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rocksdb/db/column_family.h

552 lines
22 KiB

// Copyright (c) 2011-present, Facebook, Inc. All rights reserved.
// This source code is licensed under the BSD-style license found in the
// LICENSE file in the root directory of this source tree. An additional grant
// of patent rights can be found in the PATENTS file in the same directory.
//
// Copyright (c) 2011 The LevelDB Authors. All rights reserved.
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file. See the AUTHORS file for names of contributors.
#pragma once
11 years ago
#include <unordered_map>
#include <string>
#include <vector>
#include <atomic>
#include "db/memtable_list.h"
#include "db/write_batch_internal.h"
#include "db/write_controller.h"
#include "db/table_cache.h"
#include "db/table_properties_collector.h"
#include "rocksdb/compaction_job_stats.h"
#include "rocksdb/db.h"
#include "rocksdb/env.h"
#include "rocksdb/options.h"
#include "util/mutable_cf_options.h"
#include "util/thread_local.h"
namespace rocksdb {
class Version;
class VersionSet;
class MemTable;
class MemTableListVersion;
class CompactionPicker;
class Compaction;
class InternalKey;
class InternalStats;
class ColumnFamilyData;
class DBImpl;
class LogBuffer;
class InstrumentedMutex;
class InstrumentedMutexLock;
extern const double kSlowdownRatio;
// ColumnFamilyHandleImpl is the class that clients use to access different
// column families. It has non-trivial destructor, which gets called when client
// is done using the column family
class ColumnFamilyHandleImpl : public ColumnFamilyHandle {
public:
// create while holding the mutex
ColumnFamilyHandleImpl(
ColumnFamilyData* cfd, DBImpl* db, InstrumentedMutex* mutex);
// destroy without mutex
virtual ~ColumnFamilyHandleImpl();
virtual ColumnFamilyData* cfd() const { return cfd_; }
virtual const Comparator* user_comparator() const;
virtual uint32_t GetID() const override;
virtual const std::string& GetName() const override;
virtual Status GetDescriptor(ColumnFamilyDescriptor* desc) override;
private:
ColumnFamilyData* cfd_;
DBImpl* db_;
InstrumentedMutex* mutex_;
};
// Does not ref-count ColumnFamilyData
// We use this dummy ColumnFamilyHandleImpl because sometimes MemTableInserter
// calls DBImpl methods. When this happens, MemTableInserter need access to
// ColumnFamilyHandle (same as the client would need). In that case, we feed
// MemTableInserter dummy ColumnFamilyHandle and enable it to call DBImpl
// methods
class ColumnFamilyHandleInternal : public ColumnFamilyHandleImpl {
public:
ColumnFamilyHandleInternal()
: ColumnFamilyHandleImpl(nullptr, nullptr, nullptr) {}
void SetCFD(ColumnFamilyData* _cfd) { internal_cfd_ = _cfd; }
virtual ColumnFamilyData* cfd() const override { return internal_cfd_; }
private:
ColumnFamilyData* internal_cfd_;
};
// holds references to memtable, all immutable memtables and version
struct SuperVersion {
// Accessing members of this class is not thread-safe and requires external
// synchronization (ie db mutex held or on write thread).
MemTable* mem;
MemTableListVersion* imm;
Version* current;
MutableCFOptions mutable_cf_options;
// Version number of the current SuperVersion
uint64_t version_number;
InstrumentedMutex* db_mutex;
// should be called outside the mutex
SuperVersion() = default;
~SuperVersion();
SuperVersion* Ref();
// If Unref() returns true, Cleanup() should be called with mutex held
// before deleting this SuperVersion.
bool Unref();
// call these two methods with db mutex held
// Cleanup unrefs mem, imm and current. Also, it stores all memtables
// that needs to be deleted in to_delete vector. Unrefing those
// objects needs to be done in the mutex
void Cleanup();
void Init(MemTable* new_mem, MemTableListVersion* new_imm,
Version* new_current);
// The value of dummy is not actually used. kSVInUse takes its address as a
// mark in the thread local storage to indicate the SuperVersion is in use
// by thread. This way, the value of kSVInUse is guaranteed to have no
// conflict with SuperVersion object address and portable on different
// platform.
static int dummy;
static void* const kSVInUse;
static void* const kSVObsolete;
private:
std::atomic<uint32_t> refs;
// We need to_delete because during Cleanup(), imm->Unref() returns
// all memtables that we need to free through this vector. We then
// delete all those memtables outside of mutex, during destruction
autovector<MemTable*> to_delete;
};
extern Status CheckCompressionSupported(const ColumnFamilyOptions& cf_options);
support for concurrent adds to memtable Summary: This diff adds support for concurrent adds to the skiplist memtable implementations. Memory allocation is made thread-safe by the addition of a spinlock, with small per-core buffers to avoid contention. Concurrent memtable writes are made via an additional method and don't impose a performance overhead on the non-concurrent case, so parallelism can be selected on a per-batch basis. Write thread synchronization is an increasing bottleneck for higher levels of concurrency, so this diff adds --enable_write_thread_adaptive_yield (default off). This feature causes threads joining a write batch group to spin for a short time (default 100 usec) using sched_yield, rather than going to sleep on a mutex. If the timing of the yield calls indicates that another thread has actually run during the yield then spinning is avoided. This option improves performance for concurrent situations even without parallel adds, although it has the potential to increase CPU usage (and the heuristic adaptation is not yet mature). Parallel writes are not currently compatible with inplace updates, update callbacks, or delete filtering. Enable it with --allow_concurrent_memtable_write (and --enable_write_thread_adaptive_yield). Parallel memtable writes are performance neutral when there is no actual parallelism, and in my experiments (SSD server-class Linux and varying contention and key sizes for fillrandom) they are always a performance win when there is more than one thread. Statistics are updated earlier in the write path, dropping the number of DB mutex acquisitions from 2 to 1 for almost all cases. This diff was motivated and inspired by Yahoo's cLSM work. It is more conservative than cLSM: RocksDB's write batch group leader role is preserved (along with all of the existing flush and write throttling logic) and concurrent writers are blocked until all memtable insertions have completed and the sequence number has been advanced, to preserve linearizability. My test config is "db_bench -benchmarks=fillrandom -threads=$T -batch_size=1 -memtablerep=skip_list -value_size=100 --num=1000000/$T -level0_slowdown_writes_trigger=9999 -level0_stop_writes_trigger=9999 -disable_auto_compactions --max_write_buffer_number=8 -max_background_flushes=8 --disable_wal --write_buffer_size=160000000 --block_size=16384 --allow_concurrent_memtable_write" on a two-socket Xeon E5-2660 @ 2.2Ghz with lots of memory and an SSD hard drive. With 1 thread I get ~440Kops/sec. Peak performance for 1 socket (numactl -N1) is slightly more than 1Mops/sec, at 16 threads. Peak performance across both sockets happens at 30 threads, and is ~900Kops/sec, although with fewer threads there is less performance loss when the system has background work. Test Plan: 1. concurrent stress tests for InlineSkipList and DynamicBloom 2. make clean; make check 3. make clean; DISABLE_JEMALLOC=1 make valgrind_check; valgrind db_bench 4. make clean; COMPILE_WITH_TSAN=1 make all check; db_bench 5. make clean; COMPILE_WITH_ASAN=1 make all check; db_bench 6. make clean; OPT=-DROCKSDB_LITE make check 7. verify no perf regressions when disabled Reviewers: igor, sdong Reviewed By: sdong Subscribers: MarkCallaghan, IslamAbdelRahman, anthony, yhchiang, rven, sdong, guyg8, kradhakrishnan, dhruba Differential Revision: https://reviews.facebook.net/D50589
9 years ago
extern Status CheckConcurrentWritesSupported(
const ColumnFamilyOptions& cf_options);
extern ColumnFamilyOptions SanitizeOptions(const DBOptions& db_options,
const InternalKeyComparator* icmp,
const ColumnFamilyOptions& src);
// Wrap user defined table proproties collector factories `from cf_options`
// into internal ones in int_tbl_prop_collector_factories. Add a system internal
// one too.
extern void GetIntTblPropCollectorFactory(
const ColumnFamilyOptions& cf_options,
std::vector<std::unique_ptr<IntTblPropCollectorFactory>>*
int_tbl_prop_collector_factories);
class ColumnFamilySet;
// This class keeps all the data that a column family needs.
// Most methods require DB mutex held, unless otherwise noted
class ColumnFamilyData {
public:
~ColumnFamilyData();
// thread-safe
uint32_t GetID() const { return id_; }
// thread-safe
const std::string& GetName() const { return name_; }
support for concurrent adds to memtable Summary: This diff adds support for concurrent adds to the skiplist memtable implementations. Memory allocation is made thread-safe by the addition of a spinlock, with small per-core buffers to avoid contention. Concurrent memtable writes are made via an additional method and don't impose a performance overhead on the non-concurrent case, so parallelism can be selected on a per-batch basis. Write thread synchronization is an increasing bottleneck for higher levels of concurrency, so this diff adds --enable_write_thread_adaptive_yield (default off). This feature causes threads joining a write batch group to spin for a short time (default 100 usec) using sched_yield, rather than going to sleep on a mutex. If the timing of the yield calls indicates that another thread has actually run during the yield then spinning is avoided. This option improves performance for concurrent situations even without parallel adds, although it has the potential to increase CPU usage (and the heuristic adaptation is not yet mature). Parallel writes are not currently compatible with inplace updates, update callbacks, or delete filtering. Enable it with --allow_concurrent_memtable_write (and --enable_write_thread_adaptive_yield). Parallel memtable writes are performance neutral when there is no actual parallelism, and in my experiments (SSD server-class Linux and varying contention and key sizes for fillrandom) they are always a performance win when there is more than one thread. Statistics are updated earlier in the write path, dropping the number of DB mutex acquisitions from 2 to 1 for almost all cases. This diff was motivated and inspired by Yahoo's cLSM work. It is more conservative than cLSM: RocksDB's write batch group leader role is preserved (along with all of the existing flush and write throttling logic) and concurrent writers are blocked until all memtable insertions have completed and the sequence number has been advanced, to preserve linearizability. My test config is "db_bench -benchmarks=fillrandom -threads=$T -batch_size=1 -memtablerep=skip_list -value_size=100 --num=1000000/$T -level0_slowdown_writes_trigger=9999 -level0_stop_writes_trigger=9999 -disable_auto_compactions --max_write_buffer_number=8 -max_background_flushes=8 --disable_wal --write_buffer_size=160000000 --block_size=16384 --allow_concurrent_memtable_write" on a two-socket Xeon E5-2660 @ 2.2Ghz with lots of memory and an SSD hard drive. With 1 thread I get ~440Kops/sec. Peak performance for 1 socket (numactl -N1) is slightly more than 1Mops/sec, at 16 threads. Peak performance across both sockets happens at 30 threads, and is ~900Kops/sec, although with fewer threads there is less performance loss when the system has background work. Test Plan: 1. concurrent stress tests for InlineSkipList and DynamicBloom 2. make clean; make check 3. make clean; DISABLE_JEMALLOC=1 make valgrind_check; valgrind db_bench 4. make clean; COMPILE_WITH_TSAN=1 make all check; db_bench 5. make clean; COMPILE_WITH_ASAN=1 make all check; db_bench 6. make clean; OPT=-DROCKSDB_LITE make check 7. verify no perf regressions when disabled Reviewers: igor, sdong Reviewed By: sdong Subscribers: MarkCallaghan, IslamAbdelRahman, anthony, yhchiang, rven, sdong, guyg8, kradhakrishnan, dhruba Differential Revision: https://reviews.facebook.net/D50589
9 years ago
// Ref() can only be called from a context where the caller can guarantee
// that ColumnFamilyData is alive (while holding a non-zero ref already,
// holding a DB mutex, or as the leader in a write batch group).
void Ref() { refs_.fetch_add(1, std::memory_order_relaxed); }
support for concurrent adds to memtable Summary: This diff adds support for concurrent adds to the skiplist memtable implementations. Memory allocation is made thread-safe by the addition of a spinlock, with small per-core buffers to avoid contention. Concurrent memtable writes are made via an additional method and don't impose a performance overhead on the non-concurrent case, so parallelism can be selected on a per-batch basis. Write thread synchronization is an increasing bottleneck for higher levels of concurrency, so this diff adds --enable_write_thread_adaptive_yield (default off). This feature causes threads joining a write batch group to spin for a short time (default 100 usec) using sched_yield, rather than going to sleep on a mutex. If the timing of the yield calls indicates that another thread has actually run during the yield then spinning is avoided. This option improves performance for concurrent situations even without parallel adds, although it has the potential to increase CPU usage (and the heuristic adaptation is not yet mature). Parallel writes are not currently compatible with inplace updates, update callbacks, or delete filtering. Enable it with --allow_concurrent_memtable_write (and --enable_write_thread_adaptive_yield). Parallel memtable writes are performance neutral when there is no actual parallelism, and in my experiments (SSD server-class Linux and varying contention and key sizes for fillrandom) they are always a performance win when there is more than one thread. Statistics are updated earlier in the write path, dropping the number of DB mutex acquisitions from 2 to 1 for almost all cases. This diff was motivated and inspired by Yahoo's cLSM work. It is more conservative than cLSM: RocksDB's write batch group leader role is preserved (along with all of the existing flush and write throttling logic) and concurrent writers are blocked until all memtable insertions have completed and the sequence number has been advanced, to preserve linearizability. My test config is "db_bench -benchmarks=fillrandom -threads=$T -batch_size=1 -memtablerep=skip_list -value_size=100 --num=1000000/$T -level0_slowdown_writes_trigger=9999 -level0_stop_writes_trigger=9999 -disable_auto_compactions --max_write_buffer_number=8 -max_background_flushes=8 --disable_wal --write_buffer_size=160000000 --block_size=16384 --allow_concurrent_memtable_write" on a two-socket Xeon E5-2660 @ 2.2Ghz with lots of memory and an SSD hard drive. With 1 thread I get ~440Kops/sec. Peak performance for 1 socket (numactl -N1) is slightly more than 1Mops/sec, at 16 threads. Peak performance across both sockets happens at 30 threads, and is ~900Kops/sec, although with fewer threads there is less performance loss when the system has background work. Test Plan: 1. concurrent stress tests for InlineSkipList and DynamicBloom 2. make clean; make check 3. make clean; DISABLE_JEMALLOC=1 make valgrind_check; valgrind db_bench 4. make clean; COMPILE_WITH_TSAN=1 make all check; db_bench 5. make clean; COMPILE_WITH_ASAN=1 make all check; db_bench 6. make clean; OPT=-DROCKSDB_LITE make check 7. verify no perf regressions when disabled Reviewers: igor, sdong Reviewed By: sdong Subscribers: MarkCallaghan, IslamAbdelRahman, anthony, yhchiang, rven, sdong, guyg8, kradhakrishnan, dhruba Differential Revision: https://reviews.facebook.net/D50589
9 years ago
// Unref decreases the reference count, but does not handle deletion
// when the count goes to 0. If this method returns true then the
// caller should delete the instance immediately, or later, by calling
// FreeDeadColumnFamilies(). Unref() can only be called while holding
// a DB mutex, or during single-threaded recovery.
bool Unref() {
int old_refs = refs_.fetch_sub(1, std::memory_order_relaxed);
assert(old_refs > 0);
return old_refs == 1;
}
// SetDropped() can only be called under following conditions:
// 1) Holding a DB mutex,
// 2) from single-threaded write thread, AND
// 3) from single-threaded VersionSet::LogAndApply()
// After dropping column family no other operation on that column family
// will be executed. All the files and memory will be, however, kept around
// until client drops the column family handle. That way, client can still
// access data from dropped column family.
// Column family can be dropped and still alive. In that state:
// *) Compaction and flush is not executed on the dropped column family.
// *) Client can continue reading from column family. Writes will fail unless
// WriteOptions::ignore_missing_column_families is true
// When the dropped column family is unreferenced, then we:
// *) Remove column family from the linked list maintained by ColumnFamilySet
// *) delete all memory associated with that column family
// *) delete all the files associated with that column family
void SetDropped();
bool IsDropped() const { return dropped_; }
// thread-safe
int NumberLevels() const { return ioptions_.num_levels; }
void SetLogNumber(uint64_t log_number) { log_number_ = log_number; }
uint64_t GetLogNumber() const { return log_number_; }
// !!! To be deprecated! Please don't not use this function anymore!
const Options* options() const { return &options_; }
// thread-safe
const EnvOptions* soptions() const;
const ImmutableCFOptions* ioptions() const { return &ioptions_; }
// REQUIRES: DB mutex held
// This returns the MutableCFOptions used by current SuperVersion
// You should use this API to reference MutableCFOptions most of the time.
const MutableCFOptions* GetCurrentMutableCFOptions() const {
return &(super_version_->mutable_cf_options);
}
// REQUIRES: DB mutex held
// This returns the latest MutableCFOptions, which may be not in effect yet.
const MutableCFOptions* GetLatestMutableCFOptions() const {
return &mutable_cf_options_;
}
#ifndef ROCKSDB_LITE
// REQUIRES: DB mutex held
Status SetOptions(
const std::unordered_map<std::string, std::string>& options_map);
#endif // ROCKSDB_LITE
InternalStats* internal_stats() { return internal_stats_.get(); }
MemTableList* imm() { return &imm_; }
MemTable* mem() { return mem_; }
Version* current() { return current_; }
Version* dummy_versions() { return dummy_versions_; }
void SetCurrent(Version* _current);
uint64_t GetNumLiveVersions() const; // REQUIRE: DB mutex held
uint64_t GetTotalSstFilesSize() const; // REQUIRE: DB mutex held
void SetMemtable(MemTable* new_mem) { mem_ = new_mem; }
// See Memtable constructor for explanation of earliest_seq param.
MemTable* ConstructNewMemtable(const MutableCFOptions& mutable_cf_options,
SequenceNumber earliest_seq);
void CreateNewMemtable(const MutableCFOptions& mutable_cf_options,
SequenceNumber earliest_seq);
TableCache* table_cache() const { return table_cache_.get(); }
// See documentation in compaction_picker.h
// REQUIRES: DB mutex held
Rewritten system for scheduling background work Summary: When scaling to higher number of column families, the worst bottleneck was MaybeScheduleFlushOrCompaction(), which did a for loop over all column families while holding a mutex. This patch addresses the issue. The approach is similar to our earlier efforts: instead of a pull-model, where we do something for every column family, we can do a push-based model -- when we detect that column family is ready to be flushed/compacted, we add it to the flush_queue_/compaction_queue_. That way we don't need to loop over every column family in MaybeScheduleFlushOrCompaction. Here are the performance results: Command: ./db_bench --write_buffer_size=268435456 --db_write_buffer_size=268435456 --db=/fast-rocksdb-tmp/rocks_lots_of_cf --use_existing_db=0 --open_files=55000 --statistics=1 --histogram=1 --disable_data_sync=1 --max_write_buffer_number=2 --sync=0 --benchmarks=fillrandom --threads=16 --num_column_families=5000 --disable_wal=1 --max_background_flushes=16 --max_background_compactions=16 --level0_file_num_compaction_trigger=2 --level0_slowdown_writes_trigger=2 --level0_stop_writes_trigger=3 --hard_rate_limit=1 --num=33333333 --writes=33333333 Before the patch: fillrandom : 26.950 micros/op 37105 ops/sec; 4.1 MB/s After the patch: fillrandom : 17.404 micros/op 57456 ops/sec; 6.4 MB/s Next bottleneck is VersionSet::AddLiveFiles, which is painfully slow when we have a lot of files. This is coming in the next patch, but when I removed that code, here's what I got: fillrandom : 7.590 micros/op 131758 ops/sec; 14.6 MB/s Test Plan: make check two stress tests: Big number of compactions and flushes: ./db_stress --threads=30 --ops_per_thread=20000000 --max_key=10000 --column_families=20 --clear_column_family_one_in=10000000 --verify_before_write=0 --reopen=15 --max_background_compactions=10 --max_background_flushes=10 --db=/fast-rocksdb-tmp/db_stress --prefixpercent=0 --iterpercent=0 --writepercent=75 --db_write_buffer_size=2000000 max_background_flushes=0, to verify that this case also works correctly ./db_stress --threads=30 --ops_per_thread=2000000 --max_key=10000 --column_families=20 --clear_column_family_one_in=10000000 --verify_before_write=0 --reopen=3 --max_background_compactions=3 --max_background_flushes=0 --db=/fast-rocksdb-tmp/db_stress --prefixpercent=0 --iterpercent=0 --writepercent=75 --db_write_buffer_size=2000000 Reviewers: ljin, rven, yhchiang, sdong Reviewed By: sdong Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D30123
10 years ago
bool NeedsCompaction() const;
// REQUIRES: DB mutex held
Compaction* PickCompaction(const MutableCFOptions& mutable_options,
LogBuffer* log_buffer);
// A flag to tell a manual compaction is to compact all levels together
// instad of for specific level.
static const int kCompactAllLevels;
// A flag to tell a manual compaction's output is base level.
static const int kCompactToBaseLevel;
Rewritten system for scheduling background work Summary: When scaling to higher number of column families, the worst bottleneck was MaybeScheduleFlushOrCompaction(), which did a for loop over all column families while holding a mutex. This patch addresses the issue. The approach is similar to our earlier efforts: instead of a pull-model, where we do something for every column family, we can do a push-based model -- when we detect that column family is ready to be flushed/compacted, we add it to the flush_queue_/compaction_queue_. That way we don't need to loop over every column family in MaybeScheduleFlushOrCompaction. Here are the performance results: Command: ./db_bench --write_buffer_size=268435456 --db_write_buffer_size=268435456 --db=/fast-rocksdb-tmp/rocks_lots_of_cf --use_existing_db=0 --open_files=55000 --statistics=1 --histogram=1 --disable_data_sync=1 --max_write_buffer_number=2 --sync=0 --benchmarks=fillrandom --threads=16 --num_column_families=5000 --disable_wal=1 --max_background_flushes=16 --max_background_compactions=16 --level0_file_num_compaction_trigger=2 --level0_slowdown_writes_trigger=2 --level0_stop_writes_trigger=3 --hard_rate_limit=1 --num=33333333 --writes=33333333 Before the patch: fillrandom : 26.950 micros/op 37105 ops/sec; 4.1 MB/s After the patch: fillrandom : 17.404 micros/op 57456 ops/sec; 6.4 MB/s Next bottleneck is VersionSet::AddLiveFiles, which is painfully slow when we have a lot of files. This is coming in the next patch, but when I removed that code, here's what I got: fillrandom : 7.590 micros/op 131758 ops/sec; 14.6 MB/s Test Plan: make check two stress tests: Big number of compactions and flushes: ./db_stress --threads=30 --ops_per_thread=20000000 --max_key=10000 --column_families=20 --clear_column_family_one_in=10000000 --verify_before_write=0 --reopen=15 --max_background_compactions=10 --max_background_flushes=10 --db=/fast-rocksdb-tmp/db_stress --prefixpercent=0 --iterpercent=0 --writepercent=75 --db_write_buffer_size=2000000 max_background_flushes=0, to verify that this case also works correctly ./db_stress --threads=30 --ops_per_thread=2000000 --max_key=10000 --column_families=20 --clear_column_family_one_in=10000000 --verify_before_write=0 --reopen=3 --max_background_compactions=3 --max_background_flushes=0 --db=/fast-rocksdb-tmp/db_stress --prefixpercent=0 --iterpercent=0 --writepercent=75 --db_write_buffer_size=2000000 Reviewers: ljin, rven, yhchiang, sdong Reviewed By: sdong Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D30123
10 years ago
// REQUIRES: DB mutex held
Compaction* CompactRange(const MutableCFOptions& mutable_cf_options,
int input_level, int output_level,
uint32_t output_path_id, const InternalKey* begin,
const InternalKey* end, InternalKey** compaction_end,
bool* manual_conflict);
CompactionPicker* compaction_picker() { return compaction_picker_.get(); }
// thread-safe
const Comparator* user_comparator() const {
return internal_comparator_.user_comparator();
}
// thread-safe
const InternalKeyComparator& internal_comparator() const {
return internal_comparator_;
}
const std::vector<std::unique_ptr<IntTblPropCollectorFactory>>*
int_tbl_prop_collector_factories() const {
return &int_tbl_prop_collector_factories_;
}
SuperVersion* GetSuperVersion() { return super_version_; }
// thread-safe
// Return a already referenced SuperVersion to be used safely.
SuperVersion* GetReferencedSuperVersion(InstrumentedMutex* db_mutex);
// thread-safe
// Get SuperVersion stored in thread local storage. If it does not exist,
// get a reference from a current SuperVersion.
SuperVersion* GetThreadLocalSuperVersion(InstrumentedMutex* db_mutex);
// Try to return SuperVersion back to thread local storage. Retrun true on
// success and false on failure. It fails when the thread local storage
// contains anything other than SuperVersion::kSVInUse flag.
bool ReturnThreadLocalSuperVersion(SuperVersion* sv);
// thread-safe
uint64_t GetSuperVersionNumber() const {
return super_version_number_.load();
}
// will return a pointer to SuperVersion* if previous SuperVersion
// if its reference count is zero and needs deletion or nullptr if not
// As argument takes a pointer to allocated SuperVersion to enable
// the clients to allocate SuperVersion outside of mutex.
Rewritten system for scheduling background work Summary: When scaling to higher number of column families, the worst bottleneck was MaybeScheduleFlushOrCompaction(), which did a for loop over all column families while holding a mutex. This patch addresses the issue. The approach is similar to our earlier efforts: instead of a pull-model, where we do something for every column family, we can do a push-based model -- when we detect that column family is ready to be flushed/compacted, we add it to the flush_queue_/compaction_queue_. That way we don't need to loop over every column family in MaybeScheduleFlushOrCompaction. Here are the performance results: Command: ./db_bench --write_buffer_size=268435456 --db_write_buffer_size=268435456 --db=/fast-rocksdb-tmp/rocks_lots_of_cf --use_existing_db=0 --open_files=55000 --statistics=1 --histogram=1 --disable_data_sync=1 --max_write_buffer_number=2 --sync=0 --benchmarks=fillrandom --threads=16 --num_column_families=5000 --disable_wal=1 --max_background_flushes=16 --max_background_compactions=16 --level0_file_num_compaction_trigger=2 --level0_slowdown_writes_trigger=2 --level0_stop_writes_trigger=3 --hard_rate_limit=1 --num=33333333 --writes=33333333 Before the patch: fillrandom : 26.950 micros/op 37105 ops/sec; 4.1 MB/s After the patch: fillrandom : 17.404 micros/op 57456 ops/sec; 6.4 MB/s Next bottleneck is VersionSet::AddLiveFiles, which is painfully slow when we have a lot of files. This is coming in the next patch, but when I removed that code, here's what I got: fillrandom : 7.590 micros/op 131758 ops/sec; 14.6 MB/s Test Plan: make check two stress tests: Big number of compactions and flushes: ./db_stress --threads=30 --ops_per_thread=20000000 --max_key=10000 --column_families=20 --clear_column_family_one_in=10000000 --verify_before_write=0 --reopen=15 --max_background_compactions=10 --max_background_flushes=10 --db=/fast-rocksdb-tmp/db_stress --prefixpercent=0 --iterpercent=0 --writepercent=75 --db_write_buffer_size=2000000 max_background_flushes=0, to verify that this case also works correctly ./db_stress --threads=30 --ops_per_thread=2000000 --max_key=10000 --column_families=20 --clear_column_family_one_in=10000000 --verify_before_write=0 --reopen=3 --max_background_compactions=3 --max_background_flushes=0 --db=/fast-rocksdb-tmp/db_stress --prefixpercent=0 --iterpercent=0 --writepercent=75 --db_write_buffer_size=2000000 Reviewers: ljin, rven, yhchiang, sdong Reviewed By: sdong Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D30123
10 years ago
// IMPORTANT: Only call this from DBImpl::InstallSuperVersion()
SuperVersion* InstallSuperVersion(SuperVersion* new_superversion,
InstrumentedMutex* db_mutex,
const MutableCFOptions& mutable_cf_options);
SuperVersion* InstallSuperVersion(SuperVersion* new_superversion,
InstrumentedMutex* db_mutex);
void ResetThreadLocalSuperVersions();
Rewritten system for scheduling background work Summary: When scaling to higher number of column families, the worst bottleneck was MaybeScheduleFlushOrCompaction(), which did a for loop over all column families while holding a mutex. This patch addresses the issue. The approach is similar to our earlier efforts: instead of a pull-model, where we do something for every column family, we can do a push-based model -- when we detect that column family is ready to be flushed/compacted, we add it to the flush_queue_/compaction_queue_. That way we don't need to loop over every column family in MaybeScheduleFlushOrCompaction. Here are the performance results: Command: ./db_bench --write_buffer_size=268435456 --db_write_buffer_size=268435456 --db=/fast-rocksdb-tmp/rocks_lots_of_cf --use_existing_db=0 --open_files=55000 --statistics=1 --histogram=1 --disable_data_sync=1 --max_write_buffer_number=2 --sync=0 --benchmarks=fillrandom --threads=16 --num_column_families=5000 --disable_wal=1 --max_background_flushes=16 --max_background_compactions=16 --level0_file_num_compaction_trigger=2 --level0_slowdown_writes_trigger=2 --level0_stop_writes_trigger=3 --hard_rate_limit=1 --num=33333333 --writes=33333333 Before the patch: fillrandom : 26.950 micros/op 37105 ops/sec; 4.1 MB/s After the patch: fillrandom : 17.404 micros/op 57456 ops/sec; 6.4 MB/s Next bottleneck is VersionSet::AddLiveFiles, which is painfully slow when we have a lot of files. This is coming in the next patch, but when I removed that code, here's what I got: fillrandom : 7.590 micros/op 131758 ops/sec; 14.6 MB/s Test Plan: make check two stress tests: Big number of compactions and flushes: ./db_stress --threads=30 --ops_per_thread=20000000 --max_key=10000 --column_families=20 --clear_column_family_one_in=10000000 --verify_before_write=0 --reopen=15 --max_background_compactions=10 --max_background_flushes=10 --db=/fast-rocksdb-tmp/db_stress --prefixpercent=0 --iterpercent=0 --writepercent=75 --db_write_buffer_size=2000000 max_background_flushes=0, to verify that this case also works correctly ./db_stress --threads=30 --ops_per_thread=2000000 --max_key=10000 --column_families=20 --clear_column_family_one_in=10000000 --verify_before_write=0 --reopen=3 --max_background_compactions=3 --max_background_flushes=0 --db=/fast-rocksdb-tmp/db_stress --prefixpercent=0 --iterpercent=0 --writepercent=75 --db_write_buffer_size=2000000 Reviewers: ljin, rven, yhchiang, sdong Reviewed By: sdong Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D30123
10 years ago
// Protected by DB mutex
void set_pending_flush(bool value) { pending_flush_ = value; }
void set_pending_compaction(bool value) { pending_compaction_ = value; }
bool pending_flush() { return pending_flush_; }
bool pending_compaction() { return pending_compaction_; }
// Recalculate some small conditions, which are changed only during
// compaction, adding new memtable and/or
// recalculation of compaction score. These values are used in
// DBImpl::MakeRoomForWrite function to decide, if it need to make
// a write stall
void RecalculateWriteStallConditions(
const MutableCFOptions& mutable_cf_options);
private:
friend class ColumnFamilySet;
ColumnFamilyData(uint32_t id, const std::string& name,
Version* dummy_versions, Cache* table_cache,
WriteBufferManager* write_buffer_manager,
const ColumnFamilyOptions& options,
const DBOptions* db_options, const EnvOptions& env_options,
ColumnFamilySet* column_family_set);
uint32_t id_;
const std::string name_;
Version* dummy_versions_; // Head of circular doubly-linked list of versions.
Version* current_; // == dummy_versions->prev_
std::atomic<int> refs_; // outstanding references to ColumnFamilyData
bool dropped_; // true if client dropped it
const InternalKeyComparator internal_comparator_;
std::vector<std::unique_ptr<IntTblPropCollectorFactory>>
int_tbl_prop_collector_factories_;
const Options options_;
const ImmutableCFOptions ioptions_;
MutableCFOptions mutable_cf_options_;
std::unique_ptr<TableCache> table_cache_;
std::unique_ptr<InternalStats> internal_stats_;
WriteBufferManager* write_buffer_manager_;
MemTable* mem_;
MemTableList imm_;
SuperVersion* super_version_;
// An ordinal representing the current SuperVersion. Updated by
// InstallSuperVersion(), i.e. incremented every time super_version_
// changes.
std::atomic<uint64_t> super_version_number_;
// Thread's local copy of SuperVersion pointer
// This needs to be destructed before mutex_
std::unique_ptr<ThreadLocalPtr> local_sv_;
// pointers for a circular linked list. we use it to support iterations over
// all column families that are alive (note: dropped column families can also
// be alive as long as client holds a reference)
ColumnFamilyData* next_;
ColumnFamilyData* prev_;
// This is the earliest log file number that contains data from this
// Column Family. All earlier log files must be ignored and not
// recovered from
uint64_t log_number_;
// An object that keeps all the compaction stats
// and picks the next compaction
std::unique_ptr<CompactionPicker> compaction_picker_;
ColumnFamilySet* column_family_set_;
std::unique_ptr<WriteControllerToken> write_controller_token_;
Rewritten system for scheduling background work Summary: When scaling to higher number of column families, the worst bottleneck was MaybeScheduleFlushOrCompaction(), which did a for loop over all column families while holding a mutex. This patch addresses the issue. The approach is similar to our earlier efforts: instead of a pull-model, where we do something for every column family, we can do a push-based model -- when we detect that column family is ready to be flushed/compacted, we add it to the flush_queue_/compaction_queue_. That way we don't need to loop over every column family in MaybeScheduleFlushOrCompaction. Here are the performance results: Command: ./db_bench --write_buffer_size=268435456 --db_write_buffer_size=268435456 --db=/fast-rocksdb-tmp/rocks_lots_of_cf --use_existing_db=0 --open_files=55000 --statistics=1 --histogram=1 --disable_data_sync=1 --max_write_buffer_number=2 --sync=0 --benchmarks=fillrandom --threads=16 --num_column_families=5000 --disable_wal=1 --max_background_flushes=16 --max_background_compactions=16 --level0_file_num_compaction_trigger=2 --level0_slowdown_writes_trigger=2 --level0_stop_writes_trigger=3 --hard_rate_limit=1 --num=33333333 --writes=33333333 Before the patch: fillrandom : 26.950 micros/op 37105 ops/sec; 4.1 MB/s After the patch: fillrandom : 17.404 micros/op 57456 ops/sec; 6.4 MB/s Next bottleneck is VersionSet::AddLiveFiles, which is painfully slow when we have a lot of files. This is coming in the next patch, but when I removed that code, here's what I got: fillrandom : 7.590 micros/op 131758 ops/sec; 14.6 MB/s Test Plan: make check two stress tests: Big number of compactions and flushes: ./db_stress --threads=30 --ops_per_thread=20000000 --max_key=10000 --column_families=20 --clear_column_family_one_in=10000000 --verify_before_write=0 --reopen=15 --max_background_compactions=10 --max_background_flushes=10 --db=/fast-rocksdb-tmp/db_stress --prefixpercent=0 --iterpercent=0 --writepercent=75 --db_write_buffer_size=2000000 max_background_flushes=0, to verify that this case also works correctly ./db_stress --threads=30 --ops_per_thread=2000000 --max_key=10000 --column_families=20 --clear_column_family_one_in=10000000 --verify_before_write=0 --reopen=3 --max_background_compactions=3 --max_background_flushes=0 --db=/fast-rocksdb-tmp/db_stress --prefixpercent=0 --iterpercent=0 --writepercent=75 --db_write_buffer_size=2000000 Reviewers: ljin, rven, yhchiang, sdong Reviewed By: sdong Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D30123
10 years ago
// If true --> this ColumnFamily is currently present in DBImpl::flush_queue_
bool pending_flush_;
// If true --> this ColumnFamily is currently present in
// DBImpl::compaction_queue_
bool pending_compaction_;
uint64_t prev_compaction_needed_bytes_;
};
// ColumnFamilySet has interesting thread-safety requirements
// * CreateColumnFamily() or RemoveColumnFamily() -- need to be protected by DB
// mutex AND executed in the write thread.
// CreateColumnFamily() should ONLY be called from VersionSet::LogAndApply() AND
// single-threaded write thread. It is also called during Recovery and in
// DumpManifest().
// RemoveColumnFamily() is only called from SetDropped(). DB mutex needs to be
// held and it needs to be executed from the write thread. SetDropped() also
// guarantees that it will be called only from single-threaded LogAndApply(),
// but this condition is not that important.
// * Iteration -- hold DB mutex, but you can release it in the body of
// iteration. If you release DB mutex in body, reference the column
// family before the mutex and unreference after you unlock, since the column
// family might get dropped when the DB mutex is released
// * GetDefault() -- thread safe
// * GetColumnFamily() -- either inside of DB mutex or from a write thread
// * GetNextColumnFamilyID(), GetMaxColumnFamily(), UpdateMaxColumnFamily(),
// NumberOfColumnFamilies -- inside of DB mutex
class ColumnFamilySet {
public:
// ColumnFamilySet supports iteration
class iterator {
public:
explicit iterator(ColumnFamilyData* cfd)
: current_(cfd) {}
iterator& operator++() {
// dropped column families might still be included in this iteration
// (we're only removing them when client drops the last reference to the
// column family).
// dummy is never dead, so this will never be infinite
do {
current_ = current_->next_;
} while (current_->refs_.load(std::memory_order_relaxed) == 0);
return *this;
}
bool operator!=(const iterator& other) {
return this->current_ != other.current_;
}
ColumnFamilyData* operator*() { return current_; }
private:
ColumnFamilyData* current_;
};
ColumnFamilySet(const std::string& dbname, const DBOptions* db_options,
const EnvOptions& env_options, Cache* table_cache,
WriteBufferManager* write_buffer_manager,
WriteController* write_controller);
~ColumnFamilySet();
ColumnFamilyData* GetDefault() const;
// GetColumnFamily() calls return nullptr if column family is not found
ColumnFamilyData* GetColumnFamily(uint32_t id) const;
ColumnFamilyData* GetColumnFamily(const std::string& name) const;
// this call will return the next available column family ID. it guarantees
// that there is no column family with id greater than or equal to the
// returned value in the current running instance or anytime in RocksDB
// instance history.
uint32_t GetNextColumnFamilyID();
uint32_t GetMaxColumnFamily();
void UpdateMaxColumnFamily(uint32_t new_max_column_family);
size_t NumberOfColumnFamilies() const;
ColumnFamilyData* CreateColumnFamily(const std::string& name, uint32_t id,
Version* dummy_version,
const ColumnFamilyOptions& options);
iterator begin() { return iterator(dummy_cfd_->next_); }
iterator end() { return iterator(dummy_cfd_); }
// REQUIRES: DB mutex held
// Don't call while iterating over ColumnFamilySet
void FreeDeadColumnFamilies();
Cache* get_table_cache() { return table_cache_; }
private:
friend class ColumnFamilyData;
// helper function that gets called from cfd destructor
// REQUIRES: DB mutex held
void RemoveColumnFamily(ColumnFamilyData* cfd);
// column_families_ and column_family_data_ need to be protected:
// * when mutating both conditions have to be satisfied:
// 1. DB mutex locked
// 2. thread currently in single-threaded write thread
// * when reading, at least one condition needs to be satisfied:
// 1. DB mutex locked
// 2. accessed from a single-threaded write thread
std::unordered_map<std::string, uint32_t> column_families_;
std::unordered_map<uint32_t, ColumnFamilyData*> column_family_data_;
uint32_t max_column_family_;
ColumnFamilyData* dummy_cfd_;
// We don't hold the refcount here, since default column family always exists
// We are also not responsible for cleaning up default_cfd_cache_. This is
// just a cache that makes common case (accessing default column family)
// faster
ColumnFamilyData* default_cfd_cache_;
const std::string db_name_;
const DBOptions* const db_options_;
const EnvOptions env_options_;
Cache* table_cache_;
WriteBufferManager* write_buffer_manager_;
WriteController* write_controller_;
};
// We use ColumnFamilyMemTablesImpl to provide WriteBatch a way to access
// memtables of different column families (specified by ID in the write batch)
class ColumnFamilyMemTablesImpl : public ColumnFamilyMemTables {
public:
support for concurrent adds to memtable Summary: This diff adds support for concurrent adds to the skiplist memtable implementations. Memory allocation is made thread-safe by the addition of a spinlock, with small per-core buffers to avoid contention. Concurrent memtable writes are made via an additional method and don't impose a performance overhead on the non-concurrent case, so parallelism can be selected on a per-batch basis. Write thread synchronization is an increasing bottleneck for higher levels of concurrency, so this diff adds --enable_write_thread_adaptive_yield (default off). This feature causes threads joining a write batch group to spin for a short time (default 100 usec) using sched_yield, rather than going to sleep on a mutex. If the timing of the yield calls indicates that another thread has actually run during the yield then spinning is avoided. This option improves performance for concurrent situations even without parallel adds, although it has the potential to increase CPU usage (and the heuristic adaptation is not yet mature). Parallel writes are not currently compatible with inplace updates, update callbacks, or delete filtering. Enable it with --allow_concurrent_memtable_write (and --enable_write_thread_adaptive_yield). Parallel memtable writes are performance neutral when there is no actual parallelism, and in my experiments (SSD server-class Linux and varying contention and key sizes for fillrandom) they are always a performance win when there is more than one thread. Statistics are updated earlier in the write path, dropping the number of DB mutex acquisitions from 2 to 1 for almost all cases. This diff was motivated and inspired by Yahoo's cLSM work. It is more conservative than cLSM: RocksDB's write batch group leader role is preserved (along with all of the existing flush and write throttling logic) and concurrent writers are blocked until all memtable insertions have completed and the sequence number has been advanced, to preserve linearizability. My test config is "db_bench -benchmarks=fillrandom -threads=$T -batch_size=1 -memtablerep=skip_list -value_size=100 --num=1000000/$T -level0_slowdown_writes_trigger=9999 -level0_stop_writes_trigger=9999 -disable_auto_compactions --max_write_buffer_number=8 -max_background_flushes=8 --disable_wal --write_buffer_size=160000000 --block_size=16384 --allow_concurrent_memtable_write" on a two-socket Xeon E5-2660 @ 2.2Ghz with lots of memory and an SSD hard drive. With 1 thread I get ~440Kops/sec. Peak performance for 1 socket (numactl -N1) is slightly more than 1Mops/sec, at 16 threads. Peak performance across both sockets happens at 30 threads, and is ~900Kops/sec, although with fewer threads there is less performance loss when the system has background work. Test Plan: 1. concurrent stress tests for InlineSkipList and DynamicBloom 2. make clean; make check 3. make clean; DISABLE_JEMALLOC=1 make valgrind_check; valgrind db_bench 4. make clean; COMPILE_WITH_TSAN=1 make all check; db_bench 5. make clean; COMPILE_WITH_ASAN=1 make all check; db_bench 6. make clean; OPT=-DROCKSDB_LITE make check 7. verify no perf regressions when disabled Reviewers: igor, sdong Reviewed By: sdong Subscribers: MarkCallaghan, IslamAbdelRahman, anthony, yhchiang, rven, sdong, guyg8, kradhakrishnan, dhruba Differential Revision: https://reviews.facebook.net/D50589
9 years ago
explicit ColumnFamilyMemTablesImpl(ColumnFamilySet* column_family_set)
: column_family_set_(column_family_set), current_(nullptr) {}
// Constructs a ColumnFamilyMemTablesImpl equivalent to one constructed
// with the arguments used to construct *orig.
explicit ColumnFamilyMemTablesImpl(ColumnFamilyMemTablesImpl* orig)
: column_family_set_(orig->column_family_set_), current_(nullptr) {}
// sets current_ to ColumnFamilyData with column_family_id
// returns false if column family doesn't exist
support for concurrent adds to memtable Summary: This diff adds support for concurrent adds to the skiplist memtable implementations. Memory allocation is made thread-safe by the addition of a spinlock, with small per-core buffers to avoid contention. Concurrent memtable writes are made via an additional method and don't impose a performance overhead on the non-concurrent case, so parallelism can be selected on a per-batch basis. Write thread synchronization is an increasing bottleneck for higher levels of concurrency, so this diff adds --enable_write_thread_adaptive_yield (default off). This feature causes threads joining a write batch group to spin for a short time (default 100 usec) using sched_yield, rather than going to sleep on a mutex. If the timing of the yield calls indicates that another thread has actually run during the yield then spinning is avoided. This option improves performance for concurrent situations even without parallel adds, although it has the potential to increase CPU usage (and the heuristic adaptation is not yet mature). Parallel writes are not currently compatible with inplace updates, update callbacks, or delete filtering. Enable it with --allow_concurrent_memtable_write (and --enable_write_thread_adaptive_yield). Parallel memtable writes are performance neutral when there is no actual parallelism, and in my experiments (SSD server-class Linux and varying contention and key sizes for fillrandom) they are always a performance win when there is more than one thread. Statistics are updated earlier in the write path, dropping the number of DB mutex acquisitions from 2 to 1 for almost all cases. This diff was motivated and inspired by Yahoo's cLSM work. It is more conservative than cLSM: RocksDB's write batch group leader role is preserved (along with all of the existing flush and write throttling logic) and concurrent writers are blocked until all memtable insertions have completed and the sequence number has been advanced, to preserve linearizability. My test config is "db_bench -benchmarks=fillrandom -threads=$T -batch_size=1 -memtablerep=skip_list -value_size=100 --num=1000000/$T -level0_slowdown_writes_trigger=9999 -level0_stop_writes_trigger=9999 -disable_auto_compactions --max_write_buffer_number=8 -max_background_flushes=8 --disable_wal --write_buffer_size=160000000 --block_size=16384 --allow_concurrent_memtable_write" on a two-socket Xeon E5-2660 @ 2.2Ghz with lots of memory and an SSD hard drive. With 1 thread I get ~440Kops/sec. Peak performance for 1 socket (numactl -N1) is slightly more than 1Mops/sec, at 16 threads. Peak performance across both sockets happens at 30 threads, and is ~900Kops/sec, although with fewer threads there is less performance loss when the system has background work. Test Plan: 1. concurrent stress tests for InlineSkipList and DynamicBloom 2. make clean; make check 3. make clean; DISABLE_JEMALLOC=1 make valgrind_check; valgrind db_bench 4. make clean; COMPILE_WITH_TSAN=1 make all check; db_bench 5. make clean; COMPILE_WITH_ASAN=1 make all check; db_bench 6. make clean; OPT=-DROCKSDB_LITE make check 7. verify no perf regressions when disabled Reviewers: igor, sdong Reviewed By: sdong Subscribers: MarkCallaghan, IslamAbdelRahman, anthony, yhchiang, rven, sdong, guyg8, kradhakrishnan, dhruba Differential Revision: https://reviews.facebook.net/D50589
9 years ago
// REQUIRES: use this function of DBImpl::column_family_memtables_ should be
// under a DB mutex OR from a write thread
bool Seek(uint32_t column_family_id) override;
// Returns log number of the selected column family
// REQUIRES: under a DB mutex OR from a write thread
uint64_t GetLogNumber() const override;
// REQUIRES: Seek() called first
support for concurrent adds to memtable Summary: This diff adds support for concurrent adds to the skiplist memtable implementations. Memory allocation is made thread-safe by the addition of a spinlock, with small per-core buffers to avoid contention. Concurrent memtable writes are made via an additional method and don't impose a performance overhead on the non-concurrent case, so parallelism can be selected on a per-batch basis. Write thread synchronization is an increasing bottleneck for higher levels of concurrency, so this diff adds --enable_write_thread_adaptive_yield (default off). This feature causes threads joining a write batch group to spin for a short time (default 100 usec) using sched_yield, rather than going to sleep on a mutex. If the timing of the yield calls indicates that another thread has actually run during the yield then spinning is avoided. This option improves performance for concurrent situations even without parallel adds, although it has the potential to increase CPU usage (and the heuristic adaptation is not yet mature). Parallel writes are not currently compatible with inplace updates, update callbacks, or delete filtering. Enable it with --allow_concurrent_memtable_write (and --enable_write_thread_adaptive_yield). Parallel memtable writes are performance neutral when there is no actual parallelism, and in my experiments (SSD server-class Linux and varying contention and key sizes for fillrandom) they are always a performance win when there is more than one thread. Statistics are updated earlier in the write path, dropping the number of DB mutex acquisitions from 2 to 1 for almost all cases. This diff was motivated and inspired by Yahoo's cLSM work. It is more conservative than cLSM: RocksDB's write batch group leader role is preserved (along with all of the existing flush and write throttling logic) and concurrent writers are blocked until all memtable insertions have completed and the sequence number has been advanced, to preserve linearizability. My test config is "db_bench -benchmarks=fillrandom -threads=$T -batch_size=1 -memtablerep=skip_list -value_size=100 --num=1000000/$T -level0_slowdown_writes_trigger=9999 -level0_stop_writes_trigger=9999 -disable_auto_compactions --max_write_buffer_number=8 -max_background_flushes=8 --disable_wal --write_buffer_size=160000000 --block_size=16384 --allow_concurrent_memtable_write" on a two-socket Xeon E5-2660 @ 2.2Ghz with lots of memory and an SSD hard drive. With 1 thread I get ~440Kops/sec. Peak performance for 1 socket (numactl -N1) is slightly more than 1Mops/sec, at 16 threads. Peak performance across both sockets happens at 30 threads, and is ~900Kops/sec, although with fewer threads there is less performance loss when the system has background work. Test Plan: 1. concurrent stress tests for InlineSkipList and DynamicBloom 2. make clean; make check 3. make clean; DISABLE_JEMALLOC=1 make valgrind_check; valgrind db_bench 4. make clean; COMPILE_WITH_TSAN=1 make all check; db_bench 5. make clean; COMPILE_WITH_ASAN=1 make all check; db_bench 6. make clean; OPT=-DROCKSDB_LITE make check 7. verify no perf regressions when disabled Reviewers: igor, sdong Reviewed By: sdong Subscribers: MarkCallaghan, IslamAbdelRahman, anthony, yhchiang, rven, sdong, guyg8, kradhakrishnan, dhruba Differential Revision: https://reviews.facebook.net/D50589
9 years ago
// REQUIRES: use this function of DBImpl::column_family_memtables_ should be
// under a DB mutex OR from a write thread
virtual MemTable* GetMemTable() const override;
// Returns column family handle for the selected column family
support for concurrent adds to memtable Summary: This diff adds support for concurrent adds to the skiplist memtable implementations. Memory allocation is made thread-safe by the addition of a spinlock, with small per-core buffers to avoid contention. Concurrent memtable writes are made via an additional method and don't impose a performance overhead on the non-concurrent case, so parallelism can be selected on a per-batch basis. Write thread synchronization is an increasing bottleneck for higher levels of concurrency, so this diff adds --enable_write_thread_adaptive_yield (default off). This feature causes threads joining a write batch group to spin for a short time (default 100 usec) using sched_yield, rather than going to sleep on a mutex. If the timing of the yield calls indicates that another thread has actually run during the yield then spinning is avoided. This option improves performance for concurrent situations even without parallel adds, although it has the potential to increase CPU usage (and the heuristic adaptation is not yet mature). Parallel writes are not currently compatible with inplace updates, update callbacks, or delete filtering. Enable it with --allow_concurrent_memtable_write (and --enable_write_thread_adaptive_yield). Parallel memtable writes are performance neutral when there is no actual parallelism, and in my experiments (SSD server-class Linux and varying contention and key sizes for fillrandom) they are always a performance win when there is more than one thread. Statistics are updated earlier in the write path, dropping the number of DB mutex acquisitions from 2 to 1 for almost all cases. This diff was motivated and inspired by Yahoo's cLSM work. It is more conservative than cLSM: RocksDB's write batch group leader role is preserved (along with all of the existing flush and write throttling logic) and concurrent writers are blocked until all memtable insertions have completed and the sequence number has been advanced, to preserve linearizability. My test config is "db_bench -benchmarks=fillrandom -threads=$T -batch_size=1 -memtablerep=skip_list -value_size=100 --num=1000000/$T -level0_slowdown_writes_trigger=9999 -level0_stop_writes_trigger=9999 -disable_auto_compactions --max_write_buffer_number=8 -max_background_flushes=8 --disable_wal --write_buffer_size=160000000 --block_size=16384 --allow_concurrent_memtable_write" on a two-socket Xeon E5-2660 @ 2.2Ghz with lots of memory and an SSD hard drive. With 1 thread I get ~440Kops/sec. Peak performance for 1 socket (numactl -N1) is slightly more than 1Mops/sec, at 16 threads. Peak performance across both sockets happens at 30 threads, and is ~900Kops/sec, although with fewer threads there is less performance loss when the system has background work. Test Plan: 1. concurrent stress tests for InlineSkipList and DynamicBloom 2. make clean; make check 3. make clean; DISABLE_JEMALLOC=1 make valgrind_check; valgrind db_bench 4. make clean; COMPILE_WITH_TSAN=1 make all check; db_bench 5. make clean; COMPILE_WITH_ASAN=1 make all check; db_bench 6. make clean; OPT=-DROCKSDB_LITE make check 7. verify no perf regressions when disabled Reviewers: igor, sdong Reviewed By: sdong Subscribers: MarkCallaghan, IslamAbdelRahman, anthony, yhchiang, rven, sdong, guyg8, kradhakrishnan, dhruba Differential Revision: https://reviews.facebook.net/D50589
9 years ago
// REQUIRES: use this function of DBImpl::column_family_memtables_ should be
// under a DB mutex OR from a write thread
virtual ColumnFamilyHandle* GetColumnFamilyHandle() override;
support for concurrent adds to memtable Summary: This diff adds support for concurrent adds to the skiplist memtable implementations. Memory allocation is made thread-safe by the addition of a spinlock, with small per-core buffers to avoid contention. Concurrent memtable writes are made via an additional method and don't impose a performance overhead on the non-concurrent case, so parallelism can be selected on a per-batch basis. Write thread synchronization is an increasing bottleneck for higher levels of concurrency, so this diff adds --enable_write_thread_adaptive_yield (default off). This feature causes threads joining a write batch group to spin for a short time (default 100 usec) using sched_yield, rather than going to sleep on a mutex. If the timing of the yield calls indicates that another thread has actually run during the yield then spinning is avoided. This option improves performance for concurrent situations even without parallel adds, although it has the potential to increase CPU usage (and the heuristic adaptation is not yet mature). Parallel writes are not currently compatible with inplace updates, update callbacks, or delete filtering. Enable it with --allow_concurrent_memtable_write (and --enable_write_thread_adaptive_yield). Parallel memtable writes are performance neutral when there is no actual parallelism, and in my experiments (SSD server-class Linux and varying contention and key sizes for fillrandom) they are always a performance win when there is more than one thread. Statistics are updated earlier in the write path, dropping the number of DB mutex acquisitions from 2 to 1 for almost all cases. This diff was motivated and inspired by Yahoo's cLSM work. It is more conservative than cLSM: RocksDB's write batch group leader role is preserved (along with all of the existing flush and write throttling logic) and concurrent writers are blocked until all memtable insertions have completed and the sequence number has been advanced, to preserve linearizability. My test config is "db_bench -benchmarks=fillrandom -threads=$T -batch_size=1 -memtablerep=skip_list -value_size=100 --num=1000000/$T -level0_slowdown_writes_trigger=9999 -level0_stop_writes_trigger=9999 -disable_auto_compactions --max_write_buffer_number=8 -max_background_flushes=8 --disable_wal --write_buffer_size=160000000 --block_size=16384 --allow_concurrent_memtable_write" on a two-socket Xeon E5-2660 @ 2.2Ghz with lots of memory and an SSD hard drive. With 1 thread I get ~440Kops/sec. Peak performance for 1 socket (numactl -N1) is slightly more than 1Mops/sec, at 16 threads. Peak performance across both sockets happens at 30 threads, and is ~900Kops/sec, although with fewer threads there is less performance loss when the system has background work. Test Plan: 1. concurrent stress tests for InlineSkipList and DynamicBloom 2. make clean; make check 3. make clean; DISABLE_JEMALLOC=1 make valgrind_check; valgrind db_bench 4. make clean; COMPILE_WITH_TSAN=1 make all check; db_bench 5. make clean; COMPILE_WITH_ASAN=1 make all check; db_bench 6. make clean; OPT=-DROCKSDB_LITE make check 7. verify no perf regressions when disabled Reviewers: igor, sdong Reviewed By: sdong Subscribers: MarkCallaghan, IslamAbdelRahman, anthony, yhchiang, rven, sdong, guyg8, kradhakrishnan, dhruba Differential Revision: https://reviews.facebook.net/D50589
9 years ago
// Cannot be called while another thread is calling Seek().
// REQUIRES: use this function of DBImpl::column_family_memtables_ should be
// under a DB mutex OR from a write thread
virtual ColumnFamilyData* current() override { return current_; }
private:
ColumnFamilySet* column_family_set_;
ColumnFamilyData* current_;
ColumnFamilyHandleInternal handle_;
};
extern uint32_t GetColumnFamilyID(ColumnFamilyHandle* column_family);
extern const Comparator* GetColumnFamilyUserComparator(
ColumnFamilyHandle* column_family);
} // namespace rocksdb