You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
rocksdb/db/perf_context_test.cc

520 lines
17 KiB

// 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.
//
#include <algorithm>
#include <iostream>
#include <vector>
#include "rocksdb/db.h"
#include "rocksdb/perf_context.h"
11 years ago
#include "rocksdb/slice_transform.h"
#include "rocksdb/memtablerep.h"
#include "util/histogram.h"
#include "util/stop_watch.h"
#include "util/testharness.h"
bool FLAGS_random_key = false;
[RocbsDB] Add an option to enable set based memtable for perf_context_test Summary: as title. Some result: -- Sequential insertion of 1M key/value with stock skip list (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=0 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 8.0179 StdDev: 176.34 Min: 0.0000 Median: 2.5555 Max: 88933.0000 Percentiles: P50: 2.56 P75: 2.83 P99: 58.21 P99.9: 133.62 P99.99: 987.50 Get uesr key comparison: Count: 1000000 Average: 43.4465 StdDev: 379.03 Min: 2.0000 Median: 36.0195 Max: 88939.0000 Percentiles: P50: 36.02 P75: 43.66 P99: 112.98 P99.9: 824.84 P99.99: 7615.38 real 0m21.345s user 0m14.723s sys 0m5.677s -- Sequential insertion of 1M key/value with set based memtable (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=1 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 61.5022 StdDev: 6.49 Min: 0.0000 Median: 62.4295 Max: 71.0000 Percentiles: P50: 62.43 P75: 66.61 P99: 71.00 P99.9: 71.00 P99.99: 71.00 Get uesr key comparison: Count: 1000000 Average: 29.3810 StdDev: 3.20 Min: 1.0000 Median: 29.1801 Max: 34.0000 Percentiles: P50: 29.18 P75: 32.06 P99: 34.00 P99.9: 34.00 P99.99: 34.00 real 0m28.875s user 0m21.699s sys 0m5.749s Worst case comparison for a Put is 88933 (skiplist) vs 71 (set based memetable) Of course, there's other in-efficiency in set based memtable implementation, which lead to the overall worst performance. However, P99 behavior advantage is very very obvious. Test Plan: ./perf_context_test and viewstate shadow testing Reviewers: dhruba Reviewed By: dhruba CC: leveldb Differential Revision: https://reviews.facebook.net/D13095
11 years ago
bool FLAGS_use_set_based_memetable = false;
int FLAGS_total_keys = 100;
int FLAGS_write_buffer_size = 1000000000;
int FLAGS_max_write_buffer_number = 8;
int FLAGS_min_write_buffer_number_to_merge = 7;
// Path to the database on file system
const std::string kDbName = rocksdb::test::TmpDir() + "/perf_context_test";
namespace rocksdb {
std::shared_ptr<DB> OpenDb(bool read_only = false) {
DB* db;
Options options;
options.create_if_missing = true;
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;
[RocbsDB] Add an option to enable set based memtable for perf_context_test Summary: as title. Some result: -- Sequential insertion of 1M key/value with stock skip list (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=0 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 8.0179 StdDev: 176.34 Min: 0.0000 Median: 2.5555 Max: 88933.0000 Percentiles: P50: 2.56 P75: 2.83 P99: 58.21 P99.9: 133.62 P99.99: 987.50 Get uesr key comparison: Count: 1000000 Average: 43.4465 StdDev: 379.03 Min: 2.0000 Median: 36.0195 Max: 88939.0000 Percentiles: P50: 36.02 P75: 43.66 P99: 112.98 P99.9: 824.84 P99.99: 7615.38 real 0m21.345s user 0m14.723s sys 0m5.677s -- Sequential insertion of 1M key/value with set based memtable (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=1 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 61.5022 StdDev: 6.49 Min: 0.0000 Median: 62.4295 Max: 71.0000 Percentiles: P50: 62.43 P75: 66.61 P99: 71.00 P99.9: 71.00 P99.99: 71.00 Get uesr key comparison: Count: 1000000 Average: 29.3810 StdDev: 3.20 Min: 1.0000 Median: 29.1801 Max: 34.0000 Percentiles: P50: 29.18 P75: 32.06 P99: 34.00 P99.9: 34.00 P99.99: 34.00 real 0m28.875s user 0m21.699s sys 0m5.749s Worst case comparison for a Put is 88933 (skiplist) vs 71 (set based memetable) Of course, there's other in-efficiency in set based memtable implementation, which lead to the overall worst performance. However, P99 behavior advantage is very very obvious. Test Plan: ./perf_context_test and viewstate shadow testing Reviewers: dhruba Reviewed By: dhruba CC: leveldb Differential Revision: https://reviews.facebook.net/D13095
11 years ago
if (FLAGS_use_set_based_memetable) {
options.prefix_extractor.reset(rocksdb::NewFixedPrefixTransform(0));
options.memtable_factory.reset(NewHashSkipListRepFactory());
[RocbsDB] Add an option to enable set based memtable for perf_context_test Summary: as title. Some result: -- Sequential insertion of 1M key/value with stock skip list (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=0 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 8.0179 StdDev: 176.34 Min: 0.0000 Median: 2.5555 Max: 88933.0000 Percentiles: P50: 2.56 P75: 2.83 P99: 58.21 P99.9: 133.62 P99.99: 987.50 Get uesr key comparison: Count: 1000000 Average: 43.4465 StdDev: 379.03 Min: 2.0000 Median: 36.0195 Max: 88939.0000 Percentiles: P50: 36.02 P75: 43.66 P99: 112.98 P99.9: 824.84 P99.99: 7615.38 real 0m21.345s user 0m14.723s sys 0m5.677s -- Sequential insertion of 1M key/value with set based memtable (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=1 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 61.5022 StdDev: 6.49 Min: 0.0000 Median: 62.4295 Max: 71.0000 Percentiles: P50: 62.43 P75: 66.61 P99: 71.00 P99.9: 71.00 P99.99: 71.00 Get uesr key comparison: Count: 1000000 Average: 29.3810 StdDev: 3.20 Min: 1.0000 Median: 29.1801 Max: 34.0000 Percentiles: P50: 29.18 P75: 32.06 P99: 34.00 P99.9: 34.00 P99.99: 34.00 real 0m28.875s user 0m21.699s sys 0m5.749s Worst case comparison for a Put is 88933 (skiplist) vs 71 (set based memetable) Of course, there's other in-efficiency in set based memtable implementation, which lead to the overall worst performance. However, P99 behavior advantage is very very obvious. Test Plan: ./perf_context_test and viewstate shadow testing Reviewers: dhruba Reviewed By: dhruba CC: leveldb Differential Revision: https://reviews.facebook.net/D13095
11 years ago
}
Status s;
if (!read_only) {
s = DB::Open(options, kDbName, &db);
} else {
s = DB::OpenForReadOnly(options, kDbName, &db);
}
ASSERT_OK(s);
return std::shared_ptr<DB>(db);
}
class PerfContextTest { };
TEST(PerfContextTest, SeekIntoDeletion) {
DestroyDB(kDbName, Options());
auto db = OpenDb();
WriteOptions write_options;
ReadOptions read_options;
for (int i = 0; i < FLAGS_total_keys; ++i) {
std::string key = "k" + std::to_string(i);
std::string value = "v" + std::to_string(i);
db->Put(write_options, key, value);
}
for (int i = 0; i < FLAGS_total_keys -1 ; ++i) {
std::string key = "k" + std::to_string(i);
db->Delete(write_options, key);
}
HistogramImpl hist_get;
HistogramImpl hist_get_time;
for (int i = 0; i < FLAGS_total_keys - 1; ++i) {
std::string key = "k" + std::to_string(i);
std::string value;
perf_context.Reset();
StopWatchNano timer(Env::Default());
timer.Start();
auto status = db->Get(read_options, key, &value);
auto elapsed_nanos = timer.ElapsedNanos();
ASSERT_TRUE(status.IsNotFound());
hist_get.Add(perf_context.user_key_comparison_count);
hist_get_time.Add(elapsed_nanos);
}
std::cout << "Get uesr key comparison: \n" << hist_get.ToString()
<< "Get time: \n" << hist_get_time.ToString();
HistogramImpl hist_seek_to_first;
std::unique_ptr<Iterator> iter(db->NewIterator(read_options));
perf_context.Reset();
StopWatchNano timer(Env::Default(), true);
iter->SeekToFirst();
hist_seek_to_first.Add(perf_context.user_key_comparison_count);
auto elapsed_nanos = timer.ElapsedNanos();
std::cout << "SeekToFirst uesr key comparison: \n" << hist_seek_to_first.ToString()
<< "ikey skipped: " << perf_context.internal_key_skipped_count << "\n"
<< "idelete skipped: " << perf_context.internal_delete_skipped_count << "\n"
<< "elapsed: " << elapsed_nanos << "\n";
HistogramImpl hist_seek;
for (int i = 0; i < FLAGS_total_keys; ++i) {
std::unique_ptr<Iterator> iter(db->NewIterator(read_options));
std::string key = "k" + std::to_string(i);
perf_context.Reset();
StopWatchNano timer(Env::Default(), true);
iter->Seek(key);
auto elapsed_nanos = timer.ElapsedNanos();
hist_seek.Add(perf_context.user_key_comparison_count);
std::cout << "seek cmp: " << perf_context.user_key_comparison_count
<< " ikey skipped " << perf_context.internal_key_skipped_count
<< " idelete skipped " << perf_context.internal_delete_skipped_count
<< " elapsed: " << elapsed_nanos << "ns\n";
perf_context.Reset();
ASSERT_TRUE(iter->Valid());
StopWatchNano timer2(Env::Default(), true);
iter->Next();
auto elapsed_nanos2 = timer2.ElapsedNanos();
std::cout << "next cmp: " << perf_context.user_key_comparison_count
<< "elapsed: " << elapsed_nanos2 << "ns\n";
}
std::cout << "Seek uesr key comparison: \n" << hist_seek.ToString();
}
TEST(PerfContextTest, StopWatchNanoOverhead) {
// profile the timer cost by itself!
const int kTotalIterations = 1000000;
std::vector<uint64_t> timings(kTotalIterations);
StopWatchNano timer(Env::Default(), true);
for (auto& timing : timings) {
timing = timer.ElapsedNanos(true /* reset */);
}
HistogramImpl histogram;
for (const auto timing : timings) {
histogram.Add(timing);
}
std::cout << histogram.ToString();
}
TEST(PerfContextTest, StopWatchOverhead) {
// profile the timer cost by itself!
const int kTotalIterations = 1000000;
uint64_t elapsed = 0;
std::vector<uint64_t> timings(kTotalIterations);
StopWatch timer(Env::Default(), nullptr, 0, &elapsed);
for (auto& timing : timings) {
timing = elapsed;
}
HistogramImpl histogram;
uint64_t prev_timing = 0;
for (const auto timing : timings) {
histogram.Add(timing - prev_timing);
prev_timing = timing;
}
std::cout << histogram.ToString();
}
void ProfileQueries(bool enabled_time = false) {
DestroyDB(kDbName, Options()); // Start this test with a fresh DB
auto db = OpenDb();
WriteOptions write_options;
ReadOptions read_options;
[RocbsDB] Add an option to enable set based memtable for perf_context_test Summary: as title. Some result: -- Sequential insertion of 1M key/value with stock skip list (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=0 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 8.0179 StdDev: 176.34 Min: 0.0000 Median: 2.5555 Max: 88933.0000 Percentiles: P50: 2.56 P75: 2.83 P99: 58.21 P99.9: 133.62 P99.99: 987.50 Get uesr key comparison: Count: 1000000 Average: 43.4465 StdDev: 379.03 Min: 2.0000 Median: 36.0195 Max: 88939.0000 Percentiles: P50: 36.02 P75: 43.66 P99: 112.98 P99.9: 824.84 P99.99: 7615.38 real 0m21.345s user 0m14.723s sys 0m5.677s -- Sequential insertion of 1M key/value with set based memtable (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=1 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 61.5022 StdDev: 6.49 Min: 0.0000 Median: 62.4295 Max: 71.0000 Percentiles: P50: 62.43 P75: 66.61 P99: 71.00 P99.9: 71.00 P99.99: 71.00 Get uesr key comparison: Count: 1000000 Average: 29.3810 StdDev: 3.20 Min: 1.0000 Median: 29.1801 Max: 34.0000 Percentiles: P50: 29.18 P75: 32.06 P99: 34.00 P99.9: 34.00 P99.99: 34.00 real 0m28.875s user 0m21.699s sys 0m5.749s Worst case comparison for a Put is 88933 (skiplist) vs 71 (set based memetable) Of course, there's other in-efficiency in set based memtable implementation, which lead to the overall worst performance. However, P99 behavior advantage is very very obvious. Test Plan: ./perf_context_test and viewstate shadow testing Reviewers: dhruba Reviewed By: dhruba CC: leveldb Differential Revision: https://reviews.facebook.net/D13095
11 years ago
HistogramImpl hist_put;
[RocbsDB] Add an option to enable set based memtable for perf_context_test Summary: as title. Some result: -- Sequential insertion of 1M key/value with stock skip list (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=0 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 8.0179 StdDev: 176.34 Min: 0.0000 Median: 2.5555 Max: 88933.0000 Percentiles: P50: 2.56 P75: 2.83 P99: 58.21 P99.9: 133.62 P99.99: 987.50 Get uesr key comparison: Count: 1000000 Average: 43.4465 StdDev: 379.03 Min: 2.0000 Median: 36.0195 Max: 88939.0000 Percentiles: P50: 36.02 P75: 43.66 P99: 112.98 P99.9: 824.84 P99.99: 7615.38 real 0m21.345s user 0m14.723s sys 0m5.677s -- Sequential insertion of 1M key/value with set based memtable (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=1 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 61.5022 StdDev: 6.49 Min: 0.0000 Median: 62.4295 Max: 71.0000 Percentiles: P50: 62.43 P75: 66.61 P99: 71.00 P99.9: 71.00 P99.99: 71.00 Get uesr key comparison: Count: 1000000 Average: 29.3810 StdDev: 3.20 Min: 1.0000 Median: 29.1801 Max: 34.0000 Percentiles: P50: 29.18 P75: 32.06 P99: 34.00 P99.9: 34.00 P99.99: 34.00 real 0m28.875s user 0m21.699s sys 0m5.749s Worst case comparison for a Put is 88933 (skiplist) vs 71 (set based memetable) Of course, there's other in-efficiency in set based memtable implementation, which lead to the overall worst performance. However, P99 behavior advantage is very very obvious. Test Plan: ./perf_context_test and viewstate shadow testing Reviewers: dhruba Reviewed By: dhruba CC: leveldb Differential Revision: https://reviews.facebook.net/D13095
11 years ago
HistogramImpl hist_get;
HistogramImpl hist_get_snapshot;
HistogramImpl hist_get_memtable;
HistogramImpl hist_get_files;
HistogramImpl hist_get_post_process;
HistogramImpl hist_num_memtable_checked;
HistogramImpl hist_mget;
HistogramImpl hist_mget_snapshot;
HistogramImpl hist_mget_memtable;
HistogramImpl hist_mget_files;
HistogramImpl hist_mget_post_process;
HistogramImpl hist_mget_num_memtable_checked;
HistogramImpl hist_write_pre_post;
HistogramImpl hist_write_wal_time;
HistogramImpl hist_write_memtable_time;
std::cout << "Inserting " << FLAGS_total_keys << " key/value pairs\n...\n";
[RocbsDB] Add an option to enable set based memtable for perf_context_test Summary: as title. Some result: -- Sequential insertion of 1M key/value with stock skip list (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=0 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 8.0179 StdDev: 176.34 Min: 0.0000 Median: 2.5555 Max: 88933.0000 Percentiles: P50: 2.56 P75: 2.83 P99: 58.21 P99.9: 133.62 P99.99: 987.50 Get uesr key comparison: Count: 1000000 Average: 43.4465 StdDev: 379.03 Min: 2.0000 Median: 36.0195 Max: 88939.0000 Percentiles: P50: 36.02 P75: 43.66 P99: 112.98 P99.9: 824.84 P99.99: 7615.38 real 0m21.345s user 0m14.723s sys 0m5.677s -- Sequential insertion of 1M key/value with set based memtable (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=1 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 61.5022 StdDev: 6.49 Min: 0.0000 Median: 62.4295 Max: 71.0000 Percentiles: P50: 62.43 P75: 66.61 P99: 71.00 P99.9: 71.00 P99.99: 71.00 Get uesr key comparison: Count: 1000000 Average: 29.3810 StdDev: 3.20 Min: 1.0000 Median: 29.1801 Max: 34.0000 Percentiles: P50: 29.18 P75: 32.06 P99: 34.00 P99.9: 34.00 P99.99: 34.00 real 0m28.875s user 0m21.699s sys 0m5.749s Worst case comparison for a Put is 88933 (skiplist) vs 71 (set based memetable) Of course, there's other in-efficiency in set based memtable implementation, which lead to the overall worst performance. However, P99 behavior advantage is very very obvious. Test Plan: ./perf_context_test and viewstate shadow testing Reviewers: dhruba Reviewed By: dhruba CC: leveldb Differential Revision: https://reviews.facebook.net/D13095
11 years ago
std::vector<int> keys;
const int kFlushFlag = -1;
for (int i = 0; i < FLAGS_total_keys; ++i) {
[RocbsDB] Add an option to enable set based memtable for perf_context_test Summary: as title. Some result: -- Sequential insertion of 1M key/value with stock skip list (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=0 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 8.0179 StdDev: 176.34 Min: 0.0000 Median: 2.5555 Max: 88933.0000 Percentiles: P50: 2.56 P75: 2.83 P99: 58.21 P99.9: 133.62 P99.99: 987.50 Get uesr key comparison: Count: 1000000 Average: 43.4465 StdDev: 379.03 Min: 2.0000 Median: 36.0195 Max: 88939.0000 Percentiles: P50: 36.02 P75: 43.66 P99: 112.98 P99.9: 824.84 P99.99: 7615.38 real 0m21.345s user 0m14.723s sys 0m5.677s -- Sequential insertion of 1M key/value with set based memtable (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=1 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 61.5022 StdDev: 6.49 Min: 0.0000 Median: 62.4295 Max: 71.0000 Percentiles: P50: 62.43 P75: 66.61 P99: 71.00 P99.9: 71.00 P99.99: 71.00 Get uesr key comparison: Count: 1000000 Average: 29.3810 StdDev: 3.20 Min: 1.0000 Median: 29.1801 Max: 34.0000 Percentiles: P50: 29.18 P75: 32.06 P99: 34.00 P99.9: 34.00 P99.99: 34.00 real 0m28.875s user 0m21.699s sys 0m5.749s Worst case comparison for a Put is 88933 (skiplist) vs 71 (set based memetable) Of course, there's other in-efficiency in set based memtable implementation, which lead to the overall worst performance. However, P99 behavior advantage is very very obvious. Test Plan: ./perf_context_test and viewstate shadow testing Reviewers: dhruba Reviewed By: dhruba CC: leveldb Differential Revision: https://reviews.facebook.net/D13095
11 years ago
keys.push_back(i);
if (i == FLAGS_total_keys / 2) {
// Issuing a flush in the middle.
keys.push_back(kFlushFlag);
}
[RocbsDB] Add an option to enable set based memtable for perf_context_test Summary: as title. Some result: -- Sequential insertion of 1M key/value with stock skip list (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=0 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 8.0179 StdDev: 176.34 Min: 0.0000 Median: 2.5555 Max: 88933.0000 Percentiles: P50: 2.56 P75: 2.83 P99: 58.21 P99.9: 133.62 P99.99: 987.50 Get uesr key comparison: Count: 1000000 Average: 43.4465 StdDev: 379.03 Min: 2.0000 Median: 36.0195 Max: 88939.0000 Percentiles: P50: 36.02 P75: 43.66 P99: 112.98 P99.9: 824.84 P99.99: 7615.38 real 0m21.345s user 0m14.723s sys 0m5.677s -- Sequential insertion of 1M key/value with set based memtable (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=1 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 61.5022 StdDev: 6.49 Min: 0.0000 Median: 62.4295 Max: 71.0000 Percentiles: P50: 62.43 P75: 66.61 P99: 71.00 P99.9: 71.00 P99.99: 71.00 Get uesr key comparison: Count: 1000000 Average: 29.3810 StdDev: 3.20 Min: 1.0000 Median: 29.1801 Max: 34.0000 Percentiles: P50: 29.18 P75: 32.06 P99: 34.00 P99.9: 34.00 P99.99: 34.00 real 0m28.875s user 0m21.699s sys 0m5.749s Worst case comparison for a Put is 88933 (skiplist) vs 71 (set based memetable) Of course, there's other in-efficiency in set based memtable implementation, which lead to the overall worst performance. However, P99 behavior advantage is very very obvious. Test Plan: ./perf_context_test and viewstate shadow testing Reviewers: dhruba Reviewed By: dhruba CC: leveldb Differential Revision: https://reviews.facebook.net/D13095
11 years ago
}
if (FLAGS_random_key) {
std::random_shuffle(keys.begin(), keys.end());
}
for (const int i : keys) {
if (i == kFlushFlag) {
FlushOptions fo;
db->Flush(fo);
continue;
}
std::string key = "k" + std::to_string(i);
std::string value = "v" + std::to_string(i);
std::vector<Slice> keys = {Slice(key)};
std::vector<std::string> values;
perf_context.Reset();
db->Put(write_options, key, value);
hist_write_pre_post.Add(perf_context.write_pre_and_post_process_time);
hist_write_wal_time.Add(perf_context.write_wal_time);
hist_write_memtable_time.Add(perf_context.write_memtable_time);
[RocbsDB] Add an option to enable set based memtable for perf_context_test Summary: as title. Some result: -- Sequential insertion of 1M key/value with stock skip list (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=0 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 8.0179 StdDev: 176.34 Min: 0.0000 Median: 2.5555 Max: 88933.0000 Percentiles: P50: 2.56 P75: 2.83 P99: 58.21 P99.9: 133.62 P99.99: 987.50 Get uesr key comparison: Count: 1000000 Average: 43.4465 StdDev: 379.03 Min: 2.0000 Median: 36.0195 Max: 88939.0000 Percentiles: P50: 36.02 P75: 43.66 P99: 112.98 P99.9: 824.84 P99.99: 7615.38 real 0m21.345s user 0m14.723s sys 0m5.677s -- Sequential insertion of 1M key/value with set based memtable (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=1 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 61.5022 StdDev: 6.49 Min: 0.0000 Median: 62.4295 Max: 71.0000 Percentiles: P50: 62.43 P75: 66.61 P99: 71.00 P99.9: 71.00 P99.99: 71.00 Get uesr key comparison: Count: 1000000 Average: 29.3810 StdDev: 3.20 Min: 1.0000 Median: 29.1801 Max: 34.0000 Percentiles: P50: 29.18 P75: 32.06 P99: 34.00 P99.9: 34.00 P99.99: 34.00 real 0m28.875s user 0m21.699s sys 0m5.749s Worst case comparison for a Put is 88933 (skiplist) vs 71 (set based memetable) Of course, there's other in-efficiency in set based memtable implementation, which lead to the overall worst performance. However, P99 behavior advantage is very very obvious. Test Plan: ./perf_context_test and viewstate shadow testing Reviewers: dhruba Reviewed By: dhruba CC: leveldb Differential Revision: https://reviews.facebook.net/D13095
11 years ago
hist_put.Add(perf_context.user_key_comparison_count);
}
for (const int i : keys) {
std::string key = "k" + std::to_string(i);
std::string value = "v" + std::to_string(i);
std::vector<Slice> keys = {Slice(key)};
std::vector<std::string> values;
perf_context.Reset();
db->Get(read_options, key, &value);
hist_get_snapshot.Add(perf_context.get_snapshot_time);
hist_get_memtable.Add(perf_context.get_from_memtable_time);
hist_get_files.Add(perf_context.get_from_output_files_time);
hist_num_memtable_checked.Add(perf_context.get_from_memtable_count);
hist_get_post_process.Add(perf_context.get_post_process_time);
[RocbsDB] Add an option to enable set based memtable for perf_context_test Summary: as title. Some result: -- Sequential insertion of 1M key/value with stock skip list (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=0 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 8.0179 StdDev: 176.34 Min: 0.0000 Median: 2.5555 Max: 88933.0000 Percentiles: P50: 2.56 P75: 2.83 P99: 58.21 P99.9: 133.62 P99.99: 987.50 Get uesr key comparison: Count: 1000000 Average: 43.4465 StdDev: 379.03 Min: 2.0000 Median: 36.0195 Max: 88939.0000 Percentiles: P50: 36.02 P75: 43.66 P99: 112.98 P99.9: 824.84 P99.99: 7615.38 real 0m21.345s user 0m14.723s sys 0m5.677s -- Sequential insertion of 1M key/value with set based memtable (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=1 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 61.5022 StdDev: 6.49 Min: 0.0000 Median: 62.4295 Max: 71.0000 Percentiles: P50: 62.43 P75: 66.61 P99: 71.00 P99.9: 71.00 P99.99: 71.00 Get uesr key comparison: Count: 1000000 Average: 29.3810 StdDev: 3.20 Min: 1.0000 Median: 29.1801 Max: 34.0000 Percentiles: P50: 29.18 P75: 32.06 P99: 34.00 P99.9: 34.00 P99.99: 34.00 real 0m28.875s user 0m21.699s sys 0m5.749s Worst case comparison for a Put is 88933 (skiplist) vs 71 (set based memetable) Of course, there's other in-efficiency in set based memtable implementation, which lead to the overall worst performance. However, P99 behavior advantage is very very obvious. Test Plan: ./perf_context_test and viewstate shadow testing Reviewers: dhruba Reviewed By: dhruba CC: leveldb Differential Revision: https://reviews.facebook.net/D13095
11 years ago
hist_get.Add(perf_context.user_key_comparison_count);
perf_context.Reset();
db->MultiGet(read_options, keys, &values);
hist_mget_snapshot.Add(perf_context.get_snapshot_time);
hist_mget_memtable.Add(perf_context.get_from_memtable_time);
hist_mget_files.Add(perf_context.get_from_output_files_time);
hist_mget_num_memtable_checked.Add(perf_context.get_from_memtable_count);
hist_mget_post_process.Add(perf_context.get_post_process_time);
hist_mget.Add(perf_context.user_key_comparison_count);
}
[RocbsDB] Add an option to enable set based memtable for perf_context_test Summary: as title. Some result: -- Sequential insertion of 1M key/value with stock skip list (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=0 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 8.0179 StdDev: 176.34 Min: 0.0000 Median: 2.5555 Max: 88933.0000 Percentiles: P50: 2.56 P75: 2.83 P99: 58.21 P99.9: 133.62 P99.99: 987.50 Get uesr key comparison: Count: 1000000 Average: 43.4465 StdDev: 379.03 Min: 2.0000 Median: 36.0195 Max: 88939.0000 Percentiles: P50: 36.02 P75: 43.66 P99: 112.98 P99.9: 824.84 P99.99: 7615.38 real 0m21.345s user 0m14.723s sys 0m5.677s -- Sequential insertion of 1M key/value with set based memtable (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=1 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 61.5022 StdDev: 6.49 Min: 0.0000 Median: 62.4295 Max: 71.0000 Percentiles: P50: 62.43 P75: 66.61 P99: 71.00 P99.9: 71.00 P99.99: 71.00 Get uesr key comparison: Count: 1000000 Average: 29.3810 StdDev: 3.20 Min: 1.0000 Median: 29.1801 Max: 34.0000 Percentiles: P50: 29.18 P75: 32.06 P99: 34.00 P99.9: 34.00 P99.99: 34.00 real 0m28.875s user 0m21.699s sys 0m5.749s Worst case comparison for a Put is 88933 (skiplist) vs 71 (set based memetable) Of course, there's other in-efficiency in set based memtable implementation, which lead to the overall worst performance. However, P99 behavior advantage is very very obvious. Test Plan: ./perf_context_test and viewstate shadow testing Reviewers: dhruba Reviewed By: dhruba CC: leveldb Differential Revision: https://reviews.facebook.net/D13095
11 years ago
std::cout << "Put uesr key comparison: \n" << hist_put.ToString()
<< "Get uesr key comparison: \n" << hist_get.ToString()
<< "MultiGet uesr key comparison: \n" << hist_get.ToString();
std::cout << "Put(): Pre and Post Process Time: \n"
<< hist_write_pre_post.ToString()
<< " Writing WAL time: \n"
<< hist_write_wal_time.ToString() << "\n"
<< " Writing Mem Table time: \n"
<< hist_write_memtable_time.ToString() << "\n";
std::cout << "Get(): Time to get snapshot: \n" << hist_get_snapshot.ToString()
<< " Time to get value from memtables: \n"
<< hist_get_memtable.ToString() << "\n"
<< " Time to get value from output files: \n"
<< hist_get_files.ToString() << "\n"
<< " Number of memtables checked: \n"
<< hist_num_memtable_checked.ToString() << "\n"
<< " Time to post process: \n" << hist_get_post_process.ToString()
<< "\n";
std::cout << "MultiGet(): Time to get snapshot: \n"
<< hist_mget_snapshot.ToString()
<< " Time to get value from memtables: \n"
<< hist_mget_memtable.ToString() << "\n"
<< " Time to get value from output files: \n"
<< hist_mget_files.ToString() << "\n"
<< " Number of memtables checked: \n"
<< hist_mget_num_memtable_checked.ToString() << "\n"
<< " Time to post process: \n" << hist_mget_post_process.ToString()
<< "\n";
if (enabled_time) {
ASSERT_GT(hist_get.Average(), 0);
ASSERT_GT(hist_get_snapshot.Average(), 0);
ASSERT_GT(hist_get_memtable.Average(), 0);
ASSERT_GT(hist_get_files.Average(), 0);
ASSERT_GT(hist_get_post_process.Average(), 0);
ASSERT_GT(hist_num_memtable_checked.Average(), 0);
ASSERT_GT(hist_mget.Average(), 0);
ASSERT_GT(hist_mget_snapshot.Average(), 0);
ASSERT_GT(hist_mget_memtable.Average(), 0);
ASSERT_GT(hist_mget_files.Average(), 0);
ASSERT_GT(hist_mget_post_process.Average(), 0);
ASSERT_GT(hist_mget_num_memtable_checked.Average(), 0);
}
db.reset();
db = OpenDb(true);
hist_get.Clear();
hist_get_snapshot.Clear();
hist_get_memtable.Clear();
hist_get_files.Clear();
hist_get_post_process.Clear();
hist_num_memtable_checked.Clear();
hist_mget.Clear();
hist_mget_snapshot.Clear();
hist_mget_memtable.Clear();
hist_mget_files.Clear();
hist_mget_post_process.Clear();
hist_mget_num_memtable_checked.Clear();
for (const int i : keys) {
std::string key = "k" + std::to_string(i);
std::string value = "v" + std::to_string(i);
std::vector<Slice> keys = {Slice(key)};
std::vector<std::string> values;
perf_context.Reset();
db->Get(read_options, key, &value);
hist_get_snapshot.Add(perf_context.get_snapshot_time);
hist_get_memtable.Add(perf_context.get_from_memtable_time);
hist_get_files.Add(perf_context.get_from_output_files_time);
hist_num_memtable_checked.Add(perf_context.get_from_memtable_count);
hist_get_post_process.Add(perf_context.get_post_process_time);
hist_get.Add(perf_context.user_key_comparison_count);
perf_context.Reset();
db->MultiGet(read_options, keys, &values);
hist_mget_snapshot.Add(perf_context.get_snapshot_time);
hist_mget_memtable.Add(perf_context.get_from_memtable_time);
hist_mget_files.Add(perf_context.get_from_output_files_time);
hist_mget_num_memtable_checked.Add(perf_context.get_from_memtable_count);
hist_mget_post_process.Add(perf_context.get_post_process_time);
hist_mget.Add(perf_context.user_key_comparison_count);
}
std::cout << "ReadOnly Get uesr key comparison: \n" << hist_get.ToString()
<< "ReadOnly MultiGet uesr key comparison: \n"
<< hist_mget.ToString();
std::cout << "ReadOnly Get(): Time to get snapshot: \n"
<< hist_get_snapshot.ToString()
<< " Time to get value from memtables: \n"
<< hist_get_memtable.ToString() << "\n"
<< " Time to get value from output files: \n"
<< hist_get_files.ToString() << "\n"
<< " Number of memtables checked: \n"
<< hist_num_memtable_checked.ToString() << "\n"
<< " Time to post process: \n" << hist_get_post_process.ToString()
<< "\n";
std::cout << "ReadOnly MultiGet(): Time to get snapshot: \n"
<< hist_mget_snapshot.ToString()
<< " Time to get value from memtables: \n"
<< hist_mget_memtable.ToString() << "\n"
<< " Time to get value from output files: \n"
<< hist_mget_files.ToString() << "\n"
<< " Number of memtables checked: \n"
<< hist_mget_num_memtable_checked.ToString() << "\n"
<< " Time to post process: \n" << hist_mget_post_process.ToString()
<< "\n";
if (enabled_time) {
ASSERT_GT(hist_get.Average(), 0);
ASSERT_GT(hist_get_memtable.Average(), 0);
ASSERT_GT(hist_get_files.Average(), 0);
ASSERT_GT(hist_num_memtable_checked.Average(), 0);
// In read-only mode Get(), no super version operation is needed
ASSERT_EQ(hist_get_post_process.Average(), 0);
ASSERT_EQ(hist_get_snapshot.Average(), 0);
ASSERT_GT(hist_mget.Average(), 0);
ASSERT_GT(hist_mget_snapshot.Average(), 0);
ASSERT_GT(hist_mget_memtable.Average(), 0);
ASSERT_GT(hist_mget_files.Average(), 0);
ASSERT_GT(hist_mget_post_process.Average(), 0);
ASSERT_GT(hist_mget_num_memtable_checked.Average(), 0);
}
}
TEST(PerfContextTest, KeyComparisonCount) {
SetPerfLevel(kEnableCount);
ProfileQueries();
SetPerfLevel(kDisable);
ProfileQueries();
SetPerfLevel(kEnableTime);
ProfileQueries(true);
}
// make perf_context_test
// export ROCKSDB_TESTS=PerfContextTest.SeekKeyComparison
// For one memtable:
// ./perf_context_test --write_buffer_size=500000 --total_keys=10000
// For two memtables:
// ./perf_context_test --write_buffer_size=250000 --total_keys=10000
// Specify --random_key=1 to shuffle the key before insertion
// Results show that, for sequential insertion, worst-case Seek Key comparison
// is close to the total number of keys (linear), when there is only one
// memtable. When there are two memtables, even the avg Seek Key comparison
// starts to become linear to the input size.
TEST(PerfContextTest, SeekKeyComparison) {
DestroyDB(kDbName, Options());
auto db = OpenDb();
WriteOptions write_options;
ReadOptions read_options;
std::cout << "Inserting " << FLAGS_total_keys << " key/value pairs\n...\n";
std::vector<int> keys;
for (int i = 0; i < FLAGS_total_keys; ++i) {
keys.push_back(i);
}
if (FLAGS_random_key) {
std::random_shuffle(keys.begin(), keys.end());
}
HistogramImpl hist_put_time;
HistogramImpl hist_wal_time;
HistogramImpl hist_time_diff;
SetPerfLevel(kEnableTime);
StopWatchNano timer(Env::Default());
for (const int i : keys) {
std::string key = "k" + std::to_string(i);
std::string value = "v" + std::to_string(i);
perf_context.Reset();
timer.Start();
db->Put(write_options, key, value);
auto put_time = timer.ElapsedNanos();
hist_put_time.Add(put_time);
hist_wal_time.Add(perf_context.write_wal_time);
hist_time_diff.Add(put_time - perf_context.write_wal_time);
}
std::cout << "Put time:\n" << hist_put_time.ToString()
<< "WAL time:\n" << hist_wal_time.ToString()
<< "time diff:\n" << hist_time_diff.ToString();
[RocbsDB] Add an option to enable set based memtable for perf_context_test Summary: as title. Some result: -- Sequential insertion of 1M key/value with stock skip list (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=0 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 8.0179 StdDev: 176.34 Min: 0.0000 Median: 2.5555 Max: 88933.0000 Percentiles: P50: 2.56 P75: 2.83 P99: 58.21 P99.9: 133.62 P99.99: 987.50 Get uesr key comparison: Count: 1000000 Average: 43.4465 StdDev: 379.03 Min: 2.0000 Median: 36.0195 Max: 88939.0000 Percentiles: P50: 36.02 P75: 43.66 P99: 112.98 P99.9: 824.84 P99.99: 7615.38 real 0m21.345s user 0m14.723s sys 0m5.677s -- Sequential insertion of 1M key/value with set based memtable (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=1 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 61.5022 StdDev: 6.49 Min: 0.0000 Median: 62.4295 Max: 71.0000 Percentiles: P50: 62.43 P75: 66.61 P99: 71.00 P99.9: 71.00 P99.99: 71.00 Get uesr key comparison: Count: 1000000 Average: 29.3810 StdDev: 3.20 Min: 1.0000 Median: 29.1801 Max: 34.0000 Percentiles: P50: 29.18 P75: 32.06 P99: 34.00 P99.9: 34.00 P99.99: 34.00 real 0m28.875s user 0m21.699s sys 0m5.749s Worst case comparison for a Put is 88933 (skiplist) vs 71 (set based memetable) Of course, there's other in-efficiency in set based memtable implementation, which lead to the overall worst performance. However, P99 behavior advantage is very very obvious. Test Plan: ./perf_context_test and viewstate shadow testing Reviewers: dhruba Reviewed By: dhruba CC: leveldb Differential Revision: https://reviews.facebook.net/D13095
11 years ago
HistogramImpl hist_seek;
HistogramImpl hist_next;
for (int i = 0; i < FLAGS_total_keys; ++i) {
std::string key = "k" + std::to_string(i);
std::string value = "v" + std::to_string(i);
std::unique_ptr<Iterator> iter(db->NewIterator(read_options));
perf_context.Reset();
iter->Seek(key);
ASSERT_TRUE(iter->Valid());
ASSERT_EQ(iter->value().ToString(), value);
[RocbsDB] Add an option to enable set based memtable for perf_context_test Summary: as title. Some result: -- Sequential insertion of 1M key/value with stock skip list (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=0 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 8.0179 StdDev: 176.34 Min: 0.0000 Median: 2.5555 Max: 88933.0000 Percentiles: P50: 2.56 P75: 2.83 P99: 58.21 P99.9: 133.62 P99.99: 987.50 Get uesr key comparison: Count: 1000000 Average: 43.4465 StdDev: 379.03 Min: 2.0000 Median: 36.0195 Max: 88939.0000 Percentiles: P50: 36.02 P75: 43.66 P99: 112.98 P99.9: 824.84 P99.99: 7615.38 real 0m21.345s user 0m14.723s sys 0m5.677s -- Sequential insertion of 1M key/value with set based memtable (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=1 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 61.5022 StdDev: 6.49 Min: 0.0000 Median: 62.4295 Max: 71.0000 Percentiles: P50: 62.43 P75: 66.61 P99: 71.00 P99.9: 71.00 P99.99: 71.00 Get uesr key comparison: Count: 1000000 Average: 29.3810 StdDev: 3.20 Min: 1.0000 Median: 29.1801 Max: 34.0000 Percentiles: P50: 29.18 P75: 32.06 P99: 34.00 P99.9: 34.00 P99.99: 34.00 real 0m28.875s user 0m21.699s sys 0m5.749s Worst case comparison for a Put is 88933 (skiplist) vs 71 (set based memetable) Of course, there's other in-efficiency in set based memtable implementation, which lead to the overall worst performance. However, P99 behavior advantage is very very obvious. Test Plan: ./perf_context_test and viewstate shadow testing Reviewers: dhruba Reviewed By: dhruba CC: leveldb Differential Revision: https://reviews.facebook.net/D13095
11 years ago
hist_seek.Add(perf_context.user_key_comparison_count);
}
[RocbsDB] Add an option to enable set based memtable for perf_context_test Summary: as title. Some result: -- Sequential insertion of 1M key/value with stock skip list (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=0 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 8.0179 StdDev: 176.34 Min: 0.0000 Median: 2.5555 Max: 88933.0000 Percentiles: P50: 2.56 P75: 2.83 P99: 58.21 P99.9: 133.62 P99.99: 987.50 Get uesr key comparison: Count: 1000000 Average: 43.4465 StdDev: 379.03 Min: 2.0000 Median: 36.0195 Max: 88939.0000 Percentiles: P50: 36.02 P75: 43.66 P99: 112.98 P99.9: 824.84 P99.99: 7615.38 real 0m21.345s user 0m14.723s sys 0m5.677s -- Sequential insertion of 1M key/value with set based memtable (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=1 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 61.5022 StdDev: 6.49 Min: 0.0000 Median: 62.4295 Max: 71.0000 Percentiles: P50: 62.43 P75: 66.61 P99: 71.00 P99.9: 71.00 P99.99: 71.00 Get uesr key comparison: Count: 1000000 Average: 29.3810 StdDev: 3.20 Min: 1.0000 Median: 29.1801 Max: 34.0000 Percentiles: P50: 29.18 P75: 32.06 P99: 34.00 P99.9: 34.00 P99.99: 34.00 real 0m28.875s user 0m21.699s sys 0m5.749s Worst case comparison for a Put is 88933 (skiplist) vs 71 (set based memetable) Of course, there's other in-efficiency in set based memtable implementation, which lead to the overall worst performance. However, P99 behavior advantage is very very obvious. Test Plan: ./perf_context_test and viewstate shadow testing Reviewers: dhruba Reviewed By: dhruba CC: leveldb Differential Revision: https://reviews.facebook.net/D13095
11 years ago
std::unique_ptr<Iterator> iter(db->NewIterator(read_options));
for (iter->SeekToFirst(); iter->Valid();) {
perf_context.Reset();
iter->Next();
hist_next.Add(perf_context.user_key_comparison_count);
}
std::cout << "Seek:\n" << hist_seek.ToString()
<< "Next:\n" << hist_next.ToString();
}
}
int main(int argc, char** argv) {
for (int i = 1; i < argc; i++) {
int n;
char junk;
if (sscanf(argv[i], "--write_buffer_size=%d%c", &n, &junk) == 1) {
FLAGS_write_buffer_size = n;
}
if (sscanf(argv[i], "--total_keys=%d%c", &n, &junk) == 1) {
FLAGS_total_keys = n;
}
if (sscanf(argv[i], "--random_key=%d%c", &n, &junk) == 1 &&
(n == 0 || n == 1)) {
FLAGS_random_key = n;
}
[RocbsDB] Add an option to enable set based memtable for perf_context_test Summary: as title. Some result: -- Sequential insertion of 1M key/value with stock skip list (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=0 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 8.0179 StdDev: 176.34 Min: 0.0000 Median: 2.5555 Max: 88933.0000 Percentiles: P50: 2.56 P75: 2.83 P99: 58.21 P99.9: 133.62 P99.99: 987.50 Get uesr key comparison: Count: 1000000 Average: 43.4465 StdDev: 379.03 Min: 2.0000 Median: 36.0195 Max: 88939.0000 Percentiles: P50: 36.02 P75: 43.66 P99: 112.98 P99.9: 824.84 P99.99: 7615.38 real 0m21.345s user 0m14.723s sys 0m5.677s -- Sequential insertion of 1M key/value with set based memtable (all in on memtable) time ./perf_context_test --total_keys=1000000 --use_set_based_memetable=1 Inserting 1000000 key/value pairs ... Put uesr key comparison: Count: 1000000 Average: 61.5022 StdDev: 6.49 Min: 0.0000 Median: 62.4295 Max: 71.0000 Percentiles: P50: 62.43 P75: 66.61 P99: 71.00 P99.9: 71.00 P99.99: 71.00 Get uesr key comparison: Count: 1000000 Average: 29.3810 StdDev: 3.20 Min: 1.0000 Median: 29.1801 Max: 34.0000 Percentiles: P50: 29.18 P75: 32.06 P99: 34.00 P99.9: 34.00 P99.99: 34.00 real 0m28.875s user 0m21.699s sys 0m5.749s Worst case comparison for a Put is 88933 (skiplist) vs 71 (set based memetable) Of course, there's other in-efficiency in set based memtable implementation, which lead to the overall worst performance. However, P99 behavior advantage is very very obvious. Test Plan: ./perf_context_test and viewstate shadow testing Reviewers: dhruba Reviewed By: dhruba CC: leveldb Differential Revision: https://reviews.facebook.net/D13095
11 years ago
if (sscanf(argv[i], "--use_set_based_memetable=%d%c", &n, &junk) == 1 &&
(n == 0 || n == 1)) {
FLAGS_use_set_based_memetable = n;
}
}
std::cout << kDbName << "\n";
rocksdb::test::RunAllTests();
return 0;
}