0050a73a4f
Summary: This change standardizes on a new 16-byte cache key format for block cache (incl compressed and secondary) and persistent cache (but not table cache and row cache). The goal is a really fast cache key with practically ideal stability and uniqueness properties without external dependencies (e.g. from FileSystem). A fixed key size of 16 bytes should enable future optimizations to the concurrent hash table for block cache, which is a heavy CPU user / bottleneck, but there appears to be measurable performance improvement even with no changes to LRUCache. This change replaces a lot of disjointed and ugly code handling cache keys with calls to a simple, clean new internal API (cache_key.h). (Preserving the old cache key logic under an option would be very ugly and likely negate the performance gain of the new approach. Complete replacement carries some inherent risk, but I think that's acceptable with sufficient analysis and testing.) The scheme for encoding new cache keys is complicated but explained in cache_key.cc. Also: EndianSwapValue is moved to math.h to be next to other bit operations. (Explains some new include "math.h".) ReverseBits operation added and unit tests added to hash_test for both. Fixes https://github.com/facebook/rocksdb/issues/7405 (presuming a root cause) Pull Request resolved: https://github.com/facebook/rocksdb/pull/9126 Test Plan: ### Basic correctness Several tests needed updates to work with the new functionality, mostly because we are no longer relying on filesystem for stable cache keys so table builders & readers need more context info to agree on cache keys. This functionality is so core, a huge number of existing tests exercise the cache key functionality. ### Performance Create db with `TEST_TMPDIR=/dev/shm ./db_bench -bloom_bits=10 -benchmarks=fillrandom -num=3000000 -partition_index_and_filters` And test performance with `TEST_TMPDIR=/dev/shm ./db_bench -readonly -use_existing_db -bloom_bits=10 -benchmarks=readrandom -num=3000000 -duration=30 -cache_index_and_filter_blocks -cache_size=250000 -threads=4` using DEBUG_LEVEL=0 and simultaneous before & after runs. Before ops/sec, avg over 100 runs: 121924 After ops/sec, avg over 100 runs: 125385 (+2.8%) ### Collision probability I have built a tool, ./cache_bench -stress_cache_key to broadly simulate host-wide cache activity over many months, by making some pessimistic simplifying assumptions: * Every generated file has a cache entry for every byte offset in the file (contiguous range of cache keys) * All of every file is cached for its entire lifetime We use a simple table with skewed address assignment and replacement on address collision to simulate files coming & going, with quite a variance (super-Poisson) in ages. Some output with `./cache_bench -stress_cache_key -sck_keep_bits=40`: ``` Total cache or DBs size: 32TiB Writing 925.926 MiB/s or 76.2939TiB/day Multiply by 9.22337e+18 to correct for simulation losses (but still assume whole file cached) ``` These come from default settings of 2.5M files per day of 32 MB each, and `-sck_keep_bits=40` means that to represent a single file, we are only keeping 40 bits of the 128-bit cache key. With file size of 2\*\*25 contiguous keys (pessimistic), our simulation is about 2\*\*(128-40-25) or about 9 billion billion times more prone to collision than reality. More default assumptions, relatively pessimistic: * 100 DBs in same process (doesn't matter much) * Re-open DB in same process (new session ID related to old session ID) on average every 100 files generated * Restart process (all new session IDs unrelated to old) 24 times per day After enough data, we get a result at the end: ``` (keep 40 bits) 17 collisions after 2 x 90 days, est 10.5882 days between (9.76592e+19 corrected) ``` If we believe the (pessimistic) simulation and the mathematical generalization, we would need to run a billion machines all for 97 billion days to expect a cache key collision. To help verify that our generalization ("corrected") is robust, we can make our simulation more precise with `-sck_keep_bits=41` and `42`, which takes more running time to get enough data: ``` (keep 41 bits) 16 collisions after 4 x 90 days, est 22.5 days between (1.03763e+20 corrected) (keep 42 bits) 19 collisions after 10 x 90 days, est 47.3684 days between (1.09224e+20 corrected) ``` The generalized prediction still holds. With the `-sck_randomize` option, we can see that we are beating "random" cache keys (except offsets still non-randomized) by a modest amount (roughly 20x less collision prone than random), which should make us reasonably comfortable even in "degenerate" cases: ``` 197 collisions after 1 x 90 days, est 0.456853 days between (4.21372e+18 corrected) ``` I've run other tests to validate other conditions behave as expected, never behaving "worse than random" unless we start chopping off structured data. Reviewed By: zhichao-cao Differential Revision: D33171746 Pulled By: pdillinger fbshipit-source-id: f16a57e369ed37be5e7e33525ace848d0537c88f
189 lines
7.0 KiB
C++
189 lines
7.0 KiB
C++
// Copyright (c) 2011-present, Facebook, Inc. All rights reserved.
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// This source code is licensed under both the GPLv2 (found in the
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// COPYING file in the root directory) and Apache 2.0 License
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// (found in the LICENSE.Apache file in the root directory).
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//
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// Copyright (c) 2011 The LevelDB Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style license that can be
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// found in the LICENSE file. See the AUTHORS file for names of contributors.
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#include "cache/cache_reservation_manager.h"
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#include <cassert>
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#include <cstddef>
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#include <cstring>
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#include <memory>
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#include "cache/cache_entry_roles.h"
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#include "rocksdb/cache.h"
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#include "rocksdb/slice.h"
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#include "rocksdb/status.h"
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#include "table/block_based/block_based_table_reader.h"
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#include "util/coding.h"
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namespace ROCKSDB_NAMESPACE {
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CacheReservationManager::CacheReservationManager(std::shared_ptr<Cache> cache,
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bool delayed_decrease)
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: delayed_decrease_(delayed_decrease),
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cache_allocated_size_(0),
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memory_used_(0) {
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assert(cache != nullptr);
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cache_ = cache;
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}
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CacheReservationManager::~CacheReservationManager() {
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for (auto* handle : dummy_handles_) {
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cache_->Release(handle, true);
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}
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}
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template <CacheEntryRole R>
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Status CacheReservationManager::UpdateCacheReservation(
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std::size_t new_mem_used) {
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memory_used_ = new_mem_used;
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std::size_t cur_cache_allocated_size =
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cache_allocated_size_.load(std::memory_order_relaxed);
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if (new_mem_used == cur_cache_allocated_size) {
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return Status::OK();
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} else if (new_mem_used > cur_cache_allocated_size) {
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Status s = IncreaseCacheReservation<R>(new_mem_used);
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return s;
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} else {
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// In delayed decrease mode, we don't decrease cache reservation
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// untill the memory usage is less than 3/4 of what we reserve
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// in the cache.
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// We do this because
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// (1) Dummy entry insertion is expensive in block cache
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// (2) Delayed releasing previously inserted dummy entries can save such
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// expensive dummy entry insertion on memory increase in the near future,
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// which is likely to happen when the memory usage is greater than or equal
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// to 3/4 of what we reserve
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if (delayed_decrease_ && new_mem_used >= cur_cache_allocated_size / 4 * 3) {
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return Status::OK();
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} else {
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Status s = DecreaseCacheReservation(new_mem_used);
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return s;
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}
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}
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}
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// Explicitly instantiate templates for "CacheEntryRole" values we use.
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// This makes it possible to keep the template definitions in the .cc file.
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template Status CacheReservationManager::UpdateCacheReservation<
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CacheEntryRole::kWriteBuffer>(std::size_t new_mem_used);
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template Status CacheReservationManager::UpdateCacheReservation<
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CacheEntryRole::kCompressionDictionaryBuildingBuffer>(
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std::size_t new_mem_used);
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// For cache reservation manager unit tests
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template Status CacheReservationManager::UpdateCacheReservation<
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CacheEntryRole::kMisc>(std::size_t new_mem_used);
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template <CacheEntryRole R>
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Status CacheReservationManager::MakeCacheReservation(
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std::size_t incremental_memory_used,
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std::unique_ptr<CacheReservationHandle<R>>* handle) {
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assert(handle != nullptr);
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Status s =
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UpdateCacheReservation<R>(GetTotalMemoryUsed() + incremental_memory_used);
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(*handle).reset(new CacheReservationHandle<R>(incremental_memory_used,
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shared_from_this()));
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return s;
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}
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template Status
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CacheReservationManager::MakeCacheReservation<CacheEntryRole::kMisc>(
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std::size_t incremental_memory_used,
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std::unique_ptr<CacheReservationHandle<CacheEntryRole::kMisc>>* handle);
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template Status CacheReservationManager::MakeCacheReservation<
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CacheEntryRole::kFilterConstruction>(
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std::size_t incremental_memory_used,
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std::unique_ptr<
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CacheReservationHandle<CacheEntryRole::kFilterConstruction>>* handle);
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template <CacheEntryRole R>
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Status CacheReservationManager::IncreaseCacheReservation(
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std::size_t new_mem_used) {
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Status return_status = Status::OK();
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while (new_mem_used > cache_allocated_size_.load(std::memory_order_relaxed)) {
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Cache::Handle* handle = nullptr;
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return_status = cache_->Insert(GetNextCacheKey(), nullptr, kSizeDummyEntry,
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GetNoopDeleterForRole<R>(), &handle);
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if (return_status != Status::OK()) {
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return return_status;
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}
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dummy_handles_.push_back(handle);
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cache_allocated_size_ += kSizeDummyEntry;
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}
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return return_status;
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}
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Status CacheReservationManager::DecreaseCacheReservation(
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std::size_t new_mem_used) {
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Status return_status = Status::OK();
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// Decrease to the smallest multiple of kSizeDummyEntry that is greater than
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// or equal to new_mem_used We do addition instead of new_mem_used <=
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// cache_allocated_size_.load(std::memory_order_relaxed) - kSizeDummyEntry to
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// avoid underflow of size_t when cache_allocated_size_ = 0
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while (new_mem_used + kSizeDummyEntry <=
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cache_allocated_size_.load(std::memory_order_relaxed)) {
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assert(!dummy_handles_.empty());
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auto* handle = dummy_handles_.back();
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cache_->Release(handle, true);
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dummy_handles_.pop_back();
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cache_allocated_size_ -= kSizeDummyEntry;
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}
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return return_status;
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}
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std::size_t CacheReservationManager::GetTotalReservedCacheSize() {
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return cache_allocated_size_.load(std::memory_order_relaxed);
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}
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std::size_t CacheReservationManager::GetTotalMemoryUsed() {
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return memory_used_;
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}
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Slice CacheReservationManager::GetNextCacheKey() {
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// Calling this function will have the side-effect of changing the
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// underlying cache_key_ that is shared among other keys generated from this
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// fucntion. Therefore please make sure the previous keys are saved/copied
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// before calling this function.
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cache_key_ = CacheKey::CreateUniqueForCacheLifetime(cache_.get());
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return cache_key_.AsSlice();
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}
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template <CacheEntryRole R>
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Cache::DeleterFn CacheReservationManager::TEST_GetNoopDeleterForRole() {
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return GetNoopDeleterForRole<R>();
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}
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template Cache::DeleterFn CacheReservationManager::TEST_GetNoopDeleterForRole<
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CacheEntryRole::kFilterConstruction>();
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template <CacheEntryRole R>
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CacheReservationHandle<R>::CacheReservationHandle(
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std::size_t incremental_memory_used,
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std::shared_ptr<CacheReservationManager> cache_res_mgr)
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: incremental_memory_used_(incremental_memory_used) {
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assert(cache_res_mgr != nullptr);
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cache_res_mgr_ = cache_res_mgr;
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}
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template <CacheEntryRole R>
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CacheReservationHandle<R>::~CacheReservationHandle() {
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assert(cache_res_mgr_ != nullptr);
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assert(cache_res_mgr_->GetTotalMemoryUsed() >= incremental_memory_used_);
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Status s = cache_res_mgr_->UpdateCacheReservation<R>(
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cache_res_mgr_->GetTotalMemoryUsed() - incremental_memory_used_);
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s.PermitUncheckedError();
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}
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// Explicitly instantiate templates for "CacheEntryRole" values we use.
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// This makes it possible to keep the template definitions in the .cc file.
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template class CacheReservationHandle<CacheEntryRole::kMisc>;
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template class CacheReservationHandle<CacheEntryRole::kFilterConstruction>;
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} // namespace ROCKSDB_NAMESPACE
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