
|
|
|
|
|
hist_.Merge(other.hist_);
|
|
|
|
done_ += other.done_;
|
|
|
|
bytes_ += other.bytes_;
|
|
|
|
seconds_ += other.seconds_;
|
|
|
|
if (other.start_ < start_) start_ = other.start_;
|
|
|
|
if (other.finish_ > finish_) finish_ = other.finish_;
|
|
|
|
|
|
|
|
// Just keep the messages from one thread
|
|
|
|
if (message_.empty()) message_ = other.message_;
|
|
|
|
}
|
|
|
|
|
|
|
|
void Stop() {
|
|
|
|
finish_ = FLAGS_env->NowMicros();
|
|
|
|
seconds_ = (finish_ - start_) * 1e-6;
|
|
|
|
}
|
|
|
|
|
|
|
|
void AddMessage(Slice msg) {
|
|
|
|
AppendWithSpace(&message_, msg);
|
|
|
|
}
|
|
|
|
|
|
|
|
void SetId(int id) { id_ = id; }
|
|
|
|
void SetExcludeFromMerge() { exclude_from_merge_ = true; }
|
|
|
|
|
|
|
|
void PrintThreadStatus() {
|
|
|
|
std::vector<ThreadStatus> thread_list;
|
|
|
|
FLAGS_env->GetThreadList(&thread_list);
|
|
|
|
|
|
|
|
fprintf(stderr, "\n%18s %10s %25s %12s %20s %13s %45s %12s\n",
|
|
|
|
"ThreadID", "ThreadType", "cfName", "Operation",
|
|
|
|
"OP_StartTime ", "ElapsedTime", "Stage", "State");
|
|
|
|
|
|
|
|
int64_t current_time = 0;
|
|
|
|
Env::Default()->GetCurrentTime(¤t_time);
|
|
|
|
for (auto ts : thread_list) {
|
|
|
|
char elapsed_time[25];
|
|
|
|
if (ts.op_start_time != 0) {
|
|
|
|
AppendHumanMicros(
|
|
|
|
current_time - ts.op_start_time,
|
|
|
|
elapsed_time, 24);
|
|
|
|
} else {
|
|
|
|
elapsed_time[0] = 0;
|
|
|
|
}
|
|
|
|
fprintf(stderr, "%18" PRIu64 " %10s %25s %12s %20s %13s %45s %12s\n",
|
|
|
|
ts.thread_id,
|
|
|
|
ThreadStatus::GetThreadTypeName(ts.thread_type).c_str(),
|
|
|
|
ts.cf_name.c_str(),
|
|
|
|
ThreadStatus::GetOperationName(ts.operation_type).c_str(),
|
|
|
|
ThreadStatus::TimeToString(ts.op_start_time).c_str(),
|
|
|
|
elapsed_time,
|
|
|
|
ThreadStatus::GetOperationStageName(ts.operation_stage).c_str(),
|
|
|
|
ThreadStatus::GetStateName(ts.state_type).c_str());
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void FinishedOps(DBWithColumnFamilies* db_with_cfh, DB* db, int64_t num_ops) {
|
|
|
|
if (FLAGS_histogram) {
|
|
|
|
double now = FLAGS_env->NowMicros();
|
|
|
|
double micros = now - last_op_finish_;
|
|
|
|
hist_.Add(micros);
|
|
|
|
if (micros > 20000 && !FLAGS_stats_interval) {
|
|
|
|
fprintf(stderr, "long op: %.1f micros%30s\r", micros, "");
|
|
|
|
fflush(stderr);
|
|
|
|
}
|
|
|
|
last_op_finish_ = now;
|
|
|
|
}
|
|
|
|
|
|
|
|
done_ += num_ops;
|
|
|
|
if (done_ >= next_report_) {
|
|
|
|
if (!FLAGS_stats_interval) {
|
|
|
|
if (next_report_ < 1000) next_report_ += 100;
|
|
|
|
else if (next_report_ < 5000) next_report_ += 500;
|
|
|
|
else if (next_report_ < 10000) next_report_ += 1000;
|
|
|
|
else if (next_report_ < 50000) next_report_ += 5000;
|
|
|
|
else if (next_report_ < 100000) next_report_ += 10000;
|
|
|
|
else if (next_report_ < 500000) next_report_ += 50000;
|
|
|
|
else next_report_ += 100000;
|
|
|
|
fprintf(stderr, "... finished %" PRIu64 " ops%30s\r", done_, "");
|
|
|
|
} else {
|
|
|
|
double now = FLAGS_env->NowMicros();
|
|
|
|
fprintf(stderr,
|
|
|
|
"%s ... thread %d: (%" PRIu64 ",%" PRIu64 ") ops and "
|
|
|
|
"(%.1f,%.1f) ops/second in (%.6f,%.6f) seconds\n",
|
|
|
|
FLAGS_env->TimeToString((uint64_t) now/1000000).c_str(),
|
|
|
|
id_,
|
|
|
|
done_ - last_report_done_, done_,
|
|
|
|
(done_ - last_report_done_) /
|
|
|
|
((now - last_report_finish_) / 1000000.0),
|
|
|
|
done_ / ((now - start_) / 1000000.0),
|
|
|
|
(now - last_report_finish_) / 1000000.0,
|
|
|
|
(now - start_) / 1000000.0);
|
|
|
|
|
|
|
|
if (FLAGS_stats_per_interval) {
|
|
|
|
std::string stats;
|
|
|
|
|
|
|
|
if (db_with_cfh && db_with_cfh->num_created.load()) {
|
|
|
|
for (size_t i = 0; i < db_with_cfh->num_created.load(); ++i) {
|
|
|
|
if (db->GetProperty(db_with_cfh->cfh[i], "rocksdb.cfstats",
|
|
|
|
&stats))
|
|
|
|
fprintf(stderr, "%s\n", stats.c_str());
|
|
|
|
}
|
|
|
|
|
|
|
|
} else if (db && db->GetProperty("rocksdb.stats", &stats)) {
|
|
|
|
fprintf(stderr, "%s\n", stats.c_str());
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
next_report_ += FLAGS_stats_interval;
|
|
|
|
last_report_finish_ = now;
|
|
|
|
last_report_done_ = done_;
|
|
|
|
}
|
|
|
|
if (id_ == 0 && FLAGS_thread_status_per_interval) {
|
|
|
|
PrintThreadStatus();
|
|
|
|
}
|
|
|
|
fflush(stderr);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void AddBytes(int64_t n) {
|
|
|
|
bytes_ += n;
|
|
|
|
}
|
|
|
|
|
|
|
|
void Report(const Slice& name) {
|
|
|
|
// Pretend at least one op was done in case we are running a benchmark
|
|
|
|
// that does not call FinishedOps().
|
|
|
|
if (done_ < 1) done_ = 1;
|
|
|
|
|
|
|
|
std::string extra;
|
|
|
|
if (bytes_ > 0) {
|
|
|
|
// Rate is computed on actual elapsed time, not the sum of per-thread
|
|
|
|
// elapsed times.
|
|
|
|
double elapsed = (finish_ - start_) * 1e-6;
|
|
|
|
char rate[100];
|
|
|
|
snprintf(rate, sizeof(rate), "%6.1f MB/s",
|
|
|
|
(bytes_ / 1048576.0) / elapsed);
|
|
|
|
extra = rate;
|
|
|
|
}
|
|
|
|
AppendWithSpace(&extra, message_);
|
|
|
|
double elapsed = (finish_ - start_) * 1e-6;
|
|
|
|
double throughput = (double)done_/elapsed;
|
|
|
|
|
|
|
|
fprintf(stdout, "%-12s : %11.3f micros/op %ld ops/sec;%s%s\n",
|
|
|
|
name.ToString().c_str(),
|
|
|
|
elapsed * 1e6 / done_,
|
|
|
|
(long)throughput,
|
|
|
|
(extra.empty() ? "" : " "),
|
|
|
|
extra.c_str());
|
|
|
|
if (FLAGS_histogram) {
|
|
|
|
fprintf(stdout, "Microseconds per op:\n%s\n", hist_.ToString().c_str());
|
|
|
|
}
|
|
|
|
if (FLAGS_report_file_operations) {
|
|
|
|
ReportFileOpEnv* env = static_cast<ReportFileOpEnv*>(FLAGS_env);
|
|
|
|
ReportFileOpCounters* counters = env->counters();
|
|
|
|
fprintf(stdout, "Num files opened: %d\n",
|
|
|
|
counters->open_counter_.load(std::memory_order_relaxed));
|
|
|
|
fprintf(stdout, "Num Read(): %d\n",
|
|
|
|
counters->read_counter_.load(std::memory_order_relaxed));
|
|
|
|
fprintf(stdout, "Num Append(): %d\n",
|
|
|
|
counters->append_counter_.load(std::memory_order_relaxed));
|
|
|
|
fprintf(stdout, "Num bytes read: %" PRIu64 "\n",
|
|
|
|
counters->bytes_read_.load(std::memory_order_relaxed));
|
|
|
|
fprintf(stdout, "Num bytes written: %" PRIu64 "\n",
|
|
|
|
counters->bytes_written_.load(std::memory_order_relaxed));
|
|
|
|
env->reset();
|
|
|
|
}
|
|
|
|
fflush(stdout);
|
|
|
|
}
|
|
|
|
};
|
|
|
|
|
|
|
|
// State shared by all concurrent executions of the same benchmark.
|
|
|
|
struct SharedState {
|
|
|
|
port::Mutex mu;
|
|
|
|
port::CondVar cv;
|
|
|
|
int total;
|
|
|
|
int perf_level;
|
|
|
|
|
|
|
|
// Each thread goes through the following states:
|
|
|
|
// (1) initializing
|
|
|
|
// (2) waiting for others to be initialized
|
|
|
|
// (3) running
|
|
|
|
// (4) done
|
|
|
|
|
|
|
|
long num_initialized;
|
|
|
|
long num_done;
|
|
|
|
bool start;
|
|
|
|
|
|
|
|
SharedState() : cv(&mu), perf_level(FLAGS_perf_level) { }
|
|
|
|
};
|
|
|
|
|
|
|
|
// Per-thread state for concurrent executions of the same benchmark.
|
|
|
|
struct ThreadState {
|
|
|
|
int tid; // 0..n-1 when running in n threads
|
|
|
|
Random64 rand; // Has different seeds for different threads
|
|
|
|
Stats stats;
|
|
|
|
SharedState* shared;
|
|
|
|
|
|
|
|
/* implicit */ ThreadState(int index)
|
|
|
|
: tid(index),
|
|
|
|
rand((FLAGS_seed ? FLAGS_seed : 1000) + index) {
|
|
|
|
}
|
|
|
|
};
|
|
|
|
|
|
|
|
class Duration {
|
|
|
|
public:
|
|
|
|
Duration(int max_seconds, int64_t max_ops, int64_t ops_per_stage = 0) {
|
|
|
|
max_seconds_ = max_seconds;
|
|
|
|
max_ops_= max_ops;
|
|
|
|
ops_per_stage_ = (ops_per_stage > 0) ? ops_per_stage : max_ops;
|
|
|
|
ops_ = 0;
|
|
|
|
start_at_ = FLAGS_env->NowMicros();
|
|
|
|
}
|
|
|
|
|
|
|
|
int64_t GetStage() { return std::min(ops_, max_ops_ - 1) / ops_per_stage_; }
|
|
|
|
|
|
|
|
bool Done(int64_t increment) {
|
|
|
|
if (increment <= 0) increment = 1; // avoid Done(0) and infinite loops
|
|
|
|
ops_ += increment;
|
|
|
|
|
|
|
|
if (max_seconds_) {
|
|
|
|
// Recheck every appx 1000 ops (exact iff increment is factor of 1000)
|
|
|
|
if ((ops_/1000) != ((ops_-increment)/1000)) {
|
|
|
|
double now = FLAGS_env->NowMicros();
|
|
|
|
return ((now - start_at_) / 1000000.0) >= max_seconds_;
|
|
|
|
} else {
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
} else {
|
|
|
|
return ops_ > max_ops_;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
private:
|
|
|
|
int max_seconds_;
|
|
|
|
int64_t max_ops_;
|
|
|
|
int64_t ops_per_stage_;
|
|
|
|
int64_t ops_;
|
|
|
|
double start_at_;
|
|
|
|
};
|
|
|
|
|
|
|
|
class Benchmark {
|
|
|
|
private:
|
|
|
|
std::shared_ptr<Cache> cache_;
|
|
|
|
std::shared_ptr<Cache> compressed_cache_;
|
|
|
|
std::shared_ptr<const FilterPolicy> filter_policy_;
|
|
|
|
const SliceTransform* prefix_extractor_;
|
|
|
|
DBWithColumnFamilies db_;
|
|
|
|
std::vector<DBWithColumnFamilies> multi_dbs_;
|
|
|
|
int64_t num_;
|
|
|
|
int value_size_;
|
|
|
|
int key_size_;
|
|
|
|
int prefix_size_;
|
|
|
|
int64_t keys_per_prefix_;
|
|
|
|
int64_t entries_per_batch_;
|
|
|
|
WriteOptions write_options_;
|
|
|
|
Options open_options_; // keep options around to properly destroy db later
|
|
|
|
int64_t reads_;
|
|
|
|
double read_random_exp_range_;
|
|
|
|
int64_t writes_;
|
|
|
|
int64_t readwrites_;
|
|
|
|
int64_t merge_keys_;
|
|
|
|
bool report_file_operations_;
|
|
|
|
|
|
|
|
bool SanityCheck() {
|
|
|
|
if (FLAGS_compression_ratio > 1) {
|
|
|
|
fprintf(stderr, "compression_ratio should be between 0 and 1\n");
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
|
|
|
|
void PrintHeader() {
|
|
|
|
PrintEnvironment();
|
|
|
|
fprintf(stdout, "Keys: %d bytes each\n", FLAGS_key_size);
|
|
|
|
fprintf(stdout, "Values: %d bytes each (%d bytes after compression)\n",
|
|
|
|
FLAGS_value_size,
|
|
|
|
static_cast<int>(FLAGS_value_size * FLAGS_compression_ratio + 0.5));
|
|
|
|
fprintf(stdout, "Entries: %" PRIu64 "\n", num_);
|
|
|
|
fprintf(stdout, "Prefix: %d bytes\n", FLAGS_prefix_size);
|
|
|
|
fprintf(stdout, "Keys per prefix: %" PRIu64 "\n", keys_per_prefix_);
|
|
|
|
fprintf(stdout, "RawSize: %.1f MB (estimated)\n",
|
|
|
|
((static_cast<int64_t>(FLAGS_key_size + FLAGS_value_size) * num_)
|
|
|
|
/ 1048576.0));
|
|
|
|
fprintf(stdout, "FileSize: %.1f MB (estimated)\n",
|
|
|
|
(((FLAGS_key_size + FLAGS_value_size * FLAGS_compression_ratio)
|
|
|
|
* num_)
|
|
|
|
/ 1048576.0));
|
|
|
|
fprintf(stdout, "Write rate limit: %d\n", FLAGS_writes_per_second);
|
|
|
|
if (FLAGS_enable_numa) {
|
|
|
|
fprintf(stderr, "Running in NUMA enabled mode.\n");
|
|
|
|
#ifndef NUMA
|
|
|
|
fprintf(stderr, "NUMA is not defined in the system.\n");
|
|
|
|
exit(1);
|
|
|
|
#else
|
|
|
|
if (numa_available() == -1) {
|
|
|
|
fprintf(stderr, "NUMA is not supported by the system.\n");
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
#endif
|
|
|
|
}
|
|
|
|
switch (FLAGS_compression_type_e) {
|
|
|
|
case rocksdb::kNoCompression:
|
|
|
|
fprintf(stdout, "Compression: none\n");
|
|
|
|
break;
|
|
|
|
case rocksdb::kSnappyCompression:
|
|
|
|
fprintf(stdout, "Compression: snappy\n");
|
|
|
|
break;
|
|
|
|
case rocksdb::kZlibCompression:
|
|
|
|
fprintf(stdout, "Compression: zlib\n");
|
|
|
|
break;
|
|
|
|
case rocksdb::kBZip2Compression:
|
|
|
|
fprintf(stdout, "Compression: bzip2\n");
|
|
|
|
break;
|
|
|
|
case rocksdb::kLZ4Compression:
|
|
|
|
fprintf(stdout, "Compression: lz4\n");
|
|
|
|
break;
|
|
|
|
case rocksdb::kLZ4HCCompression:
|
|
|
|
fprintf(stdout, "Compression: lz4hc\n");
|
|
|
|
break;
|
|
|
|
}
|
|
|
|
|
|
|
|
switch (FLAGS_rep_factory) {
|
|
|
|
case kPrefixHash:
|
|
|
|
fprintf(stdout, "Memtablerep: prefix_hash\n");
|
|
|
|
break;
|
|
|
|
case kSkipList:
|
|
|
|
fprintf(stdout, "Memtablerep: skip_list\n");
|
|
|
|
break;
|
|
|
|
case kVectorRep:
|
|
|
|
fprintf(stdout, "Memtablerep: vector\n");
|
|
|
|
break;
|
|
|
|
case kHashLinkedList:
|
|
|
|
fprintf(stdout, "Memtablerep: hash_linkedlist\n");
|
|
|
|
break;
|
Add a new mem-table representation based on cuckoo hash.
Summary:
= Major Changes =
* Add a new mem-table representation, HashCuckooRep, which is based cuckoo hash.
Cuckoo hash uses multiple hash functions. This allows each key to have multiple
possible locations in the mem-table.
- Put: When insert a key, it will try to find whether one of its possible
locations is vacant and store the key. If none of its possible
locations are available, then it will kick out a victim key and
store at that location. The kicked-out victim key will then be
stored at a vacant space of its possible locations or kick-out
another victim. In this diff, the kick-out path (known as
cuckoo-path) is found using BFS, which guarantees to be the shortest.
- Get: Simply tries all possible locations of a key --- this guarantees
worst-case constant time complexity.
- Time complexity: O(1) for Get, and average O(1) for Put if the
fullness of the mem-table is below 80%.
- Default using two hash functions, the number of hash functions used
by the cuckoo-hash may dynamically increase if it fails to find a
short-enough kick-out path.
- Currently, HashCuckooRep does not support iteration and snapshots,
as our current main purpose of this is to optimize point access.
= Minor Changes =
* Add IsSnapshotSupported() to DB to indicate whether the current DB
supports snapshots. If it returns false, then DB::GetSnapshot() will
always return nullptr.
Test Plan:
Run existing tests. Will develop a test specifically for cuckoo hash in
the next diff.
Reviewers: sdong, haobo
Reviewed By: sdong
CC: leveldb, dhruba, igor
Differential Revision: https://reviews.facebook.net/D16155
11 years ago
|
|
|
case kCuckoo:
|
|
|
|
fprintf(stdout, "Memtablerep: cuckoo\n");
|
|
|
|
break;
|
|
|
|
}
|
|
|
|
fprintf(stdout, "Perf Level: %d\n", FLAGS_perf_level);
|
|
|
|
|
|
|
|
PrintWarnings();
|
|
|
|
fprintf(stdout, "------------------------------------------------\n");
|
|
|
|
}
|
|
|
|
|
|
|
|
void PrintWarnings() {
|
|
|
|
#if defined(__GNUC__) && !defined(__OPTIMIZE__)
|
|
|
|
fprintf(stdout,
|
|
|
|
"WARNING: Optimization is disabled: benchmarks unnecessarily slow\n"
|
|
|
|
);
|
|
|
|
#endif
|
|
|
|
#ifndef NDEBUG
|
|
|
|
fprintf(stdout,
|
|
|
|
"WARNING: Assertions are enabled; benchmarks unnecessarily slow\n");
|
|
|
|
#endif
|
|
|
|
if (FLAGS_compression_type_e != rocksdb::kNoCompression) {
|
|
|
|
// The test string should not be too small.
|
|
|
|
const int len = FLAGS_block_size;
|
|
|
|
char* text = (char*) malloc(len+1);
|
|
|
|
bool result = true;
|
|
|
|
const char* name = nullptr;
|
|
|
|
std::string compressed;
|
|
|
|
|
|
|
|
memset(text, (int) 'y', len);
|
|
|
|
text[len] = '\0';
|
|
|
|
switch (FLAGS_compression_type_e) {
|
|
|
|
case kSnappyCompression:
|
|
|
|
result = Snappy_Compress(Options().compression_opts, text,
|
|
|
|
strlen(text), &compressed);
|
|
|
|
name = "Snappy";
|
|
|
|
break;
|
|
|
|
case kZlibCompression:
|
|
|
|
result = Zlib_Compress(Options().compression_opts, 2, text,
|
|
|
|
strlen(text), &compressed);
|
|
|
|
name = "Zlib";
|
|
|
|
break;
|
|
|
|
case kBZip2Compression:
|
|
|
|
result = BZip2_Compress(Options().compression_opts, 2, text,
|
|
|
|
strlen(text), &compressed);
|
|
|
|
name = "BZip2";
|
|
|
|
break;
|
|
|
|
case kLZ4Compression:
|
|
|
|
result = LZ4_Compress(Options().compression_opts, 2, text,
|
|
|
|
strlen(text), &compressed);
|
|
|
|
name = "LZ4";
|
|
|
|
break;
|
|
|
|
case kLZ4HCCompression:
|
|
|
|
result = LZ4HC_Compress(Options().compression_opts, 2, text,
|
|
|
|
strlen(text), &compressed);
|
|
|
|
name = "LZ4HC";
|
|
|
|
break;
|
|
|
|
case kNoCompression:
|
|
|
|
assert(false); // cannot happen
|
|
|
|
break;
|
|
|
|
}
|
|
|
|
|
|
|
|
if (!result) {
|
|
|
|
fprintf(stdout, "WARNING: %s compression is not enabled\n", name);
|
|
|
|
} else if (name && compressed.size() >= strlen(text)) {
|
|
|
|
fprintf(stdout, "WARNING: %s compression is not effective\n", name);
|
|
|
|
}
|
|
|
|
|
|
|
|
free(text);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// Current the following isn't equivalent to OS_LINUX.
|
|
|
|
#if defined(__linux)
|
|
|
|
static Slice TrimSpace(Slice s) {
|
|
|
|
unsigned int start = 0;
|
|
|
|
while (start < s.size() && isspace(s[start])) {
|
|
|
|
start++;
|
|
|
|
}
|
|
|
|
unsigned int limit = static_cast<unsigned int>(s.size());
|
|
|
|
while (limit > start && isspace(s[limit-1])) {
|
|
|
|
limit--;
|
|
|
|
}
|
|
|
|
return Slice(s.data() + start, limit - start);
|
|
|
|
}
|
|
|
|
#endif
|
|
|
|
|
|
|
|
void PrintEnvironment() {
|
|
|
|
fprintf(stderr, "LevelDB: version %d.%d\n",
|
|
|
|
kMajorVersion, kMinorVersion);
|
|
|
|
|
|
|
|
#if defined(__linux)
|
|
|
|
time_t now = time(nullptr);
|
|
|
|
fprintf(stderr, "Date: %s", ctime(&now)); // ctime() adds newline
|
|
|
|
|
|
|
|
FILE* cpuinfo = fopen("/proc/cpuinfo", "r");
|
|
|
|
if (cpuinfo != nullptr) {
|
|
|
|
char line[1000];
|
|
|
|
int num_cpus = 0;
|
|
|
|
std::string cpu_type;
|
|
|
|
std::string cache_size;
|
|
|
|
while (fgets(line, sizeof(line), cpuinfo) != nullptr) {
|
|
|
|
const char* sep = strchr(line, ':');
|
|
|
|
if (sep == nullptr) {
|
|
|
|
continue;
|
|
|
|
}
|
|
|
|
Slice key = TrimSpace(Slice(line, sep - 1 - line));
|
|
|
|
Slice val = TrimSpace(Slice(sep + 1));
|
|
|
|
if (key == "model name") {
|
|
|
|
++num_cpus;
|
|
|
|
cpu_type = val.ToString();
|
|
|
|
} else if (key == "cache size") {
|
|
|
|
cache_size = val.ToString();
|
|
|
|
}
|
|
|
|
}
|
|
|
|
fclose(cpuinfo);
|
|
|
|
fprintf(stderr, "CPU: %d * %s\n", num_cpus, cpu_type.c_str());
|
|
|
|
fprintf(stderr, "CPUCache: %s\n", cache_size.c_str());
|
|
|
|
}
|
|
|
|
#endif
|
|
|
|
}
|
|
|
|
|
|
|
|
public:
|
|
|
|
Benchmark()
|
|
|
|
: cache_(
|
|
|
|
FLAGS_cache_size >= 0
|
|
|
|
? (FLAGS_cache_numshardbits >= 1
|
|
|
|
? NewLRUCache(FLAGS_cache_size, FLAGS_cache_numshardbits)
|
|
|
|
: NewLRUCache(FLAGS_cache_size))
|
|
|
|
: nullptr),
|
|
|
|
compressed_cache_(FLAGS_compressed_cache_size >= 0
|
|
|
|
? (FLAGS_cache_numshardbits >= 1
|
|
|
|
? NewLRUCache(FLAGS_compressed_cache_size,
|
|
|
|
FLAGS_cache_numshardbits)
|
|
|
|
: NewLRUCache(FLAGS_compressed_cache_size))
|
|
|
|
: nullptr),
|
|
|
|
filter_policy_(FLAGS_bloom_bits >= 0
|
|
|
|
? NewBloomFilterPolicy(FLAGS_bloom_bits,
|
|
|
|
FLAGS_use_block_based_filter)
|
|
|
|
: nullptr),
|
|
|
|
prefix_extractor_(NewFixedPrefixTransform(FLAGS_prefix_size)),
|
|
|
|
num_(FLAGS_num),
|
|
|
|
value_size_(FLAGS_value_size),
|
|
|
|
key_size_(FLAGS_key_size),
|
|
|
|
prefix_size_(FLAGS_prefix_size),
|
|
|
|
keys_per_prefix_(FLAGS_keys_per_prefix),
|
|
|
|
entries_per_batch_(1),
|
|
|
|
reads_(FLAGS_reads < 0 ? FLAGS_num : FLAGS_reads),
|
|
|
|
read_random_exp_range_(0.0),
|
|
|
|
writes_(FLAGS_writes < 0 ? FLAGS_num : FLAGS_writes),
|
|
|
|
readwrites_(
|
|
|
|
(FLAGS_writes < 0 && FLAGS_reads < 0)
|
|
|
|
? FLAGS_num
|
|
|
|
: ((FLAGS_writes > FLAGS_reads) ? FLAGS_writes : FLAGS_reads)),
|
|
|
|
merge_keys_(FLAGS_merge_keys < 0 ? FLAGS_num : FLAGS_merge_keys),
|
|
|
|
report_file_operations_(FLAGS_report_file_operations) {
|
|
|
|
if (report_file_operations_) {
|
|
|
|
if (!FLAGS_hdfs.empty()) {
|
|
|
|
fprintf(stderr,
|
|
|
|
"--hdfs and --report_file_operations cannot be enabled "
|
|
|
|
"at the same time");
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
FLAGS_env = new ReportFileOpEnv(rocksdb::Env::Default());
|
|
|
|
}
|
|
|
|
|
|
|
|
if (FLAGS_prefix_size > FLAGS_key_size) {
|
|
|
|
fprintf(stderr, "prefix size is larger than key size");
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
|
|
|
|
std::vector<std::string> files;
|
|
|
|
FLAGS_env->GetChildren(FLAGS_db, &files);
|
|
|
|
for (unsigned int i = 0; i < files.size(); i++) {
|
|
|
|
if (Slice(files[i]).starts_with("heap-")) {
|
|
|
|
FLAGS_env->DeleteFile(FLAGS_db + "/" + files[i]);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
if (!FLAGS_use_existing_db) {
|
benchmark.sh won't run through all tests properly if one specifies wal_dir to be different than db directory.
Summary:
A command line like this to run all the tests:
source benchmark.config.sh && nohup ./benchmark.sh 'bulkload,fillseq,overwrite,filluniquerandom,readrandom,readwhilewriting'
where
benchmark.config.sh is:
export DB_DIR=/data/mysql/rocksdata
export WAL_DIR=/txlogs/rockswal
export OUTPUT_DIR=/root/rocks_benchmarking/output
Will fail for the tests that need a new DB .
Also 1) set disable_data_sync=0 and 2) add debug mode to run through all the tests more quickly
Test Plan: run ./benchmark.sh 'debug,bulkload,fillseq,overwrite,filluniquerandom,readrandom,readwhilewriting' and verify that there are no complaints about WAL dir not being empty.
Reviewers: sdong, yhchiang, rven, igor
Reviewed By: igor
Subscribers: dhruba
Differential Revision: https://reviews.facebook.net/D30909
10 years ago
|
|
|
Options options;
|
|
|
|
if (!FLAGS_wal_dir.empty()) {
|
|
|
|
options.wal_dir = FLAGS_wal_dir;
|
|
|
|
}
|
|
|
|
DestroyDB(FLAGS_db, options);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
~Benchmark() {
|
|
|
|
std::for_each(db_.cfh.begin(), db_.cfh.end(),
|
|
|
|
[](ColumnFamilyHandle* cfh) { delete cfh; });
|
|
|
|
delete db_.db;
|
|
|
|
delete prefix_extractor_;
|
|
|
|
if (cache_.get() != nullptr) {
|
|
|
|
// this will leak, but we're shutting down so nobody cares
|
|
|
|
cache_->DisownData();
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
Slice AllocateKey(std::unique_ptr<const char[]>* key_guard) {
|
|
|
|
key_guard->reset(new char[key_size_]);
|
|
|
|
return Slice(key_guard->get(), key_size_);
|
|
|
|
}
|
|
|
|
|
|
|
|
// Generate key according to the given specification and random number.
|
|
|
|
// The resulting key will have the following format (if keys_per_prefix_
|
|
|
|
// is positive), extra trailing bytes are either cut off or paddd with '0'.
|
|
|
|
// The prefix value is derived from key value.
|
|
|
|
// ----------------------------
|
|
|
|
// | prefix 00000 | key 00000 |
|
|
|
|
// ----------------------------
|
|
|
|
// If keys_per_prefix_ is 0, the key is simply a binary representation of
|
|
|
|
// random number followed by trailing '0's
|
|
|
|
// ----------------------------
|
|
|
|
// | key 00000 |
|
|
|
|
// ----------------------------
|
|
|
|
void GenerateKeyFromInt(uint64_t v, int64_t num_keys, Slice* key) {
|
|
|
|
char* start = const_cast<char*>(key->data());
|
|
|
|
char* pos = start;
|
|
|
|
if (keys_per_prefix_ > 0) {
|
|
|
|
int64_t num_prefix = num_keys / keys_per_prefix_;
|
|
|
|
int64_t prefix = v % num_prefix;
|
|
|
|
int bytes_to_fill = std::min(prefix_size_, 8);
|
|
|
|
if (port::kLittleEndian) {
|
|
|
|
for (int i = 0; i < bytes_to_fill; ++i) {
|
|
|
|
pos[i] = (prefix >> ((bytes_to_fill - i - 1) << 3)) & 0xFF;
|
|
|
|
}
|
|
|
|
} else {
|
|
|
|
memcpy(pos, static_cast<void*>(&prefix), bytes_to_fill);
|
|
|
|
}
|
|
|
|
if (prefix_size_ > 8) {
|
|
|
|
// fill the rest with 0s
|
|
|
|
memset(pos + 8, '0', prefix_size_ - 8);
|
|
|
|
}
|
|
|
|
pos += prefix_size_;
|
|
|
|
}
|
|
|
|
|
|
|
|
int bytes_to_fill = std::min(key_size_ - static_cast<int>(pos - start), 8);
|
|
|
|
if (port::kLittleEndian) {
|
|
|
|
for (int i = 0; i < bytes_to_fill; ++i) {
|
|
|
|
pos[i] = (v >> ((bytes_to_fill - i - 1) << 3)) & 0xFF;
|
|
|
|
}
|
|
|
|
} else {
|
|
|
|
memcpy(pos, static_cast<void*>(&v), bytes_to_fill);
|
|
|
|
}
|
|
|
|
pos += bytes_to_fill;
|
|
|
|
if (key_size_ > pos - start) {
|
|
|
|
memset(pos, '0', key_size_ - (pos - start));
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
std::string GetDbNameForMultiple(std::string base_name, size_t id) {
|
|
|
|
return base_name + ToString(id);
|
|
|
|
}
|
|
|
|
|
|
|
|
void Run() {
|
|
|
|
if (!SanityCheck()) {
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
PrintHeader();
|
|
|
|
Open(&open_options_);
|
|
|
|
const char* benchmarks = FLAGS_benchmarks.c_str();
|
|
|
|
while (benchmarks != nullptr) {
|
|
|
|
const char* sep = strchr(benchmarks, ',');
|
|
|
|
Slice name;
|
|
|
|
if (sep == nullptr) {
|
|
|
|
name = benchmarks;
|
|
|
|
benchmarks = nullptr;
|
|
|
|
} else {
|
|
|
|
name = Slice(benchmarks, sep - benchmarks);
|
|
|
|
benchmarks = sep + 1;
|
|
|
|
}
|
|
|
|
|
|
|
|
// Sanitize parameters
|
|
|
|
num_ = FLAGS_num;
|
|
|
|
reads_ = (FLAGS_reads < 0 ? FLAGS_num : FLAGS_reads);
|
|
|
|
writes_ = (FLAGS_writes < 0 ? FLAGS_num : FLAGS_writes);
|
|
|
|
value_size_ = FLAGS_value_size;
|
|
|
|
key_size_ = FLAGS_key_size;
|
|
|
|
entries_per_batch_ = FLAGS_batch_size;
|
|
|
|
write_options_ = WriteOptions();
|
|
|
|
read_random_exp_range_ = FLAGS_read_random_exp_range;
|
|
|
|
if (FLAGS_sync) {
|
|
|
|
write_options_.sync = true;
|
|
|
|
}
|
|
|
|
write_options_.disableWAL = FLAGS_disable_wal;
|
|
|
|
|
|
|
|
void (Benchmark::*method)(ThreadState*) = nullptr;
|
|
|
|
bool fresh_db = false;
|
|
|
|
int num_threads = FLAGS_threads;
|
|
|
|
|
|
|
|
if (name == Slice("fillseq")) {
|
|
|
|
fresh_db = true;
|
|
|
|
method = &Benchmark::WriteSeq;
|
|
|
|
} else if (name == Slice("fillbatch")) {
|
|
|
|
fresh_db = true;
|
|
|
|
entries_per_batch_ = 1000;
|
|
|
|
method = &Benchmark::WriteSeq;
|
|
|
|
} else if (name == Slice("fillrandom")) {
|
|
|
|
fresh_db = true;
|
|
|
|
method = &Benchmark::WriteRandom;
|
|
|
|
} else if (name == Slice("filluniquerandom")) {
|
|
|
|
fresh_db = true;
|
|
|
|
if (num_threads > 1) {
|
|
|
|
fprintf(stderr, "filluniquerandom multithreaded not supported"
|
|
|
|
", use 1 thread");
|
|
|
|
num_threads = 1;
|
|
|
|
}
|
|
|
|
method = &Benchmark::WriteUniqueRandom;
|
|
|
|
} else if (name == Slice("overwrite")) {
|
|
|
|
fresh_db = false;
|
|
|
|
method = &Benchmark::WriteRandom;
|
|
|
|
} else if (name == Slice("fillsync")) {
|
|
|
|
fresh_db = true;
|
|
|
|
num_ /= 1000;
|
|
|
|
write_options_.sync = true;
|
|
|
|
method = &Benchmark::WriteRandom;
|
|
|
|
} else if (name == Slice("fill100K")) {
|
|
|
|
fresh_db = true;
|
|
|
|
num_ /= 1000;
|
|
|
|
value_size_ = 100 * 1000;
|
|
|
|
method = &Benchmark::WriteRandom;
|
|
|
|
} else if (name == Slice("readseq")) {
|
|
|
|
method = &Benchmark::ReadSequential;
|
|
|
|
} else if (name == Slice("readtocache")) {
|
|
|
|
method = &Benchmark::ReadSequential;
|
|
|
|
num_threads = 1;
|
|
|
|
reads_ = num_;
|
|
|
|
} else if (name == Slice("readreverse")) {
|
|
|
|
method = &Benchmark::ReadReverse;
|
|
|
|
} else if (name == Slice("readrandom")) {
|
|
|
|
method = &Benchmark::ReadRandom;
|
|
|
|
} else if (name == Slice("readrandomfast")) {
|
|
|
|
method = &Benchmark::ReadRandomFast;
|
|
|
|
} else if (name == Slice("multireadrandom")) {
|
|
|
|
fprintf(stderr, "entries_per_batch = %" PRIi64 "\n",
|
|
|
|
entries_per_batch_);
|
|
|
|
method = &Benchmark::MultiReadRandom;
|
|
|
|
} else if (name == Slice("readmissing")) {
|
|
|
|
++key_size_;
|
|
|
|
method = &Benchmark::ReadRandom;
|
|
|
|
} else if (name == Slice("newiterator")) {
|
|
|
|
method = &Benchmark::IteratorCreation;
|
|
|
|
} else if (name == Slice("newiteratorwhilewriting")) {
|
|
|
|
num_threads++; // Add extra thread for writing
|
|
|
|
method = &Benchmark::IteratorCreationWhileWriting;
|
|
|
|
} else if (name == Slice("seekrandom")) {
|
|
|
|
method = &Benchmark::SeekRandom;
|
|
|
|
} else if (name == Slice("seekrandomwhilewriting")) {
|
|
|
|
num_threads++; // Add extra thread for writing
|
|
|
|
method = &Benchmark::SeekRandomWhileWriting;
|
|
|
|
} else if (name == Slice("readrandomsmall")) {
|
|
|
|
reads_ /= 1000;
|
|
|
|
method = &Benchmark::ReadRandom;
|
|
|
|
} else if (name == Slice("deleteseq")) {
|
|
|
|
method = &Benchmark::DeleteSeq;
|
|
|
|
} else if (name == Slice("deleterandom")) {
|
|
|
|
method = &Benchmark::DeleteRandom;
|
|
|
|
} else if (name == Slice("readwhilewriting")) {
|
|
|
|
num_threads++; // Add extra thread for writing
|
|
|
|
method = &Benchmark::ReadWhileWriting;
|
|
|
|
} else if (name == Slice("readwhilemerging")) {
|
|
|
|
num_threads++; // Add extra thread for writing
|
|
|
|
method = &Benchmark::ReadWhileMerging;
|
|
|
|
} else if (name == Slice("readrandomwriterandom")) {
|
|
|
|
method = &Benchmark::ReadRandomWriteRandom;
|
|
|
|
} else if (name == Slice("readrandommergerandom")) {
|
|
|
|
if (FLAGS_merge_operator.empty()) {
|
|
|
|
fprintf(stdout, "%-12s : skipped (--merge_operator is unknown)\n",
|
|
|
|
name.ToString().c_str());
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
method = &Benchmark::ReadRandomMergeRandom;
|
|
|
|
} else if (name == Slice("updaterandom")) {
|
|
|
|
method = &Benchmark::UpdateRandom;
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
} else if (name == Slice("appendrandom")) {
|
|
|
|
method = &Benchmark::AppendRandom;
|
|
|
|
} else if (name == Slice("mergerandom")) {
|
|
|
|
if (FLAGS_merge_operator.empty()) {
|
|
|
|
fprintf(stdout, "%-12s : skipped (--merge_operator is unknown)\n",
|
|
|
|
name.ToString().c_str());
|
|
|
|
exit(1);
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
}
|
|
|
|
method = &Benchmark::MergeRandom;
|
|
|
|
} else if (name == Slice("randomwithverify")) {
|
|
|
|
method = &Benchmark::RandomWithVerify;
|
SkipListRep::LookaheadIterator
Summary:
This diff introduces the `lookahead` argument to `SkipListFactory()`. This is an
optimization for the tailing use case which includes many seeks. E.g. consider
the following operations on a skip list iterator:
Seek(x), Next(), Next(), Seek(x+2), Next(), Seek(x+3), Next(), Next(), ...
If `lookahead` is positive, `SkipListRep` will return an iterator which also
keeps track of the previously visited node. Seek() then first does a linear
search starting from that node (up to `lookahead` steps). As in the tailing
example above, this may require fewer than ~log(n) comparisons as with regular
skip list search.
Test Plan:
Added a new benchmark (`fillseekseq`) which simulates the usage pattern. It
first writes N records (with consecutive keys), then measures how much time it
takes to read them by calling `Seek()` and `Next()`.
$ time ./db_bench -num 10000000 -benchmarks fillseekseq -prefix_size 1 \
-key_size 8 -write_buffer_size $[1024*1024*1024] -value_size 50 \
-seekseq_next 2 -skip_list_lookahead=0
[...]
DB path: [/dev/shm/rocksdbtest/dbbench]
fillseekseq : 0.389 micros/op 2569047 ops/sec;
real 0m21.806s
user 0m12.106s
sys 0m9.672s
$ time ./db_bench [...] -skip_list_lookahead=2
[...]
DB path: [/dev/shm/rocksdbtest/dbbench]
fillseekseq : 0.153 micros/op 6540684 ops/sec;
real 0m19.469s
user 0m10.192s
sys 0m9.252s
Reviewers: ljin, sdong, igor
Reviewed By: igor
Subscribers: dhruba, leveldb, march, lovro
Differential Revision: https://reviews.facebook.net/D23997
10 years ago
|
|
|
} else if (name == Slice("fillseekseq")) {
|
|
|
|
method = &Benchmark::WriteSeqSeekSeq;
|
|
|
|
} else if (name == Slice("compact")) {
|
|
|
|
method = &Benchmark::Compact;
|
|
|
|
} else if (name == Slice("crc32c")) {
|
|
|
|
method = &Benchmark::Crc32c;
|
|
|
|
} else if (name == Slice("xxhash")) {
|
|
|
|
method = &Benchmark::xxHash;
|
|
|
|
} else if (name == Slice("acquireload")) {
|
|
|
|
method = &Benchmark::AcquireLoad;
|
|
|
|
} else if (name == Slice("compress")) {
|
|
|
|
method = &Benchmark::Compress;
|
|
|
|
} else if (name == Slice("uncompress")) {
|
|
|
|
method = &Benchmark::Uncompress;
|
|
|
|
} else if (name == Slice("stats")) {
|
|
|
|
PrintStats("rocksdb.stats");
|
|
|
|
} else if (name == Slice("levelstats")) {
|
|
|
|
PrintStats("rocksdb.levelstats");
|
|
|
|
} else if (name == Slice("sstables")) {
|
|
|
|
PrintStats("rocksdb.sstables");
|
|
|
|
} else {
|
|
|
|
if (name != Slice()) { // No error message for empty name
|
|
|
|
fprintf(stderr, "unknown benchmark '%s'\n", name.ToString().c_str());
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
if (fresh_db) {
|
|
|
|
if (FLAGS_use_existing_db) {
|
|
|
|
fprintf(stdout, "%-12s : skipped (--use_existing_db is true)\n",
|
|
|
|
name.ToString().c_str());
|
|
|
|
method = nullptr;
|
|
|
|
} else {
|
|
|
|
if (db_.db != nullptr) {
|
|
|
|
std::for_each(db_.cfh.begin(), db_.cfh.end(),
|
|
|
|
[](ColumnFamilyHandle* cfh) { delete cfh; });
|
|
|
|
delete db_.db;
|
|
|
|
db_.db = nullptr;
|
|
|
|
db_.cfh.clear();
|
|
|
|
DestroyDB(FLAGS_db, open_options_);
|
|
|
|
}
|
|
|
|
for (size_t i = 0; i < multi_dbs_.size(); i++) {
|
|
|
|
delete multi_dbs_[i].db;
|
|
|
|
DestroyDB(GetDbNameForMultiple(FLAGS_db, i), open_options_);
|
|
|
|
}
|
|
|
|
multi_dbs_.clear();
|
|
|
|
}
|
|
|
|
Open(&open_options_); // use open_options for the last accessed
|
|
|
|
}
|
|
|
|
|
|
|
|
if (method != nullptr) {
|
|
|
|
fprintf(stdout, "DB path: [%s]\n", FLAGS_db.c_str());
|
|
|
|
RunBenchmark(num_threads, name, method);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
if (FLAGS_statistics) {
|
|
|
|
fprintf(stdout, "STATISTICS:\n%s\n", dbstats->ToString().c_str());
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
private:
|
|
|
|
struct ThreadArg {
|
|
|
|
Benchmark* bm;
|
|
|
|
SharedState* shared;
|
|
|
|
ThreadState* thread;
|
|
|
|
void (Benchmark::*method)(ThreadState*);
|
|
|
|
};
|
|
|
|
|
|
|
|
static void ThreadBody(void* v) {
|
|
|
|
ThreadArg* arg = reinterpret_cast<ThreadArg*>(v);
|
|
|
|
SharedState* shared = arg->shared;
|
|
|
|
ThreadState* thread = arg->thread;
|
|
|
|
{
|
|
|
|
MutexLock l(&shared->mu);
|
|
|
|
shared->num_initialized++;
|
|
|
|
if (shared->num_initialized >= shared->total) {
|
|
|
|
shared->cv.SignalAll();
|
|
|
|
}
|
|
|
|
while (!shared->start) {
|
|
|
|
shared->cv.Wait();
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
SetPerfLevel(static_cast<PerfLevel> (shared->perf_level));
|
|
|
|
thread->stats.Start(thread->tid);
|
|
|
|
(arg->bm->*(arg->method))(thread);
|
|
|
|
thread->stats.Stop();
|
|
|
|
|
|
|
|
{
|
|
|
|
MutexLock l(&shared->mu);
|
|
|
|
shared->num_done++;
|
|
|
|
if (shared->num_done >= shared->total) {
|
|
|
|
shared->cv.SignalAll();
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void RunBenchmark(int n, Slice name,
|
|
|
|
void (Benchmark::*method)(ThreadState*)) {
|
|
|
|
SharedState shared;
|
|
|
|
shared.total = n;
|
|
|
|
shared.num_initialized = 0;
|
|
|
|
shared.num_done = 0;
|
|
|
|
shared.start = false;
|
|
|
|
|
|
|
|
ThreadArg* arg = new ThreadArg[n];
|
|
|
|
|
|
|
|
for (int i = 0; i < n; i++) {
|
|
|
|
#ifdef NUMA
|
|
|
|
if (FLAGS_enable_numa) {
|
|
|
|
// Performs a local allocation of memory to threads in numa node.
|
|
|
|
int n_nodes = numa_num_task_nodes(); // Number of nodes in NUMA.
|
|
|
|
numa_exit_on_error = 1;
|
|
|
|
int numa_node = i % n_nodes;
|
|
|
|
bitmask* nodes = numa_allocate_nodemask();
|
|
|
|
numa_bitmask_clearall(nodes);
|
|
|
|
numa_bitmask_setbit(nodes, numa_node);
|
|
|
|
// numa_bind() call binds the process to the node and these
|
|
|
|
// properties are passed on to the thread that is created in
|
|
|
|
// StartThread method called later in the loop.
|
|
|
|
numa_bind(nodes);
|
|
|
|
numa_set_strict(1);
|
|
|
|
numa_free_nodemask(nodes);
|
|
|
|
}
|
|
|
|
#endif
|
|
|
|
arg[i].bm = this;
|
|
|
|
arg[i].method = method;
|
|
|
|
arg[i].shared = &shared;
|
|
|
|
arg[i].thread = new ThreadState(i);
|
|
|
|
arg[i].thread->shared = &shared;
|
|
|
|
FLAGS_env->StartThread(ThreadBody, &arg[i]);
|
|
|
|
}
|
|
|
|
|
|
|
|
shared.mu.Lock();
|
|
|
|
while (shared.num_initialized < n) {
|
|
|
|
shared.cv.Wait();
|
|
|
|
}
|
|
|
|
|
|
|
|
shared.start = true;
|
|
|
|
shared.cv.SignalAll();
|
|
|
|
while (shared.num_done < n) {
|
|
|
|
shared.cv.Wait();
|
|
|
|
}
|
|
|
|
shared.mu.Unlock();
|
|
|
|
|
|
|
|
// Stats for some threads can be excluded.
|
|
|
|
Stats merge_stats;
|
|
|
|
for (int i = 0; i < n; i++) {
|
|
|
|
merge_stats.Merge(arg[i].thread->stats);
|
|
|
|
}
|
|
|
|
merge_stats.Report(name);
|
|
|
|
|
|
|
|
for (int i = 0; i < n; i++) {
|
|
|
|
delete arg[i].thread;
|
|
|
|
}
|
|
|
|
delete[] arg;
|
|
|
|
}
|
|
|
|
|
|
|
|
void Crc32c(ThreadState* thread) {
|
|
|
|
// Checksum about 500MB of data total
|
|
|
|
const int size = 4096;
|
|
|
|
const char* label = "(4K per op)";
|
|
|
|
std::string data(size, 'x');
|
|
|
|
int64_t bytes = 0;
|
|
|
|
uint32_t crc = 0;
|
|
|
|
while (bytes < 500 * 1048576) {
|
|
|
|
crc = crc32c::Value(data.data(), size);
|
|
|
|
thread->stats.FinishedOps(nullptr, nullptr, 1);
|
|
|
|
bytes += size;
|
|
|
|
}
|
|
|
|
// Print so result is not dead
|
|
|
|
fprintf(stderr, "... crc=0x%x\r", static_cast<unsigned int>(crc));
|
|
|
|
|
|
|
|
thread->stats.AddBytes(bytes);
|
|
|
|
thread->stats.AddMessage(label);
|
|
|
|
}
|
|
|
|
|
|
|
|
void xxHash(ThreadState* thread) {
|
|
|
|
// Checksum about 500MB of data total
|
|
|
|
const int size = 4096;
|
|
|
|
const char* label = "(4K per op)";
|
|
|
|
std::string data(size, 'x');
|
|
|
|
int64_t bytes = 0;
|
|
|
|
unsigned int xxh32 = 0;
|
|
|
|
while (bytes < 500 * 1048576) {
|
|
|
|
xxh32 = XXH32(data.data(), size, 0);
|
|
|
|
thread->stats.FinishedOps(nullptr, nullptr, 1);
|
|
|
|
bytes += size;
|
|
|
|
}
|
|
|
|
// Print so result is not dead
|
|
|
|
fprintf(stderr, "... xxh32=0x%x\r", static_cast<unsigned int>(xxh32));
|
|
|
|
|
|
|
|
thread->stats.AddBytes(bytes);
|
|
|
|
thread->stats.AddMessage(label);
|
|
|
|
}
|
|
|
|
|
|
|
|
void AcquireLoad(ThreadState* thread) {
|
|
|
|
int dummy;
|
|
|
|
std::atomic<void*> ap(&dummy);
|
|
|
|
int count = 0;
|
|
|
|
void *ptr = nullptr;
|
|
|
|
thread->stats.AddMessage("(each op is 1000 loads)");
|
|
|
|
while (count < 100000) {
|
|
|
|
for (int i = 0; i < 1000; i++) {
|
|
|
|
ptr = ap.load(std::memory_order_acquire);
|
|
|
|
}
|
|
|
|
count++;
|
|
|
|
thread->stats.FinishedOps(nullptr, nullptr, 1);
|
|
|
|
}
|
|
|
|
if (ptr == nullptr) exit(1); // Disable unused variable warning.
|
|
|
|
}
|
|
|
|
|
|
|
|
void Compress(ThreadState *thread) {
|
|
|
|
RandomGenerator gen;
|
|
|
|
Slice input = gen.Generate(FLAGS_block_size);
|
|
|
|
int64_t bytes = 0;
|
|
|
|
int64_t produced = 0;
|
|
|
|
bool ok = true;
|
|
|
|
std::string compressed;
|
|
|
|
|
|
|
|
// Compress 1G
|
|
|
|
while (ok && bytes < int64_t(1) << 30) {
|
|
|
|
switch (FLAGS_compression_type_e) {
|
|
|
|
case rocksdb::kSnappyCompression:
|
|
|
|
ok = Snappy_Compress(Options().compression_opts, input.data(),
|
|
|
|
input.size(), &compressed);
|
|
|
|
break;
|
|
|
|
case rocksdb::kZlibCompression:
|
|
|
|
ok = Zlib_Compress(Options().compression_opts, 2, input.data(),
|
|
|
|
input.size(), &compressed);
|
|
|
|
break;
|
|
|
|
case rocksdb::kBZip2Compression:
|
|
|
|
ok = BZip2_Compress(Options().compression_opts, 2, input.data(),
|
|
|
|
input.size(), &compressed);
|
|
|
|
break;
|
|
|
|
case rocksdb::kLZ4Compression:
|
|
|
|
ok = LZ4_Compress(Options().compression_opts, 2, input.data(),
|
|
|
|
input.size(), &compressed);
|
|
|
|
break;
|
|
|
|
case rocksdb::kLZ4HCCompression:
|
|
|
|
ok = LZ4HC_Compress(Options().compression_opts, 2, input.data(),
|
|
|
|
input.size(), &compressed);
|
|
|
|
break;
|
|
|
|
default:
|
|
|
|
ok = false;
|
|
|
|
}
|
|
|
|
produced += compressed.size();
|
|
|
|
bytes += input.size();
|
|
|
|
thread->stats.FinishedOps(nullptr, nullptr, 1);
|
|
|
|
}
|
|
|
|
|
|
|
|
if (!ok) {
|
|
|
|
thread->stats.AddMessage("(compression failure)");
|
|
|
|
} else {
|
|
|
|
char buf[100];
|
|
|
|
snprintf(buf, sizeof(buf), "(output: %.1f%%)",
|
|
|
|
(produced * 100.0) / bytes);
|
|
|
|
thread->stats.AddMessage(buf);
|
|
|
|
thread->stats.AddBytes(bytes);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void Uncompress(ThreadState *thread) {
|
|
|
|
RandomGenerator gen;
|
|
|
|
Slice input = gen.Generate(FLAGS_block_size);
|
|
|
|
std::string compressed;
|
|
|
|
|
|
|
|
bool ok;
|
|
|
|
switch (FLAGS_compression_type_e) {
|
|
|
|
case rocksdb::kSnappyCompression:
|
|
|
|
ok = Snappy_Compress(Options().compression_opts, input.data(),
|
|
|
|
input.size(), &compressed);
|
|
|
|
break;
|
|
|
|
case rocksdb::kZlibCompression:
|
|
|
|
ok = Zlib_Compress(Options().compression_opts, 2, input.data(),
|
|
|
|
input.size(), &compressed);
|
|
|
|
break;
|
|
|
|
case rocksdb::kBZip2Compression:
|
|
|
|
ok = BZip2_Compress(Options().compression_opts, 2, input.data(),
|
|
|
|
input.size(), &compressed);
|
|
|
|
break;
|
|
|
|
case rocksdb::kLZ4Compression:
|
|
|
|
ok = LZ4_Compress(Options().compression_opts, 2, input.data(),
|
|
|
|
input.size(), &compressed);
|
|
|
|
break;
|
|
|
|
case rocksdb::kLZ4HCCompression:
|
|
|
|
ok = LZ4HC_Compress(Options().compression_opts, 2, input.data(),
|
|
|
|
input.size(), &compressed);
|
|
|
|
break;
|
|
|
|
default:
|
|
|
|
ok = false;
|
|
|
|
}
|
|
|
|
|
|
|
|
int64_t bytes = 0;
|
|
|
|
int decompress_size;
|
|
|
|
while (ok && bytes < 1024 * 1048576) {
|
|
|
|
char *uncompressed = nullptr;
|
|
|
|
switch (FLAGS_compression_type_e) {
|
|
|
|
case rocksdb::kSnappyCompression:
|
|
|
|
// allocate here to make comparison fair
|
|
|
|
uncompressed = new char[input.size()];
|
|
|
|
ok = Snappy_Uncompress(compressed.data(), compressed.size(),
|
|
|
|
uncompressed);
|
|
|
|
break;
|
|
|
|
case rocksdb::kZlibCompression:
|
|
|
|
uncompressed = Zlib_Uncompress(compressed.data(), compressed.size(),
|
|
|
|
&decompress_size, 2);
|
|
|
|
ok = uncompressed != nullptr;
|
|
|
|
break;
|
|
|
|
case rocksdb::kBZip2Compression:
|
|
|
|
uncompressed = BZip2_Uncompress(compressed.data(), compressed.size(),
|
|
|
|
&decompress_size, 2);
|
|
|
|
ok = uncompressed != nullptr;
|
|
|
|
break;
|
|
|
|
case rocksdb::kLZ4Compression:
|
|
|
|
uncompressed = LZ4_Uncompress(compressed.data(), compressed.size(),
|
|
|
|
&decompress_size, 2);
|
|
|
|
ok = uncompressed != nullptr;
|
|
|
|
break;
|
|
|
|
case rocksdb::kLZ4HCCompression:
|
|
|
|
uncompressed = LZ4_Uncompress(compressed.data(), compressed.size(),
|
|
|
|
&decompress_size, 2);
|
|
|
|
ok = uncompressed != nullptr;
|
|
|
|
break;
|
|
|
|
default:
|
|
|
|
ok = false;
|
|
|
|
}
|
|
|
|
delete[] uncompressed;
|
|
|
|
bytes += input.size();
|
|
|
|
thread->stats.FinishedOps(nullptr, nullptr, 1);
|
|
|
|
}
|
|
|
|
|
|
|
|
if (!ok) {
|
|
|
|
thread->stats.AddMessage("(compression failure)");
|
|
|
|
} else {
|
|
|
|
thread->stats.AddBytes(bytes);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void Open(Options* opts) {
|
|
|
|
Options& options = *opts;
|
|
|
|
|
|
|
|
assert(db_.db == nullptr);
|
|
|
|
|
|
|
|
options.create_if_missing = !FLAGS_use_existing_db;
|
|
|
|
options.create_missing_column_families = FLAGS_num_column_families > 1;
|
|
|
|
options.db_write_buffer_size = FLAGS_db_write_buffer_size;
|
|
|
|
options.write_buffer_size = FLAGS_write_buffer_size;
|
|
|
|
options.max_write_buffer_number = FLAGS_max_write_buffer_number;
|
|
|
|
options.min_write_buffer_number_to_merge =
|
|
|
|
FLAGS_min_write_buffer_number_to_merge;
|
|
|
|
options.max_background_compactions = FLAGS_max_background_compactions;
|
|
|
|
options.max_background_flushes = FLAGS_max_background_flushes;
|
|
|
|
options.compaction_style = FLAGS_compaction_style_e;
|
|
|
|
if (FLAGS_prefix_size != 0) {
|
|
|
|
options.prefix_extractor.reset(
|
|
|
|
NewFixedPrefixTransform(FLAGS_prefix_size));
|
|
|
|
}
|
|
|
|
if (FLAGS_use_uint64_comparator) {
|
|
|
|
options.comparator = test::Uint64Comparator();
|
|
|
|
if (FLAGS_key_size != 8) {
|
|
|
|
fprintf(stderr, "Using Uint64 comparator but key size is not 8.\n");
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
options.memtable_prefix_bloom_bits = FLAGS_memtable_bloom_bits;
|
|
|
|
options.bloom_locality = FLAGS_bloom_locality;
|
|
|
|
options.max_open_files = FLAGS_open_files;
|
|
|
|
options.statistics = dbstats;
|
|
|
|
if (FLAGS_enable_io_prio) {
|
|
|
|
FLAGS_env->LowerThreadPoolIOPriority(Env::LOW);
|
|
|
|
FLAGS_env->LowerThreadPoolIOPriority(Env::HIGH);
|
|
|
|
}
|
|
|
|
options.env = FLAGS_env;
|
|
|
|
options.disableDataSync = FLAGS_disable_data_sync;
|
|
|
|
options.use_fsync = FLAGS_use_fsync;
|
|
|
|
options.wal_dir = FLAGS_wal_dir;
|
|
|
|
options.num_levels = FLAGS_num_levels;
|
|
|
|
options.target_file_size_base = FLAGS_target_file_size_base;
|
|
|
|
options.target_file_size_multiplier = FLAGS_target_file_size_multiplier;
|
|
|
|
options.max_bytes_for_level_base = FLAGS_max_bytes_for_level_base;
|
options.level_compaction_dynamic_level_bytes to allow RocksDB to pick size bases of levels dynamically.
Summary:
When having fixed max_bytes_for_level_base, the ratio of size of largest level and the second one can range from 0 to the multiplier. This makes LSM tree frequently irregular and unpredictable. It can also cause poor space amplification in some cases.
In this improvement (proposed by Igor Kabiljo), we introduce a parameter option.level_compaction_use_dynamic_max_bytes. When turning it on, RocksDB is free to pick a level base in the range of (options.max_bytes_for_level_base/options.max_bytes_for_level_multiplier, options.max_bytes_for_level_base] so that real level ratios are close to options.max_bytes_for_level_multiplier.
Test Plan: New unit tests and pass tests suites including valgrind.
Reviewers: MarkCallaghan, rven, yhchiang, igor, ikabiljo
Reviewed By: ikabiljo
Subscribers: yoshinorim, ikabiljo, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D31437
10 years ago
|
|
|
options.level_compaction_dynamic_level_bytes =
|
|
|
|
FLAGS_level_compaction_dynamic_level_bytes;
|
|
|
|
options.max_bytes_for_level_multiplier =
|
|
|
|
FLAGS_max_bytes_for_level_multiplier;
|
|
|
|
options.filter_deletes = FLAGS_filter_deletes;
|
|
|
|
if ((FLAGS_prefix_size == 0) && (FLAGS_rep_factory == kPrefixHash ||
|
|
|
|
FLAGS_rep_factory == kHashLinkedList)) {
|
|
|
|
fprintf(stderr, "prefix_size should be non-zero if PrefixHash or "
|
|
|
|
"HashLinkedList memtablerep is used\n");
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
switch (FLAGS_rep_factory) {
|
|
|
|
case kSkipList:
|
SkipListRep::LookaheadIterator
Summary:
This diff introduces the `lookahead` argument to `SkipListFactory()`. This is an
optimization for the tailing use case which includes many seeks. E.g. consider
the following operations on a skip list iterator:
Seek(x), Next(), Next(), Seek(x+2), Next(), Seek(x+3), Next(), Next(), ...
If `lookahead` is positive, `SkipListRep` will return an iterator which also
keeps track of the previously visited node. Seek() then first does a linear
search starting from that node (up to `lookahead` steps). As in the tailing
example above, this may require fewer than ~log(n) comparisons as with regular
skip list search.
Test Plan:
Added a new benchmark (`fillseekseq`) which simulates the usage pattern. It
first writes N records (with consecutive keys), then measures how much time it
takes to read them by calling `Seek()` and `Next()`.
$ time ./db_bench -num 10000000 -benchmarks fillseekseq -prefix_size 1 \
-key_size 8 -write_buffer_size $[1024*1024*1024] -value_size 50 \
-seekseq_next 2 -skip_list_lookahead=0
[...]
DB path: [/dev/shm/rocksdbtest/dbbench]
fillseekseq : 0.389 micros/op 2569047 ops/sec;
real 0m21.806s
user 0m12.106s
sys 0m9.672s
$ time ./db_bench [...] -skip_list_lookahead=2
[...]
DB path: [/dev/shm/rocksdbtest/dbbench]
fillseekseq : 0.153 micros/op 6540684 ops/sec;
real 0m19.469s
user 0m10.192s
sys 0m9.252s
Reviewers: ljin, sdong, igor
Reviewed By: igor
Subscribers: dhruba, leveldb, march, lovro
Differential Revision: https://reviews.facebook.net/D23997
10 years ago
|
|
|
options.memtable_factory.reset(new SkipListFactory(
|
|
|
|
FLAGS_skip_list_lookahead));
|
|
|
|
break;
|
|
|
|
#ifndef ROCKSDB_LITE
|
|
|
|
case kPrefixHash:
|
|
|
|
options.memtable_factory.reset(
|
|
|
|
NewHashSkipListRepFactory(FLAGS_hash_bucket_count));
|
|
|
|
break;
|
|
|
|
case kHashLinkedList:
|
|
|
|
options.memtable_factory.reset(NewHashLinkListRepFactory(
|
|
|
|
FLAGS_hash_bucket_count));
|
|
|
|
break;
|
|
|
|
case kVectorRep:
|
|
|
|
options.memtable_factory.reset(
|
|
|
|
new VectorRepFactory
|
|
|
|
);
|
|
|
|
break;
|
Add a new mem-table representation based on cuckoo hash.
Summary:
= Major Changes =
* Add a new mem-table representation, HashCuckooRep, which is based cuckoo hash.
Cuckoo hash uses multiple hash functions. This allows each key to have multiple
possible locations in the mem-table.
- Put: When insert a key, it will try to find whether one of its possible
locations is vacant and store the key. If none of its possible
locations are available, then it will kick out a victim key and
store at that location. The kicked-out victim key will then be
stored at a vacant space of its possible locations or kick-out
another victim. In this diff, the kick-out path (known as
cuckoo-path) is found using BFS, which guarantees to be the shortest.
- Get: Simply tries all possible locations of a key --- this guarantees
worst-case constant time complexity.
- Time complexity: O(1) for Get, and average O(1) for Put if the
fullness of the mem-table is below 80%.
- Default using two hash functions, the number of hash functions used
by the cuckoo-hash may dynamically increase if it fails to find a
short-enough kick-out path.
- Currently, HashCuckooRep does not support iteration and snapshots,
as our current main purpose of this is to optimize point access.
= Minor Changes =
* Add IsSnapshotSupported() to DB to indicate whether the current DB
supports snapshots. If it returns false, then DB::GetSnapshot() will
always return nullptr.
Test Plan:
Run existing tests. Will develop a test specifically for cuckoo hash in
the next diff.
Reviewers: sdong, haobo
Reviewed By: sdong
CC: leveldb, dhruba, igor
Differential Revision: https://reviews.facebook.net/D16155
11 years ago
|
|
|
case kCuckoo:
|
|
|
|
options.memtable_factory.reset(NewHashCuckooRepFactory(
|
|
|
|
options.write_buffer_size, FLAGS_key_size + FLAGS_value_size));
|
|
|
|
break;
|
|
|
|
#else
|
|
|
|
default:
|
|
|
|
fprintf(stderr, "Only skip list is supported in lite mode\n");
|
|
|
|
exit(1);
|
|
|
|
#endif // ROCKSDB_LITE
|
|
|
|
}
|
|
|
|
if (FLAGS_use_plain_table) {
|
|
|
|
#ifndef ROCKSDB_LITE
|
|
|
|
if (FLAGS_rep_factory != kPrefixHash &&
|
|
|
|
FLAGS_rep_factory != kHashLinkedList) {
|
|
|
|
fprintf(stderr, "Waring: plain table is used with skipList\n");
|
|
|
|
}
|
|
|
|
if (!FLAGS_mmap_read && !FLAGS_mmap_write) {
|
|
|
|
fprintf(stderr, "plain table format requires mmap to operate\n");
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
|
|
|
|
int bloom_bits_per_key = FLAGS_bloom_bits;
|
|
|
|
if (bloom_bits_per_key < 0) {
|
|
|
|
bloom_bits_per_key = 0;
|
|
|
|
}
|
|
|
|
|
|
|
|
PlainTableOptions plain_table_options;
|
|
|
|
plain_table_options.user_key_len = FLAGS_key_size;
|
|
|
|
plain_table_options.bloom_bits_per_key = bloom_bits_per_key;
|
|
|
|
plain_table_options.hash_table_ratio = 0.75;
|
|
|
|
options.table_factory = std::shared_ptr<TableFactory>(
|
|
|
|
NewPlainTableFactory(plain_table_options));
|
|
|
|
#else
|
|
|
|
fprintf(stderr, "Plain table is not supported in lite mode\n");
|
|
|
|
exit(1);
|
|
|
|
#endif // ROCKSDB_LITE
|
|
|
|
} else if (FLAGS_use_cuckoo_table) {
|
|
|
|
#ifndef ROCKSDB_LITE
|
|
|
|
if (FLAGS_cuckoo_hash_ratio > 1 || FLAGS_cuckoo_hash_ratio < 0) {
|
|
|
|
fprintf(stderr, "Invalid cuckoo_hash_ratio\n");
|
|
|
|
exit(1);
|
|
|
|
}
|
CuckooTable: add one option to allow identity function for the first hash function
Summary:
MurmurHash becomes expensive when we do millions Get() a second in one
thread. Add this option to allow the first hash function to use identity
function as hash function. It results in QPS increase from 3.7M/s to
~4.3M/s. I did not observe improvement for end to end RocksDB
performance. This may be caused by other bottlenecks that I will address
in a separate diff.
Test Plan:
```
[ljin@dev1964 rocksdb] ./cuckoo_table_reader_test --enable_perf --file_dir=/dev/shm --write --identity_as_first_hash=0
==== Test CuckooReaderTest.WhenKeyExists
==== Test CuckooReaderTest.WhenKeyExistsWithUint64Comparator
==== Test CuckooReaderTest.CheckIterator
==== Test CuckooReaderTest.CheckIteratorUint64
==== Test CuckooReaderTest.WhenKeyNotFound
==== Test CuckooReaderTest.TestReadPerformance
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.272us (3.7 Mqps) with batch size of 0, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.138us (7.2 Mqps) with batch size of 10, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.142us (7.1 Mqps) with batch size of 25, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.142us (7.0 Mqps) with batch size of 50, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.144us (6.9 Mqps) with batch size of 100, # of found keys 125829120
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.201us (5.0 Mqps) with batch size of 0, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.121us (8.3 Mqps) with batch size of 10, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.123us (8.1 Mqps) with batch size of 25, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.121us (8.3 Mqps) with batch size of 50, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.112us (8.9 Mqps) with batch size of 100, # of found keys 104857600
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.251us (4.0 Mqps) with batch size of 0, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.107us (9.4 Mqps) with batch size of 10, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.099us (10.1 Mqps) with batch size of 25, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.100us (10.0 Mqps) with batch size of 50, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.116us (8.6 Mqps) with batch size of 100, # of found keys 83886080
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.189us (5.3 Mqps) with batch size of 0, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.095us (10.5 Mqps) with batch size of 10, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.096us (10.4 Mqps) with batch size of 25, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.098us (10.2 Mqps) with batch size of 50, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.105us (9.5 Mqps) with batch size of 100, # of found keys 73400320
[ljin@dev1964 rocksdb] ./cuckoo_table_reader_test --enable_perf --file_dir=/dev/shm --write --identity_as_first_hash=1
==== Test CuckooReaderTest.WhenKeyExists
==== Test CuckooReaderTest.WhenKeyExistsWithUint64Comparator
==== Test CuckooReaderTest.CheckIterator
==== Test CuckooReaderTest.CheckIteratorUint64
==== Test CuckooReaderTest.WhenKeyNotFound
==== Test CuckooReaderTest.TestReadPerformance
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.230us (4.3 Mqps) with batch size of 0, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.086us (11.7 Mqps) with batch size of 10, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.088us (11.3 Mqps) with batch size of 25, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.083us (12.1 Mqps) with batch size of 50, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.083us (12.1 Mqps) with batch size of 100, # of found keys 125829120
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.159us (6.3 Mqps) with batch size of 0, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.078us (12.8 Mqps) with batch size of 10, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.080us (12.6 Mqps) with batch size of 25, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.080us (12.5 Mqps) with batch size of 50, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.082us (12.2 Mqps) with batch size of 100, # of found keys 104857600
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.154us (6.5 Mqps) with batch size of 0, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.077us (13.0 Mqps) with batch size of 10, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.077us (12.9 Mqps) with batch size of 25, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.078us (12.8 Mqps) with batch size of 50, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.079us (12.6 Mqps) with batch size of 100, # of found keys 83886080
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.218us (4.6 Mqps) with batch size of 0, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.083us (12.0 Mqps) with batch size of 10, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.085us (11.7 Mqps) with batch size of 25, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.086us (11.6 Mqps) with batch size of 50, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.078us (12.8 Mqps) with batch size of 100, # of found keys 73400320
```
Reviewers: sdong, igor, yhchiang
Reviewed By: igor
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D23451
10 years ago
|
|
|
rocksdb::CuckooTableOptions table_options;
|
|
|
|
table_options.hash_table_ratio = FLAGS_cuckoo_hash_ratio;
|
|
|
|
table_options.identity_as_first_hash = FLAGS_identity_as_first_hash;
|
|
|
|
options.table_factory = std::shared_ptr<TableFactory>(
|
CuckooTable: add one option to allow identity function for the first hash function
Summary:
MurmurHash becomes expensive when we do millions Get() a second in one
thread. Add this option to allow the first hash function to use identity
function as hash function. It results in QPS increase from 3.7M/s to
~4.3M/s. I did not observe improvement for end to end RocksDB
performance. This may be caused by other bottlenecks that I will address
in a separate diff.
Test Plan:
```
[ljin@dev1964 rocksdb] ./cuckoo_table_reader_test --enable_perf --file_dir=/dev/shm --write --identity_as_first_hash=0
==== Test CuckooReaderTest.WhenKeyExists
==== Test CuckooReaderTest.WhenKeyExistsWithUint64Comparator
==== Test CuckooReaderTest.CheckIterator
==== Test CuckooReaderTest.CheckIteratorUint64
==== Test CuckooReaderTest.WhenKeyNotFound
==== Test CuckooReaderTest.TestReadPerformance
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.272us (3.7 Mqps) with batch size of 0, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.138us (7.2 Mqps) with batch size of 10, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.142us (7.1 Mqps) with batch size of 25, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.142us (7.0 Mqps) with batch size of 50, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.144us (6.9 Mqps) with batch size of 100, # of found keys 125829120
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.201us (5.0 Mqps) with batch size of 0, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.121us (8.3 Mqps) with batch size of 10, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.123us (8.1 Mqps) with batch size of 25, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.121us (8.3 Mqps) with batch size of 50, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.112us (8.9 Mqps) with batch size of 100, # of found keys 104857600
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.251us (4.0 Mqps) with batch size of 0, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.107us (9.4 Mqps) with batch size of 10, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.099us (10.1 Mqps) with batch size of 25, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.100us (10.0 Mqps) with batch size of 50, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.116us (8.6 Mqps) with batch size of 100, # of found keys 83886080
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.189us (5.3 Mqps) with batch size of 0, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.095us (10.5 Mqps) with batch size of 10, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.096us (10.4 Mqps) with batch size of 25, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.098us (10.2 Mqps) with batch size of 50, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.105us (9.5 Mqps) with batch size of 100, # of found keys 73400320
[ljin@dev1964 rocksdb] ./cuckoo_table_reader_test --enable_perf --file_dir=/dev/shm --write --identity_as_first_hash=1
==== Test CuckooReaderTest.WhenKeyExists
==== Test CuckooReaderTest.WhenKeyExistsWithUint64Comparator
==== Test CuckooReaderTest.CheckIterator
==== Test CuckooReaderTest.CheckIteratorUint64
==== Test CuckooReaderTest.WhenKeyNotFound
==== Test CuckooReaderTest.TestReadPerformance
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.230us (4.3 Mqps) with batch size of 0, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.086us (11.7 Mqps) with batch size of 10, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.088us (11.3 Mqps) with batch size of 25, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.083us (12.1 Mqps) with batch size of 50, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.083us (12.1 Mqps) with batch size of 100, # of found keys 125829120
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.159us (6.3 Mqps) with batch size of 0, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.078us (12.8 Mqps) with batch size of 10, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.080us (12.6 Mqps) with batch size of 25, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.080us (12.5 Mqps) with batch size of 50, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.082us (12.2 Mqps) with batch size of 100, # of found keys 104857600
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.154us (6.5 Mqps) with batch size of 0, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.077us (13.0 Mqps) with batch size of 10, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.077us (12.9 Mqps) with batch size of 25, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.078us (12.8 Mqps) with batch size of 50, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.079us (12.6 Mqps) with batch size of 100, # of found keys 83886080
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.218us (4.6 Mqps) with batch size of 0, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.083us (12.0 Mqps) with batch size of 10, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.085us (11.7 Mqps) with batch size of 25, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.086us (11.6 Mqps) with batch size of 50, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.078us (12.8 Mqps) with batch size of 100, # of found keys 73400320
```
Reviewers: sdong, igor, yhchiang
Reviewed By: igor
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D23451
10 years ago
|
|
|
NewCuckooTableFactory(table_options));
|
|
|
|
#else
|
|
|
|
fprintf(stderr, "Cuckoo table is not supported in lite mode\n");
|
|
|
|
exit(1);
|
|
|
|
#endif // ROCKSDB_LITE
|
|
|
|
} else {
|
|
|
|
BlockBasedTableOptions block_based_options;
|
|
|
|
if (FLAGS_use_hash_search) {
|
|
|
|
if (FLAGS_prefix_size == 0) {
|
|
|
|
fprintf(stderr,
|
|
|
|
"prefix_size not assigned when enable use_hash_search \n");
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
block_based_options.index_type = BlockBasedTableOptions::kHashSearch;
|
|
|
|
} else {
|
|
|
|
block_based_options.index_type = BlockBasedTableOptions::kBinarySearch;
|
|
|
|
}
|
|
|
|
if (cache_ == nullptr) {
|
|
|
|
block_based_options.no_block_cache = true;
|
|
|
|
}
|
|
|
|
block_based_options.block_cache = cache_;
|
|
|
|
block_based_options.block_cache_compressed = compressed_cache_;
|
|
|
|
block_based_options.block_size = FLAGS_block_size;
|
|
|
|
block_based_options.block_restart_interval = FLAGS_block_restart_interval;
|
|
|
|
block_based_options.filter_policy = filter_policy_;
|
|
|
|
block_based_options.format_version = 2;
|
|
|
|
options.table_factory.reset(
|
|
|
|
NewBlockBasedTableFactory(block_based_options));
|
|
|
|
}
|
|
|
|
if (FLAGS_max_bytes_for_level_multiplier_additional_v.size() > 0) {
|
|
|
|
if (FLAGS_max_bytes_for_level_multiplier_additional_v.size() !=
|
|
|
|
(unsigned int)FLAGS_num_levels) {
|
|
|
|
fprintf(stderr, "Insufficient number of fanouts specified %d\n",
|
|
|
|
(int)FLAGS_max_bytes_for_level_multiplier_additional_v.size());
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
options.max_bytes_for_level_multiplier_additional =
|
|
|
|
FLAGS_max_bytes_for_level_multiplier_additional_v;
|
|
|
|
}
|
|
|
|
options.level0_stop_writes_trigger = FLAGS_level0_stop_writes_trigger;
|
|
|
|
options.level0_file_num_compaction_trigger =
|
|
|
|
FLAGS_level0_file_num_compaction_trigger;
|
|
|
|
options.level0_slowdown_writes_trigger =
|
|
|
|
FLAGS_level0_slowdown_writes_trigger;
|
|
|
|
options.compression = FLAGS_compression_type_e;
|
|
|
|
options.compression_opts.level = FLAGS_compression_level;
|
|
|
|
options.WAL_ttl_seconds = FLAGS_wal_ttl_seconds;
|
|
|
|
options.WAL_size_limit_MB = FLAGS_wal_size_limit_MB;
|
|
|
|
options.max_total_wal_size = FLAGS_max_total_wal_size;
|
|
|
|
|
|
|
|
if (FLAGS_min_level_to_compress >= 0) {
|
|
|
|
assert(FLAGS_min_level_to_compress <= FLAGS_num_levels);
|
|
|
|
options.compression_per_level.resize(FLAGS_num_levels);
|
|
|
|
for (int i = 0; i < FLAGS_min_level_to_compress; i++) {
|
|
|
|
options.compression_per_level[i] = kNoCompression;
|
|
|
|
}
|
|
|
|
for (int i = FLAGS_min_level_to_compress;
|
|
|
|
i < FLAGS_num_levels; i++) {
|
|
|
|
options.compression_per_level[i] = FLAGS_compression_type_e;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
options.soft_rate_limit = FLAGS_soft_rate_limit;
|
|
|
|
options.hard_rate_limit = FLAGS_hard_rate_limit;
|
|
|
|
options.rate_limit_delay_max_milliseconds =
|
|
|
|
FLAGS_rate_limit_delay_max_milliseconds;
|
|
|
|
options.table_cache_numshardbits = FLAGS_table_cache_numshardbits;
|
|
|
|
options.max_grandparent_overlap_factor =
|
|
|
|
FLAGS_max_grandparent_overlap_factor;
|
|
|
|
options.disable_auto_compactions = FLAGS_disable_auto_compactions;
|
|
|
|
options.source_compaction_factor = FLAGS_source_compaction_factor;
|
|
|
|
|
|
|
|
// fill storage options
|
|
|
|
options.allow_os_buffer = FLAGS_bufferedio;
|
|
|
|
options.allow_mmap_reads = FLAGS_mmap_read;
|
|
|
|
options.allow_mmap_writes = FLAGS_mmap_write;
|
|
|
|
options.advise_random_on_open = FLAGS_advise_random_on_open;
|
|
|
|
options.access_hint_on_compaction_start = FLAGS_compaction_fadvice_e;
|
|
|
|
options.use_adaptive_mutex = FLAGS_use_adaptive_mutex;
|
|
|
|
options.bytes_per_sync = FLAGS_bytes_per_sync;
|
|
|
|
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
// merge operator options
|
|
|
|
options.merge_operator = MergeOperators::CreateFromStringId(
|
|
|
|
FLAGS_merge_operator);
|
|
|
|
if (options.merge_operator == nullptr && !FLAGS_merge_operator.empty()) {
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
fprintf(stderr, "invalid merge operator: %s\n",
|
|
|
|
FLAGS_merge_operator.c_str());
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
options.max_successive_merges = FLAGS_max_successive_merges;
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
|
|
|
|
// set universal style compaction configurations, if applicable
|
|
|
|
if (FLAGS_universal_size_ratio != 0) {
|
|
|
|
options.compaction_options_universal.size_ratio =
|
|
|
|
FLAGS_universal_size_ratio;
|
|
|
|
}
|
|
|
|
if (FLAGS_universal_min_merge_width != 0) {
|
|
|
|
options.compaction_options_universal.min_merge_width =
|
|
|
|
FLAGS_universal_min_merge_width;
|
|
|
|
}
|
|
|
|
if (FLAGS_universal_max_merge_width != 0) {
|
|
|
|
options.compaction_options_universal.max_merge_width =
|
|
|
|
FLAGS_universal_max_merge_width;
|
|
|
|
}
|
|
|
|
if (FLAGS_universal_max_size_amplification_percent != 0) {
|
|
|
|
options.compaction_options_universal.max_size_amplification_percent =
|
|
|
|
FLAGS_universal_max_size_amplification_percent;
|
|
|
|
}
|
|
|
|
if (FLAGS_universal_compression_size_percent != -1) {
|
|
|
|
options.compaction_options_universal.compression_size_percent =
|
|
|
|
FLAGS_universal_compression_size_percent;
|
|
|
|
}
|
|
|
|
if (FLAGS_thread_status_per_interval > 0) {
|
|
|
|
options.enable_thread_tracking = true;
|
|
|
|
}
|
|
|
|
|
|
|
|
if (FLAGS_num_multi_db <= 1) {
|
|
|
|
OpenDb(options, FLAGS_db, &db_);
|
|
|
|
} else {
|
|
|
|
multi_dbs_.clear();
|
|
|
|
multi_dbs_.resize(FLAGS_num_multi_db);
|
|
|
|
for (int i = 0; i < FLAGS_num_multi_db; i++) {
|
|
|
|
OpenDb(options, GetDbNameForMultiple(FLAGS_db, i), &multi_dbs_[i]);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
if (FLAGS_min_level_to_compress >= 0) {
|
|
|
|
options.compression_per_level.clear();
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void OpenDb(const Options& options, const std::string& db_name,
|
|
|
|
DBWithColumnFamilies* db) {
|
|
|
|
Status s;
|
|
|
|
// Open with column families if necessary.
|
|
|
|
if (FLAGS_num_column_families > 1) {
|
|
|
|
size_t num_hot = FLAGS_num_column_families;
|
|
|
|
if (FLAGS_num_hot_column_families > 0 &&
|
|
|
|
FLAGS_num_hot_column_families < FLAGS_num_column_families) {
|
|
|
|
num_hot = FLAGS_num_hot_column_families;
|
|
|
|
} else {
|
|
|
|
FLAGS_num_hot_column_families = FLAGS_num_column_families;
|
|
|
|
}
|
|
|
|
std::vector<ColumnFamilyDescriptor> column_families;
|
|
|
|
for (size_t i = 0; i < num_hot; i++) {
|
|
|
|
column_families.push_back(ColumnFamilyDescriptor(
|
|
|
|
ColumnFamilyName(i), ColumnFamilyOptions(options)));
|
|
|
|
}
|
|
|
|
if (FLAGS_readonly) {
|
|
|
|
s = DB::OpenForReadOnly(options, db_name, column_families,
|
|
|
|
&db->cfh, &db->db);
|
|
|
|
} else {
|
|
|
|
s = DB::Open(options, db_name, column_families, &db->cfh, &db->db);
|
|
|
|
}
|
|
|
|
db->cfh.resize(FLAGS_num_column_families);
|
|
|
|
db->num_created = num_hot;
|
|
|
|
db->num_hot = num_hot;
|
|
|
|
|
|
|
|
} else if (FLAGS_readonly) {
|
|
|
|
s = DB::OpenForReadOnly(options, db_name, &db->db);
|
|
|
|
} else {
|
|
|
|
s = DB::Open(options, db_name, &db->db);
|
|
|
|
}
|
|
|
|
if (!s.ok()) {
|
|
|
|
fprintf(stderr, "open error: %s\n", s.ToString().c_str());
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
enum WriteMode {
|
|
|
|
RANDOM, SEQUENTIAL, UNIQUE_RANDOM
|
|
|
|
};
|
|
|
|
|
|
|
|
void WriteSeq(ThreadState* thread) {
|
|
|
|
DoWrite(thread, SEQUENTIAL);
|
|
|
|
}
|
|
|
|
|
|
|
|
void WriteRandom(ThreadState* thread) {
|
|
|
|
DoWrite(thread, RANDOM);
|
|
|
|
}
|
|
|
|
|
|
|
|
void WriteUniqueRandom(ThreadState* thread) {
|
|
|
|
DoWrite(thread, UNIQUE_RANDOM);
|
|
|
|
}
|
|
|
|
|
|
|
|
class KeyGenerator {
|
|
|
|
public:
|
|
|
|
KeyGenerator(Random64* rand, WriteMode mode,
|
|
|
|
uint64_t num, uint64_t num_per_set = 64 * 1024)
|
|
|
|
: rand_(rand),
|
|
|
|
mode_(mode),
|
|
|
|
num_(num),
|
|
|
|
next_(0) {
|
|
|
|
if (mode_ == UNIQUE_RANDOM) {
|
|
|
|
// NOTE: if memory consumption of this approach becomes a concern,
|
|
|
|
// we can either break it into pieces and only random shuffle a section
|
|
|
|
// each time. Alternatively, use a bit map implementation
|
|
|
|
// (https://reviews.facebook.net/differential/diff/54627/)
|
|
|
|
values_.resize(num_);
|
|
|
|
for (uint64_t i = 0; i < num_; ++i) {
|
|
|
|
values_[i] = i;
|
|
|
|
}
|
|
|
|
std::shuffle(
|
|
|
|
values_.begin(), values_.end(),
|
|
|
|
std::default_random_engine(static_cast<unsigned int>(FLAGS_seed)));
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
uint64_t Next() {
|
|
|
|
switch (mode_) {
|
|
|
|
case SEQUENTIAL:
|
|
|
|
return next_++;
|
|
|
|
case RANDOM:
|
|
|
|
return rand_->Next() % num_;
|
|
|
|
case UNIQUE_RANDOM:
|
|
|
|
return values_[next_++];
|
|
|
|
}
|
|
|
|
assert(false);
|
|
|
|
return std::numeric_limits<uint64_t>::max();
|
|
|
|
}
|
|
|
|
|
|
|
|
private:
|
|
|
|
Random64* rand_;
|
|
|
|
WriteMode mode_;
|
|
|
|
const uint64_t num_;
|
|
|
|
uint64_t next_;
|
|
|
|
std::vector<uint64_t> values_;
|
|
|
|
};
|
|
|
|
|
|
|
|
DB* SelectDB(ThreadState* thread) {
|
|
|
|
return SelectDBWithCfh(thread)->db;
|
|
|
|
}
|
|
|
|
|
|
|
|
DBWithColumnFamilies* SelectDBWithCfh(ThreadState* thread) {
|
|
|
|
return SelectDBWithCfh(thread->rand.Next());
|
|
|
|
}
|
|
|
|
|
|
|
|
DBWithColumnFamilies* SelectDBWithCfh(uint64_t rand_int) {
|
|
|
|
if (db_.db != nullptr) {
|
|
|
|
return &db_;
|
|
|
|
} else {
|
|
|
|
return &multi_dbs_[rand_int % multi_dbs_.size()];
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void DoWrite(ThreadState* thread, WriteMode write_mode) {
|
|
|
|
const int test_duration = write_mode == RANDOM ? FLAGS_duration : 0;
|
|
|
|
const int64_t num_ops = writes_ == 0 ? num_ : writes_;
|
|
|
|
|
|
|
|
size_t num_key_gens = 1;
|
|
|
|
if (db_.db == nullptr) {
|
|
|
|
num_key_gens = multi_dbs_.size();
|
|
|
|
}
|
|
|
|
std::vector<std::unique_ptr<KeyGenerator>> key_gens(num_key_gens);
|
|
|
|
int64_t max_ops = num_ops * num_key_gens;
|
|
|
|
int64_t ops_per_stage = max_ops;
|
|
|
|
if (FLAGS_num_column_families > 1 && FLAGS_num_hot_column_families > 0) {
|
|
|
|
ops_per_stage = (max_ops - 1) / (FLAGS_num_column_families /
|
|
|
|
FLAGS_num_hot_column_families) +
|
|
|
|
1;
|
|
|
|
}
|
|
|
|
|
|
|
|
Duration duration(test_duration, max_ops, ops_per_stage);
|
|
|
|
for (size_t i = 0; i < num_key_gens; i++) {
|
|
|
|
key_gens[i].reset(new KeyGenerator(&(thread->rand), write_mode, num_,
|
|
|
|
ops_per_stage));
|
|
|
|
}
|
|
|
|
|
|
|
|
if (num_ != FLAGS_num) {
|
|
|
|
char msg[100];
|
|
|
|
snprintf(msg, sizeof(msg), "(%" PRIu64 " ops)", num_);
|
|
|
|
thread->stats.AddMessage(msg);
|
|
|
|
}
|
|
|
|
|
|
|
|
RandomGenerator gen;
|
|
|
|
WriteBatch batch;
|
|
|
|
Status s;
|
|
|
|
int64_t bytes = 0;
|
|
|
|
|
|
|
|
std::unique_ptr<const char[]> key_guard;
|
|
|
|
Slice key = AllocateKey(&key_guard);
|
|
|
|
int64_t stage = 0;
|
|
|
|
while (!duration.Done(entries_per_batch_)) {
|
|
|
|
if (duration.GetStage() != stage) {
|
|
|
|
stage = duration.GetStage();
|
|
|
|
if (db_.db != nullptr) {
|
|
|
|
db_.CreateNewCf(open_options_, stage);
|
|
|
|
} else {
|
|
|
|
for (auto& db : multi_dbs_) {
|
|
|
|
db.CreateNewCf(open_options_, stage);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
size_t id = thread->rand.Next() % num_key_gens;
|
|
|
|
DBWithColumnFamilies* db_with_cfh = SelectDBWithCfh(id);
|
|
|
|
batch.Clear();
|
|
|
|
for (int64_t j = 0; j < entries_per_batch_; j++) {
|
|
|
|
int64_t rand_num = key_gens[id]->Next();
|
|
|
|
GenerateKeyFromInt(rand_num, FLAGS_num, &key);
|
|
|
|
if (FLAGS_num_column_families <= 1) {
|
|
|
|
batch.Put(key, gen.Generate(value_size_));
|
|
|
|
} else {
|
|
|
|
// We use same rand_num as seed for key and column family so that we
|
|
|
|
// can deterministically find the cfh corresponding to a particular
|
|
|
|
// key while reading the key.
|
|
|
|
batch.Put(db_with_cfh->GetCfh(rand_num), key,
|
|
|
|
gen.Generate(value_size_));
|
|
|
|
}
|
|
|
|
bytes += value_size_ + key_size_;
|
|
|
|
}
|
|
|
|
s = db_with_cfh->db->Write(write_options_, &batch);
|
|
|
|
thread->stats.FinishedOps(db_with_cfh, db_with_cfh->db,
|
|
|
|
entries_per_batch_);
|
|
|
|
if (!s.ok()) {
|
|
|
|
fprintf(stderr, "put error: %s\n", s.ToString().c_str());
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
thread->stats.AddBytes(bytes);
|
|
|
|
}
|
|
|
|
|
|
|
|
void ReadSequential(ThreadState* thread) {
|
|
|
|
if (db_.db != nullptr) {
|
|
|
|
ReadSequential(thread, db_.db);
|
|
|
|
} else {
|
|
|
|
for (const auto& db_with_cfh : multi_dbs_) {
|
|
|
|
ReadSequential(thread, db_with_cfh.db);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void ReadSequential(ThreadState* thread, DB* db) {
|
|
|
|
ReadOptions options(FLAGS_verify_checksum, true);
|
|
|
|
options.tailing = FLAGS_use_tailing_iterator;
|
|
|
|
|
|
|
|
Iterator* iter = db->NewIterator(options);
|
|
|
|
int64_t i = 0;
|
|
|
|
int64_t bytes = 0;
|
|
|
|
for (iter->SeekToFirst(); i < reads_ && iter->Valid(); iter->Next()) {
|
|
|
|
bytes += iter->key().size() + iter->value().size();
|
|
|
|
thread->stats.FinishedOps(nullptr, db, 1);
|
|
|
|
++i;
|
|
|
|
}
|
|
|
|
delete iter;
|
|
|
|
thread->stats.AddBytes(bytes);
|
|
|
|
}
|
|
|
|
|
|
|
|
void ReadReverse(ThreadState* thread) {
|
|
|
|
if (db_.db != nullptr) {
|
|
|
|
ReadReverse(thread, db_.db);
|
|
|
|
} else {
|
|
|
|
for (const auto& db_with_cfh : multi_dbs_) {
|
|
|
|
ReadReverse(thread, db_with_cfh.db);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void ReadReverse(ThreadState* thread, DB* db) {
|
|
|
|
Iterator* iter = db->NewIterator(ReadOptions(FLAGS_verify_checksum, true));
|
|
|
|
int64_t i = 0;
|
|
|
|
int64_t bytes = 0;
|
|
|
|
for (iter->SeekToLast(); i < reads_ && iter->Valid(); iter->Prev()) {
|
|
|
|
bytes += iter->key().size() + iter->value().size();
|
|
|
|
thread->stats.FinishedOps(nullptr, db, 1);
|
|
|
|
++i;
|
|
|
|
}
|
|
|
|
delete iter;
|
|
|
|
thread->stats.AddBytes(bytes);
|
|
|
|
}
|
|
|
|
|
|
|
|
void ReadRandomFast(ThreadState* thread) {
|
|
|
|
int64_t read = 0;
|
|
|
|
int64_t found = 0;
|
|
|
|
int64_t nonexist = 0;
|
|
|
|
ReadOptions options(FLAGS_verify_checksum, true);
|
|
|
|
std::unique_ptr<const char[]> key_guard;
|
|
|
|
Slice key = AllocateKey(&key_guard);
|
|
|
|
std::string value;
|
|
|
|
DB* db = SelectDBWithCfh(thread)->db;
|
|
|
|
|
|
|
|
int64_t pot = 1;
|
|
|
|
while (pot < FLAGS_num) {
|
|
|
|
pot <<= 1;
|
|
|
|
}
|
|
|
|
|
|
|
|
Duration duration(FLAGS_duration, reads_);
|
|
|
|
do {
|
|
|
|
for (int i = 0; i < 100; ++i) {
|
|
|
|
int64_t key_rand = thread->rand.Next() & (pot - 1);
|
|
|
|
GenerateKeyFromInt(key_rand, FLAGS_num, &key);
|
|
|
|
++read;
|
|
|
|
auto status = db->Get(options, key, &value);
|
|
|
|
if (status.ok()) {
|
|
|
|
++found;
|
|
|
|
} else if (!status.IsNotFound()) {
|
|
|
|
fprintf(stderr, "Get returned an error: %s\n",
|
|
|
|
status.ToString().c_str());
|
|
|
|
abort();
|
|
|
|
}
|
|
|
|
if (key_rand >= FLAGS_num) {
|
|
|
|
++nonexist;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
thread->stats.FinishedOps(nullptr, db, 100);
|
|
|
|
} while (!duration.Done(100));
|
|
|
|
|
|
|
|
char msg[100];
|
|
|
|
snprintf(msg, sizeof(msg), "(%" PRIu64 " of %" PRIu64 " found, "
|
|
|
|
"issued %" PRIu64 " non-exist keys)\n",
|
|
|
|
found, read, nonexist);
|
|
|
|
|
|
|
|
thread->stats.AddMessage(msg);
|
|
|
|
|
|
|
|
if (FLAGS_perf_level > 0) {
|
|
|
|
thread->stats.AddMessage(perf_context.ToString());
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
int64_t GetRandomKey(Random64* rand) {
|
|
|
|
uint64_t rand_int = rand->Next();
|
|
|
|
int64_t key_rand;
|
|
|
|
if (read_random_exp_range_ == 0) {
|
|
|
|
key_rand = rand_int % FLAGS_num;
|
|
|
|
} else {
|
|
|
|
const uint64_t kBigInt = static_cast<uint64_t>(1U) << 62;
|
|
|
|
long double order = -static_cast<long double>(rand_int % kBigInt) /
|
|
|
|
static_cast<long double>(kBigInt) *
|
|
|
|
read_random_exp_range_;
|
|
|
|
long double exp_ran = std::exp(order);
|
|
|
|
uint64_t rand_num =
|
|
|
|
static_cast<int64_t>(exp_ran * static_cast<long double>(FLAGS_num));
|
|
|
|
// Map to a different number to avoid locality.
|
|
|
|
const uint64_t kBigPrime = 0x5bd1e995;
|
|
|
|
// Overflow is like %(2^64). Will have little impact of results.
|
|
|
|
key_rand = static_cast<int64_t>((rand_num * kBigPrime) % FLAGS_num);
|
|
|
|
}
|
|
|
|
return key_rand;
|
|
|
|
}
|
|
|
|
|
|
|
|
void ReadRandom(ThreadState* thread) {
|
|
|
|
int64_t read = 0;
|
|
|
|
int64_t found = 0;
|
|
|
|
ReadOptions options(FLAGS_verify_checksum, true);
|
|
|
|
std::unique_ptr<const char[]> key_guard;
|
|
|
|
Slice key = AllocateKey(&key_guard);
|
|
|
|
std::string value;
|
|
|
|
|
|
|
|
Duration duration(FLAGS_duration, reads_);
|
|
|
|
while (!duration.Done(1)) {
|
|
|
|
DBWithColumnFamilies* db_with_cfh = SelectDBWithCfh(thread);
|
|
|
|
// We use same key_rand as seed for key and column family so that we can
|
|
|
|
// deterministically find the cfh corresponding to a particular key, as it
|
|
|
|
// is done in DoWrite method.
|
|
|
|
int64_t key_rand = GetRandomKey(&thread->rand);
|
|
|
|
GenerateKeyFromInt(key_rand, FLAGS_num, &key);
|
|
|
|
read++;
|
|
|
|
Status s;
|
|
|
|
if (FLAGS_num_column_families > 1) {
|
|
|
|
s = db_with_cfh->db->Get(options, db_with_cfh->GetCfh(key_rand), key,
|
|
|
|
&value);
|
|
|
|
} else {
|
|
|
|
s = db_with_cfh->db->Get(options, key, &value);
|
|
|
|
}
|
|
|
|
if (s.ok()) {
|
|
|
|
found++;
|
|
|
|
} else if (!s.IsNotFound()) {
|
|
|
|
fprintf(stderr, "Get returned an error: %s\n", s.ToString().c_str());
|
|
|
|
abort();
|
|
|
|
}
|
|
|
|
thread->stats.FinishedOps(db_with_cfh, db_with_cfh->db, 1);
|
|
|
|
}
|
|
|
|
|
|
|
|
char msg[100];
|
|
|
|
snprintf(msg, sizeof(msg), "(%" PRIu64 " of %" PRIu64 " found)\n",
|
|
|
|
found, read);
|
|
|
|
|
|
|
|
thread->stats.AddMessage(msg);
|
|
|
|
|
|
|
|
if (FLAGS_perf_level > 0) {
|
|
|
|
thread->stats.AddMessage(perf_context.ToString());
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// Calls MultiGet over a list of keys from a random distribution.
|
|
|
|
// Returns the total number of keys found.
|
|
|
|
void MultiReadRandom(ThreadState* thread) {
|
|
|
|
int64_t read = 0;
|
|
|
|
int64_t found = 0;
|
|
|
|
ReadOptions options(FLAGS_verify_checksum, true);
|
|
|
|
std::vector<Slice> keys;
|
|
|
|
std::vector<std::unique_ptr<const char[]> > key_guards;
|
|
|
|
std::vector<std::string> values(entries_per_batch_);
|
|
|
|
while (static_cast<int64_t>(keys.size()) < entries_per_batch_) {
|
|
|
|
key_guards.push_back(std::move(std::unique_ptr<const char[]>()));
|
|
|
|
keys.push_back(AllocateKey(&key_guards.back()));
|
|
|
|
}
|
|
|
|
|
|
|
|
Duration duration(FLAGS_duration, reads_);
|
|
|
|
while (!duration.Done(1)) {
|
|
|
|
DB* db = SelectDB(thread);
|
|
|
|
for (int64_t i = 0; i < entries_per_batch_; ++i) {
|
|
|
|
GenerateKeyFromInt(GetRandomKey(&thread->rand), FLAGS_num, &keys[i]);
|
|
|
|
}
|
|
|
|
std::vector<Status> statuses = db->MultiGet(options, keys, &values);
|
|
|
|
assert(static_cast<int64_t>(statuses.size()) == entries_per_batch_);
|
|
|
|
|
|
|
|
read += entries_per_batch_;
|
|
|
|
for (int64_t i = 0; i < entries_per_batch_; ++i) {
|
|
|
|
if (statuses[i].ok()) {
|
|
|
|
++found;
|
|
|
|
} else if (!statuses[i].IsNotFound()) {
|
|
|
|
fprintf(stderr, "MultiGet returned an error: %s\n",
|
|
|
|
statuses[i].ToString().c_str());
|
|
|
|
abort();
|
|
|
|
}
|
|
|
|
}
|
|
|
|
thread->stats.FinishedOps(nullptr, db, entries_per_batch_);
|
|
|
|
}
|
|
|
|
|
|
|
|
char msg[100];
|
|
|
|
snprintf(msg, sizeof(msg), "(%" PRIu64 " of %" PRIu64 " found)",
|
|
|
|
found, read);
|
|
|
|
thread->stats.AddMessage(msg);
|
|
|
|
}
|
|
|
|
|
|
|
|
void IteratorCreation(ThreadState* thread) {
|
|
|
|
Duration duration(FLAGS_duration, reads_);
|
|
|
|
ReadOptions options(FLAGS_verify_checksum, true);
|
|
|
|
while (!duration.Done(1)) {
|
|
|
|
DB* db = SelectDB(thread);
|
|
|
|
Iterator* iter = db->NewIterator(options);
|
|
|
|
delete iter;
|
|
|
|
thread->stats.FinishedOps(nullptr, db, 1);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void IteratorCreationWhileWriting(ThreadState* thread) {
|
|
|
|
if (thread->tid > 0) {
|
|
|
|
IteratorCreation(thread);
|
|
|
|
} else {
|
|
|
|
BGWriter(thread, kPut);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void SeekRandom(ThreadState* thread) {
|
|
|
|
int64_t read = 0;
|
|
|
|
int64_t found = 0;
|
|
|
|
ReadOptions options(FLAGS_verify_checksum, true);
|
|
|
|
options.tailing = FLAGS_use_tailing_iterator;
|
|
|
|
|
|
|
|
Iterator* single_iter = nullptr;
|
|
|
|
std::vector<Iterator*> multi_iters;
|
|
|
|
if (db_.db != nullptr) {
|
|
|
|
single_iter = db_.db->NewIterator(options);
|
|
|
|
} else {
|
|
|
|
for (const auto& db_with_cfh : multi_dbs_) {
|
|
|
|
multi_iters.push_back(db_with_cfh.db->NewIterator(options));
|
|
|
|
}
|
|
|
|
}
|
|
|
|
uint64_t last_refresh = FLAGS_env->NowMicros();
|
|
|
|
|
|
|
|
std::unique_ptr<const char[]> key_guard;
|
|
|
|
Slice key = AllocateKey(&key_guard);
|
|
|
|
|
|
|
|
Duration duration(FLAGS_duration, reads_);
|
|
|
|
char value_buffer[256];
|
|
|
|
while (!duration.Done(1)) {
|
|
|
|
if (!FLAGS_use_tailing_iterator && FLAGS_iter_refresh_interval_us >= 0) {
|
|
|
|
uint64_t now = FLAGS_env->NowMicros();
|
|
|
|
if (now - last_refresh > (uint64_t)FLAGS_iter_refresh_interval_us) {
|
|
|
|
if (db_.db != nullptr) {
|
|
|
|
delete single_iter;
|
|
|
|
single_iter = db_.db->NewIterator(options);
|
|
|
|
} else {
|
|
|
|
for (auto iter : multi_iters) {
|
|
|
|
delete iter;
|
|
|
|
}
|
|
|
|
multi_iters.clear();
|
|
|
|
for (const auto& db_with_cfh : multi_dbs_) {
|
|
|
|
multi_iters.push_back(db_with_cfh.db->NewIterator(options));
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
last_refresh = now;
|
|
|
|
}
|
|
|
|
// Pick a Iterator to use
|
|
|
|
Iterator* iter_to_use = single_iter;
|
|
|
|
if (single_iter == nullptr) {
|
|
|
|
iter_to_use = multi_iters[thread->rand.Next() % multi_iters.size()];
|
|
|
|
}
|
|
|
|
|
|
|
|
GenerateKeyFromInt(thread->rand.Next() % FLAGS_num, FLAGS_num, &key);
|
|
|
|
iter_to_use->Seek(key);
|
|
|
|
read++;
|
|
|
|
if (iter_to_use->Valid() && iter_to_use->key().compare(key) == 0) {
|
|
|
|
found++;
|
|
|
|
}
|
|
|
|
|
|
|
|
for (int j = 0; j < FLAGS_seek_nexts && iter_to_use->Valid(); ++j) {
|
|
|
|
// Copy out iterator's value to make sure we read them.
|
|
|
|
Slice value = iter_to_use->value();
|
|
|
|
memcpy(value_buffer, value.data(),
|
|
|
|
std::min(value.size(), sizeof(value_buffer)));
|
|
|
|
|
|
|
|
if (!FLAGS_reverse_iterator) {
|
|
|
|
iter_to_use->Next();
|
|
|
|
} else {
|
|
|
|
iter_to_use->Prev();
|
|
|
|
}
|
|
|
|
assert(iter_to_use->status().ok());
|
|
|
|
}
|
|
|
|
|
|
|
|
thread->stats.FinishedOps(&db_, db_.db, 1);
|
|
|
|
}
|
|
|
|
delete single_iter;
|
|
|
|
for (auto iter : multi_iters) {
|
|
|
|
delete iter;
|
|
|
|
}
|
|
|
|
|
|
|
|
char msg[100];
|
|
|
|
snprintf(msg, sizeof(msg), "(%" PRIu64 " of %" PRIu64 " found)\n",
|
|
|
|
found, read);
|
|
|
|
thread->stats.AddMessage(msg);
|
|
|
|
if (FLAGS_perf_level > 0) {
|
|
|
|
thread->stats.AddMessage(perf_context.ToString());
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void SeekRandomWhileWriting(ThreadState* thread) {
|
|
|
|
if (thread->tid > 0) {
|
|
|
|
SeekRandom(thread);
|
|
|
|
} else {
|
|
|
|
BGWriter(thread, kPut);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void DoDelete(ThreadState* thread, bool seq) {
|
|
|
|
WriteBatch batch;
|
|
|
|
Duration duration(seq ? 0 : FLAGS_duration, num_);
|
|
|
|
int64_t i = 0;
|
|
|
|
std::unique_ptr<const char[]> key_guard;
|
|
|
|
Slice key = AllocateKey(&key_guard);
|
|
|
|
|
|
|
|
while (!duration.Done(entries_per_batch_)) {
|
|
|
|
DB* db = SelectDB(thread);
|
|
|
|
batch.Clear();
|
|
|
|
for (int64_t j = 0; j < entries_per_batch_; ++j) {
|
|
|
|
const int64_t k = seq ? i + j : (thread->rand.Next() % FLAGS_num);
|
|
|
|
GenerateKeyFromInt(k, FLAGS_num, &key);
|
|
|
|
batch.Delete(key);
|
|
|
|
}
|
|
|
|
auto s = db->Write(write_options_, &batch);
|
|
|
|
thread->stats.FinishedOps(nullptr, db, entries_per_batch_);
|
|
|
|
if (!s.ok()) {
|
|
|
|
fprintf(stderr, "del error: %s\n", s.ToString().c_str());
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
i += entries_per_batch_;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void DeleteSeq(ThreadState* thread) {
|
|
|
|
DoDelete(thread, true);
|
|
|
|
}
|
|
|
|
|
|
|
|
void DeleteRandom(ThreadState* thread) {
|
|
|
|
DoDelete(thread, false);
|
|
|
|
}
|
|
|
|
|
|
|
|
void ReadWhileWriting(ThreadState* thread) {
|
|
|
|
if (thread->tid > 0) {
|
|
|
|
ReadRandom(thread);
|
|
|
|
} else {
|
|
|
|
BGWriter(thread, kPut);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void ReadWhileMerging(ThreadState* thread) {
|
|
|
|
if (thread->tid > 0) {
|
|
|
|
ReadRandom(thread);
|
|
|
|
} else {
|
|
|
|
BGWriter(thread, kMerge);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void BGWriter(ThreadState* thread, enum PutOrMerge write_merge) {
|
|
|
|
// Special thread that keeps writing until other threads are done.
|
|
|
|
RandomGenerator gen;
|
|
|
|
double last = FLAGS_env->NowMicros();
|
|
|
|
int writes_per_second_by_10 = 0;
|
|
|
|
int num_writes = 0;
|
|
|
|
|
|
|
|
// --writes_per_second rate limit is enforced per 100 milliseconds
|
|
|
|
// intervals to avoid a burst of writes at the start of each second.
|
|
|
|
|
|
|
|
if (FLAGS_writes_per_second > 0)
|
|
|
|
writes_per_second_by_10 = FLAGS_writes_per_second / 10;
|
|
|
|
|
|
|
|
// Don't merge stats from this thread with the readers.
|
|
|
|
thread->stats.SetExcludeFromMerge();
|
|
|
|
|
|
|
|
std::unique_ptr<const char[]> key_guard;
|
|
|
|
Slice key = AllocateKey(&key_guard);
|
|
|
|
|
|
|
|
while (true) {
|
|
|
|
DB* db = SelectDB(thread);
|
|
|
|
{
|
|
|
|
MutexLock l(&thread->shared->mu);
|
|
|
|
if (thread->shared->num_done + 1 >= thread->shared->num_initialized) {
|
|
|
|
// Other threads have finished
|
|
|
|
break;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
GenerateKeyFromInt(thread->rand.Next() % FLAGS_num, FLAGS_num, &key);
|
|
|
|
Status s;
|
|
|
|
|
|
|
|
if (write_merge == kPut) {
|
|
|
|
s = db->Put(write_options_, key, gen.Generate(value_size_));
|
|
|
|
} else {
|
|
|
|
s = db->Merge(write_options_, key, gen.Generate(value_size_));
|
|
|
|
}
|
|
|
|
|
|
|
|
if (!s.ok()) {
|
|
|
|
fprintf(stderr, "put or merge error: %s\n", s.ToString().c_str());
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
thread->stats.FinishedOps(&db_, db_.db, 1);
|
|
|
|
|
|
|
|
++num_writes;
|
|
|
|
if (writes_per_second_by_10 && num_writes >= writes_per_second_by_10) {
|
|
|
|
double now = FLAGS_env->NowMicros();
|
|
|
|
double usecs_since_last = now - last;
|
|
|
|
|
|
|
|
num_writes = 0;
|
|
|
|
last = now;
|
|
|
|
|
|
|
|
if (usecs_since_last < 100000.0) {
|
|
|
|
FLAGS_env->SleepForMicroseconds(100000.0 - usecs_since_last);
|
|
|
|
last = FLAGS_env->NowMicros();
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// Given a key K and value V, this puts (K+"0", V), (K+"1", V), (K+"2", V)
|
|
|
|
// in DB atomically i.e in a single batch. Also refer GetMany.
|
|
|
|
Status PutMany(DB* db, const WriteOptions& writeoptions, const Slice& key,
|
|
|
|
const Slice& value) {
|
|
|
|
std::string suffixes[3] = {"2", "1", "0"};
|
|
|
|
std::string keys[3];
|
|
|
|
|
|
|
|
WriteBatch batch;
|
|
|
|
Status s;
|
|
|
|
for (int i = 0; i < 3; i++) {
|
|
|
|
keys[i] = key.ToString() + suffixes[i];
|
|
|
|
batch.Put(keys[i], value);
|
|
|
|
}
|
|
|
|
|
|
|
|
s = db->Write(writeoptions, &batch);
|
|
|
|
return s;
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
// Given a key K, this deletes (K+"0", V), (K+"1", V), (K+"2", V)
|
|
|
|
// in DB atomically i.e in a single batch. Also refer GetMany.
|
|
|
|
Status DeleteMany(DB* db, const WriteOptions& writeoptions,
|
|
|
|
const Slice& key) {
|
|
|
|
std::string suffixes[3] = {"1", "2", "0"};
|
|
|
|
std::string keys[3];
|
|
|
|
|
|
|
|
WriteBatch batch;
|
|
|
|
Status s;
|
|
|
|
for (int i = 0; i < 3; i++) {
|
|
|
|
keys[i] = key.ToString() + suffixes[i];
|
|
|
|
batch.Delete(keys[i]);
|
|
|
|
}
|
|
|
|
|
|
|
|
s = db->Write(writeoptions, &batch);
|
|
|
|
return s;
|
|
|
|
}
|
|
|
|
|
|
|
|
// Given a key K and value V, this gets values for K+"0", K+"1" and K+"2"
|
|
|
|
// in the same snapshot, and verifies that all the values are identical.
|
|
|
|
// ASSUMES that PutMany was used to put (K, V) into the DB.
|
|
|
|
Status GetMany(DB* db, const ReadOptions& readoptions, const Slice& key,
|
|
|
|
std::string* value) {
|
|
|
|
std::string suffixes[3] = {"0", "1", "2"};
|
|
|
|
std::string keys[3];
|
|
|
|
Slice key_slices[3];
|
|
|
|
std::string values[3];
|
|
|
|
ReadOptions readoptionscopy = readoptions;
|
|
|
|
readoptionscopy.snapshot = db->GetSnapshot();
|
|
|
|
Status s;
|
|
|
|
for (int i = 0; i < 3; i++) {
|
|
|
|
keys[i] = key.ToString() + suffixes[i];
|
|
|
|
key_slices[i] = keys[i];
|
|
|
|
s = db->Get(readoptionscopy, key_slices[i], value);
|
|
|
|
if (!s.ok() && !s.IsNotFound()) {
|
|
|
|
fprintf(stderr, "get error: %s\n", s.ToString().c_str());
|
|
|
|
values[i] = "";
|
|
|
|
// we continue after error rather than exiting so that we can
|
|
|
|
// find more errors if any
|
|
|
|
} else if (s.IsNotFound()) {
|
|
|
|
values[i] = "";
|
|
|
|
} else {
|
|
|
|
values[i] = *value;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
db->ReleaseSnapshot(readoptionscopy.snapshot);
|
|
|
|
|
|
|
|
if ((values[0] != values[1]) || (values[1] != values[2])) {
|
|
|
|
fprintf(stderr, "inconsistent values for key %s: %s, %s, %s\n",
|
|
|
|
key.ToString().c_str(), values[0].c_str(), values[1].c_str(),
|
|
|
|
values[2].c_str());
|
|
|
|
// we continue after error rather than exiting so that we can
|
|
|
|
// find more errors if any
|
|
|
|
}
|
|
|
|
|
|
|
|
return s;
|
|
|
|
}
|
|
|
|
|
|
|
|
// Differs from readrandomwriterandom in the following ways:
|
|
|
|
// (a) Uses GetMany/PutMany to read/write key values. Refer to those funcs.
|
|
|
|
// (b) Does deletes as well (per FLAGS_deletepercent)
|
|
|
|
// (c) In order to achieve high % of 'found' during lookups, and to do
|
|
|
|
// multiple writes (including puts and deletes) it uses upto
|
|
|
|
// FLAGS_numdistinct distinct keys instead of FLAGS_num distinct keys.
|
|
|
|
// (d) Does not have a MultiGet option.
|
|
|
|
void RandomWithVerify(ThreadState* thread) {
|
|
|
|
ReadOptions options(FLAGS_verify_checksum, true);
|
|
|
|
RandomGenerator gen;
|
|
|
|
std::string value;
|
|
|
|
int64_t found = 0;
|
|
|
|
int get_weight = 0;
|
|
|
|
int put_weight = 0;
|
|
|
|
int delete_weight = 0;
|
|
|
|
int64_t gets_done = 0;
|
|
|
|
int64_t puts_done = 0;
|
|
|
|
int64_t deletes_done = 0;
|
|
|
|
|
|
|
|
std::unique_ptr<const char[]> key_guard;
|
|
|
|
Slice key = AllocateKey(&key_guard);
|
|
|
|
|
|
|
|
// the number of iterations is the larger of read_ or write_
|
|
|
|
for (int64_t i = 0; i < readwrites_; i++) {
|
|
|
|
DB* db = SelectDB(thread);
|
|
|
|
if (get_weight == 0 && put_weight == 0 && delete_weight == 0) {
|
|
|
|
// one batch completed, reinitialize for next batch
|
|
|
|
get_weight = FLAGS_readwritepercent;
|
|
|
|
delete_weight = FLAGS_deletepercent;
|
|
|
|
put_weight = 100 - get_weight - delete_weight;
|
|
|
|
}
|
|
|
|
GenerateKeyFromInt(thread->rand.Next() % FLAGS_numdistinct,
|
|
|
|
FLAGS_numdistinct, &key);
|
|
|
|
if (get_weight > 0) {
|
|
|
|
// do all the gets first
|
|
|
|
Status s = GetMany(db, options, key, &value);
|
|
|
|
if (!s.ok() && !s.IsNotFound()) {
|
|
|
|
fprintf(stderr, "getmany error: %s\n", s.ToString().c_str());
|
|
|
|
// we continue after error rather than exiting so that we can
|
|
|
|
// find more errors if any
|
|
|
|
} else if (!s.IsNotFound()) {
|
|
|
|
found++;
|
|
|
|
}
|
|
|
|
get_weight--;
|
|
|
|
gets_done++;
|
|
|
|
} else if (put_weight > 0) {
|
|
|
|
// then do all the corresponding number of puts
|
|
|
|
// for all the gets we have done earlier
|
|
|
|
Status s = PutMany(db, write_options_, key, gen.Generate(value_size_));
|
|
|
|
if (!s.ok()) {
|
|
|
|
fprintf(stderr, "putmany error: %s\n", s.ToString().c_str());
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
put_weight--;
|
|
|
|
puts_done++;
|
|
|
|
} else if (delete_weight > 0) {
|
|
|
|
Status s = DeleteMany(db, write_options_, key);
|
|
|
|
if (!s.ok()) {
|
|
|
|
fprintf(stderr, "deletemany error: %s\n", s.ToString().c_str());
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
delete_weight--;
|
|
|
|
deletes_done++;
|
|
|
|
}
|
|
|
|
|
|
|
|
thread->stats.FinishedOps(&db_, db_.db, 1);
|
|
|
|
}
|
|
|
|
char msg[100];
|
|
|
|
snprintf(msg, sizeof(msg),
|
|
|
|
"( get:%" PRIu64 " put:%" PRIu64 " del:%" PRIu64 " total:%" \
|
|
|
|
PRIu64 " found:%" PRIu64 ")",
|
|
|
|
gets_done, puts_done, deletes_done, readwrites_, found);
|
|
|
|
thread->stats.AddMessage(msg);
|
|
|
|
}
|
|
|
|
|
|
|
|
// This is different from ReadWhileWriting because it does not use
|
|
|
|
// an extra thread.
|
|
|
|
void ReadRandomWriteRandom(ThreadState* thread) {
|
|
|
|
ReadOptions options(FLAGS_verify_checksum, true);
|
|
|
|
RandomGenerator gen;
|
|
|
|
std::string value;
|
|
|
|
int64_t found = 0;
|
|
|
|
int get_weight = 0;
|
|
|
|
int put_weight = 0;
|
|
|
|
int64_t reads_done = 0;
|
|
|
|
int64_t writes_done = 0;
|
|
|
|
Duration duration(FLAGS_duration, readwrites_);
|
|
|
|
|
|
|
|
std::unique_ptr<const char[]> key_guard;
|
|
|
|
Slice key = AllocateKey(&key_guard);
|
|
|
|
|
|
|
|
// the number of iterations is the larger of read_ or write_
|
|
|
|
while (!duration.Done(1)) {
|
|
|
|
DB* db = SelectDB(thread);
|
|
|
|
GenerateKeyFromInt(thread->rand.Next() % FLAGS_num, FLAGS_num, &key);
|
|
|
|
if (get_weight == 0 && put_weight == 0) {
|
|
|
|
// one batch completed, reinitialize for next batch
|
|
|
|
get_weight = FLAGS_readwritepercent;
|
|
|
|
put_weight = 100 - get_weight;
|
|
|
|
}
|
|
|
|
if (get_weight > 0) {
|
|
|
|
// do all the gets first
|
|
|
|
Status s = db->Get(options, key, &value);
|
|
|
|
if (!s.ok() && !s.IsNotFound()) {
|
|
|
|
fprintf(stderr, "get error: %s\n", s.ToString().c_str());
|
|
|
|
// we continue after error rather than exiting so that we can
|
|
|
|
// find more errors if any
|
|
|
|
} else if (!s.IsNotFound()) {
|
|
|
|
found++;
|
|
|
|
}
|
|
|
|
get_weight--;
|
|
|
|
reads_done++;
|
|
|
|
} else if (put_weight > 0) {
|
|
|
|
// then do all the corresponding number of puts
|
|
|
|
// for all the gets we have done earlier
|
|
|
|
Status s = db->Put(write_options_, key, gen.Generate(value_size_));
|
|
|
|
if (!s.ok()) {
|
|
|
|
fprintf(stderr, "put error: %s\n", s.ToString().c_str());
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
put_weight--;
|
|
|
|
writes_done++;
|
|
|
|
}
|
|
|
|
thread->stats.FinishedOps(nullptr, db, 1);
|
|
|
|
}
|
|
|
|
char msg[100];
|
|
|
|
snprintf(msg, sizeof(msg), "( reads:%" PRIu64 " writes:%" PRIu64 \
|
|
|
|
" total:%" PRIu64 " found:%" PRIu64 ")",
|
|
|
|
reads_done, writes_done, readwrites_, found);
|
|
|
|
thread->stats.AddMessage(msg);
|
|
|
|
}
|
|
|
|
|
|
|
|
//
|
|
|
|
// Read-modify-write for random keys
|
|
|
|
void UpdateRandom(ThreadState* thread) {
|
|
|
|
ReadOptions options(FLAGS_verify_checksum, true);
|
|
|
|
RandomGenerator gen;
|
|
|
|
std::string value;
|
|
|
|
int64_t found = 0;
|
|
|
|
Duration duration(FLAGS_duration, readwrites_);
|
|
|
|
|
|
|
|
std::unique_ptr<const char[]> key_guard;
|
|
|
|
Slice key = AllocateKey(&key_guard);
|
|
|
|
// the number of iterations is the larger of read_ or write_
|
|
|
|
while (!duration.Done(1)) {
|
|
|
|
DB* db = SelectDB(thread);
|
|
|
|
GenerateKeyFromInt(thread->rand.Next() % FLAGS_num, FLAGS_num, &key);
|
|
|
|
|
|
|
|
auto status = db->Get(options, key, &value);
|
|
|
|
if (status.ok()) {
|
|
|
|
++found;
|
|
|
|
} else if (!status.IsNotFound()) {
|
|
|
|
fprintf(stderr, "Get returned an error: %s\n",
|
|
|
|
status.ToString().c_str());
|
|
|
|
abort();
|
|
|
|
}
|
|
|
|
|
|
|
|
Status s = db->Put(write_options_, key, gen.Generate(value_size_));
|
|
|
|
if (!s.ok()) {
|
|
|
|
fprintf(stderr, "put error: %s\n", s.ToString().c_str());
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
thread->stats.FinishedOps(nullptr, db, 1);
|
|
|
|
}
|
|
|
|
char msg[100];
|
|
|
|
snprintf(msg, sizeof(msg),
|
|
|
|
"( updates:%" PRIu64 " found:%" PRIu64 ")", readwrites_, found);
|
|
|
|
thread->stats.AddMessage(msg);
|
|
|
|
}
|
|
|
|
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
// Read-modify-write for random keys.
|
|
|
|
// Each operation causes the key grow by value_size (simulating an append).
|
|
|
|
// Generally used for benchmarking against merges of similar type
|
|
|
|
void AppendRandom(ThreadState* thread) {
|
|
|
|
ReadOptions options(FLAGS_verify_checksum, true);
|
|
|
|
RandomGenerator gen;
|
|
|
|
std::string value;
|
|
|
|
int64_t found = 0;
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
|
|
|
|
std::unique_ptr<const char[]> key_guard;
|
|
|
|
Slice key = AllocateKey(&key_guard);
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
// The number of iterations is the larger of read_ or write_
|
|
|
|
Duration duration(FLAGS_duration, readwrites_);
|
|
|
|
while (!duration.Done(1)) {
|
|
|
|
DB* db = SelectDB(thread);
|
|
|
|
GenerateKeyFromInt(thread->rand.Next() % FLAGS_num, FLAGS_num, &key);
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
|
|
|
|
auto status = db->Get(options, key, &value);
|
|
|
|
if (status.ok()) {
|
|
|
|
++found;
|
|
|
|
} else if (!status.IsNotFound()) {
|
|
|
|
fprintf(stderr, "Get returned an error: %s\n",
|
|
|
|
status.ToString().c_str());
|
|
|
|
abort();
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
} else {
|
|
|
|
// If not existing, then just assume an empty string of data
|
|
|
|
value.clear();
|
|
|
|
}
|
|
|
|
|
|
|
|
// Update the value (by appending data)
|
|
|
|
Slice operand = gen.Generate(value_size_);
|
|
|
|
if (value.size() > 0) {
|
|
|
|
// Use a delimeter to match the semantics for StringAppendOperator
|
|
|
|
value.append(1,',');
|
|
|
|
}
|
|
|
|
value.append(operand.data(), operand.size());
|
|
|
|
|
|
|
|
// Write back to the database
|
|
|
|
Status s = db->Put(write_options_, key, value);
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
if (!s.ok()) {
|
|
|
|
fprintf(stderr, "put error: %s\n", s.ToString().c_str());
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
thread->stats.FinishedOps(nullptr, db, 1);
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
}
|
|
|
|
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
char msg[100];
|
|
|
|
snprintf(msg, sizeof(msg), "( updates:%" PRIu64 " found:%" PRIu64 ")",
|
|
|
|
readwrites_, found);
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
thread->stats.AddMessage(msg);
|
|
|
|
}
|
|
|
|
|
|
|
|
// Read-modify-write for random keys (using MergeOperator)
|
|
|
|
// The merge operator to use should be defined by FLAGS_merge_operator
|
|
|
|
// Adjust FLAGS_value_size so that the keys are reasonable for this operator
|
|
|
|
// Assumes that the merge operator is non-null (i.e.: is well-defined)
|
|
|
|
//
|
|
|
|
// For example, use FLAGS_merge_operator="uint64add" and FLAGS_value_size=8
|
|
|
|
// to simulate random additions over 64-bit integers using merge.
|
|
|
|
//
|
|
|
|
// The number of merges on the same key can be controlled by adjusting
|
|
|
|
// FLAGS_merge_keys.
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
void MergeRandom(ThreadState* thread) {
|
|
|
|
RandomGenerator gen;
|
|
|
|
|
|
|
|
std::unique_ptr<const char[]> key_guard;
|
|
|
|
Slice key = AllocateKey(&key_guard);
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
// The number of iterations is the larger of read_ or write_
|
|
|
|
Duration duration(FLAGS_duration, readwrites_);
|
|
|
|
while (!duration.Done(1)) {
|
|
|
|
DB* db = SelectDB(thread);
|
|
|
|
GenerateKeyFromInt(thread->rand.Next() % merge_keys_, merge_keys_, &key);
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
|
|
|
|
Status s = db->Merge(write_options_, key, gen.Generate(value_size_));
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
|
|
|
|
if (!s.ok()) {
|
|
|
|
fprintf(stderr, "merge error: %s\n", s.ToString().c_str());
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
thread->stats.FinishedOps(nullptr, db, 1);
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
}
|
|
|
|
|
|
|
|
// Print some statistics
|
|
|
|
char msg[100];
|
|
|
|
snprintf(msg, sizeof(msg), "( updates:%" PRIu64 ")", readwrites_);
|
Benchmarking for Merge Operator
Summary:
Updated db_bench and utilities/merge_operators.h to allow for dynamic benchmarking
of merge operators in db_bench. Added a new test (--benchmarks=mergerandom), which performs
a bunch of random Merge() operations over random keys. Also added a "--merge_operator=" flag
so that the tester can easily benchmark different merge operators. Currently supports
the PutOperator and UInt64Add operator. Support for stringappend or list append may come later.
Test Plan:
1. make db_bench
2. Test the PutOperator (simulating Put) as follows:
./db_bench --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom --merge_operator=put
--threads=2
3. Test the UInt64AddOperator (simulating numeric addition) similarly:
./db_bench --value_size=8 --benchmarks=fillrandom,readrandom,updaterandom,readrandom,mergerandom,readrandom
--merge_operator=uint64add --threads=2
Reviewers: haobo, dhruba, zshao, MarkCallaghan
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D11535
12 years ago
|
|
|
thread->stats.AddMessage(msg);
|
|
|
|
}
|
|
|
|
|
|
|
|
// Read and merge random keys. The amount of reads and merges are controlled
|
|
|
|
// by adjusting FLAGS_num and FLAGS_mergereadpercent. The number of distinct
|
|
|
|
// keys (and thus also the number of reads and merges on the same key) can be
|
|
|
|
// adjusted with FLAGS_merge_keys.
|
|
|
|
//
|
|
|
|
// As with MergeRandom, the merge operator to use should be defined by
|
|
|
|
// FLAGS_merge_operator.
|
|
|
|
void ReadRandomMergeRandom(ThreadState* thread) {
|
|
|
|
ReadOptions options(FLAGS_verify_checksum, true);
|
|
|
|
RandomGenerator gen;
|
|
|
|
std::string value;
|
|
|
|
int64_t num_hits = 0;
|
|
|
|
int64_t num_gets = 0;
|
|
|
|
int64_t num_merges = 0;
|
|
|
|
size_t max_length = 0;
|
|
|
|
|
|
|
|
std::unique_ptr<const char[]> key_guard;
|
|
|
|
Slice key = AllocateKey(&key_guard);
|
|
|
|
// the number of iterations is the larger of read_ or write_
|
|
|
|
Duration duration(FLAGS_duration, readwrites_);
|
|
|
|
while (!duration.Done(1)) {
|
|
|
|
DB* db = SelectDB(thread);
|
|
|
|
GenerateKeyFromInt(thread->rand.Next() % merge_keys_, merge_keys_, &key);
|
|
|
|
|
|
|
|
bool do_merge = int(thread->rand.Next() % 100) < FLAGS_mergereadpercent;
|
|
|
|
|
|
|
|
if (do_merge) {
|
|
|
|
Status s = db->Merge(write_options_, key, gen.Generate(value_size_));
|
|
|
|
if (!s.ok()) {
|
|
|
|
fprintf(stderr, "merge error: %s\n", s.ToString().c_str());
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
|
|
|
|
num_merges++;
|
|
|
|
|
|
|
|
} else {
|
|
|
|
Status s = db->Get(options, key, &value);
|
|
|
|
if (value.length() > max_length)
|
|
|
|
max_length = value.length();
|
|
|
|
|
|
|
|
if (!s.ok() && !s.IsNotFound()) {
|
|
|
|
fprintf(stderr, "get error: %s\n", s.ToString().c_str());
|
|
|
|
// we continue after error rather than exiting so that we can
|
|
|
|
// find more errors if any
|
|
|
|
} else if (!s.IsNotFound()) {
|
|
|
|
num_hits++;
|
|
|
|
}
|
|
|
|
|
|
|
|
num_gets++;
|
|
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
thread->stats.FinishedOps(nullptr, db, 1);
|
|
|
|
}
|
|
|
|
|
|
|
|
char msg[100];
|
|
|
|
snprintf(msg, sizeof(msg),
|
|
|
|
"(reads:%" PRIu64 " merges:%" PRIu64 " total:%" PRIu64 " hits:%" \
|
|
|
|
PRIu64 " maxlength:%zu)",
|
|
|
|
num_gets, num_merges, readwrites_, num_hits, max_length);
|
|
|
|
thread->stats.AddMessage(msg);
|
|
|
|
}
|
|
|
|
|
SkipListRep::LookaheadIterator
Summary:
This diff introduces the `lookahead` argument to `SkipListFactory()`. This is an
optimization for the tailing use case which includes many seeks. E.g. consider
the following operations on a skip list iterator:
Seek(x), Next(), Next(), Seek(x+2), Next(), Seek(x+3), Next(), Next(), ...
If `lookahead` is positive, `SkipListRep` will return an iterator which also
keeps track of the previously visited node. Seek() then first does a linear
search starting from that node (up to `lookahead` steps). As in the tailing
example above, this may require fewer than ~log(n) comparisons as with regular
skip list search.
Test Plan:
Added a new benchmark (`fillseekseq`) which simulates the usage pattern. It
first writes N records (with consecutive keys), then measures how much time it
takes to read them by calling `Seek()` and `Next()`.
$ time ./db_bench -num 10000000 -benchmarks fillseekseq -prefix_size 1 \
-key_size 8 -write_buffer_size $[1024*1024*1024] -value_size 50 \
-seekseq_next 2 -skip_list_lookahead=0
[...]
DB path: [/dev/shm/rocksdbtest/dbbench]
fillseekseq : 0.389 micros/op 2569047 ops/sec;
real 0m21.806s
user 0m12.106s
sys 0m9.672s
$ time ./db_bench [...] -skip_list_lookahead=2
[...]
DB path: [/dev/shm/rocksdbtest/dbbench]
fillseekseq : 0.153 micros/op 6540684 ops/sec;
real 0m19.469s
user 0m10.192s
sys 0m9.252s
Reviewers: ljin, sdong, igor
Reviewed By: igor
Subscribers: dhruba, leveldb, march, lovro
Differential Revision: https://reviews.facebook.net/D23997
10 years ago
|
|
|
void WriteSeqSeekSeq(ThreadState* thread) {
|
|
|
|
writes_ = FLAGS_num;
|
|
|
|
DoWrite(thread, SEQUENTIAL);
|
|
|
|
// exclude writes from the ops/sec calculation
|
|
|
|
thread->stats.Start(thread->tid);
|
|
|
|
|
|
|
|
DB* db = SelectDB(thread);
|
|
|
|
std::unique_ptr<Iterator> iter(
|
|
|
|
db->NewIterator(ReadOptions(FLAGS_verify_checksum, true)));
|
|
|
|
|
|
|
|
std::unique_ptr<const char[]> key_guard;
|
|
|
|
Slice key = AllocateKey(&key_guard);
|
SkipListRep::LookaheadIterator
Summary:
This diff introduces the `lookahead` argument to `SkipListFactory()`. This is an
optimization for the tailing use case which includes many seeks. E.g. consider
the following operations on a skip list iterator:
Seek(x), Next(), Next(), Seek(x+2), Next(), Seek(x+3), Next(), Next(), ...
If `lookahead` is positive, `SkipListRep` will return an iterator which also
keeps track of the previously visited node. Seek() then first does a linear
search starting from that node (up to `lookahead` steps). As in the tailing
example above, this may require fewer than ~log(n) comparisons as with regular
skip list search.
Test Plan:
Added a new benchmark (`fillseekseq`) which simulates the usage pattern. It
first writes N records (with consecutive keys), then measures how much time it
takes to read them by calling `Seek()` and `Next()`.
$ time ./db_bench -num 10000000 -benchmarks fillseekseq -prefix_size 1 \
-key_size 8 -write_buffer_size $[1024*1024*1024] -value_size 50 \
-seekseq_next 2 -skip_list_lookahead=0
[...]
DB path: [/dev/shm/rocksdbtest/dbbench]
fillseekseq : 0.389 micros/op 2569047 ops/sec;
real 0m21.806s
user 0m12.106s
sys 0m9.672s
$ time ./db_bench [...] -skip_list_lookahead=2
[...]
DB path: [/dev/shm/rocksdbtest/dbbench]
fillseekseq : 0.153 micros/op 6540684 ops/sec;
real 0m19.469s
user 0m10.192s
sys 0m9.252s
Reviewers: ljin, sdong, igor
Reviewed By: igor
Subscribers: dhruba, leveldb, march, lovro
Differential Revision: https://reviews.facebook.net/D23997
10 years ago
|
|
|
for (int64_t i = 0; i < FLAGS_num; ++i) {
|
|
|
|
GenerateKeyFromInt(i, FLAGS_num, &key);
|
|
|
|
iter->Seek(key);
|
|
|
|
assert(iter->Valid() && iter->key() == key);
|
|
|
|
thread->stats.FinishedOps(nullptr, db, 1);
|
|
|
|
|
|
|
|
for (int j = 0; j < FLAGS_seek_nexts && i + 1 < FLAGS_num; ++j) {
|
|
|
|
if (!FLAGS_reverse_iterator) {
|
|
|
|
iter->Next();
|
|
|
|
} else {
|
|
|
|
iter->Prev();
|
|
|
|
}
|
SkipListRep::LookaheadIterator
Summary:
This diff introduces the `lookahead` argument to `SkipListFactory()`. This is an
optimization for the tailing use case which includes many seeks. E.g. consider
the following operations on a skip list iterator:
Seek(x), Next(), Next(), Seek(x+2), Next(), Seek(x+3), Next(), Next(), ...
If `lookahead` is positive, `SkipListRep` will return an iterator which also
keeps track of the previously visited node. Seek() then first does a linear
search starting from that node (up to `lookahead` steps). As in the tailing
example above, this may require fewer than ~log(n) comparisons as with regular
skip list search.
Test Plan:
Added a new benchmark (`fillseekseq`) which simulates the usage pattern. It
first writes N records (with consecutive keys), then measures how much time it
takes to read them by calling `Seek()` and `Next()`.
$ time ./db_bench -num 10000000 -benchmarks fillseekseq -prefix_size 1 \
-key_size 8 -write_buffer_size $[1024*1024*1024] -value_size 50 \
-seekseq_next 2 -skip_list_lookahead=0
[...]
DB path: [/dev/shm/rocksdbtest/dbbench]
fillseekseq : 0.389 micros/op 2569047 ops/sec;
real 0m21.806s
user 0m12.106s
sys 0m9.672s
$ time ./db_bench [...] -skip_list_lookahead=2
[...]
DB path: [/dev/shm/rocksdbtest/dbbench]
fillseekseq : 0.153 micros/op 6540684 ops/sec;
real 0m19.469s
user 0m10.192s
sys 0m9.252s
Reviewers: ljin, sdong, igor
Reviewed By: igor
Subscribers: dhruba, leveldb, march, lovro
Differential Revision: https://reviews.facebook.net/D23997
10 years ago
|
|
|
GenerateKeyFromInt(++i, FLAGS_num, &key);
|
|
|
|
assert(iter->Valid() && iter->key() == key);
|
|
|
|
thread->stats.FinishedOps(nullptr, db, 1);
|
|
|
|
}
|
|
|
|
|
|
|
|
iter->Seek(key);
|
|
|
|
assert(iter->Valid() && iter->key() == key);
|
|
|
|
thread->stats.FinishedOps(nullptr, db, 1);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void Compact(ThreadState* thread) {
|
|
|
|
DB* db = SelectDB(thread);
|
|
|
|
db->CompactRange(nullptr, nullptr);
|
|
|
|
}
|
|
|
|
|
|
|
|
void PrintStats(const char* key) {
|
|
|
|
if (db_.db != nullptr) {
|
|
|
|
PrintStats(db_.db, key, false);
|
|
|
|
}
|
|
|
|
for (const auto& db_with_cfh : multi_dbs_) {
|
|
|
|
PrintStats(db_with_cfh.db, key, true);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void PrintStats(DB* db, const char* key, bool print_header = false) {
|
|
|
|
if (print_header) {
|
|
|
|
fprintf(stdout, "\n==== DB: %s ===\n", db->GetName().c_str());
|
|
|
|
}
|
|
|
|
std::string stats;
|
|
|
|
if (!db->GetProperty(key, &stats)) {
|
|
|
|
stats = "(failed)";
|
|
|
|
}
|
|
|
|
fprintf(stdout, "\n%s\n", stats.c_str());
|
|
|
|
}
|
|
|
|
};
|
|
|
|
|
|
|
|
} // namespace rocksdb
|
|
|
|
|
|
|
|
int main(int argc, char** argv) {
|
|
|
|
rocksdb::port::InstallStackTraceHandler();
|
|
|
|
SetUsageMessage(std::string("\nUSAGE:\n") + std::string(argv[0]) +
|
|
|
|
" [OPTIONS]...");
|
|
|
|
ParseCommandLineFlags(&argc, &argv, true);
|
|
|
|
|
|
|
|
FLAGS_compaction_style_e = (rocksdb::CompactionStyle) FLAGS_compaction_style;
|
|
|
|
if (FLAGS_statistics) {
|
|
|
|
dbstats = rocksdb::CreateDBStatistics();
|
|
|
|
}
|
|
|
|
|
|
|
|
std::vector<std::string> fanout = rocksdb::StringSplit(
|
|
|
|
FLAGS_max_bytes_for_level_multiplier_additional, ',');
|
|
|
|
for (unsigned int j= 0; j < fanout.size(); j++) {
|
|
|
|
FLAGS_max_bytes_for_level_multiplier_additional_v.push_back(
|
|
|
|
std::stoi(fanout[j]));
|
|
|
|
}
|
|
|
|
|
|
|
|
FLAGS_compression_type_e =
|
|
|
|
StringToCompressionType(FLAGS_compression_type.c_str());
|
|
|
|
|
|
|
|
if (!FLAGS_hdfs.empty()) {
|
|
|
|
FLAGS_env = new rocksdb::HdfsEnv(FLAGS_hdfs);
|
|
|
|
}
|
|
|
|
|
|
|
|
if (!strcasecmp(FLAGS_compaction_fadvice.c_str(), "NONE"))
|
|
|
|
FLAGS_compaction_fadvice_e = rocksdb::Options::NONE;
|
|
|
|
else if (!strcasecmp(FLAGS_compaction_fadvice.c_str(), "NORMAL"))
|
|
|
|
FLAGS_compaction_fadvice_e = rocksdb::Options::NORMAL;
|
|
|
|
else if (!strcasecmp(FLAGS_compaction_fadvice.c_str(), "SEQUENTIAL"))
|
|
|
|
FLAGS_compaction_fadvice_e = rocksdb::Options::SEQUENTIAL;
|
|
|
|
else if (!strcasecmp(FLAGS_compaction_fadvice.c_str(), "WILLNEED"))
|
|
|
|
FLAGS_compaction_fadvice_e = rocksdb::Options::WILLNEED;
|
|
|
|
else {
|
|
|
|
fprintf(stdout, "Unknown compaction fadvice:%s\n",
|
|
|
|
FLAGS_compaction_fadvice.c_str());
|
|
|
|
}
|
|
|
|
|
|
|
|
FLAGS_rep_factory = StringToRepFactory(FLAGS_memtablerep.c_str());
|
|
|
|
|
|
|
|
// The number of background threads should be at least as much the
|
|
|
|
// max number of concurrent compactions.
|
|
|
|
FLAGS_env->SetBackgroundThreads(FLAGS_max_background_compactions);
|
|
|
|
FLAGS_env->SetBackgroundThreads(FLAGS_max_background_flushes,
|
|
|
|
rocksdb::Env::Priority::HIGH);
|
|
|
|
|
|
|
|
// Choose a location for the test database if none given with --db=<path>
|
|
|
|
if (FLAGS_db.empty()) {
|
|
|
|
std::string default_db_path;
|
|
|
|
rocksdb::Env::Default()->GetTestDirectory(&default_db_path);
|
|
|
|
default_db_path += "/dbbench";
|
|
|
|
FLAGS_db = default_db_path;
|
|
|
|
}
|
|
|
|
|
|
|
|
rocksdb::Benchmark benchmark;
|
|
|
|
benchmark.Run();
|
|
|
|
return 0;
|
|
|
|
}
|
|
|
|
|
|
|
|
#endif // GFLAGS
|