7d87f02799
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
83 lines
2.7 KiB
C++
83 lines
2.7 KiB
C++
// Copyright (c) 2013, Facebook, Inc. All rights reserved.
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// This source code is licensed under the BSD-style license found in the
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// LICENSE file in the root directory of this source tree. An additional grant
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// of patent rights can be found in the PATENTS file in the same directory.
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#include "dynamic_bloom.h"
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#include <algorithm>
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#include "port/port.h"
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#include "rocksdb/slice.h"
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#include "util/allocator.h"
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#include "util/hash.h"
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namespace rocksdb {
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namespace {
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uint32_t GetTotalBitsForLocality(uint32_t total_bits) {
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uint32_t num_blocks =
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(total_bits + CACHE_LINE_SIZE * 8 - 1) / (CACHE_LINE_SIZE * 8);
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// Make num_blocks an odd number to make sure more bits are involved
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// when determining which block.
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if (num_blocks % 2 == 0) {
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num_blocks++;
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}
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return num_blocks * (CACHE_LINE_SIZE * 8);
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}
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}
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DynamicBloom::DynamicBloom(Allocator* allocator, uint32_t total_bits,
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uint32_t locality, uint32_t num_probes,
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uint32_t (*hash_func)(const Slice& key),
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size_t huge_page_tlb_size,
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Logger* logger)
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: DynamicBloom(num_probes, hash_func) {
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SetTotalBits(allocator, total_bits, locality, huge_page_tlb_size, logger);
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}
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DynamicBloom::DynamicBloom(uint32_t num_probes,
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uint32_t (*hash_func)(const Slice& key))
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: kTotalBits(0),
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kNumBlocks(0),
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kNumProbes(num_probes),
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hash_func_(hash_func == nullptr ? &BloomHash : hash_func) {}
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void DynamicBloom::SetRawData(unsigned char* raw_data, uint32_t total_bits,
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uint32_t num_blocks) {
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data_ = reinterpret_cast<std::atomic<uint8_t>*>(raw_data);
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kTotalBits = total_bits;
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kNumBlocks = num_blocks;
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}
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void DynamicBloom::SetTotalBits(Allocator* allocator,
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uint32_t total_bits, uint32_t locality,
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size_t huge_page_tlb_size,
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Logger* logger) {
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kTotalBits = (locality > 0) ? GetTotalBitsForLocality(total_bits)
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: (total_bits + 7) / 8 * 8;
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kNumBlocks = (locality > 0) ? (kTotalBits / (CACHE_LINE_SIZE * 8)) : 0;
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assert(kNumBlocks > 0 || kTotalBits > 0);
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assert(kNumProbes > 0);
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uint32_t sz = kTotalBits / 8;
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if (kNumBlocks > 0) {
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sz += CACHE_LINE_SIZE - 1;
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}
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assert(allocator);
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char* raw = allocator->AllocateAligned(sz, huge_page_tlb_size, logger);
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memset(raw, 0, sz);
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auto cache_line_offset = reinterpret_cast<uintptr_t>(raw) % CACHE_LINE_SIZE;
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if (kNumBlocks > 0 && cache_line_offset > 0) {
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raw += CACHE_LINE_SIZE - cache_line_offset;
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}
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data_ = reinterpret_cast<std::atomic<uint8_t>*>(raw);
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}
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} // rocksdb
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