rocksdb/memtable/inlineskiplist.h

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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).
//
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// 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.
//
// InlineSkipList is derived from SkipList (skiplist.h), but it optimizes
// the memory layout by requiring that the key storage be allocated through
// the skip list instance. For the common case of SkipList<const char*,
// Cmp> this saves 1 pointer per skip list node and gives better cache
// locality, at the expense of wasted padding from using AllocateAligned
// instead of Allocate for the keys. The unused padding will be from
// 0 to sizeof(void*)-1 bytes, and the space savings are sizeof(void*)
// bytes, so despite the padding the space used is always less than
// SkipList<const char*, ..>.
//
// Thread safety -------------
//
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
2015-08-15 01:59:07 +02:00
// Writes via Insert require external synchronization, most likely a mutex.
// InsertConcurrently can be safely called concurrently with reads and
// with other concurrent inserts. Reads require a guarantee that the
// InlineSkipList will not be destroyed while the read is in progress.
// Apart from that, reads progress without any internal locking or
// synchronization.
//
// Invariants:
//
// (1) Allocated nodes are never deleted until the InlineSkipList is
// destroyed. This is trivially guaranteed by the code since we never
// delete any skip list nodes.
//
// (2) The contents of a Node except for the next/prev pointers are
// immutable after the Node has been linked into the InlineSkipList.
// Only Insert() modifies the list, and it is careful to initialize a
// node and use release-stores to publish the nodes in one or more lists.
//
// ... prev vs. next pointer ordering ...
//
#pragma once
#include <assert.h>
#include <stdlib.h>
#include <algorithm>
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#include <atomic>
#include <type_traits>
#include "memory/allocator.h"
#include "port/likely.h"
#include "port/port.h"
#include "rocksdb/slice.h"
#include "util/coding.h"
#include "util/random.h"
namespace ROCKSDB_NAMESPACE {
template <class Comparator>
class InlineSkipList {
private:
struct Node;
struct Splice;
public:
using DecodedKey = \
typename std::remove_reference<Comparator>::type::DecodedType;
static const uint16_t kMaxPossibleHeight = 32;
// Create a new InlineSkipList object that will use "cmp" for comparing
// keys, and will allocate memory using "*allocator". Objects allocated
// in the allocator must remain allocated for the lifetime of the
// skiplist object.
explicit InlineSkipList(Comparator cmp, Allocator* allocator,
int32_t max_height = 12,
int32_t branching_factor = 4);
// No copying allowed
InlineSkipList(const InlineSkipList&) = delete;
InlineSkipList& operator=(const InlineSkipList&) = delete;
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
2015-08-15 01:59:07 +02:00
// Allocates a key and a skip-list node, returning a pointer to the key
// portion of the node. This method is thread-safe if the allocator
// is thread-safe.
char* AllocateKey(size_t key_size);
// Allocate a splice using allocator.
Splice* AllocateSplice();
// Allocate a splice on heap.
Splice* AllocateSpliceOnHeap();
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// Inserts a key allocated by AllocateKey, after the actual key value
// has been filled in.
//
// REQUIRES: nothing that compares equal to key is currently in the list.
// REQUIRES: no concurrent calls to any of inserts.
bool Insert(const char* key);
// Inserts a key allocated by AllocateKey with a hint of last insert
// position in the skip-list. If hint points to nullptr, a new hint will be
// populated, which can be used in subsequent calls.
//
// It can be used to optimize the workload where there are multiple groups
// of keys, and each key is likely to insert to a location close to the last
// inserted key in the same group. One example is sequential inserts.
//
// REQUIRES: nothing that compares equal to key is currently in the list.
// REQUIRES: no concurrent calls to any of inserts.
bool InsertWithHint(const char* key, void** hint);
// Like InsertConcurrently, but with a hint
//
// REQUIRES: nothing that compares equal to key is currently in the list.
// REQUIRES: no concurrent calls that use same hint
bool InsertWithHintConcurrently(const char* key, void** hint);
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
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// Like Insert, but external synchronization is not required.
bool InsertConcurrently(const char* key);
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
2015-08-15 01:59:07 +02:00
// Inserts a node into the skip list. key must have been allocated by
// AllocateKey and then filled in by the caller. If UseCAS is true,
// then external synchronization is not required, otherwise this method
// may not be called concurrently with any other insertions.
//
// Regardless of whether UseCAS is true, the splice must be owned
// exclusively by the current thread. If allow_partial_splice_fix is
// true, then the cost of insertion is amortized O(log D), where D is
// the distance from the splice to the inserted key (measured as the
// number of intervening nodes). Note that this bound is very good for
// sequential insertions! If allow_partial_splice_fix is false then
// the existing splice will be ignored unless the current key is being
// inserted immediately after the splice. allow_partial_splice_fix ==
// false has worse running time for the non-sequential case O(log N),
// but a better constant factor.
template <bool UseCAS>
bool Insert(const char* key, Splice* splice, bool allow_partial_splice_fix);
// Returns true iff an entry that compares equal to key is in the list.
bool Contains(const char* key) const;
// Return estimated number of entries smaller than `key`.
uint64_t EstimateCount(const char* key) const;
// Validate correctness of the skip-list.
void TEST_Validate() const;
// Iteration over the contents of a skip list
class Iterator {
public:
// Initialize an iterator over the specified list.
// The returned iterator is not valid.
explicit Iterator(const InlineSkipList* list);
// Change the underlying skiplist used for this iterator
// This enables us not changing the iterator without deallocating
// an old one and then allocating a new one
void SetList(const InlineSkipList* list);
// Returns true iff the iterator is positioned at a valid node.
bool Valid() const;
// Returns the key at the current position.
// REQUIRES: Valid()
const char* key() const;
// Advances to the next position.
// REQUIRES: Valid()
void Next();
// Advances to the previous position.
// REQUIRES: Valid()
void Prev();
// Advance to the first entry with a key >= target
void Seek(const char* target);
// Retreat to the last entry with a key <= target
void SeekForPrev(const char* target);
// Position at the first entry in list.
// Final state of iterator is Valid() iff list is not empty.
void SeekToFirst();
// Position at the last entry in list.
// Final state of iterator is Valid() iff list is not empty.
void SeekToLast();
private:
const InlineSkipList* list_;
Node* node_;
// Intentionally copyable
};
private:
const uint16_t kMaxHeight_;
const uint16_t kBranching_;
const uint32_t kScaledInverseBranching_;
Reorder field based on esan data Summary: Running. TEST_TMPDIR=/dev/shm ./buck-out/gen/rocks/tools/rocks_db_bench --benchmarks=readwhilewriting --num=5000000 -benchmark_write_rate_limit=2000000 --threads=32 Collected esan data and reorder field. Accesses to 4th and 6th fields take majority of the access. Group them. Overall, this struct takes 10%+ of the total accesses in the program. (637773011/6107964986) ==2433831== class rocksdb::InlineSkipList ==2433831== size = 48, count = 637773011, ratio = 112412, array access = 0 ==2433831== # 0: offset = 0, size = 2, count = 455137, type = i16 ==2433831== # 1: offset = 2, size = 2, count = 6, type = i16 ==2433831== # 2: offset = 4, size = 4, count = 182303, type = i32 ==2433831== # 3: offset = 8, size = 8, count = 263953900, type = %"class.rocksdb::MemTableRep::KeyComparator"* ==2433831== # 4: offset = 16, size = 8, count = 136409, type = %"class.rocksdb::Allocator"* ==2433831== # 5: offset = 24, size = 8, count = 366628820, type = %"struct.rocksdb::InlineSkipList<const rocksdb::MemTableRep::KeyComparator &>::Node"* ==2433831== # 6: offset = 32, size = 4, count = 6280031, type = %"struct.std::atomic" = type { %"struct.std::__atomic_base" } ==2433831== # 7: offset = 40, size = 8, count = 136405, type = %"struct.rocksdb::InlineSkipList<const rocksdb::MemTableRep::KeyComparator &>::Splice"* ==2433831==EfficiencySanitizer: total struct field access count = 6107964986 Before re-ordering [trentxintong@devbig460.frc2 ~/fbsource/fbcode]$ fgrep readwhilewriting without-ro.log readwhilewriting : 0.036 micros/op 27545605 ops/sec; 26.8 MB/s (45954 of 5000000 found) readwhilewriting : 0.036 micros/op 28024240 ops/sec; 27.2 MB/s (43158 of 5000000 found) readwhilewriting : 0.037 micros/op 27345145 ops/sec; 27.1 MB/s (46725 of 5000000 found) readwhilewriting : 0.037 micros/op 27072588 ops/sec; 27.3 MB/s (42605 of 5000000 found) readwhilewriting : 0.034 micros/op 29578781 ops/sec; 28.3 MB/s (44294 of 5000000 found) readwhilewriting : 0.035 micros/op 28528304 ops/sec; 27.7 MB/s (44176 of 5000000 found) readwhilewriting : 0.037 micros/op 27075497 ops/sec; 26.5 MB/s (43763 of 5000000 found) readwhilewriting : 0.036 micros/op 28024117 ops/sec; 27.1 MB/s (40622 of 5000000 found) readwhilewriting : 0.037 micros/op 27078709 ops/sec; 27.6 MB/s (47774 of 5000000 found) readwhilewriting : 0.034 micros/op 29020689 ops/sec; 28.1 MB/s (45066 of 5000000 found) AVERAGE()=27.37 MB/s After re-ordering [trentxintong@devbig460.frc2 ~/fbsource/fbcode]$ fgrep readwhilewriting ro.log readwhilewriting : 0.036 micros/op 27542409 ops/sec; 27.7 MB/s (46163 of 5000000 found) readwhilewriting : 0.036 micros/op 28021148 ops/sec; 28.2 MB/s (46155 of 5000000 found) readwhilewriting : 0.036 micros/op 28021035 ops/sec; 27.3 MB/s (44039 of 5000000 found) readwhilewriting : 0.036 micros/op 27538659 ops/sec; 27.5 MB/s (46781 of 5000000 found) readwhilewriting : 0.036 micros/op 28028604 ops/sec; 27.6 MB/s (44689 of 5000000 found) readwhilewriting : 0.036 micros/op 27541452 ops/sec; 27.3 MB/s (43156 of 5000000 found) readwhilewriting : 0.034 micros/op 29041338 ops/sec; 28.8 MB/s (44895 of 5000000 found) readwhilewriting : 0.036 micros/op 27784974 ops/sec; 26.3 MB/s (39963 of 5000000 found) readwhilewriting : 0.036 micros/op 27538892 ops/sec; 28.1 MB/s (46570 of 5000000 found) readwhilewriting : 0.038 micros/op 26622473 ops/sec; 27.0 MB/s (43236 of 5000000 found) AVERAGE()=27.58 MB/s Closes https://github.com/facebook/rocksdb/pull/3855 Reviewed By: siying Differential Revision: D8048781 Pulled By: trentxintong fbshipit-source-id: bc9807a9845e2a92cb171ce1ecb5a2c8a51f1481
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Allocator* const allocator_; // Allocator used for allocations of nodes
// Immutable after construction
Comparator const compare_;
Node* const head_;
// Modified only by Insert(). Read racily by readers, but stale
// values are ok.
std::atomic<int> max_height_; // Height of the entire list
// seq_splice_ is a Splice used for insertions in the non-concurrent
// case. It caches the prev and next found during the most recent
// non-concurrent insertion.
Splice* seq_splice_;
inline int GetMaxHeight() const {
return max_height_.load(std::memory_order_relaxed);
}
int RandomHeight();
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Node* AllocateNode(size_t key_size, int height);
bool Equal(const char* a, const char* b) const {
return (compare_(a, b) == 0);
}
bool LessThan(const char* a, const char* b) const {
return (compare_(a, b) < 0);
}
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// Return true if key is greater than the data stored in "n". Null n
// is considered infinite. n should not be head_.
bool KeyIsAfterNode(const char* key, Node* n) const;
bool KeyIsAfterNode(const DecodedKey& key, Node* n) const;
// Returns the earliest node with a key >= key.
// Return nullptr if there is no such node.
Node* FindGreaterOrEqual(const char* key) const;
// Return the latest node with a key < key.
// Return head_ if there is no such node.
// Fills prev[level] with pointer to previous node at "level" for every
// level in [0..max_height_-1], if prev is non-null.
Node* FindLessThan(const char* key, Node** prev = nullptr) const;
// Return the latest node with a key < key on bottom_level. Start searching
// from root node on the level below top_level.
// Fills prev[level] with pointer to previous node at "level" for every
// level in [bottom_level..top_level-1], if prev is non-null.
Node* FindLessThan(const char* key, Node** prev, Node* root, int top_level,
int bottom_level) const;
// Return the last node in the list.
// Return head_ if list is empty.
Node* FindLast() const;
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
2015-08-15 01:59:07 +02:00
// Traverses a single level of the list, setting *out_prev to the last
// node before the key and *out_next to the first node after. Assumes
// that the key is not present in the skip list. On entry, before should
// point to a node that is before the key, and after should point to
// a node that is after the key. after should be nullptr if a good after
// node isn't conveniently available.
template<bool prefetch_before>
void FindSpliceForLevel(const DecodedKey& key, Node* before, Node* after, int level,
Node** out_prev, Node** out_next);
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
2015-08-15 01:59:07 +02:00
// Recomputes Splice levels from highest_level (inclusive) down to
// lowest_level (inclusive).
void RecomputeSpliceLevels(const DecodedKey& key, Splice* splice,
int recompute_level);
};
// Implementation details follow
2015-11-19 23:24:29 +01:00
template <class Comparator>
struct InlineSkipList<Comparator>::Splice {
// The invariant of a Splice is that prev_[i+1].key <= prev_[i].key <
// next_[i].key <= next_[i+1].key for all i. That means that if a
// key is bracketed by prev_[i] and next_[i] then it is bracketed by
// all higher levels. It is _not_ required that prev_[i]->Next(i) ==
// next_[i] (it probably did at some point in the past, but intervening
// or concurrent operations might have inserted nodes in between).
int height_ = 0;
Node** prev_;
Node** next_;
};
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// The Node data type is more of a pointer into custom-managed memory than
// a traditional C++ struct. The key is stored in the bytes immediately
// after the struct, and the next_ pointers for nodes with height > 1 are
// stored immediately _before_ the struct. This avoids the need to include
// any pointer or sizing data, which reduces per-node memory overheads.
template <class Comparator>
struct InlineSkipList<Comparator>::Node {
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// Stores the height of the node in the memory location normally used for
// next_[0]. This is used for passing data from AllocateKey to Insert.
void StashHeight(const int height) {
assert(sizeof(int) <= sizeof(next_[0]));
memcpy(static_cast<void*>(&next_[0]), &height, sizeof(int));
2015-11-19 23:24:29 +01:00
}
// Retrieves the value passed to StashHeight. Undefined after a call
// to SetNext or NoBarrier_SetNext.
int UnstashHeight() const {
int rv;
memcpy(&rv, &next_[0], sizeof(int));
return rv;
}
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const char* Key() const { return reinterpret_cast<const char*>(&next_[1]); }
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// Accessors/mutators for links. Wrapped in methods so we can add
// the appropriate barriers as necessary, and perform the necessary
// addressing trickery for storing links below the Node in memory.
Node* Next(int n) {
assert(n >= 0);
// Use an 'acquire load' so that we observe a fully initialized
// version of the returned Node.
return ((&next_[0] - n)->load(std::memory_order_acquire));
}
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void SetNext(int n, Node* x) {
assert(n >= 0);
// Use a 'release store' so that anybody who reads through this
// pointer observes a fully initialized version of the inserted node.
(&next_[0] - n)->store(x, std::memory_order_release);
}
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
2015-08-15 01:59:07 +02:00
bool CASNext(int n, Node* expected, Node* x) {
assert(n >= 0);
return (&next_[0] - n)->compare_exchange_strong(expected, x);
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
2015-08-15 01:59:07 +02:00
}
// No-barrier variants that can be safely used in a few locations.
Node* NoBarrier_Next(int n) {
assert(n >= 0);
return (&next_[0] - n)->load(std::memory_order_relaxed);
}
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void NoBarrier_SetNext(int n, Node* x) {
assert(n >= 0);
(&next_[0] - n)->store(x, std::memory_order_relaxed);
}
// Insert node after prev on specific level.
void InsertAfter(Node* prev, int level) {
// NoBarrier_SetNext() suffices since we will add a barrier when
// we publish a pointer to "this" in prev.
NoBarrier_SetNext(level, prev->NoBarrier_Next(level));
prev->SetNext(level, this);
}
private:
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// next_[0] is the lowest level link (level 0). Higher levels are
// stored _earlier_, so level 1 is at next_[-1].
std::atomic<Node*> next_[1];
};
template <class Comparator>
inline InlineSkipList<Comparator>::Iterator::Iterator(
const InlineSkipList* list) {
SetList(list);
}
template <class Comparator>
inline void InlineSkipList<Comparator>::Iterator::SetList(
const InlineSkipList* list) {
list_ = list;
node_ = nullptr;
}
template <class Comparator>
inline bool InlineSkipList<Comparator>::Iterator::Valid() const {
return node_ != nullptr;
}
template <class Comparator>
inline const char* InlineSkipList<Comparator>::Iterator::key() const {
assert(Valid());
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return node_->Key();
}
template <class Comparator>
inline void InlineSkipList<Comparator>::Iterator::Next() {
assert(Valid());
node_ = node_->Next(0);
}
template <class Comparator>
inline void InlineSkipList<Comparator>::Iterator::Prev() {
// Instead of using explicit "prev" links, we just search for the
// last node that falls before key.
assert(Valid());
2015-11-19 23:24:29 +01:00
node_ = list_->FindLessThan(node_->Key());
if (node_ == list_->head_) {
node_ = nullptr;
}
}
template <class Comparator>
inline void InlineSkipList<Comparator>::Iterator::Seek(const char* target) {
node_ = list_->FindGreaterOrEqual(target);
}
template <class Comparator>
inline void InlineSkipList<Comparator>::Iterator::SeekForPrev(
const char* target) {
Seek(target);
if (!Valid()) {
SeekToLast();
}
while (Valid() && list_->LessThan(target, key())) {
Prev();
}
}
template <class Comparator>
inline void InlineSkipList<Comparator>::Iterator::SeekToFirst() {
node_ = list_->head_->Next(0);
}
template <class Comparator>
inline void InlineSkipList<Comparator>::Iterator::SeekToLast() {
node_ = list_->FindLast();
if (node_ == list_->head_) {
node_ = nullptr;
}
}
template <class Comparator>
int InlineSkipList<Comparator>::RandomHeight() {
auto rnd = Random::GetTLSInstance();
// Increase height with probability 1 in kBranching
int height = 1;
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
2015-08-15 01:59:07 +02:00
while (height < kMaxHeight_ && height < kMaxPossibleHeight &&
rnd->Next() < kScaledInverseBranching_) {
height++;
}
assert(height > 0);
assert(height <= kMaxHeight_);
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
2015-08-15 01:59:07 +02:00
assert(height <= kMaxPossibleHeight);
return height;
}
template <class Comparator>
bool InlineSkipList<Comparator>::KeyIsAfterNode(const char* key,
Node* n) const {
// nullptr n is considered infinite
assert(n != head_);
2015-11-19 23:24:29 +01:00
return (n != nullptr) && (compare_(n->Key(), key) < 0);
}
template <class Comparator>
bool InlineSkipList<Comparator>::KeyIsAfterNode(const DecodedKey& key,
Node* n) const {
// nullptr n is considered infinite
assert(n != head_);
return (n != nullptr) && (compare_(n->Key(), key) < 0);
}
template <class Comparator>
typename InlineSkipList<Comparator>::Node*
InlineSkipList<Comparator>::FindGreaterOrEqual(const char* key) const {
// Note: It looks like we could reduce duplication by implementing
// this function as FindLessThan(key)->Next(0), but we wouldn't be able
// to exit early on equality and the result wouldn't even be correct.
// A concurrent insert might occur after FindLessThan(key) but before
// we get a chance to call Next(0).
Node* x = head_;
int level = GetMaxHeight() - 1;
Node* last_bigger = nullptr;
const DecodedKey key_decoded = compare_.decode_key(key);
while (true) {
Node* next = x->Next(level);
if (next != nullptr) {
PREFETCH(next->Next(level), 0, 1);
}
// Make sure the lists are sorted
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assert(x == head_ || next == nullptr || KeyIsAfterNode(next->Key(), x));
// Make sure we haven't overshot during our search
assert(x == head_ || KeyIsAfterNode(key_decoded, x));
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int cmp = (next == nullptr || next == last_bigger)
? 1
: compare_(next->Key(), key_decoded);
if (cmp == 0 || (cmp > 0 && level == 0)) {
return next;
} else if (cmp < 0) {
// Keep searching in this list
x = next;
} else {
// Switch to next list, reuse compare_() result
last_bigger = next;
level--;
}
}
}
template <class Comparator>
typename InlineSkipList<Comparator>::Node*
InlineSkipList<Comparator>::FindLessThan(const char* key, Node** prev) const {
return FindLessThan(key, prev, head_, GetMaxHeight(), 0);
}
template <class Comparator>
typename InlineSkipList<Comparator>::Node*
InlineSkipList<Comparator>::FindLessThan(const char* key, Node** prev,
Node* root, int top_level,
int bottom_level) const {
assert(top_level > bottom_level);
int level = top_level - 1;
Node* x = root;
// KeyIsAfter(key, last_not_after) is definitely false
Node* last_not_after = nullptr;
const DecodedKey key_decoded = compare_.decode_key(key);
while (true) {
assert(x != nullptr);
Node* next = x->Next(level);
if (next != nullptr) {
PREFETCH(next->Next(level), 0, 1);
}
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assert(x == head_ || next == nullptr || KeyIsAfterNode(next->Key(), x));
assert(x == head_ || KeyIsAfterNode(key_decoded, x));
if (next != last_not_after && KeyIsAfterNode(key_decoded, next)) {
// Keep searching in this list
assert(next != nullptr);
x = next;
} else {
if (prev != nullptr) {
prev[level] = x;
}
if (level == bottom_level) {
return x;
} else {
// Switch to next list, reuse KeyIsAfterNode() result
last_not_after = next;
level--;
}
}
}
}
template <class Comparator>
typename InlineSkipList<Comparator>::Node*
InlineSkipList<Comparator>::FindLast() const {
Node* x = head_;
int level = GetMaxHeight() - 1;
while (true) {
Node* next = x->Next(level);
if (next == nullptr) {
if (level == 0) {
return x;
} else {
// Switch to next list
level--;
}
} else {
x = next;
}
}
}
template <class Comparator>
uint64_t InlineSkipList<Comparator>::EstimateCount(const char* key) const {
uint64_t count = 0;
Node* x = head_;
int level = GetMaxHeight() - 1;
const DecodedKey key_decoded = compare_.decode_key(key);
while (true) {
assert(x == head_ || compare_(x->Key(), key_decoded) < 0);
Node* next = x->Next(level);
if (next != nullptr) {
PREFETCH(next->Next(level), 0, 1);
}
if (next == nullptr || compare_(next->Key(), key_decoded) >= 0) {
if (level == 0) {
return count;
} else {
// Switch to next list
count *= kBranching_;
level--;
}
} else {
x = next;
count++;
}
}
}
template <class Comparator>
InlineSkipList<Comparator>::InlineSkipList(const Comparator cmp,
Allocator* allocator,
int32_t max_height,
int32_t branching_factor)
: kMaxHeight_(static_cast<uint16_t>(max_height)),
kBranching_(static_cast<uint16_t>(branching_factor)),
kScaledInverseBranching_((Random::kMaxNext + 1) / kBranching_),
allocator_(allocator),
Reorder field based on esan data Summary: Running. TEST_TMPDIR=/dev/shm ./buck-out/gen/rocks/tools/rocks_db_bench --benchmarks=readwhilewriting --num=5000000 -benchmark_write_rate_limit=2000000 --threads=32 Collected esan data and reorder field. Accesses to 4th and 6th fields take majority of the access. Group them. Overall, this struct takes 10%+ of the total accesses in the program. (637773011/6107964986) ==2433831== class rocksdb::InlineSkipList ==2433831== size = 48, count = 637773011, ratio = 112412, array access = 0 ==2433831== # 0: offset = 0, size = 2, count = 455137, type = i16 ==2433831== # 1: offset = 2, size = 2, count = 6, type = i16 ==2433831== # 2: offset = 4, size = 4, count = 182303, type = i32 ==2433831== # 3: offset = 8, size = 8, count = 263953900, type = %"class.rocksdb::MemTableRep::KeyComparator"* ==2433831== # 4: offset = 16, size = 8, count = 136409, type = %"class.rocksdb::Allocator"* ==2433831== # 5: offset = 24, size = 8, count = 366628820, type = %"struct.rocksdb::InlineSkipList<const rocksdb::MemTableRep::KeyComparator &>::Node"* ==2433831== # 6: offset = 32, size = 4, count = 6280031, type = %"struct.std::atomic" = type { %"struct.std::__atomic_base" } ==2433831== # 7: offset = 40, size = 8, count = 136405, type = %"struct.rocksdb::InlineSkipList<const rocksdb::MemTableRep::KeyComparator &>::Splice"* ==2433831==EfficiencySanitizer: total struct field access count = 6107964986 Before re-ordering [trentxintong@devbig460.frc2 ~/fbsource/fbcode]$ fgrep readwhilewriting without-ro.log readwhilewriting : 0.036 micros/op 27545605 ops/sec; 26.8 MB/s (45954 of 5000000 found) readwhilewriting : 0.036 micros/op 28024240 ops/sec; 27.2 MB/s (43158 of 5000000 found) readwhilewriting : 0.037 micros/op 27345145 ops/sec; 27.1 MB/s (46725 of 5000000 found) readwhilewriting : 0.037 micros/op 27072588 ops/sec; 27.3 MB/s (42605 of 5000000 found) readwhilewriting : 0.034 micros/op 29578781 ops/sec; 28.3 MB/s (44294 of 5000000 found) readwhilewriting : 0.035 micros/op 28528304 ops/sec; 27.7 MB/s (44176 of 5000000 found) readwhilewriting : 0.037 micros/op 27075497 ops/sec; 26.5 MB/s (43763 of 5000000 found) readwhilewriting : 0.036 micros/op 28024117 ops/sec; 27.1 MB/s (40622 of 5000000 found) readwhilewriting : 0.037 micros/op 27078709 ops/sec; 27.6 MB/s (47774 of 5000000 found) readwhilewriting : 0.034 micros/op 29020689 ops/sec; 28.1 MB/s (45066 of 5000000 found) AVERAGE()=27.37 MB/s After re-ordering [trentxintong@devbig460.frc2 ~/fbsource/fbcode]$ fgrep readwhilewriting ro.log readwhilewriting : 0.036 micros/op 27542409 ops/sec; 27.7 MB/s (46163 of 5000000 found) readwhilewriting : 0.036 micros/op 28021148 ops/sec; 28.2 MB/s (46155 of 5000000 found) readwhilewriting : 0.036 micros/op 28021035 ops/sec; 27.3 MB/s (44039 of 5000000 found) readwhilewriting : 0.036 micros/op 27538659 ops/sec; 27.5 MB/s (46781 of 5000000 found) readwhilewriting : 0.036 micros/op 28028604 ops/sec; 27.6 MB/s (44689 of 5000000 found) readwhilewriting : 0.036 micros/op 27541452 ops/sec; 27.3 MB/s (43156 of 5000000 found) readwhilewriting : 0.034 micros/op 29041338 ops/sec; 28.8 MB/s (44895 of 5000000 found) readwhilewriting : 0.036 micros/op 27784974 ops/sec; 26.3 MB/s (39963 of 5000000 found) readwhilewriting : 0.036 micros/op 27538892 ops/sec; 28.1 MB/s (46570 of 5000000 found) readwhilewriting : 0.038 micros/op 26622473 ops/sec; 27.0 MB/s (43236 of 5000000 found) AVERAGE()=27.58 MB/s Closes https://github.com/facebook/rocksdb/pull/3855 Reviewed By: siying Differential Revision: D8048781 Pulled By: trentxintong fbshipit-source-id: bc9807a9845e2a92cb171ce1ecb5a2c8a51f1481
2018-05-18 02:49:06 +02:00
compare_(cmp),
2015-11-19 23:24:29 +01:00
head_(AllocateNode(0, max_height)),
max_height_(1),
seq_splice_(AllocateSplice()) {
assert(max_height > 0 && kMaxHeight_ == static_cast<uint32_t>(max_height));
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
2015-08-15 01:59:07 +02:00
assert(branching_factor > 1 &&
kBranching_ == static_cast<uint32_t>(branching_factor));
assert(kScaledInverseBranching_ > 0);
for (int i = 0; i < kMaxHeight_; ++i) {
head_->SetNext(i, nullptr);
}
}
template <class Comparator>
char* InlineSkipList<Comparator>::AllocateKey(size_t key_size) {
2015-11-19 23:24:29 +01:00
return const_cast<char*>(AllocateNode(key_size, RandomHeight())->Key());
}
template <class Comparator>
typename InlineSkipList<Comparator>::Node*
InlineSkipList<Comparator>::AllocateNode(size_t key_size, int height) {
auto prefix = sizeof(std::atomic<Node*>) * (height - 1);
// prefix is space for the height - 1 pointers that we store before
// the Node instance (next_[-(height - 1) .. -1]). Node starts at
// raw + prefix, and holds the bottom-mode (level 0) skip list pointer
// next_[0]. key_size is the bytes for the key, which comes just after
// the Node.
char* raw = allocator_->AllocateAligned(prefix + sizeof(Node) + key_size);
Node* x = reinterpret_cast<Node*>(raw + prefix);
// Once we've linked the node into the skip list we don't actually need
// to know its height, because we can implicitly use the fact that we
// traversed into a node at level h to known that h is a valid level
// for that node. We need to convey the height to the Insert step,
// however, so that it can perform the proper links. Since we're not
// using the pointers at the moment, StashHeight temporarily borrow
// storage from next_[0] for that purpose.
x->StashHeight(height);
return x;
}
template <class Comparator>
typename InlineSkipList<Comparator>::Splice*
InlineSkipList<Comparator>::AllocateSplice() {
// size of prev_ and next_
size_t array_size = sizeof(Node*) * (kMaxHeight_ + 1);
char* raw = allocator_->AllocateAligned(sizeof(Splice) + array_size * 2);
Splice* splice = reinterpret_cast<Splice*>(raw);
splice->height_ = 0;
splice->prev_ = reinterpret_cast<Node**>(raw + sizeof(Splice));
splice->next_ = reinterpret_cast<Node**>(raw + sizeof(Splice) + array_size);
return splice;
}
template <class Comparator>
typename InlineSkipList<Comparator>::Splice*
InlineSkipList<Comparator>::AllocateSpliceOnHeap() {
size_t array_size = sizeof(Node*) * (kMaxHeight_ + 1);
char* raw = new char[sizeof(Splice) + array_size * 2];
Splice* splice = reinterpret_cast<Splice*>(raw);
splice->height_ = 0;
splice->prev_ = reinterpret_cast<Node**>(raw + sizeof(Splice));
splice->next_ = reinterpret_cast<Node**>(raw + sizeof(Splice) + array_size);
return splice;
}
template <class Comparator>
bool InlineSkipList<Comparator>::Insert(const char* key) {
return Insert<false>(key, seq_splice_, false);
}
template <class Comparator>
bool InlineSkipList<Comparator>::InsertConcurrently(const char* key) {
Node* prev[kMaxPossibleHeight];
Node* next[kMaxPossibleHeight];
Splice splice;
splice.prev_ = prev;
splice.next_ = next;
return Insert<true>(key, &splice, false);
}
template <class Comparator>
bool InlineSkipList<Comparator>::InsertWithHint(const char* key, void** hint) {
assert(hint != nullptr);
Splice* splice = reinterpret_cast<Splice*>(*hint);
if (splice == nullptr) {
splice = AllocateSplice();
*hint = reinterpret_cast<void*>(splice);
}
return Insert<false>(key, splice, true);
}
template <class Comparator>
bool InlineSkipList<Comparator>::InsertWithHintConcurrently(const char* key,
void** hint) {
assert(hint != nullptr);
Splice* splice = reinterpret_cast<Splice*>(*hint);
if (splice == nullptr) {
splice = AllocateSpliceOnHeap();
*hint = reinterpret_cast<void*>(splice);
}
return Insert<true>(key, splice, true);
}
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
2015-08-15 01:59:07 +02:00
template <class Comparator>
template <bool prefetch_before>
void InlineSkipList<Comparator>::FindSpliceForLevel(const DecodedKey& key,
Node* before, Node* after,
int level, Node** out_prev,
Node** out_next) {
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
2015-08-15 01:59:07 +02:00
while (true) {
Node* next = before->Next(level);
if (next != nullptr) {
PREFETCH(next->Next(level), 0, 1);
}
if (prefetch_before == true) {
if (next != nullptr && level>0) {
PREFETCH(next->Next(level-1), 0, 1);
}
}
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
2015-08-15 01:59:07 +02:00
assert(before == head_ || next == nullptr ||
KeyIsAfterNode(next->Key(), before));
assert(before == head_ || KeyIsAfterNode(key, before));
if (next == after || !KeyIsAfterNode(key, next)) {
// found it
*out_prev = before;
*out_next = next;
return;
}
before = next;
}
}
template <class Comparator>
void InlineSkipList<Comparator>::RecomputeSpliceLevels(const DecodedKey& key,
Splice* splice,
int recompute_level) {
assert(recompute_level > 0);
assert(recompute_level <= splice->height_);
for (int i = recompute_level - 1; i >= 0; --i) {
FindSpliceForLevel<true>(key, splice->prev_[i + 1], splice->next_[i + 1], i,
&splice->prev_[i], &splice->next_[i]);
}
}
template <class Comparator>
template <bool UseCAS>
bool InlineSkipList<Comparator>::Insert(const char* key, Splice* splice,
bool allow_partial_splice_fix) {
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
2015-08-15 01:59:07 +02:00
Node* x = reinterpret_cast<Node*>(const_cast<char*>(key)) - 1;
const DecodedKey key_decoded = compare_.decode_key(key);
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
2015-08-15 01:59:07 +02:00
int height = x->UnstashHeight();
assert(height >= 1 && height <= kMaxHeight_);
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
2015-08-15 01:59:07 +02:00
int max_height = max_height_.load(std::memory_order_relaxed);
while (height > max_height) {
if (max_height_.compare_exchange_weak(max_height, height)) {
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
2015-08-15 01:59:07 +02:00
// successfully updated it
max_height = height;
break;
}
// else retry, possibly exiting the loop because somebody else
// increased it
}
assert(max_height <= kMaxPossibleHeight);
int recompute_height = 0;
if (splice->height_ < max_height) {
// Either splice has never been used or max_height has grown since
// last use. We could potentially fix it in the latter case, but
// that is tricky.
splice->prev_[max_height] = head_;
splice->next_[max_height] = nullptr;
splice->height_ = max_height;
recompute_height = max_height;
} else {
// Splice is a valid proper-height splice that brackets some
// key, but does it bracket this one? We need to validate it and
// recompute a portion of the splice (levels 0..recompute_height-1)
// that is a superset of all levels that don't bracket the new key.
// Several choices are reasonable, because we have to balance the work
// saved against the extra comparisons required to validate the Splice.
//
// One strategy is just to recompute all of orig_splice_height if the
// bottom level isn't bracketing. This pessimistically assumes that
// we will either get a perfect Splice hit (increasing sequential
// inserts) or have no locality.
//
// Another strategy is to walk up the Splice's levels until we find
// a level that brackets the key. This strategy lets the Splice
// hint help for other cases: it turns insertion from O(log N) into
// O(log D), where D is the number of nodes in between the key that
// produced the Splice and the current insert (insertion is aided
// whether the new key is before or after the splice). If you have
// a way of using a prefix of the key to map directly to the closest
// Splice out of O(sqrt(N)) Splices and we make it so that splices
// can also be used as hints during read, then we end up with Oshman's
// and Shavit's SkipTrie, which has O(log log N) lookup and insertion
// (compare to O(log N) for skip list).
//
// We control the pessimistic strategy with allow_partial_splice_fix.
// A good strategy is probably to be pessimistic for seq_splice_,
// optimistic if the caller actually went to the work of providing
// a Splice.
while (recompute_height < max_height) {
if (splice->prev_[recompute_height]->Next(recompute_height) !=
splice->next_[recompute_height]) {
// splice isn't tight at this level, there must have been some inserts
// to this
// location that didn't update the splice. We might only be a little
// stale, but if
// the splice is very stale it would be O(N) to fix it. We haven't used
// up any of
// our budget of comparisons, so always move up even if we are
// pessimistic about
// our chances of success.
++recompute_height;
} else if (splice->prev_[recompute_height] != head_ &&
!KeyIsAfterNode(key_decoded,
splice->prev_[recompute_height])) {
// key is from before splice
if (allow_partial_splice_fix) {
// skip all levels with the same node without more comparisons
Node* bad = splice->prev_[recompute_height];
while (splice->prev_[recompute_height] == bad) {
++recompute_height;
}
} else {
// we're pessimistic, recompute everything
recompute_height = max_height;
}
} else if (KeyIsAfterNode(key_decoded,
splice->next_[recompute_height])) {
// key is from after splice
if (allow_partial_splice_fix) {
Node* bad = splice->next_[recompute_height];
while (splice->next_[recompute_height] == bad) {
++recompute_height;
}
} else {
recompute_height = max_height;
}
} else {
// this level brackets the key, we won!
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
2015-08-15 01:59:07 +02:00
break;
}
}
}
assert(recompute_height <= max_height);
if (recompute_height > 0) {
RecomputeSpliceLevels(key_decoded, splice, recompute_height);
}
bool splice_is_valid = true;
if (UseCAS) {
for (int i = 0; i < height; ++i) {
while (true) {
// Checking for duplicate keys on the level 0 is sufficient
if (UNLIKELY(i == 0 && splice->next_[i] != nullptr &&
compare_(x->Key(), splice->next_[i]->Key()) >= 0)) {
// duplicate key
return false;
}
if (UNLIKELY(i == 0 && splice->prev_[i] != head_ &&
compare_(splice->prev_[i]->Key(), x->Key()) >= 0)) {
// duplicate key
return false;
}
assert(splice->next_[i] == nullptr ||
compare_(x->Key(), splice->next_[i]->Key()) < 0);
assert(splice->prev_[i] == head_ ||
compare_(splice->prev_[i]->Key(), x->Key()) < 0);
x->NoBarrier_SetNext(i, splice->next_[i]);
if (splice->prev_[i]->CASNext(i, splice->next_[i], x)) {
// success
break;
}
// CAS failed, we need to recompute prev and next. It is unlikely
// to be helpful to try to use a different level as we redo the
// search, because it should be unlikely that lots of nodes have
// been inserted between prev[i] and next[i]. No point in using
// next[i] as the after hint, because we know it is stale.
FindSpliceForLevel<false>(key_decoded, splice->prev_[i], nullptr, i,
&splice->prev_[i], &splice->next_[i]);
// Since we've narrowed the bracket for level i, we might have
// violated the Splice constraint between i and i-1. Make sure
// we recompute the whole thing next time.
if (i > 0) {
splice_is_valid = false;
}
}
}
} else {
for (int i = 0; i < height; ++i) {
if (i >= recompute_height &&
splice->prev_[i]->Next(i) != splice->next_[i]) {
FindSpliceForLevel<false>(key_decoded, splice->prev_[i], nullptr, i,
&splice->prev_[i], &splice->next_[i]);
}
// Checking for duplicate keys on the level 0 is sufficient
if (UNLIKELY(i == 0 && splice->next_[i] != nullptr &&
compare_(x->Key(), splice->next_[i]->Key()) >= 0)) {
// duplicate key
return false;
}
if (UNLIKELY(i == 0 && splice->prev_[i] != head_ &&
compare_(splice->prev_[i]->Key(), x->Key()) >= 0)) {
// duplicate key
return false;
}
assert(splice->next_[i] == nullptr ||
compare_(x->Key(), splice->next_[i]->Key()) < 0);
assert(splice->prev_[i] == head_ ||
compare_(splice->prev_[i]->Key(), x->Key()) < 0);
assert(splice->prev_[i]->Next(i) == splice->next_[i]);
x->NoBarrier_SetNext(i, splice->next_[i]);
splice->prev_[i]->SetNext(i, x);
}
}
if (splice_is_valid) {
for (int i = 0; i < height; ++i) {
splice->prev_[i] = x;
}
assert(splice->prev_[splice->height_] == head_);
assert(splice->next_[splice->height_] == nullptr);
for (int i = 0; i < splice->height_; ++i) {
assert(splice->next_[i] == nullptr ||
compare_(key, splice->next_[i]->Key()) < 0);
assert(splice->prev_[i] == head_ ||
compare_(splice->prev_[i]->Key(), key) <= 0);
assert(splice->prev_[i + 1] == splice->prev_[i] ||
splice->prev_[i + 1] == head_ ||
compare_(splice->prev_[i + 1]->Key(), splice->prev_[i]->Key()) <
0);
assert(splice->next_[i + 1] == splice->next_[i] ||
splice->next_[i + 1] == nullptr ||
compare_(splice->next_[i]->Key(), splice->next_[i + 1]->Key()) <
0);
}
} else {
splice->height_ = 0;
}
return true;
}
template <class Comparator>
bool InlineSkipList<Comparator>::Contains(const char* key) const {
Node* x = FindGreaterOrEqual(key);
2015-11-19 23:24:29 +01:00
if (x != nullptr && Equal(key, x->Key())) {
return true;
} else {
return false;
}
}
template <class Comparator>
void InlineSkipList<Comparator>::TEST_Validate() const {
// Interate over all levels at the same time, and verify nodes appear in
// the right order, and nodes appear in upper level also appear in lower
// levels.
Node* nodes[kMaxPossibleHeight];
int max_height = GetMaxHeight();
assert(max_height > 0);
for (int i = 0; i < max_height; i++) {
nodes[i] = head_;
}
while (nodes[0] != nullptr) {
Node* l0_next = nodes[0]->Next(0);
if (l0_next == nullptr) {
break;
}
assert(nodes[0] == head_ || compare_(nodes[0]->Key(), l0_next->Key()) < 0);
nodes[0] = l0_next;
int i = 1;
while (i < max_height) {
Node* next = nodes[i]->Next(i);
if (next == nullptr) {
break;
}
auto cmp = compare_(nodes[0]->Key(), next->Key());
assert(cmp <= 0);
if (cmp == 0) {
assert(next == nodes[0]);
nodes[i] = next;
} else {
break;
}
i++;
}
}
for (int i = 1; i < max_height; i++) {
assert(nodes[i] != nullptr && nodes[i]->Next(i) == nullptr);
}
}
} // namespace ROCKSDB_NAMESPACE