rocksdb/db/db_basic_test.cc

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// Copyright (c) 2011-present, Facebook, Inc. All rights reserved.
// This source code is licensed under both the GPLv2 (found in the
// COPYING file in the root directory) and Apache 2.0 License
// (found in the LICENSE.Apache file in the root directory).
//
// 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.
// #include <iostream>
#include "db/db_test_util.h"
#include "port/stack_trace.h"
#include "rocksdb/perf_context.h"
#include "rocksdb/utilities/debug.h"
#include "table/block_based/block_builder.h"
#include "test_util/fault_injection_test_env.h"
#if !defined(ROCKSDB_LITE)
#include "test_util/sync_point.h"
#endif
namespace rocksdb {
class DBBasicTest : public DBTestBase {
public:
DBBasicTest() : DBTestBase("/db_basic_test") {}
};
TEST_F(DBBasicTest, OpenWhenOpen) {
Options options = CurrentOptions();
options.env = env_;
rocksdb::DB* db2 = nullptr;
rocksdb::Status s = DB::Open(options, dbname_, &db2);
ASSERT_EQ(Status::Code::kIOError, s.code());
ASSERT_EQ(Status::SubCode::kNone, s.subcode());
ASSERT_TRUE(strstr(s.getState(), "lock ") != nullptr);
delete db2;
}
#ifndef ROCKSDB_LITE
TEST_F(DBBasicTest, ReadOnlyDB) {
ASSERT_OK(Put("foo", "v1"));
ASSERT_OK(Put("bar", "v2"));
ASSERT_OK(Put("foo", "v3"));
Close();
auto options = CurrentOptions();
assert(options.env == env_);
ASSERT_OK(ReadOnlyReopen(options));
ASSERT_EQ("v3", Get("foo"));
ASSERT_EQ("v2", Get("bar"));
Iterator* iter = db_->NewIterator(ReadOptions());
int count = 0;
for (iter->SeekToFirst(); iter->Valid(); iter->Next()) {
ASSERT_OK(iter->status());
++count;
}
ASSERT_EQ(count, 2);
delete iter;
Close();
// Reopen and flush memtable.
Reopen(options);
Flush();
Close();
// Now check keys in read only mode.
ASSERT_OK(ReadOnlyReopen(options));
ASSERT_EQ("v3", Get("foo"));
ASSERT_EQ("v2", Get("bar"));
ASSERT_TRUE(db_->SyncWAL().IsNotSupported());
}
TEST_F(DBBasicTest, ReadOnlyDBWithWriteDBIdToManifestSet) {
ASSERT_OK(Put("foo", "v1"));
ASSERT_OK(Put("bar", "v2"));
ASSERT_OK(Put("foo", "v3"));
Close();
auto options = CurrentOptions();
options.write_dbid_to_manifest = true;
assert(options.env == env_);
ASSERT_OK(ReadOnlyReopen(options));
std::string db_id1;
db_->GetDbIdentity(db_id1);
ASSERT_EQ("v3", Get("foo"));
ASSERT_EQ("v2", Get("bar"));
Iterator* iter = db_->NewIterator(ReadOptions());
int count = 0;
for (iter->SeekToFirst(); iter->Valid(); iter->Next()) {
ASSERT_OK(iter->status());
++count;
}
ASSERT_EQ(count, 2);
delete iter;
Close();
// Reopen and flush memtable.
Reopen(options);
Flush();
Close();
// Now check keys in read only mode.
ASSERT_OK(ReadOnlyReopen(options));
ASSERT_EQ("v3", Get("foo"));
ASSERT_EQ("v2", Get("bar"));
ASSERT_TRUE(db_->SyncWAL().IsNotSupported());
std::string db_id2;
db_->GetDbIdentity(db_id2);
ASSERT_EQ(db_id1, db_id2);
}
TEST_F(DBBasicTest, CompactedDB) {
const uint64_t kFileSize = 1 << 20;
Options options = CurrentOptions();
options.disable_auto_compactions = true;
options.write_buffer_size = kFileSize;
options.target_file_size_base = kFileSize;
options.max_bytes_for_level_base = 1 << 30;
options.compression = kNoCompression;
Reopen(options);
// 1 L0 file, use CompactedDB if max_open_files = -1
ASSERT_OK(Put("aaa", DummyString(kFileSize / 2, '1')));
Flush();
Close();
ASSERT_OK(ReadOnlyReopen(options));
Status s = Put("new", "value");
ASSERT_EQ(s.ToString(),
"Not implemented: Not supported operation in read only mode.");
ASSERT_EQ(DummyString(kFileSize / 2, '1'), Get("aaa"));
Close();
options.max_open_files = -1;
ASSERT_OK(ReadOnlyReopen(options));
s = Put("new", "value");
ASSERT_EQ(s.ToString(),
"Not implemented: Not supported in compacted db mode.");
ASSERT_EQ(DummyString(kFileSize / 2, '1'), Get("aaa"));
Close();
Reopen(options);
// Add more L0 files
ASSERT_OK(Put("bbb", DummyString(kFileSize / 2, '2')));
Flush();
ASSERT_OK(Put("aaa", DummyString(kFileSize / 2, 'a')));
Flush();
ASSERT_OK(Put("bbb", DummyString(kFileSize / 2, 'b')));
ASSERT_OK(Put("eee", DummyString(kFileSize / 2, 'e')));
Flush();
Close();
ASSERT_OK(ReadOnlyReopen(options));
// Fallback to read-only DB
s = Put("new", "value");
ASSERT_EQ(s.ToString(),
"Not implemented: Not supported operation in read only mode.");
Close();
// Full compaction
Reopen(options);
// Add more keys
ASSERT_OK(Put("fff", DummyString(kFileSize / 2, 'f')));
ASSERT_OK(Put("hhh", DummyString(kFileSize / 2, 'h')));
ASSERT_OK(Put("iii", DummyString(kFileSize / 2, 'i')));
ASSERT_OK(Put("jjj", DummyString(kFileSize / 2, 'j')));
db_->CompactRange(CompactRangeOptions(), nullptr, nullptr);
ASSERT_EQ(3, NumTableFilesAtLevel(1));
Close();
// CompactedDB
ASSERT_OK(ReadOnlyReopen(options));
s = Put("new", "value");
ASSERT_EQ(s.ToString(),
"Not implemented: Not supported in compacted db mode.");
ASSERT_EQ("NOT_FOUND", Get("abc"));
ASSERT_EQ(DummyString(kFileSize / 2, 'a'), Get("aaa"));
ASSERT_EQ(DummyString(kFileSize / 2, 'b'), Get("bbb"));
ASSERT_EQ("NOT_FOUND", Get("ccc"));
ASSERT_EQ(DummyString(kFileSize / 2, 'e'), Get("eee"));
ASSERT_EQ(DummyString(kFileSize / 2, 'f'), Get("fff"));
ASSERT_EQ("NOT_FOUND", Get("ggg"));
ASSERT_EQ(DummyString(kFileSize / 2, 'h'), Get("hhh"));
ASSERT_EQ(DummyString(kFileSize / 2, 'i'), Get("iii"));
ASSERT_EQ(DummyString(kFileSize / 2, 'j'), Get("jjj"));
ASSERT_EQ("NOT_FOUND", Get("kkk"));
// MultiGet
std::vector<std::string> values;
std::vector<Status> status_list = dbfull()->MultiGet(
ReadOptions(),
std::vector<Slice>({Slice("aaa"), Slice("ccc"), Slice("eee"),
Slice("ggg"), Slice("iii"), Slice("kkk")}),
&values);
ASSERT_EQ(status_list.size(), static_cast<uint64_t>(6));
ASSERT_EQ(values.size(), static_cast<uint64_t>(6));
ASSERT_OK(status_list[0]);
ASSERT_EQ(DummyString(kFileSize / 2, 'a'), values[0]);
ASSERT_TRUE(status_list[1].IsNotFound());
ASSERT_OK(status_list[2]);
ASSERT_EQ(DummyString(kFileSize / 2, 'e'), values[2]);
ASSERT_TRUE(status_list[3].IsNotFound());
ASSERT_OK(status_list[4]);
ASSERT_EQ(DummyString(kFileSize / 2, 'i'), values[4]);
ASSERT_TRUE(status_list[5].IsNotFound());
Reopen(options);
// Add a key
ASSERT_OK(Put("fff", DummyString(kFileSize / 2, 'f')));
Close();
ASSERT_OK(ReadOnlyReopen(options));
s = Put("new", "value");
ASSERT_EQ(s.ToString(),
"Not implemented: Not supported operation in read only mode.");
}
TEST_F(DBBasicTest, LevelLimitReopen) {
Options options = CurrentOptions();
CreateAndReopenWithCF({"pikachu"}, options);
const std::string value(1024 * 1024, ' ');
int i = 0;
while (NumTableFilesAtLevel(2, 1) == 0) {
ASSERT_OK(Put(1, Key(i++), value));
dbfull()->TEST_WaitForFlushMemTable();
dbfull()->TEST_WaitForCompact();
}
options.num_levels = 1;
options.max_bytes_for_level_multiplier_additional.resize(1, 1);
Status s = TryReopenWithColumnFamilies({"default", "pikachu"}, options);
ASSERT_EQ(s.IsInvalidArgument(), true);
ASSERT_EQ(s.ToString(),
"Invalid argument: db has more levels than options.num_levels");
options.num_levels = 10;
options.max_bytes_for_level_multiplier_additional.resize(10, 1);
ASSERT_OK(TryReopenWithColumnFamilies({"default", "pikachu"}, options));
}
#endif // ROCKSDB_LITE
TEST_F(DBBasicTest, PutDeleteGet) {
do {
CreateAndReopenWithCF({"pikachu"}, CurrentOptions());
ASSERT_OK(Put(1, "foo", "v1"));
ASSERT_EQ("v1", Get(1, "foo"));
ASSERT_OK(Put(1, "foo", "v2"));
ASSERT_EQ("v2", Get(1, "foo"));
ASSERT_OK(Delete(1, "foo"));
ASSERT_EQ("NOT_FOUND", Get(1, "foo"));
} while (ChangeOptions());
}
TEST_F(DBBasicTest, PutSingleDeleteGet) {
do {
CreateAndReopenWithCF({"pikachu"}, CurrentOptions());
ASSERT_OK(Put(1, "foo", "v1"));
ASSERT_EQ("v1", Get(1, "foo"));
ASSERT_OK(Put(1, "foo2", "v2"));
ASSERT_EQ("v2", Get(1, "foo2"));
ASSERT_OK(SingleDelete(1, "foo"));
ASSERT_EQ("NOT_FOUND", Get(1, "foo"));
// Ski FIFO and universal compaction because they do not apply to the test
// case. Skip MergePut because single delete does not get removed when it
// encounters a merge.
} while (ChangeOptions(kSkipFIFOCompaction | kSkipUniversalCompaction |
kSkipMergePut));
}
TEST_F(DBBasicTest, EmptyFlush) {
// It is possible to produce empty flushes when using single deletes. Tests
// whether empty flushes cause issues.
do {
Random rnd(301);
Options options = CurrentOptions();
options.disable_auto_compactions = true;
CreateAndReopenWithCF({"pikachu"}, options);
Put(1, "a", Slice());
SingleDelete(1, "a");
ASSERT_OK(Flush(1));
ASSERT_EQ("[ ]", AllEntriesFor("a", 1));
// Skip FIFO and universal compaction as they do not apply to the test
// case. Skip MergePut because merges cannot be combined with single
// deletions.
} while (ChangeOptions(kSkipFIFOCompaction | kSkipUniversalCompaction |
kSkipMergePut));
}
TEST_F(DBBasicTest, GetFromVersions) {
do {
CreateAndReopenWithCF({"pikachu"}, CurrentOptions());
ASSERT_OK(Put(1, "foo", "v1"));
ASSERT_OK(Flush(1));
ASSERT_EQ("v1", Get(1, "foo"));
ASSERT_EQ("NOT_FOUND", Get(0, "foo"));
} while (ChangeOptions());
}
#ifndef ROCKSDB_LITE
TEST_F(DBBasicTest, GetSnapshot) {
anon::OptionsOverride options_override;
options_override.skip_policy = kSkipNoSnapshot;
do {
CreateAndReopenWithCF({"pikachu"}, CurrentOptions(options_override));
// Try with both a short key and a long key
for (int i = 0; i < 2; i++) {
std::string key = (i == 0) ? std::string("foo") : std::string(200, 'x');
ASSERT_OK(Put(1, key, "v1"));
const Snapshot* s1 = db_->GetSnapshot();
ASSERT_OK(Put(1, key, "v2"));
ASSERT_EQ("v2", Get(1, key));
ASSERT_EQ("v1", Get(1, key, s1));
ASSERT_OK(Flush(1));
ASSERT_EQ("v2", Get(1, key));
ASSERT_EQ("v1", Get(1, key, s1));
db_->ReleaseSnapshot(s1);
}
} while (ChangeOptions());
}
#endif // ROCKSDB_LITE
TEST_F(DBBasicTest, CheckLock) {
do {
DB* localdb;
Options options = CurrentOptions();
ASSERT_OK(TryReopen(options));
// second open should fail
ASSERT_TRUE(!(DB::Open(options, dbname_, &localdb)).ok());
} while (ChangeCompactOptions());
}
TEST_F(DBBasicTest, FlushMultipleMemtable) {
do {
Options options = CurrentOptions();
WriteOptions writeOpt = WriteOptions();
writeOpt.disableWAL = true;
options.max_write_buffer_number = 4;
options.min_write_buffer_number_to_merge = 3;
Refactor trimming logic for immutable memtables (#5022) Summary: MyRocks currently sets `max_write_buffer_number_to_maintain` in order to maintain enough history for transaction conflict checking. The effectiveness of this approach depends on the size of memtables. When memtables are small, it may not keep enough history; when memtables are large, this may consume too much memory. We are proposing a new way to configure memtable list history: by limiting the memory usage of immutable memtables. The new option is `max_write_buffer_size_to_maintain` and it will take precedence over the old `max_write_buffer_number_to_maintain` if they are both set to non-zero values. The new option accounts for the total memory usage of flushed immutable memtables and mutable memtable. When the total usage exceeds the limit, RocksDB may start dropping immutable memtables (which is also called trimming history), starting from the oldest one. The semantics of the old option actually works both as an upper bound and lower bound. History trimming will start if number of immutable memtables exceeds the limit, but it will never go below (limit-1) due to history trimming. In order the mimic the behavior with the new option, history trimming will stop if dropping the next immutable memtable causes the total memory usage go below the size limit. For example, assuming the size limit is set to 64MB, and there are 3 immutable memtables with sizes of 20, 30, 30. Although the total memory usage is 80MB > 64MB, dropping the oldest memtable will reduce the memory usage to 60MB < 64MB, so in this case no memtable will be dropped. Pull Request resolved: https://github.com/facebook/rocksdb/pull/5022 Differential Revision: D14394062 Pulled By: miasantreble fbshipit-source-id: 60457a509c6af89d0993f988c9b5c2aa9e45f5c5
2019-08-23 22:54:09 +02:00
options.max_write_buffer_size_to_maintain = -1;
CreateAndReopenWithCF({"pikachu"}, options);
ASSERT_OK(dbfull()->Put(writeOpt, handles_[1], "foo", "v1"));
ASSERT_OK(Flush(1));
ASSERT_OK(dbfull()->Put(writeOpt, handles_[1], "bar", "v1"));
ASSERT_EQ("v1", Get(1, "foo"));
ASSERT_EQ("v1", Get(1, "bar"));
ASSERT_OK(Flush(1));
} while (ChangeCompactOptions());
}
TEST_F(DBBasicTest, FlushEmptyColumnFamily) {
// Block flush thread and disable compaction thread
env_->SetBackgroundThreads(1, Env::HIGH);
env_->SetBackgroundThreads(1, Env::LOW);
test::SleepingBackgroundTask sleeping_task_low;
env_->Schedule(&test::SleepingBackgroundTask::DoSleepTask, &sleeping_task_low,
Env::Priority::LOW);
test::SleepingBackgroundTask sleeping_task_high;
env_->Schedule(&test::SleepingBackgroundTask::DoSleepTask,
&sleeping_task_high, Env::Priority::HIGH);
Options options = CurrentOptions();
// disable compaction
options.disable_auto_compactions = true;
WriteOptions writeOpt = WriteOptions();
writeOpt.disableWAL = true;
options.max_write_buffer_number = 2;
options.min_write_buffer_number_to_merge = 1;
Refactor trimming logic for immutable memtables (#5022) Summary: MyRocks currently sets `max_write_buffer_number_to_maintain` in order to maintain enough history for transaction conflict checking. The effectiveness of this approach depends on the size of memtables. When memtables are small, it may not keep enough history; when memtables are large, this may consume too much memory. We are proposing a new way to configure memtable list history: by limiting the memory usage of immutable memtables. The new option is `max_write_buffer_size_to_maintain` and it will take precedence over the old `max_write_buffer_number_to_maintain` if they are both set to non-zero values. The new option accounts for the total memory usage of flushed immutable memtables and mutable memtable. When the total usage exceeds the limit, RocksDB may start dropping immutable memtables (which is also called trimming history), starting from the oldest one. The semantics of the old option actually works both as an upper bound and lower bound. History trimming will start if number of immutable memtables exceeds the limit, but it will never go below (limit-1) due to history trimming. In order the mimic the behavior with the new option, history trimming will stop if dropping the next immutable memtable causes the total memory usage go below the size limit. For example, assuming the size limit is set to 64MB, and there are 3 immutable memtables with sizes of 20, 30, 30. Although the total memory usage is 80MB > 64MB, dropping the oldest memtable will reduce the memory usage to 60MB < 64MB, so in this case no memtable will be dropped. Pull Request resolved: https://github.com/facebook/rocksdb/pull/5022 Differential Revision: D14394062 Pulled By: miasantreble fbshipit-source-id: 60457a509c6af89d0993f988c9b5c2aa9e45f5c5
2019-08-23 22:54:09 +02:00
options.max_write_buffer_size_to_maintain =
static_cast<int64_t>(options.write_buffer_size);
CreateAndReopenWithCF({"pikachu"}, options);
// Compaction can still go through even if no thread can flush the
// mem table.
ASSERT_OK(Flush(0));
ASSERT_OK(Flush(1));
// Insert can go through
ASSERT_OK(dbfull()->Put(writeOpt, handles_[0], "foo", "v1"));
ASSERT_OK(dbfull()->Put(writeOpt, handles_[1], "bar", "v1"));
ASSERT_EQ("v1", Get(0, "foo"));
ASSERT_EQ("v1", Get(1, "bar"));
sleeping_task_high.WakeUp();
sleeping_task_high.WaitUntilDone();
// Flush can still go through.
ASSERT_OK(Flush(0));
ASSERT_OK(Flush(1));
sleeping_task_low.WakeUp();
sleeping_task_low.WaitUntilDone();
}
TEST_F(DBBasicTest, FLUSH) {
do {
CreateAndReopenWithCF({"pikachu"}, CurrentOptions());
WriteOptions writeOpt = WriteOptions();
writeOpt.disableWAL = true;
SetPerfLevel(kEnableTime);
ASSERT_OK(dbfull()->Put(writeOpt, handles_[1], "foo", "v1"));
// this will now also flush the last 2 writes
ASSERT_OK(Flush(1));
ASSERT_OK(dbfull()->Put(writeOpt, handles_[1], "bar", "v1"));
get_perf_context()->Reset();
Get(1, "foo");
ASSERT_TRUE((int)get_perf_context()->get_from_output_files_time > 0);
ASSERT_EQ(2, (int)get_perf_context()->get_read_bytes);
ReopenWithColumnFamilies({"default", "pikachu"}, CurrentOptions());
ASSERT_EQ("v1", Get(1, "foo"));
ASSERT_EQ("v1", Get(1, "bar"));
writeOpt.disableWAL = true;
ASSERT_OK(dbfull()->Put(writeOpt, handles_[1], "bar", "v2"));
ASSERT_OK(dbfull()->Put(writeOpt, handles_[1], "foo", "v2"));
ASSERT_OK(Flush(1));
ReopenWithColumnFamilies({"default", "pikachu"}, CurrentOptions());
ASSERT_EQ("v2", Get(1, "bar"));
get_perf_context()->Reset();
ASSERT_EQ("v2", Get(1, "foo"));
ASSERT_TRUE((int)get_perf_context()->get_from_output_files_time > 0);
writeOpt.disableWAL = false;
ASSERT_OK(dbfull()->Put(writeOpt, handles_[1], "bar", "v3"));
ASSERT_OK(dbfull()->Put(writeOpt, handles_[1], "foo", "v3"));
ASSERT_OK(Flush(1));
ReopenWithColumnFamilies({"default", "pikachu"}, CurrentOptions());
// 'foo' should be there because its put
// has WAL enabled.
ASSERT_EQ("v3", Get(1, "foo"));
ASSERT_EQ("v3", Get(1, "bar"));
SetPerfLevel(kDisable);
} while (ChangeCompactOptions());
}
TEST_F(DBBasicTest, ManifestRollOver) {
do {
Options options;
options.max_manifest_file_size = 10; // 10 bytes
options = CurrentOptions(options);
CreateAndReopenWithCF({"pikachu"}, options);
{
ASSERT_OK(Put(1, "manifest_key1", std::string(1000, '1')));
ASSERT_OK(Put(1, "manifest_key2", std::string(1000, '2')));
ASSERT_OK(Put(1, "manifest_key3", std::string(1000, '3')));
uint64_t manifest_before_flush = dbfull()->TEST_Current_Manifest_FileNo();
ASSERT_OK(Flush(1)); // This should trigger LogAndApply.
uint64_t manifest_after_flush = dbfull()->TEST_Current_Manifest_FileNo();
ASSERT_GT(manifest_after_flush, manifest_before_flush);
ReopenWithColumnFamilies({"default", "pikachu"}, options);
ASSERT_GT(dbfull()->TEST_Current_Manifest_FileNo(), manifest_after_flush);
// check if a new manifest file got inserted or not.
ASSERT_EQ(std::string(1000, '1'), Get(1, "manifest_key1"));
ASSERT_EQ(std::string(1000, '2'), Get(1, "manifest_key2"));
ASSERT_EQ(std::string(1000, '3'), Get(1, "manifest_key3"));
}
} while (ChangeCompactOptions());
}
TEST_F(DBBasicTest, IdentityAcrossRestarts1) {
do {
std::string id1;
ASSERT_OK(db_->GetDbIdentity(id1));
Options options = CurrentOptions();
Reopen(options);
std::string id2;
ASSERT_OK(db_->GetDbIdentity(id2));
// id1 should match id2 because identity was not regenerated
ASSERT_EQ(id1.compare(id2), 0);
std::string idfilename = IdentityFileName(dbname_);
ASSERT_OK(env_->DeleteFile(idfilename));
Reopen(options);
std::string id3;
ASSERT_OK(db_->GetDbIdentity(id3));
if (options.write_dbid_to_manifest) {
ASSERT_EQ(id1.compare(id3), 0);
} else {
// id1 should NOT match id3 because identity was regenerated
ASSERT_NE(id1.compare(id3), 0);
}
} while (ChangeCompactOptions());
}
TEST_F(DBBasicTest, IdentityAcrossRestarts2) {
do {
std::string id1;
ASSERT_OK(db_->GetDbIdentity(id1));
Options options = CurrentOptions();
options.write_dbid_to_manifest = true;
Reopen(options);
std::string id2;
ASSERT_OK(db_->GetDbIdentity(id2));
// id1 should match id2 because identity was not regenerated
ASSERT_EQ(id1.compare(id2), 0);
std::string idfilename = IdentityFileName(dbname_);
ASSERT_OK(env_->DeleteFile(idfilename));
Reopen(options);
std::string id3;
ASSERT_OK(db_->GetDbIdentity(id3));
// id1 should NOT match id3 because identity was regenerated
ASSERT_EQ(id1, id3);
} while (ChangeCompactOptions());
}
#ifndef ROCKSDB_LITE
TEST_F(DBBasicTest, Snapshot) {
anon::OptionsOverride options_override;
options_override.skip_policy = kSkipNoSnapshot;
do {
CreateAndReopenWithCF({"pikachu"}, CurrentOptions(options_override));
Put(0, "foo", "0v1");
Put(1, "foo", "1v1");
const Snapshot* s1 = db_->GetSnapshot();
ASSERT_EQ(1U, GetNumSnapshots());
uint64_t time_snap1 = GetTimeOldestSnapshots();
ASSERT_GT(time_snap1, 0U);
Put(0, "foo", "0v2");
Put(1, "foo", "1v2");
env_->addon_time_.fetch_add(1);
const Snapshot* s2 = db_->GetSnapshot();
ASSERT_EQ(2U, GetNumSnapshots());
ASSERT_EQ(time_snap1, GetTimeOldestSnapshots());
Put(0, "foo", "0v3");
Put(1, "foo", "1v3");
{
ManagedSnapshot s3(db_);
ASSERT_EQ(3U, GetNumSnapshots());
ASSERT_EQ(time_snap1, GetTimeOldestSnapshots());
Put(0, "foo", "0v4");
Put(1, "foo", "1v4");
ASSERT_EQ("0v1", Get(0, "foo", s1));
ASSERT_EQ("1v1", Get(1, "foo", s1));
ASSERT_EQ("0v2", Get(0, "foo", s2));
ASSERT_EQ("1v2", Get(1, "foo", s2));
ASSERT_EQ("0v3", Get(0, "foo", s3.snapshot()));
ASSERT_EQ("1v3", Get(1, "foo", s3.snapshot()));
ASSERT_EQ("0v4", Get(0, "foo"));
ASSERT_EQ("1v4", Get(1, "foo"));
}
ASSERT_EQ(2U, GetNumSnapshots());
ASSERT_EQ(time_snap1, GetTimeOldestSnapshots());
ASSERT_EQ("0v1", Get(0, "foo", s1));
ASSERT_EQ("1v1", Get(1, "foo", s1));
ASSERT_EQ("0v2", Get(0, "foo", s2));
ASSERT_EQ("1v2", Get(1, "foo", s2));
ASSERT_EQ("0v4", Get(0, "foo"));
ASSERT_EQ("1v4", Get(1, "foo"));
db_->ReleaseSnapshot(s1);
ASSERT_EQ("0v2", Get(0, "foo", s2));
ASSERT_EQ("1v2", Get(1, "foo", s2));
ASSERT_EQ("0v4", Get(0, "foo"));
ASSERT_EQ("1v4", Get(1, "foo"));
ASSERT_EQ(1U, GetNumSnapshots());
ASSERT_LT(time_snap1, GetTimeOldestSnapshots());
db_->ReleaseSnapshot(s2);
ASSERT_EQ(0U, GetNumSnapshots());
ASSERT_EQ("0v4", Get(0, "foo"));
ASSERT_EQ("1v4", Get(1, "foo"));
} while (ChangeOptions());
}
#endif // ROCKSDB_LITE
TEST_F(DBBasicTest, CompactBetweenSnapshots) {
anon::OptionsOverride options_override;
options_override.skip_policy = kSkipNoSnapshot;
do {
Options options = CurrentOptions(options_override);
options.disable_auto_compactions = true;
CreateAndReopenWithCF({"pikachu"}, options);
Random rnd(301);
FillLevels("a", "z", 1);
Put(1, "foo", "first");
const Snapshot* snapshot1 = db_->GetSnapshot();
Put(1, "foo", "second");
Put(1, "foo", "third");
Put(1, "foo", "fourth");
const Snapshot* snapshot2 = db_->GetSnapshot();
Put(1, "foo", "fifth");
Put(1, "foo", "sixth");
// All entries (including duplicates) exist
// before any compaction or flush is triggered.
ASSERT_EQ(AllEntriesFor("foo", 1),
"[ sixth, fifth, fourth, third, second, first ]");
ASSERT_EQ("sixth", Get(1, "foo"));
ASSERT_EQ("fourth", Get(1, "foo", snapshot2));
ASSERT_EQ("first", Get(1, "foo", snapshot1));
// After a flush, "second", "third" and "fifth" should
// be removed
ASSERT_OK(Flush(1));
ASSERT_EQ(AllEntriesFor("foo", 1), "[ sixth, fourth, first ]");
// after we release the snapshot1, only two values left
db_->ReleaseSnapshot(snapshot1);
FillLevels("a", "z", 1);
dbfull()->CompactRange(CompactRangeOptions(), handles_[1], nullptr,
nullptr);
// We have only one valid snapshot snapshot2. Since snapshot1 is
// not valid anymore, "first" should be removed by a compaction.
ASSERT_EQ("sixth", Get(1, "foo"));
ASSERT_EQ("fourth", Get(1, "foo", snapshot2));
ASSERT_EQ(AllEntriesFor("foo", 1), "[ sixth, fourth ]");
// after we release the snapshot2, only one value should be left
db_->ReleaseSnapshot(snapshot2);
FillLevels("a", "z", 1);
dbfull()->CompactRange(CompactRangeOptions(), handles_[1], nullptr,
nullptr);
ASSERT_EQ("sixth", Get(1, "foo"));
ASSERT_EQ(AllEntriesFor("foo", 1), "[ sixth ]");
} while (ChangeOptions(kSkipFIFOCompaction));
}
TEST_F(DBBasicTest, DBOpen_Options) {
Options options = CurrentOptions();
Close();
Destroy(options);
// Does not exist, and create_if_missing == false: error
DB* db = nullptr;
options.create_if_missing = false;
Status s = DB::Open(options, dbname_, &db);
ASSERT_TRUE(strstr(s.ToString().c_str(), "does not exist") != nullptr);
ASSERT_TRUE(db == nullptr);
// Does not exist, and create_if_missing == true: OK
options.create_if_missing = true;
s = DB::Open(options, dbname_, &db);
ASSERT_OK(s);
ASSERT_TRUE(db != nullptr);
delete db;
db = nullptr;
// Does exist, and error_if_exists == true: error
options.create_if_missing = false;
options.error_if_exists = true;
s = DB::Open(options, dbname_, &db);
ASSERT_TRUE(strstr(s.ToString().c_str(), "exists") != nullptr);
ASSERT_TRUE(db == nullptr);
// Does exist, and error_if_exists == false: OK
options.create_if_missing = true;
options.error_if_exists = false;
s = DB::Open(options, dbname_, &db);
ASSERT_OK(s);
ASSERT_TRUE(db != nullptr);
delete db;
db = nullptr;
}
TEST_F(DBBasicTest, CompactOnFlush) {
anon::OptionsOverride options_override;
options_override.skip_policy = kSkipNoSnapshot;
do {
Options options = CurrentOptions(options_override);
options.disable_auto_compactions = true;
CreateAndReopenWithCF({"pikachu"}, options);
Put(1, "foo", "v1");
ASSERT_OK(Flush(1));
ASSERT_EQ(AllEntriesFor("foo", 1), "[ v1 ]");
// Write two new keys
Put(1, "a", "begin");
Put(1, "z", "end");
Flush(1);
// Case1: Delete followed by a put
Delete(1, "foo");
Put(1, "foo", "v2");
ASSERT_EQ(AllEntriesFor("foo", 1), "[ v2, DEL, v1 ]");
// After the current memtable is flushed, the DEL should
// have been removed
ASSERT_OK(Flush(1));
ASSERT_EQ(AllEntriesFor("foo", 1), "[ v2, v1 ]");
dbfull()->CompactRange(CompactRangeOptions(), handles_[1], nullptr,
nullptr);
ASSERT_EQ(AllEntriesFor("foo", 1), "[ v2 ]");
// Case 2: Delete followed by another delete
Delete(1, "foo");
Delete(1, "foo");
ASSERT_EQ(AllEntriesFor("foo", 1), "[ DEL, DEL, v2 ]");
ASSERT_OK(Flush(1));
ASSERT_EQ(AllEntriesFor("foo", 1), "[ DEL, v2 ]");
dbfull()->CompactRange(CompactRangeOptions(), handles_[1], nullptr,
nullptr);
ASSERT_EQ(AllEntriesFor("foo", 1), "[ ]");
// Case 3: Put followed by a delete
Put(1, "foo", "v3");
Delete(1, "foo");
ASSERT_EQ(AllEntriesFor("foo", 1), "[ DEL, v3 ]");
ASSERT_OK(Flush(1));
ASSERT_EQ(AllEntriesFor("foo", 1), "[ DEL ]");
dbfull()->CompactRange(CompactRangeOptions(), handles_[1], nullptr,
nullptr);
ASSERT_EQ(AllEntriesFor("foo", 1), "[ ]");
// Case 4: Put followed by another Put
Put(1, "foo", "v4");
Put(1, "foo", "v5");
ASSERT_EQ(AllEntriesFor("foo", 1), "[ v5, v4 ]");
ASSERT_OK(Flush(1));
ASSERT_EQ(AllEntriesFor("foo", 1), "[ v5 ]");
dbfull()->CompactRange(CompactRangeOptions(), handles_[1], nullptr,
nullptr);
ASSERT_EQ(AllEntriesFor("foo", 1), "[ v5 ]");
// clear database
Delete(1, "foo");
dbfull()->CompactRange(CompactRangeOptions(), handles_[1], nullptr,
nullptr);
ASSERT_EQ(AllEntriesFor("foo", 1), "[ ]");
// Case 5: Put followed by snapshot followed by another Put
// Both puts should remain.
Put(1, "foo", "v6");
const Snapshot* snapshot = db_->GetSnapshot();
Put(1, "foo", "v7");
ASSERT_OK(Flush(1));
ASSERT_EQ(AllEntriesFor("foo", 1), "[ v7, v6 ]");
db_->ReleaseSnapshot(snapshot);
// clear database
Delete(1, "foo");
dbfull()->CompactRange(CompactRangeOptions(), handles_[1], nullptr,
nullptr);
ASSERT_EQ(AllEntriesFor("foo", 1), "[ ]");
// Case 5: snapshot followed by a put followed by another Put
// Only the last put should remain.
const Snapshot* snapshot1 = db_->GetSnapshot();
Put(1, "foo", "v8");
Put(1, "foo", "v9");
ASSERT_OK(Flush(1));
ASSERT_EQ(AllEntriesFor("foo", 1), "[ v9 ]");
db_->ReleaseSnapshot(snapshot1);
} while (ChangeCompactOptions());
}
TEST_F(DBBasicTest, FlushOneColumnFamily) {
Options options = CurrentOptions();
CreateAndReopenWithCF({"pikachu", "ilya", "muromec", "dobrynia", "nikitich",
"alyosha", "popovich"},
options);
ASSERT_OK(Put(0, "Default", "Default"));
ASSERT_OK(Put(1, "pikachu", "pikachu"));
ASSERT_OK(Put(2, "ilya", "ilya"));
ASSERT_OK(Put(3, "muromec", "muromec"));
ASSERT_OK(Put(4, "dobrynia", "dobrynia"));
ASSERT_OK(Put(5, "nikitich", "nikitich"));
ASSERT_OK(Put(6, "alyosha", "alyosha"));
ASSERT_OK(Put(7, "popovich", "popovich"));
for (int i = 0; i < 8; ++i) {
Flush(i);
auto tables = ListTableFiles(env_, dbname_);
ASSERT_EQ(tables.size(), i + 1U);
}
}
TEST_F(DBBasicTest, MultiGetSimple) {
do {
CreateAndReopenWithCF({"pikachu"}, CurrentOptions());
SetPerfLevel(kEnableCount);
ASSERT_OK(Put(1, "k1", "v1"));
ASSERT_OK(Put(1, "k2", "v2"));
ASSERT_OK(Put(1, "k3", "v3"));
ASSERT_OK(Put(1, "k4", "v4"));
ASSERT_OK(Delete(1, "k4"));
ASSERT_OK(Put(1, "k5", "v5"));
ASSERT_OK(Delete(1, "no_key"));
std::vector<Slice> keys({"k1", "k2", "k3", "k4", "k5", "no_key"});
std::vector<std::string> values(20, "Temporary data to be overwritten");
std::vector<ColumnFamilyHandle*> cfs(keys.size(), handles_[1]);
get_perf_context()->Reset();
std::vector<Status> s = db_->MultiGet(ReadOptions(), cfs, keys, &values);
ASSERT_EQ(values.size(), keys.size());
ASSERT_EQ(values[0], "v1");
ASSERT_EQ(values[1], "v2");
ASSERT_EQ(values[2], "v3");
ASSERT_EQ(values[4], "v5");
// four kv pairs * two bytes per value
ASSERT_EQ(8, (int)get_perf_context()->multiget_read_bytes);
ASSERT_OK(s[0]);
ASSERT_OK(s[1]);
ASSERT_OK(s[2]);
ASSERT_TRUE(s[3].IsNotFound());
ASSERT_OK(s[4]);
ASSERT_TRUE(s[5].IsNotFound());
SetPerfLevel(kDisable);
} while (ChangeCompactOptions());
}
TEST_F(DBBasicTest, MultiGetEmpty) {
do {
CreateAndReopenWithCF({"pikachu"}, CurrentOptions());
// Empty Key Set
std::vector<Slice> keys;
std::vector<std::string> values;
std::vector<ColumnFamilyHandle*> cfs;
std::vector<Status> s = db_->MultiGet(ReadOptions(), cfs, keys, &values);
ASSERT_EQ(s.size(), 0U);
// Empty Database, Empty Key Set
Options options = CurrentOptions();
options.create_if_missing = true;
DestroyAndReopen(options);
CreateAndReopenWithCF({"pikachu"}, options);
s = db_->MultiGet(ReadOptions(), cfs, keys, &values);
ASSERT_EQ(s.size(), 0U);
// Empty Database, Search for Keys
keys.resize(2);
keys[0] = "a";
keys[1] = "b";
cfs.push_back(handles_[0]);
cfs.push_back(handles_[1]);
s = db_->MultiGet(ReadOptions(), cfs, keys, &values);
ASSERT_EQ(static_cast<int>(s.size()), 2);
ASSERT_TRUE(s[0].IsNotFound() && s[1].IsNotFound());
} while (ChangeCompactOptions());
}
TEST_F(DBBasicTest, ChecksumTest) {
BlockBasedTableOptions table_options;
Options options = CurrentOptions();
// change when new checksum type added
int max_checksum = static_cast<int>(kxxHash64);
const int kNumPerFile = 2;
// generate one table with each type of checksum
for (int i = 0; i <= max_checksum; ++i) {
table_options.checksum = static_cast<ChecksumType>(i);
options.table_factory.reset(NewBlockBasedTableFactory(table_options));
Reopen(options);
for (int j = 0; j < kNumPerFile; ++j) {
ASSERT_OK(Put(Key(i * kNumPerFile + j), Key(i * kNumPerFile + j)));
}
ASSERT_OK(Flush());
}
// with each valid checksum type setting...
for (int i = 0; i <= max_checksum; ++i) {
table_options.checksum = static_cast<ChecksumType>(i);
options.table_factory.reset(NewBlockBasedTableFactory(table_options));
Reopen(options);
// verify every type of checksum (should be regardless of that setting)
for (int j = 0; j < (max_checksum + 1) * kNumPerFile; ++j) {
ASSERT_EQ(Key(j), Get(Key(j)));
}
}
}
// On Windows you can have either memory mapped file or a file
// with unbuffered access. So this asserts and does not make
// sense to run
#ifndef OS_WIN
TEST_F(DBBasicTest, MmapAndBufferOptions) {
Encryption at rest support Summary: This PR adds support for encrypting data stored by RocksDB when written to disk. It adds an `EncryptedEnv` override of the `Env` class with matching overrides for sequential&random access files. The encryption itself is done through a configurable `EncryptionProvider`. This class creates is asked to create `BlockAccessCipherStream` for a file. This is where the actual encryption/decryption is being done. Currently there is a Counter mode implementation of `BlockAccessCipherStream` with a `ROT13` block cipher (NOTE the `ROT13` is for demo purposes only!!). The Counter operation mode uses an initial counter & random initialization vector (IV). Both are created randomly for each file and stored in a 4K (default size) block that is prefixed to that file. The `EncryptedEnv` implementation is such that clients of the `Env` class do not see this prefix (nor data, nor in filesize). The largest part of the prefix block is also encrypted, and there is room left for implementation specific settings/values/keys in there. To test the encryption, the `DBTestBase` class has been extended to consider a new environment variable called `ENCRYPTED_ENV`. If set, the test will setup a encrypted instance of the `Env` class to use for all tests. Typically you would run it like this: ``` ENCRYPTED_ENV=1 make check_some ``` There is also an added test that checks that some data inserted into the database is or is not "visible" on disk. With `ENCRYPTED_ENV` active it must not find plain text strings, with `ENCRYPTED_ENV` unset, it must find the plain text strings. Closes https://github.com/facebook/rocksdb/pull/2424 Differential Revision: D5322178 Pulled By: sdwilsh fbshipit-source-id: 253b0a9c2c498cc98f580df7f2623cbf7678a27f
2017-06-27 01:52:06 +02:00
if (!IsMemoryMappedAccessSupported()) {
return;
}
Options options = CurrentOptions();
options.use_direct_reads = true;
options.allow_mmap_reads = true;
ASSERT_NOK(TryReopen(options));
// All other combinations are acceptable
options.use_direct_reads = false;
ASSERT_OK(TryReopen(options));
if (IsDirectIOSupported()) {
options.use_direct_reads = true;
options.allow_mmap_reads = false;
ASSERT_OK(TryReopen(options));
}
options.use_direct_reads = false;
ASSERT_OK(TryReopen(options));
}
#endif
class TestEnv : public EnvWrapper {
public:
explicit TestEnv(Env* base_env) : EnvWrapper(base_env), close_count(0) {}
class TestLogger : public Logger {
public:
using Logger::Logv;
explicit TestLogger(TestEnv* env_ptr) : Logger() { env = env_ptr; }
~TestLogger() override {
if (!closed_) {
CloseHelper();
}
}
void Logv(const char* /*format*/, va_list /*ap*/) override {}
protected:
Status CloseImpl() override { return CloseHelper(); }
private:
Status CloseHelper() {
env->CloseCountInc();
;
return Status::IOError();
}
TestEnv* env;
};
void CloseCountInc() { close_count++; }
int GetCloseCount() { return close_count; }
Status NewLogger(const std::string& /*fname*/,
std::shared_ptr<Logger>* result) override {
result->reset(new TestLogger(this));
return Status::OK();
}
private:
int close_count;
};
TEST_F(DBBasicTest, DBClose) {
Options options = GetDefaultOptions();
std::string dbname = test::PerThreadDBPath("db_close_test");
ASSERT_OK(DestroyDB(dbname, options));
DB* db = nullptr;
TestEnv* env = new TestEnv(env_);
std::unique_ptr<TestEnv> local_env_guard(env);
options.create_if_missing = true;
options.env = env;
Status s = DB::Open(options, dbname, &db);
ASSERT_OK(s);
ASSERT_TRUE(db != nullptr);
s = db->Close();
ASSERT_EQ(env->GetCloseCount(), 1);
ASSERT_EQ(s, Status::IOError());
delete db;
ASSERT_EQ(env->GetCloseCount(), 1);
// Do not call DB::Close() and ensure our logger Close() still gets called
s = DB::Open(options, dbname, &db);
ASSERT_OK(s);
ASSERT_TRUE(db != nullptr);
delete db;
ASSERT_EQ(env->GetCloseCount(), 2);
// Provide our own logger and ensure DB::Close() does not close it
options.info_log.reset(new TestEnv::TestLogger(env));
options.create_if_missing = false;
s = DB::Open(options, dbname, &db);
ASSERT_OK(s);
ASSERT_TRUE(db != nullptr);
s = db->Close();
ASSERT_EQ(s, Status::OK());
delete db;
ASSERT_EQ(env->GetCloseCount(), 2);
options.info_log.reset();
ASSERT_EQ(env->GetCloseCount(), 3);
}
TEST_F(DBBasicTest, DBCloseFlushError) {
std::unique_ptr<FaultInjectionTestEnv> fault_injection_env(
new FaultInjectionTestEnv(env_));
Options options = GetDefaultOptions();
options.create_if_missing = true;
options.manual_wal_flush = true;
options.write_buffer_size=100;
options.env = fault_injection_env.get();
Reopen(options);
ASSERT_OK(Put("key1", "value1"));
ASSERT_OK(Put("key2", "value2"));
ASSERT_OK(dbfull()->TEST_SwitchMemtable());
ASSERT_OK(Put("key3", "value3"));
fault_injection_env->SetFilesystemActive(false);
Status s = dbfull()->Close();
fault_injection_env->SetFilesystemActive(true);
ASSERT_NE(s, Status::OK());
Destroy(options);
}
TEST_F(DBBasicTest, MultiGetMultiCF) {
Options options = CurrentOptions();
CreateAndReopenWithCF({"pikachu", "ilya", "muromec", "dobrynia", "nikitich",
"alyosha", "popovich"},
options);
for (int i = 0; i < 8; ++i) {
ASSERT_OK(Put(i, "cf" + std::to_string(i) + "_key",
"cf" + std::to_string(i) + "_val"));
}
int get_sv_count = 0;
rocksdb::DBImpl* db = reinterpret_cast<DBImpl*>(db_);
rocksdb::SyncPoint::GetInstance()->SetCallBack(
"DBImpl::MultiGet::AfterRefSV", [&](void* /*arg*/) {
if (++get_sv_count == 2) {
// After MultiGet refs a couple of CFs, flush all CFs so MultiGet
// is forced to repeat the process
for (int i = 0; i < 8; ++i) {
ASSERT_OK(Flush(i));
ASSERT_OK(Put(i, "cf" + std::to_string(i) + "_key",
"cf" + std::to_string(i) + "_val2"));
}
}
if (get_sv_count == 11) {
for (int i = 0; i < 8; ++i) {
auto* cfd = reinterpret_cast<ColumnFamilyHandleImpl*>(
db->GetColumnFamilyHandle(i))
->cfd();
ASSERT_EQ(cfd->TEST_GetLocalSV()->Get(), SuperVersion::kSVInUse);
}
}
});
rocksdb::SyncPoint::GetInstance()->EnableProcessing();
std::vector<int> cfs;
std::vector<std::string> keys;
std::vector<std::string> values;
for (int i = 0; i < 8; ++i) {
cfs.push_back(i);
keys.push_back("cf" + std::to_string(i) + "_key");
}
Introduce a new MultiGet batching implementation (#5011) Summary: This PR introduces a new MultiGet() API, with the underlying implementation grouping keys based on SST file and batching lookups in a file. The reason for the new API is twofold - the definition allows callers to allocate storage for status and values on stack instead of std::vector, as well as return values as PinnableSlices in order to avoid copying, and it keeps the original MultiGet() implementation intact while we experiment with batching. Batching is useful when there is some spatial locality to the keys being queries, as well as larger batch sizes. The main benefits are due to - 1. Fewer function calls, especially to BlockBasedTableReader::MultiGet() and FullFilterBlockReader::KeysMayMatch() 2. Bloom filter cachelines can be prefetched, hiding the cache miss latency The next step is to optimize the binary searches in the level_storage_info, index blocks and data blocks, since we could reduce the number of key comparisons if the keys are relatively close to each other. The batching optimizations also need to be extended to other formats, such as PlainTable and filter formats. This also needs to be added to db_stress. Benchmark results from db_bench for various batch size/locality of reference combinations are given below. Locality was simulated by offsetting the keys in a batch by a stride length. Each SST file is about 8.6MB uncompressed and key/value size is 16/100 uncompressed. To focus on the cpu benefit of batching, the runs were single threaded and bound to the same cpu to eliminate interference from other system events. The results show a 10-25% improvement in micros/op from smaller to larger batch sizes (4 - 32). Batch Sizes 1 | 2 | 4 | 8 | 16 | 32 Random pattern (Stride length 0) 4.158 | 4.109 | 4.026 | 4.05 | 4.1 | 4.074 - Get 4.438 | 4.302 | 4.165 | 4.122 | 4.096 | 4.075 - MultiGet (no batching) 4.461 | 4.256 | 4.277 | 4.11 | 4.182 | 4.14 - MultiGet (w/ batching) Good locality (Stride length 16) 4.048 | 3.659 | 3.248 | 2.99 | 2.84 | 2.753 4.429 | 3.728 | 3.406 | 3.053 | 2.911 | 2.781 4.452 | 3.45 | 2.833 | 2.451 | 2.233 | 2.135 Good locality (Stride length 256) 4.066 | 3.786 | 3.581 | 3.447 | 3.415 | 3.232 4.406 | 4.005 | 3.644 | 3.49 | 3.381 | 3.268 4.393 | 3.649 | 3.186 | 2.882 | 2.676 | 2.62 Medium locality (Stride length 4096) 4.012 | 3.922 | 3.768 | 3.61 | 3.582 | 3.555 4.364 | 4.057 | 3.791 | 3.65 | 3.57 | 3.465 4.479 | 3.758 | 3.316 | 3.077 | 2.959 | 2.891 dbbench command used (on a DB with 4 levels, 12 million keys)- TEST_TMPDIR=/dev/shm numactl -C 10 ./db_bench.tmp -use_existing_db=true -benchmarks="readseq,multireadrandom" -write_buffer_size=4194304 -target_file_size_base=4194304 -max_bytes_for_level_base=16777216 -num=12000000 -reads=12000000 -duration=90 -threads=1 -compression_type=none -cache_size=4194304000 -batch_size=32 -disable_auto_compactions=true -bloom_bits=10 -cache_index_and_filter_blocks=true -pin_l0_filter_and_index_blocks_in_cache=true -multiread_batched=true -multiread_stride=4 Pull Request resolved: https://github.com/facebook/rocksdb/pull/5011 Differential Revision: D14348703 Pulled By: anand1976 fbshipit-source-id: 774406dab3776d979c809522a67bedac6c17f84b
2019-04-11 23:24:09 +02:00
values = MultiGet(cfs, keys, nullptr);
ASSERT_EQ(values.size(), 8);
for (unsigned int j = 0; j < values.size(); ++j) {
ASSERT_EQ(values[j], "cf" + std::to_string(j) + "_val2");
}
for (int i = 0; i < 8; ++i) {
auto* cfd = reinterpret_cast<ColumnFamilyHandleImpl*>(
reinterpret_cast<DBImpl*>(db_)->GetColumnFamilyHandle(i))
->cfd();
ASSERT_NE(cfd->TEST_GetLocalSV()->Get(), SuperVersion::kSVInUse);
ASSERT_NE(cfd->TEST_GetLocalSV()->Get(), SuperVersion::kSVObsolete);
}
}
TEST_F(DBBasicTest, MultiGetMultiCFMutex) {
Options options = CurrentOptions();
CreateAndReopenWithCF({"pikachu", "ilya", "muromec", "dobrynia", "nikitich",
"alyosha", "popovich"},
options);
for (int i = 0; i < 8; ++i) {
ASSERT_OK(Put(i, "cf" + std::to_string(i) + "_key",
"cf" + std::to_string(i) + "_val"));
}
int get_sv_count = 0;
int retries = 0;
bool last_try = false;
rocksdb::SyncPoint::GetInstance()->SetCallBack(
"DBImpl::MultiGet::LastTry", [&](void* /*arg*/) {
last_try = true;
rocksdb::SyncPoint::GetInstance()->DisableProcessing();
});
rocksdb::SyncPoint::GetInstance()->SetCallBack(
"DBImpl::MultiGet::AfterRefSV", [&](void* /*arg*/) {
if (last_try) {
return;
}
if (++get_sv_count == 2) {
++retries;
get_sv_count = 0;
for (int i = 0; i < 8; ++i) {
ASSERT_OK(Flush(i));
ASSERT_OK(Put(
i, "cf" + std::to_string(i) + "_key",
"cf" + std::to_string(i) + "_val" + std::to_string(retries)));
}
}
});
rocksdb::SyncPoint::GetInstance()->EnableProcessing();
std::vector<int> cfs;
std::vector<std::string> keys;
std::vector<std::string> values;
for (int i = 0; i < 8; ++i) {
cfs.push_back(i);
keys.push_back("cf" + std::to_string(i) + "_key");
}
Introduce a new MultiGet batching implementation (#5011) Summary: This PR introduces a new MultiGet() API, with the underlying implementation grouping keys based on SST file and batching lookups in a file. The reason for the new API is twofold - the definition allows callers to allocate storage for status and values on stack instead of std::vector, as well as return values as PinnableSlices in order to avoid copying, and it keeps the original MultiGet() implementation intact while we experiment with batching. Batching is useful when there is some spatial locality to the keys being queries, as well as larger batch sizes. The main benefits are due to - 1. Fewer function calls, especially to BlockBasedTableReader::MultiGet() and FullFilterBlockReader::KeysMayMatch() 2. Bloom filter cachelines can be prefetched, hiding the cache miss latency The next step is to optimize the binary searches in the level_storage_info, index blocks and data blocks, since we could reduce the number of key comparisons if the keys are relatively close to each other. The batching optimizations also need to be extended to other formats, such as PlainTable and filter formats. This also needs to be added to db_stress. Benchmark results from db_bench for various batch size/locality of reference combinations are given below. Locality was simulated by offsetting the keys in a batch by a stride length. Each SST file is about 8.6MB uncompressed and key/value size is 16/100 uncompressed. To focus on the cpu benefit of batching, the runs were single threaded and bound to the same cpu to eliminate interference from other system events. The results show a 10-25% improvement in micros/op from smaller to larger batch sizes (4 - 32). Batch Sizes 1 | 2 | 4 | 8 | 16 | 32 Random pattern (Stride length 0) 4.158 | 4.109 | 4.026 | 4.05 | 4.1 | 4.074 - Get 4.438 | 4.302 | 4.165 | 4.122 | 4.096 | 4.075 - MultiGet (no batching) 4.461 | 4.256 | 4.277 | 4.11 | 4.182 | 4.14 - MultiGet (w/ batching) Good locality (Stride length 16) 4.048 | 3.659 | 3.248 | 2.99 | 2.84 | 2.753 4.429 | 3.728 | 3.406 | 3.053 | 2.911 | 2.781 4.452 | 3.45 | 2.833 | 2.451 | 2.233 | 2.135 Good locality (Stride length 256) 4.066 | 3.786 | 3.581 | 3.447 | 3.415 | 3.232 4.406 | 4.005 | 3.644 | 3.49 | 3.381 | 3.268 4.393 | 3.649 | 3.186 | 2.882 | 2.676 | 2.62 Medium locality (Stride length 4096) 4.012 | 3.922 | 3.768 | 3.61 | 3.582 | 3.555 4.364 | 4.057 | 3.791 | 3.65 | 3.57 | 3.465 4.479 | 3.758 | 3.316 | 3.077 | 2.959 | 2.891 dbbench command used (on a DB with 4 levels, 12 million keys)- TEST_TMPDIR=/dev/shm numactl -C 10 ./db_bench.tmp -use_existing_db=true -benchmarks="readseq,multireadrandom" -write_buffer_size=4194304 -target_file_size_base=4194304 -max_bytes_for_level_base=16777216 -num=12000000 -reads=12000000 -duration=90 -threads=1 -compression_type=none -cache_size=4194304000 -batch_size=32 -disable_auto_compactions=true -bloom_bits=10 -cache_index_and_filter_blocks=true -pin_l0_filter_and_index_blocks_in_cache=true -multiread_batched=true -multiread_stride=4 Pull Request resolved: https://github.com/facebook/rocksdb/pull/5011 Differential Revision: D14348703 Pulled By: anand1976 fbshipit-source-id: 774406dab3776d979c809522a67bedac6c17f84b
2019-04-11 23:24:09 +02:00
values = MultiGet(cfs, keys, nullptr);
ASSERT_TRUE(last_try);
ASSERT_EQ(values.size(), 8);
for (unsigned int j = 0; j < values.size(); ++j) {
ASSERT_EQ(values[j],
"cf" + std::to_string(j) + "_val" + std::to_string(retries));
}
for (int i = 0; i < 8; ++i) {
auto* cfd = reinterpret_cast<ColumnFamilyHandleImpl*>(
reinterpret_cast<DBImpl*>(db_)->GetColumnFamilyHandle(i))
->cfd();
ASSERT_NE(cfd->TEST_GetLocalSV()->Get(), SuperVersion::kSVInUse);
}
}
TEST_F(DBBasicTest, MultiGetMultiCFSnapshot) {
Options options = CurrentOptions();
CreateAndReopenWithCF({"pikachu", "ilya", "muromec", "dobrynia", "nikitich",
"alyosha", "popovich"},
options);
for (int i = 0; i < 8; ++i) {
ASSERT_OK(Put(i, "cf" + std::to_string(i) + "_key",
"cf" + std::to_string(i) + "_val"));
}
int get_sv_count = 0;
rocksdb::DBImpl* db = reinterpret_cast<DBImpl*>(db_);
rocksdb::SyncPoint::GetInstance()->SetCallBack(
"DBImpl::MultiGet::AfterRefSV", [&](void* /*arg*/) {
if (++get_sv_count == 2) {
for (int i = 0; i < 8; ++i) {
ASSERT_OK(Flush(i));
ASSERT_OK(Put(i, "cf" + std::to_string(i) + "_key",
"cf" + std::to_string(i) + "_val2"));
}
}
if (get_sv_count == 8) {
for (int i = 0; i < 8; ++i) {
auto* cfd = reinterpret_cast<ColumnFamilyHandleImpl*>(
db->GetColumnFamilyHandle(i))
->cfd();
ASSERT_TRUE(
(cfd->TEST_GetLocalSV()->Get() == SuperVersion::kSVInUse) ||
(cfd->TEST_GetLocalSV()->Get() == SuperVersion::kSVObsolete));
}
}
});
rocksdb::SyncPoint::GetInstance()->EnableProcessing();
std::vector<int> cfs;
std::vector<std::string> keys;
std::vector<std::string> values;
for (int i = 0; i < 8; ++i) {
cfs.push_back(i);
keys.push_back("cf" + std::to_string(i) + "_key");
}
const Snapshot* snapshot = db_->GetSnapshot();
values = MultiGet(cfs, keys, snapshot);
db_->ReleaseSnapshot(snapshot);
ASSERT_EQ(values.size(), 8);
for (unsigned int j = 0; j < values.size(); ++j) {
ASSERT_EQ(values[j], "cf" + std::to_string(j) + "_val");
}
for (int i = 0; i < 8; ++i) {
auto* cfd = reinterpret_cast<ColumnFamilyHandleImpl*>(
reinterpret_cast<DBImpl*>(db_)->GetColumnFamilyHandle(i))
->cfd();
ASSERT_NE(cfd->TEST_GetLocalSV()->Get(), SuperVersion::kSVInUse);
}
}
TEST_F(DBBasicTest, MultiGetBatchedSimpleUnsorted) {
do {
CreateAndReopenWithCF({"pikachu"}, CurrentOptions());
SetPerfLevel(kEnableCount);
ASSERT_OK(Put(1, "k1", "v1"));
ASSERT_OK(Put(1, "k2", "v2"));
ASSERT_OK(Put(1, "k3", "v3"));
ASSERT_OK(Put(1, "k4", "v4"));
ASSERT_OK(Delete(1, "k4"));
ASSERT_OK(Put(1, "k5", "v5"));
ASSERT_OK(Delete(1, "no_key"));
get_perf_context()->Reset();
std::vector<Slice> keys({"no_key", "k5", "k4", "k3", "k2", "k1"});
std::vector<PinnableSlice> values(keys.size());
std::vector<ColumnFamilyHandle*> cfs(keys.size(), handles_[1]);
std::vector<Status> s(keys.size());
db_->MultiGet(ReadOptions(), handles_[1], keys.size(), keys.data(),
values.data(), s.data(), false);
ASSERT_EQ(values.size(), keys.size());
ASSERT_EQ(std::string(values[5].data(), values[5].size()), "v1");
ASSERT_EQ(std::string(values[4].data(), values[4].size()), "v2");
ASSERT_EQ(std::string(values[3].data(), values[3].size()), "v3");
ASSERT_EQ(std::string(values[1].data(), values[1].size()), "v5");
// four kv pairs * two bytes per value
ASSERT_EQ(8, (int)get_perf_context()->multiget_read_bytes);
ASSERT_TRUE(s[0].IsNotFound());
ASSERT_OK(s[1]);
ASSERT_TRUE(s[2].IsNotFound());
ASSERT_OK(s[3]);
ASSERT_OK(s[4]);
ASSERT_OK(s[5]);
SetPerfLevel(kDisable);
} while (ChangeCompactOptions());
}
TEST_F(DBBasicTest, MultiGetBatchedSimpleSorted) {
do {
CreateAndReopenWithCF({"pikachu"}, CurrentOptions());
SetPerfLevel(kEnableCount);
ASSERT_OK(Put(1, "k1", "v1"));
ASSERT_OK(Put(1, "k2", "v2"));
ASSERT_OK(Put(1, "k3", "v3"));
ASSERT_OK(Put(1, "k4", "v4"));
ASSERT_OK(Delete(1, "k4"));
ASSERT_OK(Put(1, "k5", "v5"));
ASSERT_OK(Delete(1, "no_key"));
get_perf_context()->Reset();
std::vector<Slice> keys({"k1", "k2", "k3", "k4", "k5", "no_key"});
std::vector<PinnableSlice> values(keys.size());
std::vector<ColumnFamilyHandle*> cfs(keys.size(), handles_[1]);
std::vector<Status> s(keys.size());
db_->MultiGet(ReadOptions(), handles_[1], keys.size(), keys.data(),
values.data(), s.data(), true);
ASSERT_EQ(values.size(), keys.size());
ASSERT_EQ(std::string(values[0].data(), values[0].size()), "v1");
ASSERT_EQ(std::string(values[1].data(), values[1].size()), "v2");
ASSERT_EQ(std::string(values[2].data(), values[2].size()), "v3");
ASSERT_EQ(std::string(values[4].data(), values[4].size()), "v5");
// four kv pairs * two bytes per value
ASSERT_EQ(8, (int)get_perf_context()->multiget_read_bytes);
ASSERT_OK(s[0]);
ASSERT_OK(s[1]);
ASSERT_OK(s[2]);
ASSERT_TRUE(s[3].IsNotFound());
ASSERT_OK(s[4]);
ASSERT_TRUE(s[5].IsNotFound());
SetPerfLevel(kDisable);
} while (ChangeCompactOptions());
}
Introduce a new MultiGet batching implementation (#5011) Summary: This PR introduces a new MultiGet() API, with the underlying implementation grouping keys based on SST file and batching lookups in a file. The reason for the new API is twofold - the definition allows callers to allocate storage for status and values on stack instead of std::vector, as well as return values as PinnableSlices in order to avoid copying, and it keeps the original MultiGet() implementation intact while we experiment with batching. Batching is useful when there is some spatial locality to the keys being queries, as well as larger batch sizes. The main benefits are due to - 1. Fewer function calls, especially to BlockBasedTableReader::MultiGet() and FullFilterBlockReader::KeysMayMatch() 2. Bloom filter cachelines can be prefetched, hiding the cache miss latency The next step is to optimize the binary searches in the level_storage_info, index blocks and data blocks, since we could reduce the number of key comparisons if the keys are relatively close to each other. The batching optimizations also need to be extended to other formats, such as PlainTable and filter formats. This also needs to be added to db_stress. Benchmark results from db_bench for various batch size/locality of reference combinations are given below. Locality was simulated by offsetting the keys in a batch by a stride length. Each SST file is about 8.6MB uncompressed and key/value size is 16/100 uncompressed. To focus on the cpu benefit of batching, the runs were single threaded and bound to the same cpu to eliminate interference from other system events. The results show a 10-25% improvement in micros/op from smaller to larger batch sizes (4 - 32). Batch Sizes 1 | 2 | 4 | 8 | 16 | 32 Random pattern (Stride length 0) 4.158 | 4.109 | 4.026 | 4.05 | 4.1 | 4.074 - Get 4.438 | 4.302 | 4.165 | 4.122 | 4.096 | 4.075 - MultiGet (no batching) 4.461 | 4.256 | 4.277 | 4.11 | 4.182 | 4.14 - MultiGet (w/ batching) Good locality (Stride length 16) 4.048 | 3.659 | 3.248 | 2.99 | 2.84 | 2.753 4.429 | 3.728 | 3.406 | 3.053 | 2.911 | 2.781 4.452 | 3.45 | 2.833 | 2.451 | 2.233 | 2.135 Good locality (Stride length 256) 4.066 | 3.786 | 3.581 | 3.447 | 3.415 | 3.232 4.406 | 4.005 | 3.644 | 3.49 | 3.381 | 3.268 4.393 | 3.649 | 3.186 | 2.882 | 2.676 | 2.62 Medium locality (Stride length 4096) 4.012 | 3.922 | 3.768 | 3.61 | 3.582 | 3.555 4.364 | 4.057 | 3.791 | 3.65 | 3.57 | 3.465 4.479 | 3.758 | 3.316 | 3.077 | 2.959 | 2.891 dbbench command used (on a DB with 4 levels, 12 million keys)- TEST_TMPDIR=/dev/shm numactl -C 10 ./db_bench.tmp -use_existing_db=true -benchmarks="readseq,multireadrandom" -write_buffer_size=4194304 -target_file_size_base=4194304 -max_bytes_for_level_base=16777216 -num=12000000 -reads=12000000 -duration=90 -threads=1 -compression_type=none -cache_size=4194304000 -batch_size=32 -disable_auto_compactions=true -bloom_bits=10 -cache_index_and_filter_blocks=true -pin_l0_filter_and_index_blocks_in_cache=true -multiread_batched=true -multiread_stride=4 Pull Request resolved: https://github.com/facebook/rocksdb/pull/5011 Differential Revision: D14348703 Pulled By: anand1976 fbshipit-source-id: 774406dab3776d979c809522a67bedac6c17f84b
2019-04-11 23:24:09 +02:00
TEST_F(DBBasicTest, MultiGetBatchedMultiLevel) {
Options options = CurrentOptions();
options.disable_auto_compactions = true;
Reopen(options);
int num_keys = 0;
for (int i = 0; i < 128; ++i) {
ASSERT_OK(Put("key_" + std::to_string(i), "val_l2_" + std::to_string(i)));
num_keys++;
if (num_keys == 8) {
Flush();
num_keys = 0;
}
}
if (num_keys > 0) {
Flush();
num_keys = 0;
}
MoveFilesToLevel(2);
for (int i = 0; i < 128; i += 3) {
ASSERT_OK(Put("key_" + std::to_string(i), "val_l1_" + std::to_string(i)));
num_keys++;
if (num_keys == 8) {
Flush();
num_keys = 0;
}
}
if (num_keys > 0) {
Flush();
num_keys = 0;
}
MoveFilesToLevel(1);
for (int i = 0; i < 128; i += 5) {
ASSERT_OK(Put("key_" + std::to_string(i), "val_l0_" + std::to_string(i)));
num_keys++;
if (num_keys == 8) {
Flush();
num_keys = 0;
}
}
if (num_keys > 0) {
Flush();
num_keys = 0;
}
ASSERT_EQ(0, num_keys);
Introduce a new MultiGet batching implementation (#5011) Summary: This PR introduces a new MultiGet() API, with the underlying implementation grouping keys based on SST file and batching lookups in a file. The reason for the new API is twofold - the definition allows callers to allocate storage for status and values on stack instead of std::vector, as well as return values as PinnableSlices in order to avoid copying, and it keeps the original MultiGet() implementation intact while we experiment with batching. Batching is useful when there is some spatial locality to the keys being queries, as well as larger batch sizes. The main benefits are due to - 1. Fewer function calls, especially to BlockBasedTableReader::MultiGet() and FullFilterBlockReader::KeysMayMatch() 2. Bloom filter cachelines can be prefetched, hiding the cache miss latency The next step is to optimize the binary searches in the level_storage_info, index blocks and data blocks, since we could reduce the number of key comparisons if the keys are relatively close to each other. The batching optimizations also need to be extended to other formats, such as PlainTable and filter formats. This also needs to be added to db_stress. Benchmark results from db_bench for various batch size/locality of reference combinations are given below. Locality was simulated by offsetting the keys in a batch by a stride length. Each SST file is about 8.6MB uncompressed and key/value size is 16/100 uncompressed. To focus on the cpu benefit of batching, the runs were single threaded and bound to the same cpu to eliminate interference from other system events. The results show a 10-25% improvement in micros/op from smaller to larger batch sizes (4 - 32). Batch Sizes 1 | 2 | 4 | 8 | 16 | 32 Random pattern (Stride length 0) 4.158 | 4.109 | 4.026 | 4.05 | 4.1 | 4.074 - Get 4.438 | 4.302 | 4.165 | 4.122 | 4.096 | 4.075 - MultiGet (no batching) 4.461 | 4.256 | 4.277 | 4.11 | 4.182 | 4.14 - MultiGet (w/ batching) Good locality (Stride length 16) 4.048 | 3.659 | 3.248 | 2.99 | 2.84 | 2.753 4.429 | 3.728 | 3.406 | 3.053 | 2.911 | 2.781 4.452 | 3.45 | 2.833 | 2.451 | 2.233 | 2.135 Good locality (Stride length 256) 4.066 | 3.786 | 3.581 | 3.447 | 3.415 | 3.232 4.406 | 4.005 | 3.644 | 3.49 | 3.381 | 3.268 4.393 | 3.649 | 3.186 | 2.882 | 2.676 | 2.62 Medium locality (Stride length 4096) 4.012 | 3.922 | 3.768 | 3.61 | 3.582 | 3.555 4.364 | 4.057 | 3.791 | 3.65 | 3.57 | 3.465 4.479 | 3.758 | 3.316 | 3.077 | 2.959 | 2.891 dbbench command used (on a DB with 4 levels, 12 million keys)- TEST_TMPDIR=/dev/shm numactl -C 10 ./db_bench.tmp -use_existing_db=true -benchmarks="readseq,multireadrandom" -write_buffer_size=4194304 -target_file_size_base=4194304 -max_bytes_for_level_base=16777216 -num=12000000 -reads=12000000 -duration=90 -threads=1 -compression_type=none -cache_size=4194304000 -batch_size=32 -disable_auto_compactions=true -bloom_bits=10 -cache_index_and_filter_blocks=true -pin_l0_filter_and_index_blocks_in_cache=true -multiread_batched=true -multiread_stride=4 Pull Request resolved: https://github.com/facebook/rocksdb/pull/5011 Differential Revision: D14348703 Pulled By: anand1976 fbshipit-source-id: 774406dab3776d979c809522a67bedac6c17f84b
2019-04-11 23:24:09 +02:00
for (int i = 0; i < 128; i += 9) {
ASSERT_OK(Put("key_" + std::to_string(i), "val_mem_" + std::to_string(i)));
}
std::vector<std::string> keys;
std::vector<std::string> values;
for (int i = 64; i < 80; ++i) {
keys.push_back("key_" + std::to_string(i));
}
values = MultiGet(keys, nullptr);
ASSERT_EQ(values.size(), 16);
for (unsigned int j = 0; j < values.size(); ++j) {
int key = j + 64;
if (key % 9 == 0) {
ASSERT_EQ(values[j], "val_mem_" + std::to_string(key));
} else if (key % 5 == 0) {
ASSERT_EQ(values[j], "val_l0_" + std::to_string(key));
} else if (key % 3 == 0) {
ASSERT_EQ(values[j], "val_l1_" + std::to_string(key));
} else {
ASSERT_EQ(values[j], "val_l2_" + std::to_string(key));
}
}
}
Add support for timestamp in Get/Put (#5079) Summary: It's useful to be able to (optionally) associate key-value pairs with user-provided timestamps. This PR is an early effort towards this goal and continues the work of facebook#4942. A suite of new unit tests exist in DBBasicTestWithTimestampWithParam. Support for timestamp requires the user to provide timestamp as a slice in `ReadOptions` and `WriteOptions`. All timestamps of the same database must share the same length, format, etc. The format of the timestamp is the same throughout the same database, and the user is responsible for providing a comparator function (Comparator) to order the <key, timestamp> tuples. Once created, the format and length of the timestamp cannot change (at least for now). Test plan (on devserver): ``` $COMPILE_WITH_ASAN=1 make -j32 all $./db_basic_test --gtest_filter=Timestamp/DBBasicTestWithTimestampWithParam.PutAndGet/* $make check ``` All tests must pass. We also run the following db_bench tests to verify whether there is regression on Get/Put while timestamp is not enabled. ``` $TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=fillseq,readrandom -num=1000000 $TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=fillrandom -num=1000000 ``` Repeat for 6 times for both versions. Results are as follows: ``` | | readrandom | fillrandom | | master | 16.77 MB/s | 47.05 MB/s | | PR5079 | 16.44 MB/s | 47.03 MB/s | ``` Pull Request resolved: https://github.com/facebook/rocksdb/pull/5079 Differential Revision: D15132946 Pulled By: riversand963 fbshipit-source-id: 833a0d657eac21182f0f206c910a6438154c742c
2019-06-06 08:07:28 +02:00
// Test class for batched MultiGet with prefix extractor
// Param bool - If true, use partitioned filters
// If false, use full filter block
class MultiGetPrefixExtractorTest : public DBBasicTest,
public ::testing::WithParamInterface<bool> {
};
TEST_P(MultiGetPrefixExtractorTest, Batched) {
Options options = CurrentOptions();
options.prefix_extractor.reset(NewFixedPrefixTransform(2));
MultiGet batching in memtable (#5818) Summary: RocksDB has a MultiGet() API that implements batched key lookup for higher performance (https://github.com/facebook/rocksdb/blob/master/include/rocksdb/db.h#L468). Currently, batching is implemented in BlockBasedTableReader::MultiGet() for SST file lookups. One of the ways it improves performance is by pipelining bloom filter lookups (by prefetching required cachelines for all the keys in the batch, and then doing the probe) and thus hiding the cache miss latency. The same concept can be extended to the memtable as well. This PR involves implementing a pipelined bloom filter lookup in DynamicBloom, and implementing MemTable::MultiGet() that can leverage it. Pull Request resolved: https://github.com/facebook/rocksdb/pull/5818 Test Plan: Existing tests Performance Test: Ran the below command which fills up the memtable and makes sure there are no flushes and then call multiget. Ran it on master and on the new change and see atleast 1% performance improvement across all the test runs I did. Sometimes the improvement was upto 5%. TEST_TMPDIR=/data/users/$USER/benchmarks/feature/ numactl -C 10 ./db_bench -benchmarks="fillseq,multireadrandom" -num=600000 -compression_type="none" -level_compaction_dynamic_level_bytes -write_buffer_size=200000000 -target_file_size_base=200000000 -max_bytes_for_level_base=16777216 -reads=90000 -threads=1 -compression_type=none -cache_size=4194304000 -batch_size=32 -disable_auto_compactions=true -bloom_bits=10 -cache_index_and_filter_blocks=true -pin_l0_filter_and_index_blocks_in_cache=true -multiread_batched=true -multiread_stride=4 -statistics -memtable_whole_key_filtering=true -memtable_bloom_size_ratio=10 Differential Revision: D17578869 Pulled By: vjnadimpalli fbshipit-source-id: 23dc651d9bf49db11d22375bf435708875a1f192
2019-10-10 18:37:38 +02:00
options.memtable_prefix_bloom_size_ratio = 10;
BlockBasedTableOptions bbto;
if (GetParam()) {
bbto.index_type = BlockBasedTableOptions::IndexType::kTwoLevelIndexSearch;
bbto.partition_filters = true;
}
bbto.filter_policy.reset(NewBloomFilterPolicy(10, false));
bbto.whole_key_filtering = false;
bbto.cache_index_and_filter_blocks = false;
options.table_factory.reset(NewBlockBasedTableFactory(bbto));
Reopen(options);
MultiGet batching in memtable (#5818) Summary: RocksDB has a MultiGet() API that implements batched key lookup for higher performance (https://github.com/facebook/rocksdb/blob/master/include/rocksdb/db.h#L468). Currently, batching is implemented in BlockBasedTableReader::MultiGet() for SST file lookups. One of the ways it improves performance is by pipelining bloom filter lookups (by prefetching required cachelines for all the keys in the batch, and then doing the probe) and thus hiding the cache miss latency. The same concept can be extended to the memtable as well. This PR involves implementing a pipelined bloom filter lookup in DynamicBloom, and implementing MemTable::MultiGet() that can leverage it. Pull Request resolved: https://github.com/facebook/rocksdb/pull/5818 Test Plan: Existing tests Performance Test: Ran the below command which fills up the memtable and makes sure there are no flushes and then call multiget. Ran it on master and on the new change and see atleast 1% performance improvement across all the test runs I did. Sometimes the improvement was upto 5%. TEST_TMPDIR=/data/users/$USER/benchmarks/feature/ numactl -C 10 ./db_bench -benchmarks="fillseq,multireadrandom" -num=600000 -compression_type="none" -level_compaction_dynamic_level_bytes -write_buffer_size=200000000 -target_file_size_base=200000000 -max_bytes_for_level_base=16777216 -reads=90000 -threads=1 -compression_type=none -cache_size=4194304000 -batch_size=32 -disable_auto_compactions=true -bloom_bits=10 -cache_index_and_filter_blocks=true -pin_l0_filter_and_index_blocks_in_cache=true -multiread_batched=true -multiread_stride=4 -statistics -memtable_whole_key_filtering=true -memtable_bloom_size_ratio=10 Differential Revision: D17578869 Pulled By: vjnadimpalli fbshipit-source-id: 23dc651d9bf49db11d22375bf435708875a1f192
2019-10-10 18:37:38 +02:00
SetPerfLevel(kEnableCount);
get_perf_context()->Reset();
// First key is not in the prefix_extractor domain
ASSERT_OK(Put("k", "v0"));
ASSERT_OK(Put("kk1", "v1"));
ASSERT_OK(Put("kk2", "v2"));
ASSERT_OK(Put("kk3", "v3"));
ASSERT_OK(Put("kk4", "v4"));
MultiGet batching in memtable (#5818) Summary: RocksDB has a MultiGet() API that implements batched key lookup for higher performance (https://github.com/facebook/rocksdb/blob/master/include/rocksdb/db.h#L468). Currently, batching is implemented in BlockBasedTableReader::MultiGet() for SST file lookups. One of the ways it improves performance is by pipelining bloom filter lookups (by prefetching required cachelines for all the keys in the batch, and then doing the probe) and thus hiding the cache miss latency. The same concept can be extended to the memtable as well. This PR involves implementing a pipelined bloom filter lookup in DynamicBloom, and implementing MemTable::MultiGet() that can leverage it. Pull Request resolved: https://github.com/facebook/rocksdb/pull/5818 Test Plan: Existing tests Performance Test: Ran the below command which fills up the memtable and makes sure there are no flushes and then call multiget. Ran it on master and on the new change and see atleast 1% performance improvement across all the test runs I did. Sometimes the improvement was upto 5%. TEST_TMPDIR=/data/users/$USER/benchmarks/feature/ numactl -C 10 ./db_bench -benchmarks="fillseq,multireadrandom" -num=600000 -compression_type="none" -level_compaction_dynamic_level_bytes -write_buffer_size=200000000 -target_file_size_base=200000000 -max_bytes_for_level_base=16777216 -reads=90000 -threads=1 -compression_type=none -cache_size=4194304000 -batch_size=32 -disable_auto_compactions=true -bloom_bits=10 -cache_index_and_filter_blocks=true -pin_l0_filter_and_index_blocks_in_cache=true -multiread_batched=true -multiread_stride=4 -statistics -memtable_whole_key_filtering=true -memtable_bloom_size_ratio=10 Differential Revision: D17578869 Pulled By: vjnadimpalli fbshipit-source-id: 23dc651d9bf49db11d22375bf435708875a1f192
2019-10-10 18:37:38 +02:00
std::vector<std::string> mem_keys(
{"k", "kk1", "kk2", "kk3", "kk4", "rofl", "lmho"});
std::vector<std::string> inmem_values;
inmem_values = MultiGet(mem_keys, nullptr);
ASSERT_EQ(inmem_values[0], "v0");
ASSERT_EQ(inmem_values[1], "v1");
ASSERT_EQ(inmem_values[2], "v2");
ASSERT_EQ(inmem_values[3], "v3");
ASSERT_EQ(inmem_values[4], "v4");
ASSERT_EQ(get_perf_context()->bloom_memtable_miss_count, 2);
ASSERT_EQ(get_perf_context()->bloom_memtable_hit_count, 5);
ASSERT_OK(Flush());
std::vector<std::string> keys({"k", "kk1", "kk2", "kk3", "kk4"});
std::vector<std::string> values;
get_perf_context()->Reset();
values = MultiGet(keys, nullptr);
ASSERT_EQ(values[0], "v0");
ASSERT_EQ(values[1], "v1");
ASSERT_EQ(values[2], "v2");
ASSERT_EQ(values[3], "v3");
ASSERT_EQ(values[4], "v4");
// Filter hits for 4 in-domain keys
ASSERT_EQ(get_perf_context()->bloom_sst_hit_count, 4);
}
INSTANTIATE_TEST_CASE_P(MultiGetPrefix, MultiGetPrefixExtractorTest,
::testing::Bool());
#ifndef ROCKSDB_LITE
class DBMultiGetRowCacheTest : public DBBasicTest,
public ::testing::WithParamInterface<bool> {};
TEST_P(DBMultiGetRowCacheTest, MultiGetBatched) {
do {
option_config_ = kRowCache;
Options options = CurrentOptions();
options.statistics = rocksdb::CreateDBStatistics();
CreateAndReopenWithCF({"pikachu"}, options);
SetPerfLevel(kEnableCount);
ASSERT_OK(Put(1, "k1", "v1"));
ASSERT_OK(Put(1, "k2", "v2"));
ASSERT_OK(Put(1, "k3", "v3"));
ASSERT_OK(Put(1, "k4", "v4"));
Flush(1);
ASSERT_OK(Put(1, "k5", "v5"));
const Snapshot* snap1 = dbfull()->GetSnapshot();
ASSERT_OK(Delete(1, "k4"));
Flush(1);
const Snapshot* snap2 = dbfull()->GetSnapshot();
get_perf_context()->Reset();
std::vector<Slice> keys({"no_key", "k5", "k4", "k3", "k1"});
std::vector<PinnableSlice> values(keys.size());
std::vector<ColumnFamilyHandle*> cfs(keys.size(), handles_[1]);
std::vector<Status> s(keys.size());
ReadOptions ro;
bool use_snapshots = GetParam();
if (use_snapshots) {
ro.snapshot = snap2;
}
db_->MultiGet(ro, handles_[1], keys.size(), keys.data(), values.data(),
s.data(), false);
ASSERT_EQ(values.size(), keys.size());
ASSERT_EQ(std::string(values[4].data(), values[4].size()), "v1");
ASSERT_EQ(std::string(values[3].data(), values[3].size()), "v3");
ASSERT_EQ(std::string(values[1].data(), values[1].size()), "v5");
// four kv pairs * two bytes per value
ASSERT_EQ(6, (int)get_perf_context()->multiget_read_bytes);
ASSERT_TRUE(s[0].IsNotFound());
ASSERT_OK(s[1]);
ASSERT_TRUE(s[2].IsNotFound());
ASSERT_OK(s[3]);
ASSERT_OK(s[4]);
// Call MultiGet() again with some intersection with the previous set of
// keys. Those should already be in the row cache.
keys.assign({"no_key", "k5", "k3", "k2"});
for (size_t i = 0; i < keys.size(); ++i) {
values[i].Reset();
s[i] = Status::OK();
}
get_perf_context()->Reset();
if (use_snapshots) {
ro.snapshot = snap1;
}
db_->MultiGet(ReadOptions(), handles_[1], keys.size(), keys.data(),
values.data(), s.data(), false);
ASSERT_EQ(std::string(values[3].data(), values[3].size()), "v2");
ASSERT_EQ(std::string(values[2].data(), values[2].size()), "v3");
ASSERT_EQ(std::string(values[1].data(), values[1].size()), "v5");
// four kv pairs * two bytes per value
ASSERT_EQ(6, (int)get_perf_context()->multiget_read_bytes);
ASSERT_TRUE(s[0].IsNotFound());
ASSERT_OK(s[1]);
ASSERT_OK(s[2]);
ASSERT_OK(s[3]);
if (use_snapshots) {
// Only reads from the first SST file would have been cached, since
// snapshot seq no is > fd.largest_seqno
ASSERT_EQ(1, TestGetTickerCount(options, ROW_CACHE_HIT));
} else {
ASSERT_EQ(2, TestGetTickerCount(options, ROW_CACHE_HIT));
}
SetPerfLevel(kDisable);
dbfull()->ReleaseSnapshot(snap1);
dbfull()->ReleaseSnapshot(snap2);
} while (ChangeCompactOptions());
}
INSTANTIATE_TEST_CASE_P(DBMultiGetRowCacheTest, DBMultiGetRowCacheTest,
testing::Values(true, false));
TEST_F(DBBasicTest, GetAllKeyVersions) {
Options options = CurrentOptions();
options.env = env_;
options.create_if_missing = true;
options.disable_auto_compactions = true;
CreateAndReopenWithCF({"pikachu"}, options);
ASSERT_EQ(2, handles_.size());
const size_t kNumInserts = 4;
const size_t kNumDeletes = 4;
const size_t kNumUpdates = 4;
// Check default column family
for (size_t i = 0; i != kNumInserts; ++i) {
ASSERT_OK(Put(std::to_string(i), "value"));
}
for (size_t i = 0; i != kNumUpdates; ++i) {
ASSERT_OK(Put(std::to_string(i), "value1"));
}
for (size_t i = 0; i != kNumDeletes; ++i) {
ASSERT_OK(Delete(std::to_string(i)));
}
std::vector<KeyVersion> key_versions;
ASSERT_OK(rocksdb::GetAllKeyVersions(db_, Slice(), Slice(),
std::numeric_limits<size_t>::max(),
&key_versions));
ASSERT_EQ(kNumInserts + kNumDeletes + kNumUpdates, key_versions.size());
ASSERT_OK(rocksdb::GetAllKeyVersions(db_, handles_[0], Slice(), Slice(),
std::numeric_limits<size_t>::max(),
&key_versions));
ASSERT_EQ(kNumInserts + kNumDeletes + kNumUpdates, key_versions.size());
// Check non-default column family
for (size_t i = 0; i != kNumInserts - 1; ++i) {
ASSERT_OK(Put(1, std::to_string(i), "value"));
}
for (size_t i = 0; i != kNumUpdates - 1; ++i) {
ASSERT_OK(Put(1, std::to_string(i), "value1"));
}
for (size_t i = 0; i != kNumDeletes - 1; ++i) {
ASSERT_OK(Delete(1, std::to_string(i)));
}
ASSERT_OK(rocksdb::GetAllKeyVersions(db_, handles_[1], Slice(), Slice(),
std::numeric_limits<size_t>::max(),
&key_versions));
ASSERT_EQ(kNumInserts + kNumDeletes + kNumUpdates - 3, key_versions.size());
}
#endif // !ROCKSDB_LITE
class DBBasicTestWithParallelIO
: public DBTestBase,
public testing::WithParamInterface<std::tuple<bool, bool, bool, bool>> {
public:
DBBasicTestWithParallelIO() : DBTestBase("/db_basic_test_with_parallel_io") {
bool compressed_cache = std::get<0>(GetParam());
bool uncompressed_cache = std::get<1>(GetParam());
compression_enabled_ = std::get<2>(GetParam());
fill_cache_ = std::get<3>(GetParam());
if (compressed_cache) {
std::shared_ptr<Cache> cache = NewLRUCache(1048576);
compressed_cache_ = std::make_shared<MyBlockCache>(cache);
}
if (uncompressed_cache) {
std::shared_ptr<Cache> cache = NewLRUCache(1048576);
uncompressed_cache_ = std::make_shared<MyBlockCache>(cache);
}
env_->count_random_reads_ = true;
Options options = CurrentOptions();
Random rnd(301);
BlockBasedTableOptions table_options;
table_options.pin_l0_filter_and_index_blocks_in_cache = true;
table_options.block_cache = uncompressed_cache_;
table_options.block_cache_compressed = compressed_cache_;
table_options.flush_block_policy_factory.reset(
new MyFlushBlockPolicyFactory());
options.table_factory.reset(new BlockBasedTableFactory(table_options));
if (!compression_enabled_) {
options.compression = kNoCompression;
}
Reopen(options);
std::string zero_str(128, '\0');
for (int i = 0; i < 100; ++i) {
// Make the value compressible. A purely random string doesn't compress
// and the resultant data block will not be compressed
values_.emplace_back(RandomString(&rnd, 128) + zero_str);
assert(Put(Key(i), values_[i]) == Status::OK());
}
Flush();
}
bool CheckValue(int i, const std::string& value) {
if (values_[i].compare(value) == 0) {
return true;
}
return false;
}
int num_lookups() { return uncompressed_cache_->num_lookups(); }
int num_found() { return uncompressed_cache_->num_found(); }
int num_inserts() { return uncompressed_cache_->num_inserts(); }
int num_lookups_compressed() { return compressed_cache_->num_lookups(); }
int num_found_compressed() { return compressed_cache_->num_found(); }
int num_inserts_compressed() { return compressed_cache_->num_inserts(); }
bool fill_cache() { return fill_cache_; }
static void SetUpTestCase() {}
static void TearDownTestCase() {}
private:
class MyFlushBlockPolicyFactory : public FlushBlockPolicyFactory {
public:
MyFlushBlockPolicyFactory() {}
virtual const char* Name() const override {
return "MyFlushBlockPolicyFactory";
}
virtual FlushBlockPolicy* NewFlushBlockPolicy(
const BlockBasedTableOptions& /*table_options*/,
const BlockBuilder& data_block_builder) const override {
return new MyFlushBlockPolicy(data_block_builder);
}
};
class MyFlushBlockPolicy : public FlushBlockPolicy {
public:
explicit MyFlushBlockPolicy(const BlockBuilder& data_block_builder)
: num_keys_(0), data_block_builder_(data_block_builder) {}
bool Update(const Slice& /*key*/, const Slice& /*value*/) override {
if (data_block_builder_.empty()) {
// First key in this block
num_keys_ = 1;
return false;
}
// Flush every 10 keys
if (num_keys_ == 10) {
num_keys_ = 1;
return true;
}
num_keys_++;
return false;
}
private:
int num_keys_;
const BlockBuilder& data_block_builder_;
};
class MyBlockCache : public Cache {
public:
explicit MyBlockCache(std::shared_ptr<Cache>& target)
: target_(target), num_lookups_(0), num_found_(0), num_inserts_(0) {}
virtual const char* Name() const override { return "MyBlockCache"; }
virtual Status Insert(const Slice& key, void* value, size_t charge,
void (*deleter)(const Slice& key, void* value),
Handle** handle = nullptr,
Priority priority = Priority::LOW) override {
num_inserts_++;
return target_->Insert(key, value, charge, deleter, handle, priority);
}
virtual Handle* Lookup(const Slice& key,
Statistics* stats = nullptr) override {
num_lookups_++;
Handle* handle = target_->Lookup(key, stats);
if (handle != nullptr) {
num_found_++;
}
return handle;
}
virtual bool Ref(Handle* handle) override { return target_->Ref(handle); }
virtual bool Release(Handle* handle, bool force_erase = false) override {
return target_->Release(handle, force_erase);
}
virtual void* Value(Handle* handle) override {
return target_->Value(handle);
}
virtual void Erase(const Slice& key) override { target_->Erase(key); }
virtual uint64_t NewId() override { return target_->NewId(); }
virtual void SetCapacity(size_t capacity) override {
target_->SetCapacity(capacity);
}
virtual void SetStrictCapacityLimit(bool strict_capacity_limit) override {
target_->SetStrictCapacityLimit(strict_capacity_limit);
}
virtual bool HasStrictCapacityLimit() const override {
return target_->HasStrictCapacityLimit();
}
virtual size_t GetCapacity() const override {
return target_->GetCapacity();
}
virtual size_t GetUsage() const override { return target_->GetUsage(); }
virtual size_t GetUsage(Handle* handle) const override {
return target_->GetUsage(handle);
}
virtual size_t GetPinnedUsage() const override {
return target_->GetPinnedUsage();
}
virtual size_t GetCharge(Handle* /*handle*/) const override { return 0; }
virtual void ApplyToAllCacheEntries(void (*callback)(void*, size_t),
bool thread_safe) override {
return target_->ApplyToAllCacheEntries(callback, thread_safe);
}
virtual void EraseUnRefEntries() override {
return target_->EraseUnRefEntries();
}
int num_lookups() { return num_lookups_; }
int num_found() { return num_found_; }
int num_inserts() { return num_inserts_; }
private:
std::shared_ptr<Cache> target_;
int num_lookups_;
int num_found_;
int num_inserts_;
};
std::shared_ptr<MyBlockCache> compressed_cache_;
std::shared_ptr<MyBlockCache> uncompressed_cache_;
bool compression_enabled_;
std::vector<std::string> values_;
bool fill_cache_;
};
TEST_P(DBBasicTestWithParallelIO, MultiGet) {
std::vector<std::string> key_data(10);
std::vector<Slice> keys;
// We cannot resize a PinnableSlice vector, so just set initial size to
// largest we think we will need
std::vector<PinnableSlice> values(10);
std::vector<Status> statuses;
ReadOptions ro;
ro.fill_cache = fill_cache();
// Warm up the cache first
key_data.emplace_back(Key(0));
keys.emplace_back(Slice(key_data.back()));
key_data.emplace_back(Key(50));
keys.emplace_back(Slice(key_data.back()));
statuses.resize(keys.size());
dbfull()->MultiGet(ro, dbfull()->DefaultColumnFamily(), keys.size(),
keys.data(), values.data(), statuses.data(), true);
ASSERT_TRUE(CheckValue(0, values[0].ToString()));
ASSERT_TRUE(CheckValue(50, values[1].ToString()));
int random_reads = env_->random_read_counter_.Read();
key_data[0] = Key(1);
key_data[1] = Key(51);
keys[0] = Slice(key_data[0]);
keys[1] = Slice(key_data[1]);
values[0].Reset();
values[1].Reset();
dbfull()->MultiGet(ro, dbfull()->DefaultColumnFamily(), keys.size(),
keys.data(), values.data(), statuses.data(), true);
ASSERT_TRUE(CheckValue(1, values[0].ToString()));
ASSERT_TRUE(CheckValue(51, values[1].ToString()));
int expected_reads = random_reads + (fill_cache() ? 0 : 2);
ASSERT_EQ(env_->random_read_counter_.Read(), expected_reads);
keys.resize(10);
statuses.resize(10);
std::vector<int> key_ints{1, 2, 15, 16, 55, 81, 82, 83, 84, 85};
for (size_t i = 0; i < key_ints.size(); ++i) {
key_data[i] = Key(key_ints[i]);
keys[i] = Slice(key_data[i]);
statuses[i] = Status::OK();
values[i].Reset();
}
dbfull()->MultiGet(ro, dbfull()->DefaultColumnFamily(), keys.size(),
keys.data(), values.data(), statuses.data(), true);
for (size_t i = 0; i < key_ints.size(); ++i) {
ASSERT_OK(statuses[i]);
ASSERT_TRUE(CheckValue(key_ints[i], values[i].ToString()));
}
expected_reads += (fill_cache() ? 2 : 4);
ASSERT_EQ(env_->random_read_counter_.Read(), expected_reads);
}
INSTANTIATE_TEST_CASE_P(
ParallelIO, DBBasicTestWithParallelIO,
// Params are as follows -
// Param 0 - Compressed cache enabled
// Param 1 - Uncompressed cache enabled
// Param 2 - Data compression enabled
// Param 3 - ReadOptions::fill_cache
::testing::Values(std::make_tuple(false, true, true, true),
std::make_tuple(true, true, true, true),
std::make_tuple(false, true, false, true),
std::make_tuple(false, true, true, false),
std::make_tuple(true, true, true, false),
std::make_tuple(false, true, false, false)));
Add support for timestamp in Get/Put (#5079) Summary: It's useful to be able to (optionally) associate key-value pairs with user-provided timestamps. This PR is an early effort towards this goal and continues the work of facebook#4942. A suite of new unit tests exist in DBBasicTestWithTimestampWithParam. Support for timestamp requires the user to provide timestamp as a slice in `ReadOptions` and `WriteOptions`. All timestamps of the same database must share the same length, format, etc. The format of the timestamp is the same throughout the same database, and the user is responsible for providing a comparator function (Comparator) to order the <key, timestamp> tuples. Once created, the format and length of the timestamp cannot change (at least for now). Test plan (on devserver): ``` $COMPILE_WITH_ASAN=1 make -j32 all $./db_basic_test --gtest_filter=Timestamp/DBBasicTestWithTimestampWithParam.PutAndGet/* $make check ``` All tests must pass. We also run the following db_bench tests to verify whether there is regression on Get/Put while timestamp is not enabled. ``` $TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=fillseq,readrandom -num=1000000 $TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=fillrandom -num=1000000 ``` Repeat for 6 times for both versions. Results are as follows: ``` | | readrandom | fillrandom | | master | 16.77 MB/s | 47.05 MB/s | | PR5079 | 16.44 MB/s | 47.03 MB/s | ``` Pull Request resolved: https://github.com/facebook/rocksdb/pull/5079 Differential Revision: D15132946 Pulled By: riversand963 fbshipit-source-id: 833a0d657eac21182f0f206c910a6438154c742c
2019-06-06 08:07:28 +02:00
class DBBasicTestWithTimestampWithParam
: public DBTestBase,
public testing::WithParamInterface<bool> {
public:
DBBasicTestWithTimestampWithParam()
: DBTestBase("/db_basic_test_with_timestamp") {}
protected:
class TestComparator : public Comparator {
private:
const Comparator* cmp_without_ts_;
public:
explicit TestComparator(size_t ts_sz)
: Comparator(ts_sz), cmp_without_ts_(nullptr) {
cmp_without_ts_ = BytewiseComparator();
}
const char* Name() const override { return "TestComparator"; }
void FindShortSuccessor(std::string*) const override {}
void FindShortestSeparator(std::string*, const Slice&) const override {}
int Compare(const Slice& a, const Slice& b) const override {
int r = CompareWithoutTimestamp(a, b);
if (r != 0 || 0 == timestamp_size()) {
return r;
}
return CompareTimestamp(
Slice(a.data() + a.size() - timestamp_size(), timestamp_size()),
Slice(b.data() + b.size() - timestamp_size(), timestamp_size()));
}
int CompareWithoutTimestamp(const Slice& a, const Slice& b) const override {
assert(a.size() >= timestamp_size());
assert(b.size() >= timestamp_size());
Slice k1 = StripTimestampFromUserKey(a, timestamp_size());
Slice k2 = StripTimestampFromUserKey(b, timestamp_size());
return cmp_without_ts_->Compare(k1, k2);
}
int CompareTimestamp(const Slice& ts1, const Slice& ts2) const override {
if (!ts1.data() && !ts2.data()) {
return 0;
} else if (ts1.data() && !ts2.data()) {
return 1;
} else if (!ts1.data() && ts2.data()) {
return -1;
}
assert(ts1.size() == ts2.size());
uint64_t low1 = 0;
uint64_t low2 = 0;
uint64_t high1 = 0;
uint64_t high2 = 0;
auto* ptr1 = const_cast<Slice*>(&ts1);
auto* ptr2 = const_cast<Slice*>(&ts2);
if (!GetFixed64(ptr1, &low1) || !GetFixed64(ptr1, &high1) ||
!GetFixed64(ptr2, &low2) || !GetFixed64(ptr2, &high2)) {
assert(false);
}
if (high1 < high2) {
return 1;
} else if (high1 > high2) {
return -1;
}
if (low1 < low2) {
return 1;
} else if (low1 > low2) {
return -1;
}
return 0;
}
};
Slice EncodeTimestamp(uint64_t low, uint64_t high, std::string* ts) {
assert(nullptr != ts);
ts->clear();
PutFixed64(ts, low);
PutFixed64(ts, high);
assert(ts->size() == sizeof(low) + sizeof(high));
return Slice(*ts);
}
};
TEST_P(DBBasicTestWithTimestampWithParam, PutAndGet) {
const int kNumKeysPerFile = 8192;
const size_t kNumTimestamps = 6;
bool memtable_only = GetParam();
Options options = CurrentOptions();
options.create_if_missing = true;
options.env = env_;
options.memtable_factory.reset(new SpecialSkipListFactory(kNumKeysPerFile));
std::string tmp;
size_t ts_sz = EncodeTimestamp(0, 0, &tmp).size();
TestComparator test_cmp(ts_sz);
options.comparator = &test_cmp;
BlockBasedTableOptions bbto;
bbto.filter_policy.reset(NewBloomFilterPolicy(
10 /*bits_per_key*/, false /*use_block_based_builder*/));
bbto.whole_key_filtering = true;
options.table_factory.reset(NewBlockBasedTableFactory(bbto));
DestroyAndReopen(options);
CreateAndReopenWithCF({"pikachu"}, options);
size_t num_cfs = handles_.size();
ASSERT_EQ(2, num_cfs);
std::vector<std::string> write_ts_strs(kNumTimestamps);
std::vector<std::string> read_ts_strs(kNumTimestamps);
std::vector<Slice> write_ts_list;
std::vector<Slice> read_ts_list;
for (size_t i = 0; i != kNumTimestamps; ++i) {
write_ts_list.emplace_back(EncodeTimestamp(i * 2, 0, &write_ts_strs[i]));
read_ts_list.emplace_back(EncodeTimestamp(1 + i * 2, 0, &read_ts_strs[i]));
const Slice& write_ts = write_ts_list.back();
WriteOptions wopts;
wopts.timestamp = &write_ts;
for (int cf = 0; cf != static_cast<int>(num_cfs); ++cf) {
for (size_t j = 0; j != (kNumKeysPerFile - 1) / kNumTimestamps; ++j) {
ASSERT_OK(Put(cf, "key" + std::to_string(j),
"value_" + std::to_string(j) + "_" + std::to_string(i),
wopts));
}
if (!memtable_only) {
ASSERT_OK(Flush(cf));
}
}
}
const auto& verify_db_func = [&]() {
for (size_t i = 0; i != kNumTimestamps; ++i) {
ReadOptions ropts;
ropts.timestamp = &read_ts_list[i];
for (int cf = 0; cf != static_cast<int>(num_cfs); ++cf) {
ColumnFamilyHandle* cfh = handles_[cf];
for (size_t j = 0; j != (kNumKeysPerFile - 1) / kNumTimestamps; ++j) {
std::string value;
ASSERT_OK(db_->Get(ropts, cfh, "key" + std::to_string(j), &value));
ASSERT_EQ("value_" + std::to_string(j) + "_" + std::to_string(i),
value);
}
}
}
};
verify_db_func();
}
INSTANTIATE_TEST_CASE_P(Timestamp, DBBasicTestWithTimestampWithParam,
::testing::Bool());
} // namespace rocksdb
#ifdef ROCKSDB_UNITTESTS_WITH_CUSTOM_OBJECTS_FROM_STATIC_LIBS
extern "C" {
void RegisterCustomObjects(int argc, char** argv);
}
#else
void RegisterCustomObjects(int /*argc*/, char** /*argv*/) {}
#endif // !ROCKSDB_UNITTESTS_WITH_CUSTOM_OBJECTS_FROM_STATIC_LIBS
int main(int argc, char** argv) {
rocksdb::port::InstallStackTraceHandler();
::testing::InitGoogleTest(&argc, argv);
RegisterCustomObjects(argc, argv);
return RUN_ALL_TESTS();
}