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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).
//
// Copyright (c) 2011 The LevelDB Authors. All rights reserved.
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file. See the AUTHORS file for names of contributors.
#pragma once
#include "table/block_based/block_based_table_reader.h"
#include "table/block_based/reader_common.h"
// The file contains some member functions of BlockBasedTable that
// cannot be implemented in block_based_table_reader.cc because
// it's called by other files (e.g. block_based_iterator.h) and
// are templates.
namespace ROCKSDB_NAMESPACE {
// Convert an index iterator value (i.e., an encoded BlockHandle)
// into an iterator over the contents of the corresponding block.
// If input_iter is null, new a iterator
// If input_iter is not null, update this iter and return it
template <typename TBlockIter>
TBlockIter* BlockBasedTable::NewDataBlockIterator(
const ReadOptions& ro, const BlockHandle& handle, TBlockIter* input_iter,
BlockType block_type, GetContext* get_context,
Seek parallelization (#9994) Summary: The RocksDB iterator is a hierarchy of iterators. MergingIterator maintains a heap of LevelIterators, one for each L0 file and for each non-zero level. The Seek() operation naturally lends itself to parallelization, as it involves positioning every LevelIterator on the correct data block in the correct SST file. It lookups a level for a target key, to find the first key that's >= the target key. This typically involves reading one data block that is likely to contain the target key, and scan forward to find the first valid key. The forward scan may read more data blocks. In order to find the right data block, the iterator may read some metadata blocks (required for opening a file and searching the index). This flow can be parallelized. Design: Seek will be called two times under async_io option. First seek will send asynchronous request to prefetch the data blocks at each level and second seek will follow the normal flow and in FilePrefetchBuffer::TryReadFromCacheAsync it will wait for the Poll() to get the results and add the iterator to min_heap. - Status::TryAgain is passed down from FilePrefetchBuffer::PrefetchAsync to block_iter_.Status indicating asynchronous request has been submitted. - If for some reason asynchronous request returns error in submitting the request, it will fallback to sequential reading of blocks in one pass. - If the data already exists in prefetch_buffer, it will return the data without prefetching further and it will be treated as single pass of seek. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9994 Test Plan: - **Run Regressions.** ``` ./db_bench -db=/tmp/prefix_scan_prefetch_main -benchmarks="fillseq" -key_size=32 -value_size=512 -num=5000000 -use_direct_io_for_flush_and_compaction=true -target_file_size_base=16777216 ``` i) Previous release 7.0 run for normal prefetching with async_io disabled: ``` ./db_bench -use_existing_db=true -db=/tmp/prefix_scan_prefetch_main -benchmarks="seekrandom" -key_size=32 -value_size=512 -num=5000000 -use_direct_reads=true -seek_nexts=327680 -duration=120 -ops_between_duration_checks=1 Initializing RocksDB Options from the specified file Initializing RocksDB Options from command-line flags RocksDB: version 7.0 Date: Thu Mar 17 13:11:34 2022 CPU: 24 * Intel Core Processor (Broadwell) CPUCache: 16384 KB Keys: 32 bytes each (+ 0 bytes user-defined timestamp) Values: 512 bytes each (256 bytes after compression) Entries: 5000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 2594.0 MB (estimated) FileSize: 1373.3 MB (estimated) Write rate: 0 bytes/second Read rate: 0 ops/second Compression: Snappy Compression sampling rate: 0 Memtablerep: SkipListFactory Perf Level: 1 ------------------------------------------------ DB path: [/tmp/prefix_scan_prefetch_main] seekrandom : 483618.390 micros/op 2 ops/sec; 338.9 MB/s (249 of 249 found) ``` ii) normal prefetching after changes with async_io disable: ``` ./db_bench -use_existing_db=true -db=/tmp/prefix_scan_prefetch_main -benchmarks="seekrandom" -key_size=32 -value_size=512 -num=5000000 -use_direct_reads=true -seek_nexts=327680 -duration=120 -ops_between_duration_checks=1 Set seed to 1652922591315307 because --seed was 0 Initializing RocksDB Options from the specified file Initializing RocksDB Options from command-line flags RocksDB: version 7.3 Date: Wed May 18 18:09:51 2022 CPU: 32 * Intel Xeon Processor (Skylake) CPUCache: 16384 KB Keys: 32 bytes each (+ 0 bytes user-defined timestamp) Values: 512 bytes each (256 bytes after compression) Entries: 5000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 2594.0 MB (estimated) FileSize: 1373.3 MB (estimated) Write rate: 0 bytes/second Read rate: 0 ops/second Compression: Snappy Compression sampling rate: 0 Memtablerep: SkipListFactory Perf Level: 1 ------------------------------------------------ DB path: [/tmp/prefix_scan_prefetch_main] seekrandom : 483080.466 micros/op 2 ops/sec 120.287 seconds 249 operations; 340.8 MB/s (249 of 249 found) ``` iii) db_bench with async_io enabled completed succesfully ``` ./db_bench -use_existing_db=true -db=/tmp/prefix_scan_prefetch_main -benchmarks="seekrandom" -key_size=32 -value_size=512 -num=5000000 -use_direct_reads=true -seek_nexts=327680 -duration=120 -ops_between_duration_checks=1 -async_io=1 -adaptive_readahead=1 Set seed to 1652924062021732 because --seed was 0 Initializing RocksDB Options from the specified file Initializing RocksDB Options from command-line flags RocksDB: version 7.3 Date: Wed May 18 18:34:22 2022 CPU: 32 * Intel Xeon Processor (Skylake) CPUCache: 16384 KB Keys: 32 bytes each (+ 0 bytes user-defined timestamp) Values: 512 bytes each (256 bytes after compression) Entries: 5000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 2594.0 MB (estimated) FileSize: 1373.3 MB (estimated) Write rate: 0 bytes/second Read rate: 0 ops/second Compression: Snappy Compression sampling rate: 0 Memtablerep: SkipListFactory Perf Level: 1 ------------------------------------------------ DB path: [/tmp/prefix_scan_prefetch_main] seekrandom : 553913.576 micros/op 1 ops/sec 120.199 seconds 217 operations; 293.6 MB/s (217 of 217 found) ``` - db_stress with async_io disabled completed succesfully ``` export CRASH_TEST_EXT_ARGS=" --async_io=0" make crash_test -j ``` I**n Progress**: db_stress with async_io is failing and working on debugging/fixing it. Reviewed By: anand1976 Differential Revision: D36459323 Pulled By: akankshamahajan15 fbshipit-source-id: abb1cd944abe712bae3986ae5b16704b3338917c
3 years ago
BlockCacheLookupContext* lookup_context,
FilePrefetchBuffer* prefetch_buffer, bool for_compaction, bool async_read,
Status& s) const {
PERF_TIMER_GUARD(new_table_block_iter_nanos);
TBlockIter* iter = input_iter != nullptr ? input_iter : new TBlockIter;
if (!s.ok()) {
iter->Invalidate(s);
return iter;
}
Updated NewDataBlockIterator to not fetch compression dict for non-da… (#10310) Summary: …ta blocks During MyShadow testing, ajkr helped me find out that with partitioned index and dictionary compression enabled, `PartitionedIndexIterator::InitPartitionedIndexBlock()` spent considerable amount of time (1-2% CPU) on fetching uncompression dictionary. Fetching uncompression dict was not needed since the index blocks were not compressed (and even if they were, they use empty dictionary). This should only affect use cases with partitioned index, dictionary compression and without uncompression dictionary pinned. This PR updates NewDataBlockIterator to not fetch uncompression dictionary when it is not for data blocks. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10310 Test Plan: 1. `make check` 2. Perf benchmark: 1.5% (143950 -> 146176) improvement in op/sec for partitioned index + dict compression benchmark. For default config without partitioned index and without dict compression, there is no regression in readrandom perf from multiple runs of db_bench. ``` # Set up for partitioned index with dictionary compression TEST_TMPDIR=/dev/shm ./db_bench_main -benchmarks=filluniquerandom,compact -max_background_jobs=24 -memtablerep=vector -allow_concurrent_memtable_write=false -partition_index=true -compression_max_dict_bytes=16384 -compression_zstd_max_train_bytes=1638400 # Pre PR TEST_TMPDIR=/dev/shm ./db_bench_main -use_existing_db=true -benchmarks=readrandom[-X50] -partition_index=true readrandom [AVG 50 runs] : 143950 (± 1108) ops/sec; 15.9 (± 0.1) MB/sec readrandom [MEDIAN 50 runs] : 144406 ops/sec; 16.0 MB/sec # Post PR TEST_TMPDIR=/dev/shm ./db_bench_opt -use_existing_db=true -benchmarks=readrandom[-X50] -partition_index=true readrandom [AVG 50 runs] : 146176 (± 1121) ops/sec; 16.2 (± 0.1) MB/sec readrandom [MEDIAN 50 runs] : 146014 ops/sec; 16.2 MB/sec # Set up for no partitioned index and no dictionary compression TEST_TMPDIR=/dev/shm/baseline ./db_bench_main -benchmarks=filluniquerandom,compact -max_background_jobs=24 -memtablerep=vector -allow_concurrent_memtable_write=false # Pre PR TEST_TMPDIR=/dev/shm/baseline/ ./db_bench_main --use_existing_db=true "--benchmarks=readrandom[-X50]" readrandom [AVG 50 runs] : 158546 (± 1000) ops/sec; 17.5 (± 0.1) MB/sec readrandom [MEDIAN 50 runs] : 158280 ops/sec; 17.5 MB/sec # Post PR TEST_TMPDIR=/dev/shm/baseline/ ./db_bench_opt --use_existing_db=true "--benchmarks=readrandom[-X50]" readrandom [AVG 50 runs] : 161061 (± 1520) ops/sec; 17.8 (± 0.2) MB/sec readrandom [MEDIAN 50 runs] : 161596 ops/sec; 17.9 MB/sec ``` Reviewed By: ajkr Differential Revision: D37631358 Pulled By: cbi42 fbshipit-source-id: 6ca2665e270e63871968e061ba4a99d3136785d9
3 years ago
CachableEntry<Block> block;
if (rep_->uncompression_dict_reader && block_type == BlockType::kData) {
CachableEntry<UncompressionDict> uncompression_dict;
const bool no_io = (ro.read_tier == kBlockCacheTier);
s = rep_->uncompression_dict_reader->GetOrReadUncompressionDictionary(
prefetch_buffer, no_io, ro.verify_checksums, get_context,
lookup_context, &uncompression_dict);
if (!s.ok()) {
iter->Invalidate(s);
return iter;
}
Updated NewDataBlockIterator to not fetch compression dict for non-da… (#10310) Summary: …ta blocks During MyShadow testing, ajkr helped me find out that with partitioned index and dictionary compression enabled, `PartitionedIndexIterator::InitPartitionedIndexBlock()` spent considerable amount of time (1-2% CPU) on fetching uncompression dictionary. Fetching uncompression dict was not needed since the index blocks were not compressed (and even if they were, they use empty dictionary). This should only affect use cases with partitioned index, dictionary compression and without uncompression dictionary pinned. This PR updates NewDataBlockIterator to not fetch uncompression dictionary when it is not for data blocks. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10310 Test Plan: 1. `make check` 2. Perf benchmark: 1.5% (143950 -> 146176) improvement in op/sec for partitioned index + dict compression benchmark. For default config without partitioned index and without dict compression, there is no regression in readrandom perf from multiple runs of db_bench. ``` # Set up for partitioned index with dictionary compression TEST_TMPDIR=/dev/shm ./db_bench_main -benchmarks=filluniquerandom,compact -max_background_jobs=24 -memtablerep=vector -allow_concurrent_memtable_write=false -partition_index=true -compression_max_dict_bytes=16384 -compression_zstd_max_train_bytes=1638400 # Pre PR TEST_TMPDIR=/dev/shm ./db_bench_main -use_existing_db=true -benchmarks=readrandom[-X50] -partition_index=true readrandom [AVG 50 runs] : 143950 (± 1108) ops/sec; 15.9 (± 0.1) MB/sec readrandom [MEDIAN 50 runs] : 144406 ops/sec; 16.0 MB/sec # Post PR TEST_TMPDIR=/dev/shm ./db_bench_opt -use_existing_db=true -benchmarks=readrandom[-X50] -partition_index=true readrandom [AVG 50 runs] : 146176 (± 1121) ops/sec; 16.2 (± 0.1) MB/sec readrandom [MEDIAN 50 runs] : 146014 ops/sec; 16.2 MB/sec # Set up for no partitioned index and no dictionary compression TEST_TMPDIR=/dev/shm/baseline ./db_bench_main -benchmarks=filluniquerandom,compact -max_background_jobs=24 -memtablerep=vector -allow_concurrent_memtable_write=false # Pre PR TEST_TMPDIR=/dev/shm/baseline/ ./db_bench_main --use_existing_db=true "--benchmarks=readrandom[-X50]" readrandom [AVG 50 runs] : 158546 (± 1000) ops/sec; 17.5 (± 0.1) MB/sec readrandom [MEDIAN 50 runs] : 158280 ops/sec; 17.5 MB/sec # Post PR TEST_TMPDIR=/dev/shm/baseline/ ./db_bench_opt --use_existing_db=true "--benchmarks=readrandom[-X50]" readrandom [AVG 50 runs] : 161061 (± 1520) ops/sec; 17.8 (± 0.2) MB/sec readrandom [MEDIAN 50 runs] : 161596 ops/sec; 17.9 MB/sec ``` Reviewed By: ajkr Differential Revision: D37631358 Pulled By: cbi42 fbshipit-source-id: 6ca2665e270e63871968e061ba4a99d3136785d9
3 years ago
const UncompressionDict& dict = uncompression_dict.GetValue()
? *uncompression_dict.GetValue()
: UncompressionDict::GetEmptyDict();
s = RetrieveBlock(prefetch_buffer, ro, handle, dict, &block, block_type,
get_context, lookup_context, for_compaction,
/* use_cache */ true, /* wait_for_cache */ true,
async_read);
} else {
s = RetrieveBlock(
prefetch_buffer, ro, handle, UncompressionDict::GetEmptyDict(), &block,
block_type, get_context, lookup_context, for_compaction,
/* use_cache */ true, /* wait_for_cache */ true, async_read);
}
Seek parallelization (#9994) Summary: The RocksDB iterator is a hierarchy of iterators. MergingIterator maintains a heap of LevelIterators, one for each L0 file and for each non-zero level. The Seek() operation naturally lends itself to parallelization, as it involves positioning every LevelIterator on the correct data block in the correct SST file. It lookups a level for a target key, to find the first key that's >= the target key. This typically involves reading one data block that is likely to contain the target key, and scan forward to find the first valid key. The forward scan may read more data blocks. In order to find the right data block, the iterator may read some metadata blocks (required for opening a file and searching the index). This flow can be parallelized. Design: Seek will be called two times under async_io option. First seek will send asynchronous request to prefetch the data blocks at each level and second seek will follow the normal flow and in FilePrefetchBuffer::TryReadFromCacheAsync it will wait for the Poll() to get the results and add the iterator to min_heap. - Status::TryAgain is passed down from FilePrefetchBuffer::PrefetchAsync to block_iter_.Status indicating asynchronous request has been submitted. - If for some reason asynchronous request returns error in submitting the request, it will fallback to sequential reading of blocks in one pass. - If the data already exists in prefetch_buffer, it will return the data without prefetching further and it will be treated as single pass of seek. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9994 Test Plan: - **Run Regressions.** ``` ./db_bench -db=/tmp/prefix_scan_prefetch_main -benchmarks="fillseq" -key_size=32 -value_size=512 -num=5000000 -use_direct_io_for_flush_and_compaction=true -target_file_size_base=16777216 ``` i) Previous release 7.0 run for normal prefetching with async_io disabled: ``` ./db_bench -use_existing_db=true -db=/tmp/prefix_scan_prefetch_main -benchmarks="seekrandom" -key_size=32 -value_size=512 -num=5000000 -use_direct_reads=true -seek_nexts=327680 -duration=120 -ops_between_duration_checks=1 Initializing RocksDB Options from the specified file Initializing RocksDB Options from command-line flags RocksDB: version 7.0 Date: Thu Mar 17 13:11:34 2022 CPU: 24 * Intel Core Processor (Broadwell) CPUCache: 16384 KB Keys: 32 bytes each (+ 0 bytes user-defined timestamp) Values: 512 bytes each (256 bytes after compression) Entries: 5000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 2594.0 MB (estimated) FileSize: 1373.3 MB (estimated) Write rate: 0 bytes/second Read rate: 0 ops/second Compression: Snappy Compression sampling rate: 0 Memtablerep: SkipListFactory Perf Level: 1 ------------------------------------------------ DB path: [/tmp/prefix_scan_prefetch_main] seekrandom : 483618.390 micros/op 2 ops/sec; 338.9 MB/s (249 of 249 found) ``` ii) normal prefetching after changes with async_io disable: ``` ./db_bench -use_existing_db=true -db=/tmp/prefix_scan_prefetch_main -benchmarks="seekrandom" -key_size=32 -value_size=512 -num=5000000 -use_direct_reads=true -seek_nexts=327680 -duration=120 -ops_between_duration_checks=1 Set seed to 1652922591315307 because --seed was 0 Initializing RocksDB Options from the specified file Initializing RocksDB Options from command-line flags RocksDB: version 7.3 Date: Wed May 18 18:09:51 2022 CPU: 32 * Intel Xeon Processor (Skylake) CPUCache: 16384 KB Keys: 32 bytes each (+ 0 bytes user-defined timestamp) Values: 512 bytes each (256 bytes after compression) Entries: 5000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 2594.0 MB (estimated) FileSize: 1373.3 MB (estimated) Write rate: 0 bytes/second Read rate: 0 ops/second Compression: Snappy Compression sampling rate: 0 Memtablerep: SkipListFactory Perf Level: 1 ------------------------------------------------ DB path: [/tmp/prefix_scan_prefetch_main] seekrandom : 483080.466 micros/op 2 ops/sec 120.287 seconds 249 operations; 340.8 MB/s (249 of 249 found) ``` iii) db_bench with async_io enabled completed succesfully ``` ./db_bench -use_existing_db=true -db=/tmp/prefix_scan_prefetch_main -benchmarks="seekrandom" -key_size=32 -value_size=512 -num=5000000 -use_direct_reads=true -seek_nexts=327680 -duration=120 -ops_between_duration_checks=1 -async_io=1 -adaptive_readahead=1 Set seed to 1652924062021732 because --seed was 0 Initializing RocksDB Options from the specified file Initializing RocksDB Options from command-line flags RocksDB: version 7.3 Date: Wed May 18 18:34:22 2022 CPU: 32 * Intel Xeon Processor (Skylake) CPUCache: 16384 KB Keys: 32 bytes each (+ 0 bytes user-defined timestamp) Values: 512 bytes each (256 bytes after compression) Entries: 5000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 2594.0 MB (estimated) FileSize: 1373.3 MB (estimated) Write rate: 0 bytes/second Read rate: 0 ops/second Compression: Snappy Compression sampling rate: 0 Memtablerep: SkipListFactory Perf Level: 1 ------------------------------------------------ DB path: [/tmp/prefix_scan_prefetch_main] seekrandom : 553913.576 micros/op 1 ops/sec 120.199 seconds 217 operations; 293.6 MB/s (217 of 217 found) ``` - db_stress with async_io disabled completed succesfully ``` export CRASH_TEST_EXT_ARGS=" --async_io=0" make crash_test -j ``` I**n Progress**: db_stress with async_io is failing and working on debugging/fixing it. Reviewed By: anand1976 Differential Revision: D36459323 Pulled By: akankshamahajan15 fbshipit-source-id: abb1cd944abe712bae3986ae5b16704b3338917c
3 years ago
if (s.IsTryAgain() && async_read) {
return iter;
}
if (!s.ok()) {
assert(block.IsEmpty());
iter->Invalidate(s);
return iter;
}
assert(block.GetValue() != nullptr);
// Block contents are pinned and it is still pinned after the iterator
// is destroyed as long as cleanup functions are moved to another object,
// when:
// 1. block cache handle is set to be released in cleanup function, or
// 2. it's pointing to immortal source. If own_bytes is true then we are
// not reading data from the original source, whether immortal or not.
// Otherwise, the block is pinned iff the source is immortal.
const bool block_contents_pinned =
block.IsCached() ||
(!block.GetValue()->own_bytes() && rep_->immortal_table);
iter = InitBlockIterator<TBlockIter>(rep_, block.GetValue(), block_type, iter,
block_contents_pinned);
if (!block.IsCached()) {
New stable, fixed-length cache keys (#9126) 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
3 years ago
if (!ro.fill_cache) {
Cache* const block_cache = rep_->table_options.block_cache.get();
New stable, fixed-length cache keys (#9126) 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
3 years ago
if (block_cache) {
// insert a dummy record to block cache to track the memory usage
Cache::Handle* cache_handle = nullptr;
CacheKey key = CacheKey::CreateUniqueForCacheLifetime(block_cache);
s = block_cache->Insert(key.AsSlice(), nullptr,
block.GetValue()->ApproximateMemoryUsage(),
nullptr, &cache_handle);
if (s.ok()) {
assert(cache_handle != nullptr);
iter->RegisterCleanup(&ForceReleaseCachedEntry, block_cache,
cache_handle);
}
}
}
} else {
iter->SetCacheHandle(block.GetCacheHandle());
}
block.TransferTo(iter);
return iter;
}
// Convert an uncompressed data block (i.e CachableEntry<Block>)
// into an iterator over the contents of the corresponding block.
// If input_iter is null, new a iterator
// If input_iter is not null, update this iter and return it
template <typename TBlockIter>
TBlockIter* BlockBasedTable::NewDataBlockIterator(const ReadOptions& ro,
CachableEntry<Block>& block,
TBlockIter* input_iter,
Status s) const {
PERF_TIMER_GUARD(new_table_block_iter_nanos);
TBlockIter* iter = input_iter != nullptr ? input_iter : new TBlockIter;
if (!s.ok()) {
iter->Invalidate(s);
return iter;
}
assert(block.GetValue() != nullptr);
// Block contents are pinned and it is still pinned after the iterator
// is destroyed as long as cleanup functions are moved to another object,
// when:
// 1. block cache handle is set to be released in cleanup function, or
// 2. it's pointing to immortal source. If own_bytes is true then we are
// not reading data from the original source, whether immortal or not.
// Otherwise, the block is pinned iff the source is immortal.
const bool block_contents_pinned =
block.IsCached() ||
(!block.GetValue()->own_bytes() && rep_->immortal_table);
iter = InitBlockIterator<TBlockIter>(rep_, block.GetValue(), BlockType::kData,
iter, block_contents_pinned);
if (!block.IsCached()) {
New stable, fixed-length cache keys (#9126) 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
3 years ago
if (!ro.fill_cache) {
Cache* const block_cache = rep_->table_options.block_cache.get();
New stable, fixed-length cache keys (#9126) 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
3 years ago
if (block_cache) {
// insert a dummy record to block cache to track the memory usage
Cache::Handle* cache_handle = nullptr;
CacheKey key = CacheKey::CreateUniqueForCacheLifetime(block_cache);
s = block_cache->Insert(key.AsSlice(), nullptr,
block.GetValue()->ApproximateMemoryUsage(),
nullptr, &cache_handle);
if (s.ok()) {
assert(cache_handle != nullptr);
iter->RegisterCleanup(&ForceReleaseCachedEntry, block_cache,
cache_handle);
}
}
}
} else {
iter->SetCacheHandle(block.GetCacheHandle());
}
block.TransferTo(iter);
return iter;
}
} // namespace ROCKSDB_NAMESPACE