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rocksdb/cache/clock_cache.cc

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27 KiB

// Copyright (c) 2011-present, Facebook, Inc. All rights reserved.
// This source code is licensed under both the GPLv2 (found in the
// COPYING file in the root directory) and Apache 2.0 License
// (found in the LICENSE.Apache file in the root directory).
//
// Copyright (c) 2011 The LevelDB Authors. All rights reserved.
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file. See the AUTHORS file for names of contributors.
#include "cache/clock_cache.h"
#ifndef SUPPORT_CLOCK_CACHE
namespace ROCKSDB_NAMESPACE {
std::shared_ptr<Cache> NewClockCache(
size_t /*capacity*/, int /*num_shard_bits*/, bool /*strict_capacity_limit*/,
CacheMetadataChargePolicy /*metadata_charge_policy*/) {
// Clock cache not supported.
return nullptr;
}
} // namespace ROCKSDB_NAMESPACE
#else
#include <assert.h>
#include <atomic>
#include <deque>
// "tbb/concurrent_hash_map.h" requires RTTI if exception is enabled.
// Disable it so users can chooose to disable RTTI.
#ifndef ROCKSDB_USE_RTTI
#define TBB_USE_EXCEPTIONS 0
#endif
#include "tbb/concurrent_hash_map.h"
#include "cache/sharded_cache.h"
#include "port/malloc.h"
#include "port/port.h"
#include "util/autovector.h"
#include "util/mutexlock.h"
namespace ROCKSDB_NAMESPACE {
namespace {
// An implementation of the Cache interface based on CLOCK algorithm, with
// better concurrent performance than LRUCache. The idea of CLOCK algorithm
// is to maintain all cache entries in a circular list, and an iterator
// (the "head") pointing to the last examined entry. Eviction starts from the
// current head. Each entry is given a second chance before eviction, if it
// has been access since last examine. In contrast to LRU, no modification
// to the internal data-structure (except for flipping the usage bit) needs
// to be done upon lookup. This gives us oppertunity to implement a cache
// with better concurrency.
//
// Each cache entry is represented by a cache handle, and all the handles
// are arranged in a circular list, as describe above. Upon erase of an entry,
// we never remove the handle. Instead, the handle is put into a recycle bin
// to be re-use. This is to avoid memory dealocation, which is hard to deal
// with in concurrent environment.
//
// The cache also maintains a concurrent hash map for lookup. Any concurrent
// hash map implementation should do the work. We currently use
// tbb::concurrent_hash_map because it supports concurrent erase.
//
// Each cache handle has the following flags and counters, which are squeeze
// in an atomic interger, to make sure the handle always be in a consistent
// state:
//
// * In-cache bit: whether the entry is reference by the cache itself. If
// an entry is in cache, its key would also be available in the hash map.
// * Usage bit: whether the entry has been access by user since last
// examine for eviction. Can be reset by eviction.
// * Reference count: reference count by user.
//
// An entry can be reference only when it's in cache. An entry can be evicted
// only when it is in cache, has no usage since last examine, and reference
// count is zero.
//
// The follow figure shows a possible layout of the cache. Boxes represents
// cache handles and numbers in each box being in-cache bit, usage bit and
// reference count respectively.
//
// hash map:
// +-------+--------+
// | key | handle |
// +-------+--------+
// | "foo" | 5 |-------------------------------------+
// +-------+--------+ |
// | "bar" | 2 |--+ |
// +-------+--------+ | |
// | |
// head | |
// | | |
// circular list: | | |
// +-------+ +-------+ +-------+ +-------+ +-------+ +-------
// |(0,0,0)|---|(1,1,0)|---|(0,0,0)|---|(0,1,3)|---|(1,0,0)|---| ...
// +-------+ +-------+ +-------+ +-------+ +-------+ +-------
// | |
// +-------+ +-----------+
// | |
// +---+---+
// recycle bin: | 1 | 3 |
// +---+---+
//
// Suppose we try to insert "baz" into the cache at this point and the cache is
// full. The cache will first look for entries to evict, starting from where
// head points to (the second entry). It resets usage bit of the second entry,
// skips the third and fourth entry since they are not in cache, and finally
// evict the fifth entry ("foo"). It looks at recycle bin for available handle,
// grabs handle 3, and insert the key into the handle. The following figure
// shows the resulting layout.
//
// hash map:
// +-------+--------+
// | key | handle |
// +-------+--------+
// | "baz" | 3 |-------------+
// +-------+--------+ |
// | "bar" | 2 |--+ |
// +-------+--------+ | |
// | |
// | | head
// | | |
// circular list: | | |
// +-------+ +-------+ +-------+ +-------+ +-------+ +-------
// |(0,0,0)|---|(1,0,0)|---|(1,0,0)|---|(0,1,3)|---|(0,0,0)|---| ...
// +-------+ +-------+ +-------+ +-------+ +-------+ +-------
// | |
// +-------+ +-----------------------------------+
// | |
// +---+---+
// recycle bin: | 1 | 5 |
// +---+---+
//
// A global mutex guards the circular list, the head, and the recycle bin.
// We additionally require that modifying the hash map needs to hold the mutex.
// As such, Modifying the cache (such as Insert() and Erase()) require to
// hold the mutex. Lookup() only access the hash map and the flags associated
// with each handle, and don't require explicit locking. Release() has to
// acquire the mutex only when it releases the last reference to the entry and
// the entry has been erased from cache explicitly. A future improvement could
// be to remove the mutex completely.
//
// Benchmark:
// We run readrandom db_bench on a test DB of size 13GB, with size of each
// level:
//
// Level Files Size(MB)
// -------------------------
// L0 1 0.01
// L1 18 17.32
// L2 230 182.94
// L3 1186 1833.63
// L4 4602 8140.30
//
// We test with both 32 and 16 read threads, with 2GB cache size (the whole DB
// doesn't fits in) and 64GB cache size (the whole DB can fit in cache), and
// whether to put index and filter blocks in block cache. The benchmark runs
// with
// with RocksDB 4.10. We got the following result:
//
// Threads Cache Cache ClockCache LRUCache
// Size Index/Filter Throughput(MB/s) Hit Throughput(MB/s) Hit
// 32 2GB yes 466.7 85.9% 433.7 86.5%
// 32 2GB no 529.9 72.7% 532.7 73.9%
// 32 64GB yes 649.9 99.9% 507.9 99.9%
// 32 64GB no 740.4 99.9% 662.8 99.9%
// 16 2GB yes 278.4 85.9% 283.4 86.5%
// 16 2GB no 318.6 72.7% 335.8 73.9%
// 16 64GB yes 391.9 99.9% 353.3 99.9%
// 16 64GB no 433.8 99.8% 419.4 99.8%
// Cache entry meta data.
struct CacheHandle {
Slice key;
uint32_t hash;
void* value;
size_t charge;
void (*deleter)(const Slice&, void* value);
// Flags and counters associated with the cache handle:
// lowest bit: in-cache bit
// second lowest bit: usage bit
// the rest bits: reference count
// The handle is unused when flags equals to 0. The thread decreases the count
// to 0 is responsible to put the handle back to recycle_ and cleanup memory.
std::atomic<uint32_t> flags;
CacheHandle() = default;
CacheHandle(const CacheHandle& a) { *this = a; }
CacheHandle(const Slice& k, void* v,
void (*del)(const Slice& key, void* value))
: key(k), value(v), deleter(del) {}
CacheHandle& operator=(const CacheHandle& a) {
// Only copy members needed for deletion.
key = a.key;
value = a.value;
deleter = a.deleter;
return *this;
}
inline static size_t CalcTotalCharge(
Slice key, size_t charge,
CacheMetadataChargePolicy metadata_charge_policy) {
size_t meta_charge = 0;
if (metadata_charge_policy == kFullChargeCacheMetadata) {
meta_charge += sizeof(CacheHandle);
#ifdef ROCKSDB_MALLOC_USABLE_SIZE
meta_charge +=
malloc_usable_size(static_cast<void*>(const_cast<char*>(key.data())));
#else
meta_charge += key.size();
#endif
}
return charge + meta_charge;
}
inline size_t CalcTotalCharge(
CacheMetadataChargePolicy metadata_charge_policy) {
return CalcTotalCharge(key, charge, metadata_charge_policy);
}
};
// Key of hash map. We store hash value with the key for convenience.
struct CacheKey {
Slice key;
uint32_t hash_value;
CacheKey() = default;
CacheKey(const Slice& k, uint32_t h) {
key = k;
hash_value = h;
}
static bool equal(const CacheKey& a, const CacheKey& b) {
return a.hash_value == b.hash_value && a.key == b.key;
}
static size_t hash(const CacheKey& a) {
return static_cast<size_t>(a.hash_value);
}
};
struct CleanupContext {
// List of values to be deleted, along with the key and deleter.
autovector<CacheHandle> to_delete_value;
// List of keys to be deleted.
autovector<const char*> to_delete_key;
};
// A cache shard which maintains its own CLOCK cache.
class ClockCacheShard final : public CacheShard {
public:
// Hash map type.
typedef tbb::concurrent_hash_map<CacheKey, CacheHandle*, CacheKey> HashTable;
ClockCacheShard();
~ClockCacheShard() override;
// Interfaces
void SetCapacity(size_t capacity) override;
void SetStrictCapacityLimit(bool strict_capacity_limit) override;
Status Insert(const Slice& key, uint32_t hash, void* value, size_t charge,
void (*deleter)(const Slice& key, void* value),
Cache::Handle** handle, Cache::Priority priority) override;
Cache::Handle* Lookup(const Slice& key, uint32_t hash) override;
// If the entry in in cache, increase reference count and return true.
// Return false otherwise.
//
// Not necessary to hold mutex_ before being called.
bool Ref(Cache::Handle* handle) override;
bool Release(Cache::Handle* handle, bool force_erase = false) override;
void Erase(const Slice& key, uint32_t hash) override;
bool EraseAndConfirm(const Slice& key, uint32_t hash,
CleanupContext* context);
size_t GetUsage() const override;
size_t GetPinnedUsage() const override;
void EraseUnRefEntries() override;
void ApplyToAllCacheEntries(void (*callback)(void*, size_t),
bool thread_safe) override;
private:
static const uint32_t kInCacheBit = 1;
static const uint32_t kUsageBit = 2;
static const uint32_t kRefsOffset = 2;
static const uint32_t kOneRef = 1 << kRefsOffset;
// Helper functions to extract cache handle flags and counters.
static bool InCache(uint32_t flags) { return flags & kInCacheBit; }
static bool HasUsage(uint32_t flags) { return flags & kUsageBit; }
static uint32_t CountRefs(uint32_t flags) { return flags >> kRefsOffset; }
// Decrease reference count of the entry. If this decreases the count to 0,
// recycle the entry. If set_usage is true, also set the usage bit.
//
// returns true if a value is erased.
//
// Not necessary to hold mutex_ before being called.
bool Unref(CacheHandle* handle, bool set_usage, CleanupContext* context);
// Unset in-cache bit of the entry. Recycle the handle if necessary.
//
// returns true if a value is erased.
//
// Has to hold mutex_ before being called.
bool UnsetInCache(CacheHandle* handle, CleanupContext* context);
// Put the handle back to recycle_ list, and put the value associated with
// it into to-be-deleted list. It doesn't cleanup the key as it might be
// reused by another handle.
//
// Has to hold mutex_ before being called.
void RecycleHandle(CacheHandle* handle, CleanupContext* context);
// Delete keys and values in to-be-deleted list. Call the method without
// holding mutex, as destructors can be expensive.
void Cleanup(const CleanupContext& context);
// Examine the handle for eviction. If the handle is in cache, usage bit is
// not set, and referece count is 0, evict it from cache. Otherwise unset
// the usage bit.
//
// Has to hold mutex_ before being called.
bool TryEvict(CacheHandle* value, CleanupContext* context);
// Scan through the circular list, evict entries until we get enough capacity
// for new cache entry of specific size. Return true if success, false
// otherwise.
//
// Has to hold mutex_ before being called.
bool EvictFromCache(size_t charge, CleanupContext* context);
CacheHandle* Insert(const Slice& key, uint32_t hash, void* value,
size_t change,
void (*deleter)(const Slice& key, void* value),
Stats for redundant insertions into block cache (#6681) Summary: Since read threads do not coordinate on loading data into block cache, two threads between Lookup and Insert can end up loading and inserting the same data. This is particularly concerning with cache_index_and_filter_blocks since those are hot and more likely to be race targets if ejected from (or not pre-populated in) the cache. Particularly with moves toward disaggregated / network storage, the cost of redundant retrieval might be high, and we should at least have some hard statistics from which we can estimate impact. Example with full filter thrashing "cliff": $ ./db_bench --benchmarks=fillrandom --num=15000000 --cache_index_and_filter_blocks -bloom_bits=10 ... $ ./db_bench --db=/tmp/rocksdbtest-172704/dbbench --use_existing_db --benchmarks=readrandom,stats --num=200000 --cache_index_and_filter_blocks --cache_size=$((130 * 1024 * 1024)) --bloom_bits=10 --threads=16 -statistics 2>&1 | egrep '^rocksdb.block.cache.(.*add|.*redundant)' | grep -v compress | sort rocksdb.block.cache.add COUNT : 14181 rocksdb.block.cache.add.failures COUNT : 0 rocksdb.block.cache.add.redundant COUNT : 476 rocksdb.block.cache.data.add COUNT : 12749 rocksdb.block.cache.data.add.redundant COUNT : 18 rocksdb.block.cache.filter.add COUNT : 1003 rocksdb.block.cache.filter.add.redundant COUNT : 217 rocksdb.block.cache.index.add COUNT : 429 rocksdb.block.cache.index.add.redundant COUNT : 241 $ ./db_bench --db=/tmp/rocksdbtest-172704/dbbench --use_existing_db --benchmarks=readrandom,stats --num=200000 --cache_index_and_filter_blocks --cache_size=$((120 * 1024 * 1024)) --bloom_bits=10 --threads=16 -statistics 2>&1 | egrep '^rocksdb.block.cache.(.*add|.*redundant)' | grep -v compress | sort rocksdb.block.cache.add COUNT : 1182223 rocksdb.block.cache.add.failures COUNT : 0 rocksdb.block.cache.add.redundant COUNT : 302728 rocksdb.block.cache.data.add COUNT : 31425 rocksdb.block.cache.data.add.redundant COUNT : 12 rocksdb.block.cache.filter.add COUNT : 795455 rocksdb.block.cache.filter.add.redundant COUNT : 130238 rocksdb.block.cache.index.add COUNT : 355343 rocksdb.block.cache.index.add.redundant COUNT : 172478 Pull Request resolved: https://github.com/facebook/rocksdb/pull/6681 Test Plan: Some manual testing (above) and unit test covering key metrics is included Reviewed By: ltamasi Differential Revision: D21134113 Pulled By: pdillinger fbshipit-source-id: c11497b5f00f4ffdfe919823904e52d0a1a91d87
5 years ago
bool hold_reference, CleanupContext* context,
bool* overwritten);
// Guards list_, head_, and recycle_. In addition, updating table_ also has
// to hold the mutex, to avoid the cache being in inconsistent state.
mutable port::Mutex mutex_;
// The circular list of cache handles. Initially the list is empty. Once a
// handle is needed by insertion, and no more handles are available in
// recycle bin, one more handle is appended to the end.
//
// We use std::deque for the circular list because we want to make sure
// pointers to handles are valid through out the life-cycle of the cache
// (in contrast to std::vector), and be able to grow the list (in contrast
// to statically allocated arrays).
std::deque<CacheHandle> list_;
// Pointer to the next handle in the circular list to be examine for
// eviction.
size_t head_;
// Recycle bin of cache handles.
autovector<CacheHandle*> recycle_;
// Maximum cache size.
std::atomic<size_t> capacity_;
// Current total size of the cache.
std::atomic<size_t> usage_;
// Total un-released cache size.
std::atomic<size_t> pinned_usage_;
// Whether allow insert into cache if cache is full.
std::atomic<bool> strict_capacity_limit_;
// Hash table (tbb::concurrent_hash_map) for lookup.
HashTable table_;
};
ClockCacheShard::ClockCacheShard()
: head_(0), usage_(0), pinned_usage_(0), strict_capacity_limit_(false) {}
ClockCacheShard::~ClockCacheShard() {
for (auto& handle : list_) {
uint32_t flags = handle.flags.load(std::memory_order_relaxed);
if (InCache(flags) || CountRefs(flags) > 0) {
if (handle.deleter != nullptr) {
(*handle.deleter)(handle.key, handle.value);
}
delete[] handle.key.data();
}
}
}
size_t ClockCacheShard::GetUsage() const {
return usage_.load(std::memory_order_relaxed);
}
size_t ClockCacheShard::GetPinnedUsage() const {
return pinned_usage_.load(std::memory_order_relaxed);
}
void ClockCacheShard::ApplyToAllCacheEntries(void (*callback)(void*, size_t),
bool thread_safe) {
if (thread_safe) {
mutex_.Lock();
}
for (auto& handle : list_) {
// Use relaxed semantics instead of acquire semantics since we are either
// holding mutex, or don't have thread safe requirement.
uint32_t flags = handle.flags.load(std::memory_order_relaxed);
if (InCache(flags)) {
callback(handle.value, handle.charge);
}
}
if (thread_safe) {
mutex_.Unlock();
}
}
void ClockCacheShard::RecycleHandle(CacheHandle* handle,
CleanupContext* context) {
mutex_.AssertHeld();
assert(!InCache(handle->flags) && CountRefs(handle->flags) == 0);
context->to_delete_key.push_back(handle->key.data());
context->to_delete_value.emplace_back(*handle);
size_t total_charge = handle->CalcTotalCharge(metadata_charge_policy_);
handle->key.clear();
handle->value = nullptr;
handle->deleter = nullptr;
recycle_.push_back(handle);
usage_.fetch_sub(total_charge, std::memory_order_relaxed);
}
void ClockCacheShard::Cleanup(const CleanupContext& context) {
for (const CacheHandle& handle : context.to_delete_value) {
if (handle.deleter) {
(*handle.deleter)(handle.key, handle.value);
}
}
for (const char* key : context.to_delete_key) {
delete[] key;
}
}
bool ClockCacheShard::Ref(Cache::Handle* h) {
auto handle = reinterpret_cast<CacheHandle*>(h);
// CAS loop to increase reference count.
uint32_t flags = handle->flags.load(std::memory_order_relaxed);
while (InCache(flags)) {
// Use acquire semantics on success, as further operations on the cache
// entry has to be order after reference count is increased.
if (handle->flags.compare_exchange_weak(flags, flags + kOneRef,
std::memory_order_acquire,
std::memory_order_relaxed)) {
if (CountRefs(flags) == 0) {
// No reference count before the operation.
size_t total_charge = handle->CalcTotalCharge(metadata_charge_policy_);
pinned_usage_.fetch_add(total_charge, std::memory_order_relaxed);
}
return true;
}
}
return false;
}
bool ClockCacheShard::Unref(CacheHandle* handle, bool set_usage,
CleanupContext* context) {
if (set_usage) {
handle->flags.fetch_or(kUsageBit, std::memory_order_relaxed);
}
// Use acquire-release semantics as previous operations on the cache entry
// has to be order before reference count is decreased, and potential cleanup
// of the entry has to be order after.
uint32_t flags = handle->flags.fetch_sub(kOneRef, std::memory_order_acq_rel);
assert(CountRefs(flags) > 0);
if (CountRefs(flags) == 1) {
// this is the last reference.
size_t total_charge = handle->CalcTotalCharge(metadata_charge_policy_);
pinned_usage_.fetch_sub(total_charge, std::memory_order_relaxed);
// Cleanup if it is the last reference.
if (!InCache(flags)) {
MutexLock l(&mutex_);
RecycleHandle(handle, context);
}
}
return context->to_delete_value.size();
}
bool ClockCacheShard::UnsetInCache(CacheHandle* handle,
CleanupContext* context) {
mutex_.AssertHeld();
// Use acquire-release semantics as previous operations on the cache entry
// has to be order before reference count is decreased, and potential cleanup
// of the entry has to be order after.
uint32_t flags =
handle->flags.fetch_and(~kInCacheBit, std::memory_order_acq_rel);
// Cleanup if it is the last reference.
if (InCache(flags) && CountRefs(flags) == 0) {
RecycleHandle(handle, context);
}
return context->to_delete_value.size();
}
bool ClockCacheShard::TryEvict(CacheHandle* handle, CleanupContext* context) {
mutex_.AssertHeld();
uint32_t flags = kInCacheBit;
if (handle->flags.compare_exchange_strong(flags, 0, std::memory_order_acquire,
std::memory_order_relaxed)) {
bool erased __attribute__((__unused__)) =
table_.erase(CacheKey(handle->key, handle->hash));
assert(erased);
RecycleHandle(handle, context);
return true;
}
handle->flags.fetch_and(~kUsageBit, std::memory_order_relaxed);
return false;
}
bool ClockCacheShard::EvictFromCache(size_t charge, CleanupContext* context) {
size_t usage = usage_.load(std::memory_order_relaxed);
size_t capacity = capacity_.load(std::memory_order_relaxed);
if (usage == 0) {
return charge <= capacity;
}
size_t new_head = head_;
bool second_iteration = false;
while (usage + charge > capacity) {
assert(new_head < list_.size());
if (TryEvict(&list_[new_head], context)) {
usage = usage_.load(std::memory_order_relaxed);
}
new_head = (new_head + 1 >= list_.size()) ? 0 : new_head + 1;
if (new_head == head_) {
if (second_iteration) {
return false;
} else {
second_iteration = true;
}
}
}
head_ = new_head;
return true;
}
void ClockCacheShard::SetCapacity(size_t capacity) {
CleanupContext context;
{
MutexLock l(&mutex_);
capacity_.store(capacity, std::memory_order_relaxed);
EvictFromCache(0, &context);
}
Cleanup(context);
}
void ClockCacheShard::SetStrictCapacityLimit(bool strict_capacity_limit) {
strict_capacity_limit_.store(strict_capacity_limit,
std::memory_order_relaxed);
}
CacheHandle* ClockCacheShard::Insert(
const Slice& key, uint32_t hash, void* value, size_t charge,
void (*deleter)(const Slice& key, void* value), bool hold_reference,
Stats for redundant insertions into block cache (#6681) Summary: Since read threads do not coordinate on loading data into block cache, two threads between Lookup and Insert can end up loading and inserting the same data. This is particularly concerning with cache_index_and_filter_blocks since those are hot and more likely to be race targets if ejected from (or not pre-populated in) the cache. Particularly with moves toward disaggregated / network storage, the cost of redundant retrieval might be high, and we should at least have some hard statistics from which we can estimate impact. Example with full filter thrashing "cliff": $ ./db_bench --benchmarks=fillrandom --num=15000000 --cache_index_and_filter_blocks -bloom_bits=10 ... $ ./db_bench --db=/tmp/rocksdbtest-172704/dbbench --use_existing_db --benchmarks=readrandom,stats --num=200000 --cache_index_and_filter_blocks --cache_size=$((130 * 1024 * 1024)) --bloom_bits=10 --threads=16 -statistics 2>&1 | egrep '^rocksdb.block.cache.(.*add|.*redundant)' | grep -v compress | sort rocksdb.block.cache.add COUNT : 14181 rocksdb.block.cache.add.failures COUNT : 0 rocksdb.block.cache.add.redundant COUNT : 476 rocksdb.block.cache.data.add COUNT : 12749 rocksdb.block.cache.data.add.redundant COUNT : 18 rocksdb.block.cache.filter.add COUNT : 1003 rocksdb.block.cache.filter.add.redundant COUNT : 217 rocksdb.block.cache.index.add COUNT : 429 rocksdb.block.cache.index.add.redundant COUNT : 241 $ ./db_bench --db=/tmp/rocksdbtest-172704/dbbench --use_existing_db --benchmarks=readrandom,stats --num=200000 --cache_index_and_filter_blocks --cache_size=$((120 * 1024 * 1024)) --bloom_bits=10 --threads=16 -statistics 2>&1 | egrep '^rocksdb.block.cache.(.*add|.*redundant)' | grep -v compress | sort rocksdb.block.cache.add COUNT : 1182223 rocksdb.block.cache.add.failures COUNT : 0 rocksdb.block.cache.add.redundant COUNT : 302728 rocksdb.block.cache.data.add COUNT : 31425 rocksdb.block.cache.data.add.redundant COUNT : 12 rocksdb.block.cache.filter.add COUNT : 795455 rocksdb.block.cache.filter.add.redundant COUNT : 130238 rocksdb.block.cache.index.add COUNT : 355343 rocksdb.block.cache.index.add.redundant COUNT : 172478 Pull Request resolved: https://github.com/facebook/rocksdb/pull/6681 Test Plan: Some manual testing (above) and unit test covering key metrics is included Reviewed By: ltamasi Differential Revision: D21134113 Pulled By: pdillinger fbshipit-source-id: c11497b5f00f4ffdfe919823904e52d0a1a91d87
5 years ago
CleanupContext* context, bool* overwritten) {
assert(overwritten != nullptr && *overwritten == false);
size_t total_charge =
CacheHandle::CalcTotalCharge(key, charge, metadata_charge_policy_);
MutexLock l(&mutex_);
bool success = EvictFromCache(total_charge, context);
bool strict = strict_capacity_limit_.load(std::memory_order_relaxed);
if (!success && (strict || !hold_reference)) {
context->to_delete_key.push_back(key.data());
if (!hold_reference) {
context->to_delete_value.emplace_back(key, value, deleter);
}
return nullptr;
}
// Grab available handle from recycle bin. If recycle bin is empty, create
// and append new handle to end of circular list.
CacheHandle* handle = nullptr;
if (!recycle_.empty()) {
handle = recycle_.back();
recycle_.pop_back();
} else {
list_.emplace_back();
handle = &list_.back();
}
// Fill handle.
handle->key = key;
handle->hash = hash;
handle->value = value;
handle->charge = charge;
handle->deleter = deleter;
uint32_t flags = hold_reference ? kInCacheBit + kOneRef : kInCacheBit;
handle->flags.store(flags, std::memory_order_relaxed);
HashTable::accessor accessor;
if (table_.find(accessor, CacheKey(key, hash))) {
Stats for redundant insertions into block cache (#6681) Summary: Since read threads do not coordinate on loading data into block cache, two threads between Lookup and Insert can end up loading and inserting the same data. This is particularly concerning with cache_index_and_filter_blocks since those are hot and more likely to be race targets if ejected from (or not pre-populated in) the cache. Particularly with moves toward disaggregated / network storage, the cost of redundant retrieval might be high, and we should at least have some hard statistics from which we can estimate impact. Example with full filter thrashing "cliff": $ ./db_bench --benchmarks=fillrandom --num=15000000 --cache_index_and_filter_blocks -bloom_bits=10 ... $ ./db_bench --db=/tmp/rocksdbtest-172704/dbbench --use_existing_db --benchmarks=readrandom,stats --num=200000 --cache_index_and_filter_blocks --cache_size=$((130 * 1024 * 1024)) --bloom_bits=10 --threads=16 -statistics 2>&1 | egrep '^rocksdb.block.cache.(.*add|.*redundant)' | grep -v compress | sort rocksdb.block.cache.add COUNT : 14181 rocksdb.block.cache.add.failures COUNT : 0 rocksdb.block.cache.add.redundant COUNT : 476 rocksdb.block.cache.data.add COUNT : 12749 rocksdb.block.cache.data.add.redundant COUNT : 18 rocksdb.block.cache.filter.add COUNT : 1003 rocksdb.block.cache.filter.add.redundant COUNT : 217 rocksdb.block.cache.index.add COUNT : 429 rocksdb.block.cache.index.add.redundant COUNT : 241 $ ./db_bench --db=/tmp/rocksdbtest-172704/dbbench --use_existing_db --benchmarks=readrandom,stats --num=200000 --cache_index_and_filter_blocks --cache_size=$((120 * 1024 * 1024)) --bloom_bits=10 --threads=16 -statistics 2>&1 | egrep '^rocksdb.block.cache.(.*add|.*redundant)' | grep -v compress | sort rocksdb.block.cache.add COUNT : 1182223 rocksdb.block.cache.add.failures COUNT : 0 rocksdb.block.cache.add.redundant COUNT : 302728 rocksdb.block.cache.data.add COUNT : 31425 rocksdb.block.cache.data.add.redundant COUNT : 12 rocksdb.block.cache.filter.add COUNT : 795455 rocksdb.block.cache.filter.add.redundant COUNT : 130238 rocksdb.block.cache.index.add COUNT : 355343 rocksdb.block.cache.index.add.redundant COUNT : 172478 Pull Request resolved: https://github.com/facebook/rocksdb/pull/6681 Test Plan: Some manual testing (above) and unit test covering key metrics is included Reviewed By: ltamasi Differential Revision: D21134113 Pulled By: pdillinger fbshipit-source-id: c11497b5f00f4ffdfe919823904e52d0a1a91d87
5 years ago
*overwritten = true;
CacheHandle* existing_handle = accessor->second;
table_.erase(accessor);
UnsetInCache(existing_handle, context);
}
table_.insert(HashTable::value_type(CacheKey(key, hash), handle));
if (hold_reference) {
pinned_usage_.fetch_add(total_charge, std::memory_order_relaxed);
}
usage_.fetch_add(total_charge, std::memory_order_relaxed);
return handle;
}
Status ClockCacheShard::Insert(const Slice& key, uint32_t hash, void* value,
size_t charge,
void (*deleter)(const Slice& key, void* value),
Cache::Handle** out_handle,
Cache::Priority /*priority*/) {
CleanupContext context;
HashTable::accessor accessor;
char* key_data = new char[key.size()];
memcpy(key_data, key.data(), key.size());
Slice key_copy(key_data, key.size());
Stats for redundant insertions into block cache (#6681) Summary: Since read threads do not coordinate on loading data into block cache, two threads between Lookup and Insert can end up loading and inserting the same data. This is particularly concerning with cache_index_and_filter_blocks since those are hot and more likely to be race targets if ejected from (or not pre-populated in) the cache. Particularly with moves toward disaggregated / network storage, the cost of redundant retrieval might be high, and we should at least have some hard statistics from which we can estimate impact. Example with full filter thrashing "cliff": $ ./db_bench --benchmarks=fillrandom --num=15000000 --cache_index_and_filter_blocks -bloom_bits=10 ... $ ./db_bench --db=/tmp/rocksdbtest-172704/dbbench --use_existing_db --benchmarks=readrandom,stats --num=200000 --cache_index_and_filter_blocks --cache_size=$((130 * 1024 * 1024)) --bloom_bits=10 --threads=16 -statistics 2>&1 | egrep '^rocksdb.block.cache.(.*add|.*redundant)' | grep -v compress | sort rocksdb.block.cache.add COUNT : 14181 rocksdb.block.cache.add.failures COUNT : 0 rocksdb.block.cache.add.redundant COUNT : 476 rocksdb.block.cache.data.add COUNT : 12749 rocksdb.block.cache.data.add.redundant COUNT : 18 rocksdb.block.cache.filter.add COUNT : 1003 rocksdb.block.cache.filter.add.redundant COUNT : 217 rocksdb.block.cache.index.add COUNT : 429 rocksdb.block.cache.index.add.redundant COUNT : 241 $ ./db_bench --db=/tmp/rocksdbtest-172704/dbbench --use_existing_db --benchmarks=readrandom,stats --num=200000 --cache_index_and_filter_blocks --cache_size=$((120 * 1024 * 1024)) --bloom_bits=10 --threads=16 -statistics 2>&1 | egrep '^rocksdb.block.cache.(.*add|.*redundant)' | grep -v compress | sort rocksdb.block.cache.add COUNT : 1182223 rocksdb.block.cache.add.failures COUNT : 0 rocksdb.block.cache.add.redundant COUNT : 302728 rocksdb.block.cache.data.add COUNT : 31425 rocksdb.block.cache.data.add.redundant COUNT : 12 rocksdb.block.cache.filter.add COUNT : 795455 rocksdb.block.cache.filter.add.redundant COUNT : 130238 rocksdb.block.cache.index.add COUNT : 355343 rocksdb.block.cache.index.add.redundant COUNT : 172478 Pull Request resolved: https://github.com/facebook/rocksdb/pull/6681 Test Plan: Some manual testing (above) and unit test covering key metrics is included Reviewed By: ltamasi Differential Revision: D21134113 Pulled By: pdillinger fbshipit-source-id: c11497b5f00f4ffdfe919823904e52d0a1a91d87
5 years ago
bool overwritten = false;
CacheHandle* handle = Insert(key_copy, hash, value, charge, deleter,
Stats for redundant insertions into block cache (#6681) Summary: Since read threads do not coordinate on loading data into block cache, two threads between Lookup and Insert can end up loading and inserting the same data. This is particularly concerning with cache_index_and_filter_blocks since those are hot and more likely to be race targets if ejected from (or not pre-populated in) the cache. Particularly with moves toward disaggregated / network storage, the cost of redundant retrieval might be high, and we should at least have some hard statistics from which we can estimate impact. Example with full filter thrashing "cliff": $ ./db_bench --benchmarks=fillrandom --num=15000000 --cache_index_and_filter_blocks -bloom_bits=10 ... $ ./db_bench --db=/tmp/rocksdbtest-172704/dbbench --use_existing_db --benchmarks=readrandom,stats --num=200000 --cache_index_and_filter_blocks --cache_size=$((130 * 1024 * 1024)) --bloom_bits=10 --threads=16 -statistics 2>&1 | egrep '^rocksdb.block.cache.(.*add|.*redundant)' | grep -v compress | sort rocksdb.block.cache.add COUNT : 14181 rocksdb.block.cache.add.failures COUNT : 0 rocksdb.block.cache.add.redundant COUNT : 476 rocksdb.block.cache.data.add COUNT : 12749 rocksdb.block.cache.data.add.redundant COUNT : 18 rocksdb.block.cache.filter.add COUNT : 1003 rocksdb.block.cache.filter.add.redundant COUNT : 217 rocksdb.block.cache.index.add COUNT : 429 rocksdb.block.cache.index.add.redundant COUNT : 241 $ ./db_bench --db=/tmp/rocksdbtest-172704/dbbench --use_existing_db --benchmarks=readrandom,stats --num=200000 --cache_index_and_filter_blocks --cache_size=$((120 * 1024 * 1024)) --bloom_bits=10 --threads=16 -statistics 2>&1 | egrep '^rocksdb.block.cache.(.*add|.*redundant)' | grep -v compress | sort rocksdb.block.cache.add COUNT : 1182223 rocksdb.block.cache.add.failures COUNT : 0 rocksdb.block.cache.add.redundant COUNT : 302728 rocksdb.block.cache.data.add COUNT : 31425 rocksdb.block.cache.data.add.redundant COUNT : 12 rocksdb.block.cache.filter.add COUNT : 795455 rocksdb.block.cache.filter.add.redundant COUNT : 130238 rocksdb.block.cache.index.add COUNT : 355343 rocksdb.block.cache.index.add.redundant COUNT : 172478 Pull Request resolved: https://github.com/facebook/rocksdb/pull/6681 Test Plan: Some manual testing (above) and unit test covering key metrics is included Reviewed By: ltamasi Differential Revision: D21134113 Pulled By: pdillinger fbshipit-source-id: c11497b5f00f4ffdfe919823904e52d0a1a91d87
5 years ago
out_handle != nullptr, &context, &overwritten);
Status s;
if (out_handle != nullptr) {
if (handle == nullptr) {
s = Status::Incomplete("Insert failed due to LRU cache being full.");
} else {
*out_handle = reinterpret_cast<Cache::Handle*>(handle);
}
}
Stats for redundant insertions into block cache (#6681) Summary: Since read threads do not coordinate on loading data into block cache, two threads between Lookup and Insert can end up loading and inserting the same data. This is particularly concerning with cache_index_and_filter_blocks since those are hot and more likely to be race targets if ejected from (or not pre-populated in) the cache. Particularly with moves toward disaggregated / network storage, the cost of redundant retrieval might be high, and we should at least have some hard statistics from which we can estimate impact. Example with full filter thrashing "cliff": $ ./db_bench --benchmarks=fillrandom --num=15000000 --cache_index_and_filter_blocks -bloom_bits=10 ... $ ./db_bench --db=/tmp/rocksdbtest-172704/dbbench --use_existing_db --benchmarks=readrandom,stats --num=200000 --cache_index_and_filter_blocks --cache_size=$((130 * 1024 * 1024)) --bloom_bits=10 --threads=16 -statistics 2>&1 | egrep '^rocksdb.block.cache.(.*add|.*redundant)' | grep -v compress | sort rocksdb.block.cache.add COUNT : 14181 rocksdb.block.cache.add.failures COUNT : 0 rocksdb.block.cache.add.redundant COUNT : 476 rocksdb.block.cache.data.add COUNT : 12749 rocksdb.block.cache.data.add.redundant COUNT : 18 rocksdb.block.cache.filter.add COUNT : 1003 rocksdb.block.cache.filter.add.redundant COUNT : 217 rocksdb.block.cache.index.add COUNT : 429 rocksdb.block.cache.index.add.redundant COUNT : 241 $ ./db_bench --db=/tmp/rocksdbtest-172704/dbbench --use_existing_db --benchmarks=readrandom,stats --num=200000 --cache_index_and_filter_blocks --cache_size=$((120 * 1024 * 1024)) --bloom_bits=10 --threads=16 -statistics 2>&1 | egrep '^rocksdb.block.cache.(.*add|.*redundant)' | grep -v compress | sort rocksdb.block.cache.add COUNT : 1182223 rocksdb.block.cache.add.failures COUNT : 0 rocksdb.block.cache.add.redundant COUNT : 302728 rocksdb.block.cache.data.add COUNT : 31425 rocksdb.block.cache.data.add.redundant COUNT : 12 rocksdb.block.cache.filter.add COUNT : 795455 rocksdb.block.cache.filter.add.redundant COUNT : 130238 rocksdb.block.cache.index.add COUNT : 355343 rocksdb.block.cache.index.add.redundant COUNT : 172478 Pull Request resolved: https://github.com/facebook/rocksdb/pull/6681 Test Plan: Some manual testing (above) and unit test covering key metrics is included Reviewed By: ltamasi Differential Revision: D21134113 Pulled By: pdillinger fbshipit-source-id: c11497b5f00f4ffdfe919823904e52d0a1a91d87
5 years ago
if (overwritten) {
assert(s.ok());
s = Status::OkOverwritten();
}
Cleanup(context);
return s;
}
Cache::Handle* ClockCacheShard::Lookup(const Slice& key, uint32_t hash) {
HashTable::const_accessor accessor;
if (!table_.find(accessor, CacheKey(key, hash))) {
return nullptr;
}
CacheHandle* handle = accessor->second;
accessor.release();
// Ref() could fail if another thread sneak in and evict/erase the cache
// entry before we are able to hold reference.
if (!Ref(reinterpret_cast<Cache::Handle*>(handle))) {
return nullptr;
}
// Double check the key since the handle may now representing another key
// if other threads sneak in, evict/erase the entry and re-used the handle
// for another cache entry.
if (hash != handle->hash || key != handle->key) {
CleanupContext context;
Unref(handle, false, &context);
// It is possible Unref() delete the entry, so we need to cleanup.
Cleanup(context);
return nullptr;
}
return reinterpret_cast<Cache::Handle*>(handle);
}
bool ClockCacheShard::Release(Cache::Handle* h, bool force_erase) {
CleanupContext context;
CacheHandle* handle = reinterpret_cast<CacheHandle*>(h);
bool erased = Unref(handle, true, &context);
if (force_erase && !erased) {
erased = EraseAndConfirm(handle->key, handle->hash, &context);
}
Cleanup(context);
return erased;
}
void ClockCacheShard::Erase(const Slice& key, uint32_t hash) {
CleanupContext context;
EraseAndConfirm(key, hash, &context);
Cleanup(context);
}
bool ClockCacheShard::EraseAndConfirm(const Slice& key, uint32_t hash,
CleanupContext* context) {
MutexLock l(&mutex_);
HashTable::accessor accessor;
bool erased = false;
if (table_.find(accessor, CacheKey(key, hash))) {
CacheHandle* handle = accessor->second;
table_.erase(accessor);
erased = UnsetInCache(handle, context);
}
return erased;
}
void ClockCacheShard::EraseUnRefEntries() {
CleanupContext context;
{
MutexLock l(&mutex_);
table_.clear();
for (auto& handle : list_) {
UnsetInCache(&handle, &context);
}
}
Cleanup(context);
}
class ClockCache final : public ShardedCache {
public:
ClockCache(size_t capacity, int num_shard_bits, bool strict_capacity_limit,
CacheMetadataChargePolicy metadata_charge_policy)
: ShardedCache(capacity, num_shard_bits, strict_capacity_limit) {
int num_shards = 1 << num_shard_bits;
shards_ = new ClockCacheShard[num_shards];
for (int i = 0; i < num_shards; i++) {
shards_[i].set_metadata_charge_policy(metadata_charge_policy);
}
SetCapacity(capacity);
SetStrictCapacityLimit(strict_capacity_limit);
}
~ClockCache() override { delete[] shards_; }
const char* Name() const override { return "ClockCache"; }
CacheShard* GetShard(int shard) override {
return reinterpret_cast<CacheShard*>(&shards_[shard]);
}
const CacheShard* GetShard(int shard) const override {
return reinterpret_cast<CacheShard*>(&shards_[shard]);
}
void* Value(Handle* handle) override {
return reinterpret_cast<const CacheHandle*>(handle)->value;
}
size_t GetCharge(Handle* handle) const override {
return reinterpret_cast<const CacheHandle*>(handle)->charge;
}
uint32_t GetHash(Handle* handle) const override {
return reinterpret_cast<const CacheHandle*>(handle)->hash;
}
void DisownData() override { shards_ = nullptr; }
private:
ClockCacheShard* shards_;
};
} // end anonymous namespace
std::shared_ptr<Cache> NewClockCache(
size_t capacity, int num_shard_bits, bool strict_capacity_limit,
CacheMetadataChargePolicy metadata_charge_policy) {
if (num_shard_bits < 0) {
num_shard_bits = GetDefaultCacheShardBits(capacity);
}
return std::make_shared<ClockCache>(
capacity, num_shard_bits, strict_capacity_limit, metadata_charge_policy);
}
} // namespace ROCKSDB_NAMESPACE
#endif // SUPPORT_CLOCK_CACHE