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rocksdb/table/block_based/block_based_table_builder.cc

2098 lines
78 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 "table/block_based/block_based_table_builder.h"
#include <assert.h>
#include <stdio.h>
Limit buffering for collecting samples for compression dictionary (#7970) Summary: For dictionary compression, we need to collect some representative samples of the data to be compressed, which we use to either generate or train (when `CompressionOptions::zstd_max_train_bytes > 0`) a dictionary. Previously, the strategy was to buffer all the data blocks during flush, and up to the target file size during compaction. That strategy allowed us to randomly pick samples from as wide a range as possible that'd be guaranteed to land in a single output file. However, some users try to make huge files in memory-constrained environments, where this strategy can cause OOM. This PR introduces an option, `CompressionOptions::max_dict_buffer_bytes`, that limits how much data blocks are buffered before we switch to unbuffered mode (which means creating the per-SST dictionary, writing out the buffered data, and compressing/writing new blocks as soon as they are built). It is not strict as we currently buffer more than just data blocks -- also keys are buffered. But it does make a step towards giving users predictable memory usage. Related changes include: - Changed sampling for dictionary compression to select unique data blocks when there is limited availability of data blocks - Made use of `BlockBuilder::SwapAndReset()` to save an allocation+memcpy when buffering data blocks for building a dictionary - Changed `ParseBoolean()` to accept an input containing characters after the boolean. This is necessary since, with this PR, a value for `CompressionOptions::enabled` is no longer necessarily the final component in the `CompressionOptions` string. Pull Request resolved: https://github.com/facebook/rocksdb/pull/7970 Test Plan: - updated `CompressionOptions` unit tests to verify limit is respected (to the extent expected in the current implementation) in various scenarios of flush/compaction to bottommost/non-bottommost level - looked at jemalloc heap profiles right before and after switching to unbuffered mode during flush/compaction. Verified memory usage in buffering is proportional to the limit set. Reviewed By: pdillinger Differential Revision: D26467994 Pulled By: ajkr fbshipit-source-id: 3da4ef9fba59974e4ef40e40c01611002c861465
4 years ago
#include <atomic>
#include <list>
#include <map>
#include <memory>
Limit buffering for collecting samples for compression dictionary (#7970) Summary: For dictionary compression, we need to collect some representative samples of the data to be compressed, which we use to either generate or train (when `CompressionOptions::zstd_max_train_bytes > 0`) a dictionary. Previously, the strategy was to buffer all the data blocks during flush, and up to the target file size during compaction. That strategy allowed us to randomly pick samples from as wide a range as possible that'd be guaranteed to land in a single output file. However, some users try to make huge files in memory-constrained environments, where this strategy can cause OOM. This PR introduces an option, `CompressionOptions::max_dict_buffer_bytes`, that limits how much data blocks are buffered before we switch to unbuffered mode (which means creating the per-SST dictionary, writing out the buffered data, and compressing/writing new blocks as soon as they are built). It is not strict as we currently buffer more than just data blocks -- also keys are buffered. But it does make a step towards giving users predictable memory usage. Related changes include: - Changed sampling for dictionary compression to select unique data blocks when there is limited availability of data blocks - Made use of `BlockBuilder::SwapAndReset()` to save an allocation+memcpy when buffering data blocks for building a dictionary - Changed `ParseBoolean()` to accept an input containing characters after the boolean. This is necessary since, with this PR, a value for `CompressionOptions::enabled` is no longer necessarily the final component in the `CompressionOptions` string. Pull Request resolved: https://github.com/facebook/rocksdb/pull/7970 Test Plan: - updated `CompressionOptions` unit tests to verify limit is respected (to the extent expected in the current implementation) in various scenarios of flush/compaction to bottommost/non-bottommost level - looked at jemalloc heap profiles right before and after switching to unbuffered mode during flush/compaction. Verified memory usage in buffering is proportional to the limit set. Reviewed By: pdillinger Differential Revision: D26467994 Pulled By: ajkr fbshipit-source-id: 3da4ef9fba59974e4ef40e40c01611002c861465
4 years ago
#include <numeric>
#include <string>
#include <unordered_map>
#include <utility>
#include "cache/cache_entry_roles.h"
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
#include "cache/cache_key.h"
#include "cache/cache_reservation_manager.h"
#include "db/dbformat.h"
#include "index_builder.h"
#include "logging/logging.h"
Limit buffering for collecting samples for compression dictionary (#7970) Summary: For dictionary compression, we need to collect some representative samples of the data to be compressed, which we use to either generate or train (when `CompressionOptions::zstd_max_train_bytes > 0`) a dictionary. Previously, the strategy was to buffer all the data blocks during flush, and up to the target file size during compaction. That strategy allowed us to randomly pick samples from as wide a range as possible that'd be guaranteed to land in a single output file. However, some users try to make huge files in memory-constrained environments, where this strategy can cause OOM. This PR introduces an option, `CompressionOptions::max_dict_buffer_bytes`, that limits how much data blocks are buffered before we switch to unbuffered mode (which means creating the per-SST dictionary, writing out the buffered data, and compressing/writing new blocks as soon as they are built). It is not strict as we currently buffer more than just data blocks -- also keys are buffered. But it does make a step towards giving users predictable memory usage. Related changes include: - Changed sampling for dictionary compression to select unique data blocks when there is limited availability of data blocks - Made use of `BlockBuilder::SwapAndReset()` to save an allocation+memcpy when buffering data blocks for building a dictionary - Changed `ParseBoolean()` to accept an input containing characters after the boolean. This is necessary since, with this PR, a value for `CompressionOptions::enabled` is no longer necessarily the final component in the `CompressionOptions` string. Pull Request resolved: https://github.com/facebook/rocksdb/pull/7970 Test Plan: - updated `CompressionOptions` unit tests to verify limit is respected (to the extent expected in the current implementation) in various scenarios of flush/compaction to bottommost/non-bottommost level - looked at jemalloc heap profiles right before and after switching to unbuffered mode during flush/compaction. Verified memory usage in buffering is proportional to the limit set. Reviewed By: pdillinger Differential Revision: D26467994 Pulled By: ajkr fbshipit-source-id: 3da4ef9fba59974e4ef40e40c01611002c861465
4 years ago
#include "memory/memory_allocator.h"
#include "rocksdb/cache.h"
#include "rocksdb/comparator.h"
#include "rocksdb/env.h"
#include "rocksdb/filter_policy.h"
#include "rocksdb/flush_block_policy.h"
#include "rocksdb/merge_operator.h"
#include "rocksdb/table.h"
#include "rocksdb/types.h"
#include "table/block_based/block.h"
#include "table/block_based/block_based_table_factory.h"
#include "table/block_based/block_based_table_reader.h"
#include "table/block_based/block_builder.h"
#include "table/block_based/block_like_traits.h"
#include "table/block_based/filter_block.h"
New Bloom filter implementation for full and partitioned filters (#6007) Summary: Adds an improved, replacement Bloom filter implementation (FastLocalBloom) for full and partitioned filters in the block-based table. This replacement is faster and more accurate, especially for high bits per key or millions of keys in a single filter. Speed The improved speed, at least on recent x86_64, comes from * Using fastrange instead of modulo (%) * Using our new hash function (XXH3 preview, added in a previous commit), which is much faster for large keys and only *slightly* slower on keys around 12 bytes if hashing the same size many thousands of times in a row. * Optimizing the Bloom filter queries with AVX2 SIMD operations. (Added AVX2 to the USE_SSE=1 build.) Careful design was required to support (a) SIMD-optimized queries, (b) compatible non-SIMD code that's simple and efficient, (c) flexible choice of number of probes, and (d) essentially maximized accuracy for a cache-local Bloom filter. Probes are made eight at a time, so any number of probes up to 8 is the same speed, then up to 16, etc. * Prefetching cache lines when building the filter. Although this optimization could be applied to the old structure as well, it seems to balance out the small added cost of accumulating 64 bit hashes for adding to the filter rather than 32 bit hashes. Here's nominal speed data from filter_bench (200MB in filters, about 10k keys each, 10 bits filter data / key, 6 probes, avg key size 24 bytes, includes hashing time) on Skylake DE (relatively low clock speed): $ ./filter_bench -quick -impl=2 -net_includes_hashing # New Bloom filter Build avg ns/key: 47.7135 Mixed inside/outside queries... Single filter net ns/op: 26.2825 Random filter net ns/op: 150.459 Average FP rate %: 0.954651 $ ./filter_bench -quick -impl=0 -net_includes_hashing # Old Bloom filter Build avg ns/key: 47.2245 Mixed inside/outside queries... Single filter net ns/op: 63.2978 Random filter net ns/op: 188.038 Average FP rate %: 1.13823 Similar build time but dramatically faster query times on hot data (63 ns to 26 ns), and somewhat faster on stale data (188 ns to 150 ns). Performance differences on batched and skewed query loads are between these extremes as expected. The only other interesting thing about speed is "inside" (query key was added to filter) vs. "outside" (query key was not added to filter) query times. The non-SIMD implementations are substantially slower when most queries are "outside" vs. "inside". This goes against what one might expect or would have observed years ago, as "outside" queries only need about two probes on average, due to short-circuiting, while "inside" always have num_probes (say 6). The problem is probably the nastily unpredictable branch. The SIMD implementation has few branches (very predictable) and has pretty consistent running time regardless of query outcome. Accuracy The generally improved accuracy (re: Issue https://github.com/facebook/rocksdb/issues/5857) comes from a better design for probing indices within a cache line (re: Issue https://github.com/facebook/rocksdb/issues/4120) and improved accuracy for millions of keys in a single filter from using a 64-bit hash function (XXH3p). Design details in code comments. Accuracy data (generalizes, except old impl gets worse with millions of keys): Memory bits per key: FP rate percent old impl -> FP rate percent new impl 6: 5.70953 -> 5.69888 8: 2.45766 -> 2.29709 10: 1.13977 -> 0.959254 12: 0.662498 -> 0.411593 16: 0.353023 -> 0.0873754 24: 0.261552 -> 0.0060971 50: 0.225453 -> ~0.00003 (less than 1 in a million queries are FP) Fixes https://github.com/facebook/rocksdb/issues/5857 Fixes https://github.com/facebook/rocksdb/issues/4120 Unlike the old implementation, this implementation has a fixed cache line size (64 bytes). At 10 bits per key, the accuracy of this new implementation is very close to the old implementation with 128-byte cache line size. If there's sufficient demand, this implementation could be generalized. Compatibility Although old releases would see the new structure as corrupt filter data and read the table as if there's no filter, we've decided only to enable the new Bloom filter with new format_version=5. This provides a smooth path for automatic adoption over time, with an option for early opt-in. Pull Request resolved: https://github.com/facebook/rocksdb/pull/6007 Test Plan: filter_bench has been used thoroughly to validate speed, accuracy, and correctness. Unit tests have been carefully updated to exercise new and old implementations, as well as the logic to select an implementation based on context (format_version). Differential Revision: D18294749 Pulled By: pdillinger fbshipit-source-id: d44c9db3696e4d0a17caaec47075b7755c262c5f
5 years ago
#include "table/block_based/filter_policy_internal.h"
#include "table/block_based/full_filter_block.h"
#include "table/block_based/partitioned_filter_block.h"
#include "table/format.h"
Improve / clean up meta block code & integrity (#9163) Summary: * Checksums are now checked on meta blocks unless specifically suppressed or not applicable (e.g. plain table). (Was other way around.) This means a number of cases that were not checking checksums now are, including direct read TableProperties in Version::GetTableProperties (fixed in meta_blocks ReadTableProperties), reading any block from PersistentCache (fixed in BlockFetcher), read TableProperties in SstFileDumper (ldb/sst_dump/BackupEngine) before table reader open, maybe more. * For that to work, I moved the global_seqno+TableProperties checksum logic to the shared table/ code, because that is used by many utilies such as SstFileDumper. * Also for that to work, we have to know when we're dealing with a block that has a checksum (trailer), so added that capability to Footer based on magic number, and from there BlockFetcher. * Knowledge of trailer presence has also fixed a problem where other table formats were reading blocks including bytes for a non-existant trailer--and awkwardly kind-of not using them, e.g. no shared code checking checksums. (BlockFetcher compression type was populated incorrectly.) Now we only read what is needed. * Minimized code duplication and differing/incompatible/awkward abstractions in meta_blocks.{cc,h} (e.g. SeekTo in metaindex block without parsing block handle) * Moved some meta block handling code from table_properties*.* * Moved some code specific to block-based table from shared table/ code to BlockBasedTable class. The checksum stuff means we can't completely separate it, but things that don't need to be in shared table/ code should not be. * Use unique_ptr rather than raw ptr in more places. (Note: you can std::move from unique_ptr to shared_ptr.) Without enhancements to GetPropertiesOfAllTablesTest (see below), net reduction of roughly 100 lines of code. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9163 Test Plan: existing tests and * Enhanced DBTablePropertiesTest.GetPropertiesOfAllTablesTest to verify that checksums are now checked on direct read of table properties by TableCache (new test would fail before this change) * Also enhanced DBTablePropertiesTest.GetPropertiesOfAllTablesTest to test putting table properties under old meta name * Also generally enhanced that same test to actually test what it was supposed to be testing already, by kicking things out of table cache when we don't want them there. Reviewed By: ajkr, mrambacher Differential Revision: D32514757 Pulled By: pdillinger fbshipit-source-id: 507964b9311d186ae8d1131182290cbd97a99fa9
3 years ago
#include "table/meta_blocks.h"
#include "table/table_builder.h"
#include "util/coding.h"
#include "util/compression.h"
#include "util/stop_watch.h"
#include "util/string_util.h"
#include "util/work_queue.h"
namespace ROCKSDB_NAMESPACE {
extern const std::string kHashIndexPrefixesBlock;
extern const std::string kHashIndexPrefixesMetadataBlock;
// Without anonymous namespace here, we fail the warning -Wmissing-prototypes
namespace {
Improve / clean up meta block code & integrity (#9163) Summary: * Checksums are now checked on meta blocks unless specifically suppressed or not applicable (e.g. plain table). (Was other way around.) This means a number of cases that were not checking checksums now are, including direct read TableProperties in Version::GetTableProperties (fixed in meta_blocks ReadTableProperties), reading any block from PersistentCache (fixed in BlockFetcher), read TableProperties in SstFileDumper (ldb/sst_dump/BackupEngine) before table reader open, maybe more. * For that to work, I moved the global_seqno+TableProperties checksum logic to the shared table/ code, because that is used by many utilies such as SstFileDumper. * Also for that to work, we have to know when we're dealing with a block that has a checksum (trailer), so added that capability to Footer based on magic number, and from there BlockFetcher. * Knowledge of trailer presence has also fixed a problem where other table formats were reading blocks including bytes for a non-existant trailer--and awkwardly kind-of not using them, e.g. no shared code checking checksums. (BlockFetcher compression type was populated incorrectly.) Now we only read what is needed. * Minimized code duplication and differing/incompatible/awkward abstractions in meta_blocks.{cc,h} (e.g. SeekTo in metaindex block without parsing block handle) * Moved some meta block handling code from table_properties*.* * Moved some code specific to block-based table from shared table/ code to BlockBasedTable class. The checksum stuff means we can't completely separate it, but things that don't need to be in shared table/ code should not be. * Use unique_ptr rather than raw ptr in more places. (Note: you can std::move from unique_ptr to shared_ptr.) Without enhancements to GetPropertiesOfAllTablesTest (see below), net reduction of roughly 100 lines of code. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9163 Test Plan: existing tests and * Enhanced DBTablePropertiesTest.GetPropertiesOfAllTablesTest to verify that checksums are now checked on direct read of table properties by TableCache (new test would fail before this change) * Also enhanced DBTablePropertiesTest.GetPropertiesOfAllTablesTest to test putting table properties under old meta name * Also generally enhanced that same test to actually test what it was supposed to be testing already, by kicking things out of table cache when we don't want them there. Reviewed By: ajkr, mrambacher Differential Revision: D32514757 Pulled By: pdillinger fbshipit-source-id: 507964b9311d186ae8d1131182290cbd97a99fa9
3 years ago
constexpr size_t kBlockTrailerSize = BlockBasedTable::kBlockTrailerSize;
// Create a filter block builder based on its type.
FilterBlockBuilder* CreateFilterBlockBuilder(
const ImmutableCFOptions& /*opt*/, const MutableCFOptions& mopt,
const FilterBuildingContext& context,
const bool use_delta_encoding_for_index_values,
PartitionedIndexBuilder* const p_index_builder) {
const BlockBasedTableOptions& table_opt = context.table_options;
Add more LSM info to FilterBuildingContext (#8246) Summary: Add `num_levels`, `is_bottommost`, and table file creation `reason` to `FilterBuildingContext`, in anticipation of more powerful Bloom-like filter support. To support this, added `is_bottommost` and `reason` to `TableBuilderOptions`, which allowed removing `reason` parameter from `rocksdb::BuildTable`. I attempted to remove `skip_filters` from `TableBuilderOptions`, because filter construction decisions should arise from options, not one-off parameters. I could not completely remove it because the public API for SstFileWriter takes a `skip_filters` parameter, and translating this into an option change would mean awkwardly replacing the table_factory if it is BlockBasedTableFactory with new filter_policy=nullptr option. I marked this public skip_filters option as deprecated because of this oddity. (skip_filters on the read side probably makes sense.) At least `skip_filters` is now largely hidden for users of `TableBuilderOptions` and is no longer used for implementing the optimize_filters_for_hits option. Bringing the logic for that option closer to handling of FilterBuildingContext makes it more obvious that hese two are using the same notion of "bottommost." (Planned: configuration options for Bloom-like filters that generalize `optimize_filters_for_hits`) Recommended follow-up: Try to get away from "bottommost level" naming of things, which is inaccurate (see VersionStorageInfo::RangeMightExistAfterSortedRun), and move to "bottommost run" or just "bottommost." Pull Request resolved: https://github.com/facebook/rocksdb/pull/8246 Test Plan: extended an existing unit test to exercise and check various filter building contexts. Also, existing tests for optimize_filters_for_hits validate some of the "bottommost" handling, which is now closely connected to FilterBuildingContext::is_bottommost through TableBuilderOptions::is_bottommost Reviewed By: mrambacher Differential Revision: D28099346 Pulled By: pdillinger fbshipit-source-id: 2c1072e29c24d4ac404c761a7b7663292372600a
4 years ago
assert(table_opt.filter_policy); // precondition
Implement full filter for block based table. Summary: 1. Make filter_block.h a base class. Derive block_based_filter_block and full_filter_block. The previous one is the traditional filter block. The full_filter_block is newly added. It would generate a filter block that contain all the keys in SST file. 2. When querying a key, table would first check if full_filter is available. If not, it would go to the exact data block and check using block_based filter. 3. User could choose to use full_filter or tradional(block_based_filter). They would be stored in SST file with different meta index name. "filter.filter_policy" or "full_filter.filter_policy". Then, Table reader is able to know the fllter block type. 4. Some optimizations have been done for full_filter_block, thus it requires a different interface compared to the original one in filter_policy.h. 5. Actual implementation of filter bits coding/decoding is placed in util/bloom_impl.cc Benchmark: base commit 1d23b5c470844c1208301311f0889eca750431c0 Command: db_bench --db=/dev/shm/rocksdb --num_levels=6 --key_size=20 --prefix_size=20 --keys_per_prefix=0 --value_size=100 --write_buffer_size=134217728 --max_write_buffer_number=2 --target_file_size_base=33554432 --max_bytes_for_level_base=1073741824 --verify_checksum=false --max_background_compactions=4 --use_plain_table=0 --memtablerep=prefix_hash --open_files=-1 --mmap_read=1 --mmap_write=0 --bloom_bits=10 --bloom_locality=1 --memtable_bloom_bits=500000 --compression_type=lz4 --num=393216000 --use_hash_search=1 --block_size=1024 --block_restart_interval=16 --use_existing_db=1 --threads=1 --benchmarks=readrandom —disable_auto_compactions=1 Read QPS increase for about 30% from 2230002 to 2991411. Test Plan: make all check valgrind db_test db_stress --use_block_based_filter = 0 ./auto_sanity_test.sh Reviewers: igor, yhchiang, ljin, sdong Reviewed By: sdong Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D20979
10 years ago
FilterBitsBuilder* filter_bits_builder =
BloomFilterPolicy::GetBuilderFromContext(context);
Implement full filter for block based table. Summary: 1. Make filter_block.h a base class. Derive block_based_filter_block and full_filter_block. The previous one is the traditional filter block. The full_filter_block is newly added. It would generate a filter block that contain all the keys in SST file. 2. When querying a key, table would first check if full_filter is available. If not, it would go to the exact data block and check using block_based filter. 3. User could choose to use full_filter or tradional(block_based_filter). They would be stored in SST file with different meta index name. "filter.filter_policy" or "full_filter.filter_policy". Then, Table reader is able to know the fllter block type. 4. Some optimizations have been done for full_filter_block, thus it requires a different interface compared to the original one in filter_policy.h. 5. Actual implementation of filter bits coding/decoding is placed in util/bloom_impl.cc Benchmark: base commit 1d23b5c470844c1208301311f0889eca750431c0 Command: db_bench --db=/dev/shm/rocksdb --num_levels=6 --key_size=20 --prefix_size=20 --keys_per_prefix=0 --value_size=100 --write_buffer_size=134217728 --max_write_buffer_number=2 --target_file_size_base=33554432 --max_bytes_for_level_base=1073741824 --verify_checksum=false --max_background_compactions=4 --use_plain_table=0 --memtablerep=prefix_hash --open_files=-1 --mmap_read=1 --mmap_write=0 --bloom_bits=10 --bloom_locality=1 --memtable_bloom_bits=500000 --compression_type=lz4 --num=393216000 --use_hash_search=1 --block_size=1024 --block_restart_interval=16 --use_existing_db=1 --threads=1 --benchmarks=readrandom —disable_auto_compactions=1 Read QPS increase for about 30% from 2230002 to 2991411. Test Plan: make all check valgrind db_test db_stress --use_block_based_filter = 0 ./auto_sanity_test.sh Reviewers: igor, yhchiang, ljin, sdong Reviewed By: sdong Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D20979
10 years ago
if (filter_bits_builder == nullptr) {
FilterPolicy API changes for 7.0 (#9501) Summary: * Inefficient block-based filter is no longer customizable in the public API, though (for now) can still be enabled. * Removed deprecated FilterPolicy::CreateFilter() and FilterPolicy::KeyMayMatch() * Removed `rocksdb_filterpolicy_create()` from C API * Change meaning of nullptr return from GetBuilderWithContext() from "use block-based filter" to "generate no filter in this case." This is a cleaner solution to the proposal in https://github.com/facebook/rocksdb/issues/8250. * Also, when user specifies bits_per_key < 0.5, we now round this down to "no filter" because we expect a filter with >= 80% FP rate is unlikely to be worth the CPU cost of accessing it (esp with cache_index_and_filter_blocks=1 or partition_filters=1). * bits_per_key >= 0.5 and < 1.0 is still rounded up to 1.0 (for 62% FP rate) * This also gives us some support for configuring filters from OPTIONS file as currently saved: `filter_policy=rocksdb.BuiltinBloomFilter`. Opening from such an options file will enable reading filters (an improvement) but not writing new ones. (See Customizable follow-up below.) * Also removed deprecated functions * FilterBitsBuilder::CalculateNumEntry() * FilterPolicy::GetFilterBitsBuilder() * NewExperimentalRibbonFilterPolicy() * Remove default implementations of * FilterBitsBuilder::EstimateEntriesAdded() * FilterBitsBuilder::ApproximateNumEntries() * FilterPolicy::GetBuilderWithContext() * Remove support for "filter_policy=experimental_ribbon" configuration string. * Allow "filter_policy=bloomfilter:n" without bool to discourage use of block-based filter. Some pieces for https://github.com/facebook/rocksdb/issues/9389 Likely follow-up (later PRs): * Refactoring toward FilterPolicy Customizable, so that we can generate filters with same configuration as before when configuring from options file. * Remove support for user enabling block-based filter (ignore `bool use_block_based_builder`) * Some months after this change, we could even remove read support for block-based filter, because it is not critical to DB data preservation. * Make FilterBitsBuilder::FinishV2 to avoid `using FilterBitsBuilder::Finish` mess and add support for specifying a MemoryAllocator (for cache warming) Pull Request resolved: https://github.com/facebook/rocksdb/pull/9501 Test Plan: A number of obsolete tests deleted and new tests or test cases added or updated. Reviewed By: hx235 Differential Revision: D34008011 Pulled By: pdillinger fbshipit-source-id: a39a720457c354e00d5b59166b686f7f59e392aa
3 years ago
return nullptr;
Implement full filter for block based table. Summary: 1. Make filter_block.h a base class. Derive block_based_filter_block and full_filter_block. The previous one is the traditional filter block. The full_filter_block is newly added. It would generate a filter block that contain all the keys in SST file. 2. When querying a key, table would first check if full_filter is available. If not, it would go to the exact data block and check using block_based filter. 3. User could choose to use full_filter or tradional(block_based_filter). They would be stored in SST file with different meta index name. "filter.filter_policy" or "full_filter.filter_policy". Then, Table reader is able to know the fllter block type. 4. Some optimizations have been done for full_filter_block, thus it requires a different interface compared to the original one in filter_policy.h. 5. Actual implementation of filter bits coding/decoding is placed in util/bloom_impl.cc Benchmark: base commit 1d23b5c470844c1208301311f0889eca750431c0 Command: db_bench --db=/dev/shm/rocksdb --num_levels=6 --key_size=20 --prefix_size=20 --keys_per_prefix=0 --value_size=100 --write_buffer_size=134217728 --max_write_buffer_number=2 --target_file_size_base=33554432 --max_bytes_for_level_base=1073741824 --verify_checksum=false --max_background_compactions=4 --use_plain_table=0 --memtablerep=prefix_hash --open_files=-1 --mmap_read=1 --mmap_write=0 --bloom_bits=10 --bloom_locality=1 --memtable_bloom_bits=500000 --compression_type=lz4 --num=393216000 --use_hash_search=1 --block_size=1024 --block_restart_interval=16 --use_existing_db=1 --threads=1 --benchmarks=readrandom —disable_auto_compactions=1 Read QPS increase for about 30% from 2230002 to 2991411. Test Plan: make all check valgrind db_test db_stress --use_block_based_filter = 0 ./auto_sanity_test.sh Reviewers: igor, yhchiang, ljin, sdong Reviewed By: sdong Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D20979
10 years ago
} else {
if (table_opt.partition_filters) {
assert(p_index_builder != nullptr);
// Since after partition cut request from filter builder it takes time
Use size_t for filter APIs, protect against overflow (#7726) Summary: Deprecate CalculateNumEntry and replace with ApproximateNumEntries (better name) using size_t instead of int and uint32_t, to minimize confusing casts and bad overflow behavior (possible though probably not realistic). Bloom sizes are now explicitly capped at max size supported by implementations: just under 4GiB for fv=5 Bloom, and just under 512MiB for fv<5 Legacy Bloom. This hardening could help to set up for fuzzing. Also, since RocksDB only uses this information as an approximation for trying to hit certain sizes for partitioned filters, it's more important that the function be reasonably fast than for it to be completely accurate. It's hard enough to be 100% accurate for Ribbon (currently reversing CalculateSpace) that adding optimize_filters_for_memory into the mix is just not worth trying to be 100% accurate for num entries for bytes. Also: - Cleaned up filter_policy.h to remove MSVC warning handling and potentially unsafe use of exception for "not implemented" - Correct the number of entries limit beyond which current Ribbon implementation falls back on Bloom instead. - Consistently use "num_entries" rather than "num_entry" - Remove LegacyBloomBitsBuilder::CalculateNumEntry as it's essentially obsolete from general implementation BuiltinFilterBitsBuilder::CalculateNumEntries. - Fix filter_bench to skip some tests that don't make sense when only one or a small number of filters has been generated. Pull Request resolved: https://github.com/facebook/rocksdb/pull/7726 Test Plan: expanded existing unit tests for CalculateSpace / ApproximateNumEntries. Also manually used filter_bench to verify Legacy and fv=5 Bloom size caps work (much too expensive for unit test). Note that the actual bits per key is below requested due to space cap. $ ./filter_bench -impl=0 -bits_per_key=20 -average_keys_per_filter=256000000 -vary_key_count_ratio=0 -m_keys_total_max=256 -allow_bad_fp_rate ... Total size (MB): 511.992 Bits/key stored: 16.777 ... $ ./filter_bench -impl=2 -bits_per_key=20 -average_keys_per_filter=2000000000 -vary_key_count_ratio=0 -m_keys_total_max=2000 ... Total size (MB): 4096 Bits/key stored: 17.1799 ... $ Reviewed By: jay-zhuang Differential Revision: D25239800 Pulled By: pdillinger fbshipit-source-id: f94e6d065efd31e05ec630ae1a82e6400d8390c4
4 years ago
// until index builder actully cuts the partition, until the end of a
// data block potentially with many keys, we take the lower bound as
// partition size.
assert(table_opt.block_size_deviation <= 100);
auto partition_size =
static_cast<uint32_t>(((table_opt.metadata_block_size *
(100 - table_opt.block_size_deviation)) +
99) /
100);
partition_size = std::max(partition_size, static_cast<uint32_t>(1));
return new PartitionedFilterBlockBuilder(
mopt.prefix_extractor.get(), table_opt.whole_key_filtering,
filter_bits_builder, table_opt.index_block_restart_interval,
use_delta_encoding_for_index_values, p_index_builder, partition_size);
} else {
return new FullFilterBlockBuilder(mopt.prefix_extractor.get(),
table_opt.whole_key_filtering,
filter_bits_builder);
}
Implement full filter for block based table. Summary: 1. Make filter_block.h a base class. Derive block_based_filter_block and full_filter_block. The previous one is the traditional filter block. The full_filter_block is newly added. It would generate a filter block that contain all the keys in SST file. 2. When querying a key, table would first check if full_filter is available. If not, it would go to the exact data block and check using block_based filter. 3. User could choose to use full_filter or tradional(block_based_filter). They would be stored in SST file with different meta index name. "filter.filter_policy" or "full_filter.filter_policy". Then, Table reader is able to know the fllter block type. 4. Some optimizations have been done for full_filter_block, thus it requires a different interface compared to the original one in filter_policy.h. 5. Actual implementation of filter bits coding/decoding is placed in util/bloom_impl.cc Benchmark: base commit 1d23b5c470844c1208301311f0889eca750431c0 Command: db_bench --db=/dev/shm/rocksdb --num_levels=6 --key_size=20 --prefix_size=20 --keys_per_prefix=0 --value_size=100 --write_buffer_size=134217728 --max_write_buffer_number=2 --target_file_size_base=33554432 --max_bytes_for_level_base=1073741824 --verify_checksum=false --max_background_compactions=4 --use_plain_table=0 --memtablerep=prefix_hash --open_files=-1 --mmap_read=1 --mmap_write=0 --bloom_bits=10 --bloom_locality=1 --memtable_bloom_bits=500000 --compression_type=lz4 --num=393216000 --use_hash_search=1 --block_size=1024 --block_restart_interval=16 --use_existing_db=1 --threads=1 --benchmarks=readrandom —disable_auto_compactions=1 Read QPS increase for about 30% from 2230002 to 2991411. Test Plan: make all check valgrind db_test db_stress --use_block_based_filter = 0 ./auto_sanity_test.sh Reviewers: igor, yhchiang, ljin, sdong Reviewed By: sdong Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D20979
10 years ago
}
}
bool GoodCompressionRatio(size_t compressed_size, size_t raw_size) {
// Check to see if compressed less than 12.5%
return compressed_size < raw_size - (raw_size / 8u);
}
} // namespace
// format_version is the block format as defined in include/rocksdb/table.h
Slice CompressBlock(const Slice& raw, const CompressionInfo& info,
CompressionType* type, uint32_t format_version,
bool do_sample, std::string* compressed_output,
std::string* sampled_output_fast,
std::string* sampled_output_slow) {
assert(type);
assert(compressed_output);
assert(compressed_output->empty());
// If requested, we sample one in every N block with a
// fast and slow compression algorithm and report the stats.
// The users can use these stats to decide if it is worthwhile
// enabling compression and they also get a hint about which
// compression algorithm wil be beneficial.
if (do_sample && info.SampleForCompression() &&
Random::GetTLSInstance()->OneIn(
static_cast<int>(info.SampleForCompression()))) {
// Sampling with a fast compression algorithm
if (sampled_output_fast && (LZ4_Supported() || Snappy_Supported())) {
CompressionType c =
LZ4_Supported() ? kLZ4Compression : kSnappyCompression;
CompressionContext context(c);
CompressionOptions options;
CompressionInfo info_tmp(options, context,
CompressionDict::GetEmptyDict(), c,
info.SampleForCompression());
CompressData(raw, info_tmp, GetCompressFormatForVersion(format_version),
sampled_output_fast);
}
// Sampling with a slow but high-compression algorithm
if (sampled_output_slow && (ZSTD_Supported() || Zlib_Supported())) {
CompressionType c = ZSTD_Supported() ? kZSTD : kZlibCompression;
CompressionContext context(c);
CompressionOptions options;
CompressionInfo info_tmp(options, context,
CompressionDict::GetEmptyDict(), c,
info.SampleForCompression());
CompressData(raw, info_tmp, GetCompressFormatForVersion(format_version),
sampled_output_slow);
}
}
if (info.type() == kNoCompression) {
*type = kNoCompression;
return raw;
}
// Actually compress the data; if the compression method is not supported,
// or the compression fails etc., just fall back to uncompressed
if (!CompressData(raw, info, GetCompressFormatForVersion(format_version),
compressed_output)) {
*type = kNoCompression;
return raw;
}
// Check the compression ratio; if it's not good enough, just fall back to
// uncompressed
if (!GoodCompressionRatio(compressed_output->size(), raw.size())) {
*type = kNoCompression;
return raw;
}
*type = info.type();
return *compressed_output;
}
// kBlockBasedTableMagicNumber was picked by running
// echo rocksdb.table.block_based | sha1sum
// and taking the leading 64 bits.
// Please note that kBlockBasedTableMagicNumber may also be accessed by other
// .cc files
// for that reason we declare it extern in the header but to get the space
// allocated
// it must be not extern in one place.
const uint64_t kBlockBasedTableMagicNumber = 0x88e241b785f4cff7ull;
// We also support reading and writing legacy block based table format (for
// backwards compatibility)
const uint64_t kLegacyBlockBasedTableMagicNumber = 0xdb4775248b80fb57ull;
// A collector that collects properties of interest to block-based table.
// For now this class looks heavy-weight since we only write one additional
// property.
10 years ago
// But in the foreseeable future, we will add more and more properties that are
// specific to block-based table.
class BlockBasedTableBuilder::BlockBasedTablePropertiesCollector
: public IntTblPropCollector {
public:
explicit BlockBasedTablePropertiesCollector(
BlockBasedTableOptions::IndexType index_type, bool whole_key_filtering,
bool prefix_filtering)
: index_type_(index_type),
whole_key_filtering_(whole_key_filtering),
prefix_filtering_(prefix_filtering) {}
Status InternalAdd(const Slice& /*key*/, const Slice& /*value*/,
uint64_t /*file_size*/) override {
// Intentionally left blank. Have no interest in collecting stats for
// individual key/value pairs.
return Status::OK();
}
virtual void BlockAdd(uint64_t /* block_raw_bytes */,
uint64_t /* block_compressed_bytes_fast */,
uint64_t /* block_compressed_bytes_slow */) override {
// Intentionally left blank. No interest in collecting stats for
// blocks.
return;
}
Status Finish(UserCollectedProperties* properties) override {
std::string val;
PutFixed32(&val, static_cast<uint32_t>(index_type_));
properties->insert({BlockBasedTablePropertyNames::kIndexType, val});
properties->insert({BlockBasedTablePropertyNames::kWholeKeyFiltering,
whole_key_filtering_ ? kPropTrue : kPropFalse});
properties->insert({BlockBasedTablePropertyNames::kPrefixFiltering,
prefix_filtering_ ? kPropTrue : kPropFalse});
return Status::OK();
}
// The name of the properties collector can be used for debugging purpose.
const char* Name() const override {
return "BlockBasedTablePropertiesCollector";
}
UserCollectedProperties GetReadableProperties() const override {
// Intentionally left blank.
return UserCollectedProperties();
}
private:
BlockBasedTableOptions::IndexType index_type_;
bool whole_key_filtering_;
bool prefix_filtering_;
};
struct BlockBasedTableBuilder::Rep {
const ImmutableOptions ioptions;
const MutableCFOptions moptions;
const BlockBasedTableOptions table_options;
const InternalKeyComparator& internal_comparator;
WritableFileWriter* file;
std::atomic<uint64_t> offset;
size_t alignment;
BlockBuilder data_block;
// Buffers uncompressed data blocks to replay later. Needed when
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
// compression dictionary is enabled so we can finalize the dictionary before
// compressing any data blocks.
std::vector<std::string> data_block_buffers;
BlockBuilder range_del_block;
InternalKeySliceTransform internal_prefix_transform;
std::unique_ptr<IndexBuilder> index_builder;
PartitionedIndexBuilder* p_index_builder_ = nullptr;
std::string last_key;
const Slice* first_key_in_next_block = nullptr;
CompressionType compression_type;
uint64_t sample_for_compression;
std::atomic<uint64_t> compressible_input_data_bytes;
std::atomic<uint64_t> uncompressible_input_data_bytes;
std::atomic<uint64_t> sampled_input_data_bytes;
std::atomic<uint64_t> sampled_output_slow_data_bytes;
std::atomic<uint64_t> sampled_output_fast_data_bytes;
CompressionOptions compression_opts;
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
std::unique_ptr<CompressionDict> compression_dict;
std::vector<std::unique_ptr<CompressionContext>> compression_ctxs;
std::vector<std::unique_ptr<UncompressionContext>> verify_ctxs;
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
std::unique_ptr<UncompressionDict> verify_dict;
size_t data_begin_offset = 0;
TableProperties props;
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
// States of the builder.
//
// - `kBuffered`: This is the initial state where zero or more data blocks are
// accumulated uncompressed in-memory. From this state, call
// `EnterUnbuffered()` to finalize the compression dictionary if enabled,
// compress/write out any buffered blocks, and proceed to the `kUnbuffered`
// state.
//
// - `kUnbuffered`: This is the state when compression dictionary is finalized
// either because it wasn't enabled in the first place or it's been created
// from sampling previously buffered data. In this state, blocks are simply
// compressed/written out as they fill up. From this state, call `Finish()`
// to complete the file (write meta-blocks, etc.), or `Abandon()` to delete
// the partially created file.
//
// - `kClosed`: This indicates either `Finish()` or `Abandon()` has been
// called, so the table builder is no longer usable. We must be in this
// state by the time the destructor runs.
enum class State {
kBuffered,
kUnbuffered,
kClosed,
};
State state;
Limit buffering for collecting samples for compression dictionary (#7970) Summary: For dictionary compression, we need to collect some representative samples of the data to be compressed, which we use to either generate or train (when `CompressionOptions::zstd_max_train_bytes > 0`) a dictionary. Previously, the strategy was to buffer all the data blocks during flush, and up to the target file size during compaction. That strategy allowed us to randomly pick samples from as wide a range as possible that'd be guaranteed to land in a single output file. However, some users try to make huge files in memory-constrained environments, where this strategy can cause OOM. This PR introduces an option, `CompressionOptions::max_dict_buffer_bytes`, that limits how much data blocks are buffered before we switch to unbuffered mode (which means creating the per-SST dictionary, writing out the buffered data, and compressing/writing new blocks as soon as they are built). It is not strict as we currently buffer more than just data blocks -- also keys are buffered. But it does make a step towards giving users predictable memory usage. Related changes include: - Changed sampling for dictionary compression to select unique data blocks when there is limited availability of data blocks - Made use of `BlockBuilder::SwapAndReset()` to save an allocation+memcpy when buffering data blocks for building a dictionary - Changed `ParseBoolean()` to accept an input containing characters after the boolean. This is necessary since, with this PR, a value for `CompressionOptions::enabled` is no longer necessarily the final component in the `CompressionOptions` string. Pull Request resolved: https://github.com/facebook/rocksdb/pull/7970 Test Plan: - updated `CompressionOptions` unit tests to verify limit is respected (to the extent expected in the current implementation) in various scenarios of flush/compaction to bottommost/non-bottommost level - looked at jemalloc heap profiles right before and after switching to unbuffered mode during flush/compaction. Verified memory usage in buffering is proportional to the limit set. Reviewed By: pdillinger Differential Revision: D26467994 Pulled By: ajkr fbshipit-source-id: 3da4ef9fba59974e4ef40e40c01611002c861465
4 years ago
// `kBuffered` state is allowed only as long as the buffering of uncompressed
// data blocks (see `data_block_buffers`) does not exceed `buffer_limit`.
Limit buffering for collecting samples for compression dictionary (#7970) Summary: For dictionary compression, we need to collect some representative samples of the data to be compressed, which we use to either generate or train (when `CompressionOptions::zstd_max_train_bytes > 0`) a dictionary. Previously, the strategy was to buffer all the data blocks during flush, and up to the target file size during compaction. That strategy allowed us to randomly pick samples from as wide a range as possible that'd be guaranteed to land in a single output file. However, some users try to make huge files in memory-constrained environments, where this strategy can cause OOM. This PR introduces an option, `CompressionOptions::max_dict_buffer_bytes`, that limits how much data blocks are buffered before we switch to unbuffered mode (which means creating the per-SST dictionary, writing out the buffered data, and compressing/writing new blocks as soon as they are built). It is not strict as we currently buffer more than just data blocks -- also keys are buffered. But it does make a step towards giving users predictable memory usage. Related changes include: - Changed sampling for dictionary compression to select unique data blocks when there is limited availability of data blocks - Made use of `BlockBuilder::SwapAndReset()` to save an allocation+memcpy when buffering data blocks for building a dictionary - Changed `ParseBoolean()` to accept an input containing characters after the boolean. This is necessary since, with this PR, a value for `CompressionOptions::enabled` is no longer necessarily the final component in the `CompressionOptions` string. Pull Request resolved: https://github.com/facebook/rocksdb/pull/7970 Test Plan: - updated `CompressionOptions` unit tests to verify limit is respected (to the extent expected in the current implementation) in various scenarios of flush/compaction to bottommost/non-bottommost level - looked at jemalloc heap profiles right before and after switching to unbuffered mode during flush/compaction. Verified memory usage in buffering is proportional to the limit set. Reviewed By: pdillinger Differential Revision: D26467994 Pulled By: ajkr fbshipit-source-id: 3da4ef9fba59974e4ef40e40c01611002c861465
4 years ago
uint64_t buffer_limit;
Account memory of big memory users in BlockBasedTable in global memory limit (#9748) Summary: **Context:** Through heap profiling, we discovered that `BlockBasedTableReader` objects can accumulate and lead to high memory usage (e.g, `max_open_file = -1`). These memories are currently not saved, not tracked, not constrained and not cache evict-able. As a first step to improve this, similar to https://github.com/facebook/rocksdb/pull/8428, this PR is to track an estimate of `BlockBasedTableReader` object's memory in block cache and fail future creation if the memory usage exceeds the available space of cache at the time of creation. **Summary:** - Approximate big memory users (`BlockBasedTable::Rep` and `TableProperties` )' memory usage in addition to the existing estimated ones (filter block/index block/un-compression dictionary) - Charge all of these memory usages to block cache on `BlockBasedTable::Open()` and release them on `~BlockBasedTable()` as there is no memory usage fluctuation of concern in between - Refactor on CacheReservationManager (and its call-sites) to add concurrent support for BlockBasedTable used in this PR. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9748 Test Plan: - New unit tests - db bench: `OpenDb` : **-0.52% in ms** - Setup `./db_bench -benchmarks=fillseq -db=/dev/shm/testdb -disable_auto_compactions=1 -write_buffer_size=1048576` - Repeated run with pre-change w/o feature and post-change with feature, benchmark `OpenDb`: `./db_bench -benchmarks=readrandom -use_existing_db=1 -db=/dev/shm/testdb -reserve_table_reader_memory=true (remove this when running w/o feature) -file_opening_threads=3 -open_files=-1 -report_open_timing=true| egrep 'OpenDb:'` #-run | (feature-off) avg milliseconds | std milliseconds | (feature-on) avg milliseconds | std milliseconds | change (%) -- | -- | -- | -- | -- | -- 10 | 11.4018 | 5.95173 | 9.47788 | 1.57538 | -16.87382694 20 | 9.23746 | 0.841053 | 9.32377 | 1.14074 | 0.9343477536 40 | 9.0876 | 0.671129 | 9.35053 | 1.11713 | 2.893283155 80 | 9.72514 | 2.28459 | 9.52013 | 1.0894 | -2.108041632 160 | 9.74677 | 0.991234 | 9.84743 | 1.73396 | 1.032752389 320 | 10.7297 | 5.11555 | 10.547 | 1.97692 | **-1.70275031** 640 | 11.7092 | 2.36565 | 11.7869 | 2.69377 | **0.6635807741** - db bench on write with cost to cache in WriteBufferManager (just in case this PR's CRM refactoring accidentally slows down anything in WBM) : `fillseq` : **+0.54% in micros/op** `./db_bench -benchmarks=fillseq -db=/dev/shm/testdb -disable_auto_compactions=1 -cost_write_buffer_to_cache=true -write_buffer_size=10000000000 | egrep 'fillseq'` #-run | (pre-PR) avg micros/op | std micros/op | (post-PR) avg micros/op | std micros/op | change (%) -- | -- | -- | -- | -- | -- 10 | 6.15 | 0.260187 | 6.289 | 0.371192 | 2.260162602 20 | 7.28025 | 0.465402 | 7.37255 | 0.451256 | 1.267813605 40 | 7.06312 | 0.490654 | 7.13803 | 0.478676 | **1.060579461** 80 | 7.14035 | 0.972831 | 7.14196 | 0.92971 | **0.02254791432** - filter bench: `bloom filter`: **-0.78% in ms/key** - ` ./filter_bench -impl=2 -quick -reserve_table_builder_memory=true | grep 'Build avg'` #-run | (pre-PR) avg ns/key | std ns/key | (post-PR) ns/key | std ns/key | change (%) -- | -- | -- | -- | -- | -- 10 | 26.4369 | 0.442182 | 26.3273 | 0.422919 | **-0.4145720565** 20 | 26.4451 | 0.592787 | 26.1419 | 0.62451 | **-1.1465262** - Crash test `python3 tools/db_crashtest.py blackbox --reserve_table_reader_memory=1 --cache_size=1` killed as normal Reviewed By: ajkr Differential Revision: D35136549 Pulled By: hx235 fbshipit-source-id: 146978858d0f900f43f4eb09bfd3e83195e3be28
3 years ago
std::shared_ptr<CacheReservationManager>
compression_dict_buffer_cache_res_mgr;
const bool use_delta_encoding_for_index_values;
std::unique_ptr<FilterBlockBuilder> filter_builder;
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
OffsetableCacheKey base_cache_key;
const TableFileCreationReason reason;
BlockHandle pending_handle; // Handle to add to index block
std::string compressed_output;
std::unique_ptr<FlushBlockPolicy> flush_block_policy;
std::vector<std::unique_ptr<IntTblPropCollector>> table_properties_collectors;
TablePropertiesCollectorFactory Summary: This diff addresses task #4296714 and rethinks how users provide us with TablePropertiesCollectors as part of Options. Here's description of task #4296714: I'm debugging #4295529 and noticed that our count of user properties kDeletedKeys is wrong. We're sharing one single InternalKeyPropertiesCollector with all Table Builders. In LOG Files, we're outputting number of kDeletedKeys as connected with a single table, while it's actually the total count of deleted keys since creation of the DB. For example, this table has 3155 entries and 1391828 deleted keys. The problem with current approach that we call methods on a single TablePropertiesCollector for all the tables we create. Even worse, we could do it from multiple threads at the same time and TablePropertiesCollector has no way of knowing which table we're calling it for. Good part: Looks like nobody inside Facebook is using Options::table_properties_collectors. This means we should be able to painfully change the API. In this change, I introduce TablePropertiesCollectorFactory. For every table we create, we call `CreateTablePropertiesCollector`, which creates a TablePropertiesCollector for a single table. We then use it sequentially from a single thread, which means it doesn't have to be thread-safe. Test Plan: Added a test in table_properties_collector_test that fails on master (build two tables, assert that kDeletedKeys count is correct for the second one). Also, all other tests Reviewers: sdong, dhruba, haobo, kailiu Reviewed By: kailiu CC: leveldb Differential Revision: https://reviews.facebook.net/D18579
11 years ago
std::unique_ptr<ParallelCompressionRep> pc_rep;
uint64_t get_offset() { return offset.load(std::memory_order_relaxed); }
void set_offset(uint64_t o) { offset.store(o, std::memory_order_relaxed); }
bool IsParallelCompressionEnabled() const {
return compression_opts.parallel_threads > 1;
}
Status GetStatus() {
// We need to make modifications of status visible when status_ok is set
// to false, and this is ensured by status_mutex, so no special memory
// order for status_ok is required.
if (status_ok.load(std::memory_order_relaxed)) {
return Status::OK();
} else {
return CopyStatus();
}
}
Status CopyStatus() {
std::lock_guard<std::mutex> lock(status_mutex);
return status;
}
IOStatus GetIOStatus() {
// We need to make modifications of io_status visible when status_ok is set
// to false, and this is ensured by io_status_mutex, so no special memory
// order for io_status_ok is required.
if (io_status_ok.load(std::memory_order_relaxed)) {
return IOStatus::OK();
} else {
return CopyIOStatus();
}
}
IOStatus CopyIOStatus() {
std::lock_guard<std::mutex> lock(io_status_mutex);
return io_status;
}
// Never erase an existing status that is not OK.
void SetStatus(Status s) {
if (!s.ok() && status_ok.load(std::memory_order_relaxed)) {
// Locking is an overkill for non compression_opts.parallel_threads
// case but since it's unlikely that s is not OK, we take this cost
// to be simplicity.
std::lock_guard<std::mutex> lock(status_mutex);
status = s;
status_ok.store(false, std::memory_order_relaxed);
}
}
// Never erase an existing I/O status that is not OK.
// Calling this will also SetStatus(ios)
void SetIOStatus(IOStatus ios) {
if (!ios.ok() && io_status_ok.load(std::memory_order_relaxed)) {
// Locking is an overkill for non compression_opts.parallel_threads
// case but since it's unlikely that s is not OK, we take this cost
// to be simplicity.
std::lock_guard<std::mutex> lock(io_status_mutex);
io_status = ios;
io_status_ok.store(false, std::memory_order_relaxed);
}
SetStatus(ios);
}
Rep(const BlockBasedTableOptions& table_opt, const TableBuilderOptions& tbo,
WritableFileWriter* f)
: ioptions(tbo.ioptions),
moptions(tbo.moptions),
table_options(table_opt),
internal_comparator(tbo.internal_comparator),
file(f),
offset(0),
alignment(table_options.block_align
? std::min(static_cast<size_t>(table_options.block_size),
kDefaultPageSize)
: 0),
Introduce ReadOptions::pin_data (support zero copy for keys) Summary: This patch update the Iterator API to introduce new functions that allow users to keep the Slices returned by key() valid as long as the Iterator is not deleted ReadOptions::pin_data : If true keep loaded blocks in memory as long as the iterator is not deleted Iterator::IsKeyPinned() : If true, this mean that the Slice returned by key() is valid as long as the iterator is not deleted Also add a new option BlockBasedTableOptions::use_delta_encoding to allow users to disable delta_encoding if needed. Benchmark results (using https://phabricator.fb.com/P20083553) ``` // $ du -h /home/tec/local/normal.4K.Snappy/db10077 // 6.1G /home/tec/local/normal.4K.Snappy/db10077 // $ du -h /home/tec/local/zero.8K.LZ4/db10077 // 6.4G /home/tec/local/zero.8K.LZ4/db10077 // Benchmarks for shard db10077 // _build/opt/rocks/benchmark/rocks_copy_benchmark \ // --normal_db_path="/home/tec/local/normal.4K.Snappy/db10077" \ // --zero_db_path="/home/tec/local/zero.8K.LZ4/db10077" // First run // ============================================================================ // rocks/benchmark/RocksCopyBenchmark.cpp relative time/iter iters/s // ============================================================================ // BM_StringCopy 1.73s 576.97m // BM_StringPiece 103.74% 1.67s 598.55m // ============================================================================ // Match rate : 1000000 / 1000000 // Second run // ============================================================================ // rocks/benchmark/RocksCopyBenchmark.cpp relative time/iter iters/s // ============================================================================ // BM_StringCopy 611.99ms 1.63 // BM_StringPiece 203.76% 300.35ms 3.33 // ============================================================================ // Match rate : 1000000 / 1000000 ``` Test Plan: Unit tests Reviewers: sdong, igor, anthony, yhchiang, rven Reviewed By: rven Subscribers: dhruba, lovro, adsharma Differential Revision: https://reviews.facebook.net/D48999
9 years ago
data_block(table_options.block_restart_interval,
table_options.use_delta_encoding,
false /* use_value_delta_encoding */,
tbo.internal_comparator.user_comparator()
->CanKeysWithDifferentByteContentsBeEqual()
? BlockBasedTableOptions::kDataBlockBinarySearch
: table_options.data_block_index_type,
table_options.data_block_hash_table_util_ratio),
range_del_block(1 /* block_restart_interval */),
internal_prefix_transform(tbo.moptions.prefix_extractor.get()),
compression_type(tbo.compression_type),
sample_for_compression(tbo.moptions.sample_for_compression),
compressible_input_data_bytes(0),
uncompressible_input_data_bytes(0),
sampled_input_data_bytes(0),
sampled_output_slow_data_bytes(0),
sampled_output_fast_data_bytes(0),
compression_opts(tbo.compression_opts),
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
compression_dict(),
compression_ctxs(tbo.compression_opts.parallel_threads),
verify_ctxs(tbo.compression_opts.parallel_threads),
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
verify_dict(),
state((tbo.compression_opts.max_dict_bytes > 0) ? State::kBuffered
: State::kUnbuffered),
use_delta_encoding_for_index_values(table_opt.format_version >= 4 &&
!table_opt.block_align),
reason(tbo.reason),
flush_block_policy(
table_options.flush_block_policy_factory->NewFlushBlockPolicy(
table_options, data_block)),
status_ok(true),
io_status_ok(true) {
if (tbo.target_file_size == 0) {
Limit buffering for collecting samples for compression dictionary (#7970) Summary: For dictionary compression, we need to collect some representative samples of the data to be compressed, which we use to either generate or train (when `CompressionOptions::zstd_max_train_bytes > 0`) a dictionary. Previously, the strategy was to buffer all the data blocks during flush, and up to the target file size during compaction. That strategy allowed us to randomly pick samples from as wide a range as possible that'd be guaranteed to land in a single output file. However, some users try to make huge files in memory-constrained environments, where this strategy can cause OOM. This PR introduces an option, `CompressionOptions::max_dict_buffer_bytes`, that limits how much data blocks are buffered before we switch to unbuffered mode (which means creating the per-SST dictionary, writing out the buffered data, and compressing/writing new blocks as soon as they are built). It is not strict as we currently buffer more than just data blocks -- also keys are buffered. But it does make a step towards giving users predictable memory usage. Related changes include: - Changed sampling for dictionary compression to select unique data blocks when there is limited availability of data blocks - Made use of `BlockBuilder::SwapAndReset()` to save an allocation+memcpy when buffering data blocks for building a dictionary - Changed `ParseBoolean()` to accept an input containing characters after the boolean. This is necessary since, with this PR, a value for `CompressionOptions::enabled` is no longer necessarily the final component in the `CompressionOptions` string. Pull Request resolved: https://github.com/facebook/rocksdb/pull/7970 Test Plan: - updated `CompressionOptions` unit tests to verify limit is respected (to the extent expected in the current implementation) in various scenarios of flush/compaction to bottommost/non-bottommost level - looked at jemalloc heap profiles right before and after switching to unbuffered mode during flush/compaction. Verified memory usage in buffering is proportional to the limit set. Reviewed By: pdillinger Differential Revision: D26467994 Pulled By: ajkr fbshipit-source-id: 3da4ef9fba59974e4ef40e40c01611002c861465
4 years ago
buffer_limit = compression_opts.max_dict_buffer_bytes;
} else if (compression_opts.max_dict_buffer_bytes == 0) {
buffer_limit = tbo.target_file_size;
Limit buffering for collecting samples for compression dictionary (#7970) Summary: For dictionary compression, we need to collect some representative samples of the data to be compressed, which we use to either generate or train (when `CompressionOptions::zstd_max_train_bytes > 0`) a dictionary. Previously, the strategy was to buffer all the data blocks during flush, and up to the target file size during compaction. That strategy allowed us to randomly pick samples from as wide a range as possible that'd be guaranteed to land in a single output file. However, some users try to make huge files in memory-constrained environments, where this strategy can cause OOM. This PR introduces an option, `CompressionOptions::max_dict_buffer_bytes`, that limits how much data blocks are buffered before we switch to unbuffered mode (which means creating the per-SST dictionary, writing out the buffered data, and compressing/writing new blocks as soon as they are built). It is not strict as we currently buffer more than just data blocks -- also keys are buffered. But it does make a step towards giving users predictable memory usage. Related changes include: - Changed sampling for dictionary compression to select unique data blocks when there is limited availability of data blocks - Made use of `BlockBuilder::SwapAndReset()` to save an allocation+memcpy when buffering data blocks for building a dictionary - Changed `ParseBoolean()` to accept an input containing characters after the boolean. This is necessary since, with this PR, a value for `CompressionOptions::enabled` is no longer necessarily the final component in the `CompressionOptions` string. Pull Request resolved: https://github.com/facebook/rocksdb/pull/7970 Test Plan: - updated `CompressionOptions` unit tests to verify limit is respected (to the extent expected in the current implementation) in various scenarios of flush/compaction to bottommost/non-bottommost level - looked at jemalloc heap profiles right before and after switching to unbuffered mode during flush/compaction. Verified memory usage in buffering is proportional to the limit set. Reviewed By: pdillinger Differential Revision: D26467994 Pulled By: ajkr fbshipit-source-id: 3da4ef9fba59974e4ef40e40c01611002c861465
4 years ago
} else {
buffer_limit = std::min(tbo.target_file_size,
compression_opts.max_dict_buffer_bytes);
Limit buffering for collecting samples for compression dictionary (#7970) Summary: For dictionary compression, we need to collect some representative samples of the data to be compressed, which we use to either generate or train (when `CompressionOptions::zstd_max_train_bytes > 0`) a dictionary. Previously, the strategy was to buffer all the data blocks during flush, and up to the target file size during compaction. That strategy allowed us to randomly pick samples from as wide a range as possible that'd be guaranteed to land in a single output file. However, some users try to make huge files in memory-constrained environments, where this strategy can cause OOM. This PR introduces an option, `CompressionOptions::max_dict_buffer_bytes`, that limits how much data blocks are buffered before we switch to unbuffered mode (which means creating the per-SST dictionary, writing out the buffered data, and compressing/writing new blocks as soon as they are built). It is not strict as we currently buffer more than just data blocks -- also keys are buffered. But it does make a step towards giving users predictable memory usage. Related changes include: - Changed sampling for dictionary compression to select unique data blocks when there is limited availability of data blocks - Made use of `BlockBuilder::SwapAndReset()` to save an allocation+memcpy when buffering data blocks for building a dictionary - Changed `ParseBoolean()` to accept an input containing characters after the boolean. This is necessary since, with this PR, a value for `CompressionOptions::enabled` is no longer necessarily the final component in the `CompressionOptions` string. Pull Request resolved: https://github.com/facebook/rocksdb/pull/7970 Test Plan: - updated `CompressionOptions` unit tests to verify limit is respected (to the extent expected in the current implementation) in various scenarios of flush/compaction to bottommost/non-bottommost level - looked at jemalloc heap profiles right before and after switching to unbuffered mode during flush/compaction. Verified memory usage in buffering is proportional to the limit set. Reviewed By: pdillinger Differential Revision: D26467994 Pulled By: ajkr fbshipit-source-id: 3da4ef9fba59974e4ef40e40c01611002c861465
4 years ago
}
Rewrite memory-charging feature's option API (#9926) Summary: **Context:** Previous PR https://github.com/facebook/rocksdb/pull/9748, https://github.com/facebook/rocksdb/pull/9073, https://github.com/facebook/rocksdb/pull/8428 added separate flag for each charged memory area. Such API design is not scalable as we charge more and more memory areas. Also, we foresee an opportunity to consolidate this feature with other cache usage related features such as `cache_index_and_filter_blocks` using `CacheEntryRole`. Therefore we decided to consolidate all these flags with `CacheUsageOptions cache_usage_options` and this PR serves as the first step by consolidating memory-charging related flags. **Summary:** - Replaced old API reference with new ones, including making `kCompressionDictionaryBuildingBuffer` opt-out and added a unit test for that - Added missing db bench/stress test for some memory charging features - Renamed related test suite to indicate they are under the same theme of memory charging - Refactored a commonly used mocked cache component in memory charging related tests to reduce code duplication - Replaced the phrases "memory tracking" / "cache reservation" (other than CacheReservationManager-related ones) with "memory charging" for standard description of this feature. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9926 Test Plan: - New unit test for opt-out `kCompressionDictionaryBuildingBuffer` `TEST_F(ChargeCompressionDictionaryBuildingBufferTest, Basic)` - New unit test for option validation/sanitization `TEST_F(CacheUsageOptionsOverridesTest, SanitizeAndValidateOptions)` - CI - db bench (in case querying new options introduces regression) **+0.5% micros/op**: `TEST_TMPDIR=/dev/shm/testdb ./db_bench -benchmarks=fillseq -db=$TEST_TMPDIR -charge_compression_dictionary_building_buffer=1(remove this for comparison) -compression_max_dict_bytes=10000 -disable_auto_compactions=1 -write_buffer_size=100000 -num=4000000 | egrep 'fillseq'` #-run | (pre-PR) avg micros/op | std micros/op | (post-PR) micros/op | std micros/op | change (%) -- | -- | -- | -- | -- | -- 10 | 3.9711 | 0.264408 | 3.9914 | 0.254563 | 0.5111933721 20 | 3.83905 | 0.0664488 | 3.8251 | 0.0695456 | **-0.3633711465** 40 | 3.86625 | 0.136669 | 3.8867 | 0.143765 | **0.5289363078** - db_stress: `python3 tools/db_crashtest.py blackbox -charge_compression_dictionary_building_buffer=1 -charge_filter_construction=1 -charge_table_reader=1 -cache_size=1` killed as normal Reviewed By: ajkr Differential Revision: D36054712 Pulled By: hx235 fbshipit-source-id: d406e90f5e0c5ea4dbcb585a484ad9302d4302af
3 years ago
const auto compress_dict_build_buffer_charged =
table_options.cache_usage_options.options_overrides
.at(CacheEntryRole::kCompressionDictionaryBuildingBuffer)
.charged;
if (table_options.block_cache &&
(compress_dict_build_buffer_charged ==
CacheEntryRoleOptions::Decision::kEnabled ||
compress_dict_build_buffer_charged ==
CacheEntryRoleOptions::Decision::kFallback)) {
Account memory of big memory users in BlockBasedTable in global memory limit (#9748) Summary: **Context:** Through heap profiling, we discovered that `BlockBasedTableReader` objects can accumulate and lead to high memory usage (e.g, `max_open_file = -1`). These memories are currently not saved, not tracked, not constrained and not cache evict-able. As a first step to improve this, similar to https://github.com/facebook/rocksdb/pull/8428, this PR is to track an estimate of `BlockBasedTableReader` object's memory in block cache and fail future creation if the memory usage exceeds the available space of cache at the time of creation. **Summary:** - Approximate big memory users (`BlockBasedTable::Rep` and `TableProperties` )' memory usage in addition to the existing estimated ones (filter block/index block/un-compression dictionary) - Charge all of these memory usages to block cache on `BlockBasedTable::Open()` and release them on `~BlockBasedTable()` as there is no memory usage fluctuation of concern in between - Refactor on CacheReservationManager (and its call-sites) to add concurrent support for BlockBasedTable used in this PR. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9748 Test Plan: - New unit tests - db bench: `OpenDb` : **-0.52% in ms** - Setup `./db_bench -benchmarks=fillseq -db=/dev/shm/testdb -disable_auto_compactions=1 -write_buffer_size=1048576` - Repeated run with pre-change w/o feature and post-change with feature, benchmark `OpenDb`: `./db_bench -benchmarks=readrandom -use_existing_db=1 -db=/dev/shm/testdb -reserve_table_reader_memory=true (remove this when running w/o feature) -file_opening_threads=3 -open_files=-1 -report_open_timing=true| egrep 'OpenDb:'` #-run | (feature-off) avg milliseconds | std milliseconds | (feature-on) avg milliseconds | std milliseconds | change (%) -- | -- | -- | -- | -- | -- 10 | 11.4018 | 5.95173 | 9.47788 | 1.57538 | -16.87382694 20 | 9.23746 | 0.841053 | 9.32377 | 1.14074 | 0.9343477536 40 | 9.0876 | 0.671129 | 9.35053 | 1.11713 | 2.893283155 80 | 9.72514 | 2.28459 | 9.52013 | 1.0894 | -2.108041632 160 | 9.74677 | 0.991234 | 9.84743 | 1.73396 | 1.032752389 320 | 10.7297 | 5.11555 | 10.547 | 1.97692 | **-1.70275031** 640 | 11.7092 | 2.36565 | 11.7869 | 2.69377 | **0.6635807741** - db bench on write with cost to cache in WriteBufferManager (just in case this PR's CRM refactoring accidentally slows down anything in WBM) : `fillseq` : **+0.54% in micros/op** `./db_bench -benchmarks=fillseq -db=/dev/shm/testdb -disable_auto_compactions=1 -cost_write_buffer_to_cache=true -write_buffer_size=10000000000 | egrep 'fillseq'` #-run | (pre-PR) avg micros/op | std micros/op | (post-PR) avg micros/op | std micros/op | change (%) -- | -- | -- | -- | -- | -- 10 | 6.15 | 0.260187 | 6.289 | 0.371192 | 2.260162602 20 | 7.28025 | 0.465402 | 7.37255 | 0.451256 | 1.267813605 40 | 7.06312 | 0.490654 | 7.13803 | 0.478676 | **1.060579461** 80 | 7.14035 | 0.972831 | 7.14196 | 0.92971 | **0.02254791432** - filter bench: `bloom filter`: **-0.78% in ms/key** - ` ./filter_bench -impl=2 -quick -reserve_table_builder_memory=true | grep 'Build avg'` #-run | (pre-PR) avg ns/key | std ns/key | (post-PR) ns/key | std ns/key | change (%) -- | -- | -- | -- | -- | -- 10 | 26.4369 | 0.442182 | 26.3273 | 0.422919 | **-0.4145720565** 20 | 26.4451 | 0.592787 | 26.1419 | 0.62451 | **-1.1465262** - Crash test `python3 tools/db_crashtest.py blackbox --reserve_table_reader_memory=1 --cache_size=1` killed as normal Reviewed By: ajkr Differential Revision: D35136549 Pulled By: hx235 fbshipit-source-id: 146978858d0f900f43f4eb09bfd3e83195e3be28
3 years ago
compression_dict_buffer_cache_res_mgr =
std::make_shared<CacheReservationManagerImpl<
CacheEntryRole::kCompressionDictionaryBuildingBuffer>>(
table_options.block_cache);
Rewrite memory-charging feature's option API (#9926) Summary: **Context:** Previous PR https://github.com/facebook/rocksdb/pull/9748, https://github.com/facebook/rocksdb/pull/9073, https://github.com/facebook/rocksdb/pull/8428 added separate flag for each charged memory area. Such API design is not scalable as we charge more and more memory areas. Also, we foresee an opportunity to consolidate this feature with other cache usage related features such as `cache_index_and_filter_blocks` using `CacheEntryRole`. Therefore we decided to consolidate all these flags with `CacheUsageOptions cache_usage_options` and this PR serves as the first step by consolidating memory-charging related flags. **Summary:** - Replaced old API reference with new ones, including making `kCompressionDictionaryBuildingBuffer` opt-out and added a unit test for that - Added missing db bench/stress test for some memory charging features - Renamed related test suite to indicate they are under the same theme of memory charging - Refactored a commonly used mocked cache component in memory charging related tests to reduce code duplication - Replaced the phrases "memory tracking" / "cache reservation" (other than CacheReservationManager-related ones) with "memory charging" for standard description of this feature. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9926 Test Plan: - New unit test for opt-out `kCompressionDictionaryBuildingBuffer` `TEST_F(ChargeCompressionDictionaryBuildingBufferTest, Basic)` - New unit test for option validation/sanitization `TEST_F(CacheUsageOptionsOverridesTest, SanitizeAndValidateOptions)` - CI - db bench (in case querying new options introduces regression) **+0.5% micros/op**: `TEST_TMPDIR=/dev/shm/testdb ./db_bench -benchmarks=fillseq -db=$TEST_TMPDIR -charge_compression_dictionary_building_buffer=1(remove this for comparison) -compression_max_dict_bytes=10000 -disable_auto_compactions=1 -write_buffer_size=100000 -num=4000000 | egrep 'fillseq'` #-run | (pre-PR) avg micros/op | std micros/op | (post-PR) micros/op | std micros/op | change (%) -- | -- | -- | -- | -- | -- 10 | 3.9711 | 0.264408 | 3.9914 | 0.254563 | 0.5111933721 20 | 3.83905 | 0.0664488 | 3.8251 | 0.0695456 | **-0.3633711465** 40 | 3.86625 | 0.136669 | 3.8867 | 0.143765 | **0.5289363078** - db_stress: `python3 tools/db_crashtest.py blackbox -charge_compression_dictionary_building_buffer=1 -charge_filter_construction=1 -charge_table_reader=1 -cache_size=1` killed as normal Reviewed By: ajkr Differential Revision: D36054712 Pulled By: hx235 fbshipit-source-id: d406e90f5e0c5ea4dbcb585a484ad9302d4302af
3 years ago
} else {
compression_dict_buffer_cache_res_mgr = nullptr;
}
Rewrite memory-charging feature's option API (#9926) Summary: **Context:** Previous PR https://github.com/facebook/rocksdb/pull/9748, https://github.com/facebook/rocksdb/pull/9073, https://github.com/facebook/rocksdb/pull/8428 added separate flag for each charged memory area. Such API design is not scalable as we charge more and more memory areas. Also, we foresee an opportunity to consolidate this feature with other cache usage related features such as `cache_index_and_filter_blocks` using `CacheEntryRole`. Therefore we decided to consolidate all these flags with `CacheUsageOptions cache_usage_options` and this PR serves as the first step by consolidating memory-charging related flags. **Summary:** - Replaced old API reference with new ones, including making `kCompressionDictionaryBuildingBuffer` opt-out and added a unit test for that - Added missing db bench/stress test for some memory charging features - Renamed related test suite to indicate they are under the same theme of memory charging - Refactored a commonly used mocked cache component in memory charging related tests to reduce code duplication - Replaced the phrases "memory tracking" / "cache reservation" (other than CacheReservationManager-related ones) with "memory charging" for standard description of this feature. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9926 Test Plan: - New unit test for opt-out `kCompressionDictionaryBuildingBuffer` `TEST_F(ChargeCompressionDictionaryBuildingBufferTest, Basic)` - New unit test for option validation/sanitization `TEST_F(CacheUsageOptionsOverridesTest, SanitizeAndValidateOptions)` - CI - db bench (in case querying new options introduces regression) **+0.5% micros/op**: `TEST_TMPDIR=/dev/shm/testdb ./db_bench -benchmarks=fillseq -db=$TEST_TMPDIR -charge_compression_dictionary_building_buffer=1(remove this for comparison) -compression_max_dict_bytes=10000 -disable_auto_compactions=1 -write_buffer_size=100000 -num=4000000 | egrep 'fillseq'` #-run | (pre-PR) avg micros/op | std micros/op | (post-PR) micros/op | std micros/op | change (%) -- | -- | -- | -- | -- | -- 10 | 3.9711 | 0.264408 | 3.9914 | 0.254563 | 0.5111933721 20 | 3.83905 | 0.0664488 | 3.8251 | 0.0695456 | **-0.3633711465** 40 | 3.86625 | 0.136669 | 3.8867 | 0.143765 | **0.5289363078** - db_stress: `python3 tools/db_crashtest.py blackbox -charge_compression_dictionary_building_buffer=1 -charge_filter_construction=1 -charge_table_reader=1 -cache_size=1` killed as normal Reviewed By: ajkr Differential Revision: D36054712 Pulled By: hx235 fbshipit-source-id: d406e90f5e0c5ea4dbcb585a484ad9302d4302af
3 years ago
for (uint32_t i = 0; i < compression_opts.parallel_threads; i++) {
compression_ctxs[i].reset(new CompressionContext(compression_type));
}
if (table_options.index_type ==
BlockBasedTableOptions::kTwoLevelIndexSearch) {
p_index_builder_ = PartitionedIndexBuilder::CreateIndexBuilder(
&internal_comparator, use_delta_encoding_for_index_values,
table_options);
index_builder.reset(p_index_builder_);
} else {
index_builder.reset(IndexBuilder::CreateIndexBuilder(
table_options.index_type, &internal_comparator,
&this->internal_prefix_transform, use_delta_encoding_for_index_values,
table_options));
}
Add more LSM info to FilterBuildingContext (#8246) Summary: Add `num_levels`, `is_bottommost`, and table file creation `reason` to `FilterBuildingContext`, in anticipation of more powerful Bloom-like filter support. To support this, added `is_bottommost` and `reason` to `TableBuilderOptions`, which allowed removing `reason` parameter from `rocksdb::BuildTable`. I attempted to remove `skip_filters` from `TableBuilderOptions`, because filter construction decisions should arise from options, not one-off parameters. I could not completely remove it because the public API for SstFileWriter takes a `skip_filters` parameter, and translating this into an option change would mean awkwardly replacing the table_factory if it is BlockBasedTableFactory with new filter_policy=nullptr option. I marked this public skip_filters option as deprecated because of this oddity. (skip_filters on the read side probably makes sense.) At least `skip_filters` is now largely hidden for users of `TableBuilderOptions` and is no longer used for implementing the optimize_filters_for_hits option. Bringing the logic for that option closer to handling of FilterBuildingContext makes it more obvious that hese two are using the same notion of "bottommost." (Planned: configuration options for Bloom-like filters that generalize `optimize_filters_for_hits`) Recommended follow-up: Try to get away from "bottommost level" naming of things, which is inaccurate (see VersionStorageInfo::RangeMightExistAfterSortedRun), and move to "bottommost run" or just "bottommost." Pull Request resolved: https://github.com/facebook/rocksdb/pull/8246 Test Plan: extended an existing unit test to exercise and check various filter building contexts. Also, existing tests for optimize_filters_for_hits validate some of the "bottommost" handling, which is now closely connected to FilterBuildingContext::is_bottommost through TableBuilderOptions::is_bottommost Reviewed By: mrambacher Differential Revision: D28099346 Pulled By: pdillinger fbshipit-source-id: 2c1072e29c24d4ac404c761a7b7663292372600a
4 years ago
if (ioptions.optimize_filters_for_hits && tbo.is_bottommost) {
// Apply optimize_filters_for_hits setting here when applicable by
// skipping filter generation
filter_builder.reset();
} else if (tbo.skip_filters) {
// For SstFileWriter skip_filters
filter_builder.reset();
} else if (!table_options.filter_policy) {
// Null filter_policy -> no filter
filter_builder.reset();
} else {
FilterBuildingContext filter_context(table_options);
filter_context.info_log = ioptions.logger;
Add more LSM info to FilterBuildingContext (#8246) Summary: Add `num_levels`, `is_bottommost`, and table file creation `reason` to `FilterBuildingContext`, in anticipation of more powerful Bloom-like filter support. To support this, added `is_bottommost` and `reason` to `TableBuilderOptions`, which allowed removing `reason` parameter from `rocksdb::BuildTable`. I attempted to remove `skip_filters` from `TableBuilderOptions`, because filter construction decisions should arise from options, not one-off parameters. I could not completely remove it because the public API for SstFileWriter takes a `skip_filters` parameter, and translating this into an option change would mean awkwardly replacing the table_factory if it is BlockBasedTableFactory with new filter_policy=nullptr option. I marked this public skip_filters option as deprecated because of this oddity. (skip_filters on the read side probably makes sense.) At least `skip_filters` is now largely hidden for users of `TableBuilderOptions` and is no longer used for implementing the optimize_filters_for_hits option. Bringing the logic for that option closer to handling of FilterBuildingContext makes it more obvious that hese two are using the same notion of "bottommost." (Planned: configuration options for Bloom-like filters that generalize `optimize_filters_for_hits`) Recommended follow-up: Try to get away from "bottommost level" naming of things, which is inaccurate (see VersionStorageInfo::RangeMightExistAfterSortedRun), and move to "bottommost run" or just "bottommost." Pull Request resolved: https://github.com/facebook/rocksdb/pull/8246 Test Plan: extended an existing unit test to exercise and check various filter building contexts. Also, existing tests for optimize_filters_for_hits validate some of the "bottommost" handling, which is now closely connected to FilterBuildingContext::is_bottommost through TableBuilderOptions::is_bottommost Reviewed By: mrambacher Differential Revision: D28099346 Pulled By: pdillinger fbshipit-source-id: 2c1072e29c24d4ac404c761a7b7663292372600a
4 years ago
filter_context.column_family_name = tbo.column_family_name;
filter_context.reason = reason;
Add more LSM info to FilterBuildingContext (#8246) Summary: Add `num_levels`, `is_bottommost`, and table file creation `reason` to `FilterBuildingContext`, in anticipation of more powerful Bloom-like filter support. To support this, added `is_bottommost` and `reason` to `TableBuilderOptions`, which allowed removing `reason` parameter from `rocksdb::BuildTable`. I attempted to remove `skip_filters` from `TableBuilderOptions`, because filter construction decisions should arise from options, not one-off parameters. I could not completely remove it because the public API for SstFileWriter takes a `skip_filters` parameter, and translating this into an option change would mean awkwardly replacing the table_factory if it is BlockBasedTableFactory with new filter_policy=nullptr option. I marked this public skip_filters option as deprecated because of this oddity. (skip_filters on the read side probably makes sense.) At least `skip_filters` is now largely hidden for users of `TableBuilderOptions` and is no longer used for implementing the optimize_filters_for_hits option. Bringing the logic for that option closer to handling of FilterBuildingContext makes it more obvious that hese two are using the same notion of "bottommost." (Planned: configuration options for Bloom-like filters that generalize `optimize_filters_for_hits`) Recommended follow-up: Try to get away from "bottommost level" naming of things, which is inaccurate (see VersionStorageInfo::RangeMightExistAfterSortedRun), and move to "bottommost run" or just "bottommost." Pull Request resolved: https://github.com/facebook/rocksdb/pull/8246 Test Plan: extended an existing unit test to exercise and check various filter building contexts. Also, existing tests for optimize_filters_for_hits validate some of the "bottommost" handling, which is now closely connected to FilterBuildingContext::is_bottommost through TableBuilderOptions::is_bottommost Reviewed By: mrambacher Differential Revision: D28099346 Pulled By: pdillinger fbshipit-source-id: 2c1072e29c24d4ac404c761a7b7663292372600a
4 years ago
// Only populate other fields if known to be in LSM rather than
// generating external SST file
if (reason != TableFileCreationReason::kMisc) {
Add more LSM info to FilterBuildingContext (#8246) Summary: Add `num_levels`, `is_bottommost`, and table file creation `reason` to `FilterBuildingContext`, in anticipation of more powerful Bloom-like filter support. To support this, added `is_bottommost` and `reason` to `TableBuilderOptions`, which allowed removing `reason` parameter from `rocksdb::BuildTable`. I attempted to remove `skip_filters` from `TableBuilderOptions`, because filter construction decisions should arise from options, not one-off parameters. I could not completely remove it because the public API for SstFileWriter takes a `skip_filters` parameter, and translating this into an option change would mean awkwardly replacing the table_factory if it is BlockBasedTableFactory with new filter_policy=nullptr option. I marked this public skip_filters option as deprecated because of this oddity. (skip_filters on the read side probably makes sense.) At least `skip_filters` is now largely hidden for users of `TableBuilderOptions` and is no longer used for implementing the optimize_filters_for_hits option. Bringing the logic for that option closer to handling of FilterBuildingContext makes it more obvious that hese two are using the same notion of "bottommost." (Planned: configuration options for Bloom-like filters that generalize `optimize_filters_for_hits`) Recommended follow-up: Try to get away from "bottommost level" naming of things, which is inaccurate (see VersionStorageInfo::RangeMightExistAfterSortedRun), and move to "bottommost run" or just "bottommost." Pull Request resolved: https://github.com/facebook/rocksdb/pull/8246 Test Plan: extended an existing unit test to exercise and check various filter building contexts. Also, existing tests for optimize_filters_for_hits validate some of the "bottommost" handling, which is now closely connected to FilterBuildingContext::is_bottommost through TableBuilderOptions::is_bottommost Reviewed By: mrambacher Differential Revision: D28099346 Pulled By: pdillinger fbshipit-source-id: 2c1072e29c24d4ac404c761a7b7663292372600a
4 years ago
filter_context.compaction_style = ioptions.compaction_style;
filter_context.num_levels = ioptions.num_levels;
filter_context.level_at_creation = tbo.level_at_creation;
filter_context.is_bottommost = tbo.is_bottommost;
assert(filter_context.level_at_creation < filter_context.num_levels);
}
filter_builder.reset(CreateFilterBlockBuilder(
ioptions, moptions, filter_context,
use_delta_encoding_for_index_values, p_index_builder_));
}
assert(tbo.int_tbl_prop_collector_factories);
for (auto& factory : *tbo.int_tbl_prop_collector_factories) {
assert(factory);
TablePropertiesCollectorFactory Summary: This diff addresses task #4296714 and rethinks how users provide us with TablePropertiesCollectors as part of Options. Here's description of task #4296714: I'm debugging #4295529 and noticed that our count of user properties kDeletedKeys is wrong. We're sharing one single InternalKeyPropertiesCollector with all Table Builders. In LOG Files, we're outputting number of kDeletedKeys as connected with a single table, while it's actually the total count of deleted keys since creation of the DB. For example, this table has 3155 entries and 1391828 deleted keys. The problem with current approach that we call methods on a single TablePropertiesCollector for all the tables we create. Even worse, we could do it from multiple threads at the same time and TablePropertiesCollector has no way of knowing which table we're calling it for. Good part: Looks like nobody inside Facebook is using Options::table_properties_collectors. This means we should be able to painfully change the API. In this change, I introduce TablePropertiesCollectorFactory. For every table we create, we call `CreateTablePropertiesCollector`, which creates a TablePropertiesCollector for a single table. We then use it sequentially from a single thread, which means it doesn't have to be thread-safe. Test Plan: Added a test in table_properties_collector_test that fails on master (build two tables, assert that kDeletedKeys count is correct for the second one). Also, all other tests Reviewers: sdong, dhruba, haobo, kailiu Reviewed By: kailiu CC: leveldb Differential Revision: https://reviews.facebook.net/D18579
11 years ago
table_properties_collectors.emplace_back(
Support "level_at_creation" in TablePropertiesCollectorFactory::Context (#8919) Summary: Context: Exposing the level of the sst file (i.e, table) where it is created in `TablePropertiesCollectorFactory::Context` allows users of `TablePropertiesCollectorFactory` to customize some implementation details of `TablePropertiesCollectorFactory` and `TablePropertiesCollector` based on the level of creation. For example, `TablePropertiesCollector::NeedCompact()` can return different values based on level of creation. - Declared an extra field `level_at_creation` in `TablePropertiesCollectorFactory::Context` - Allowed `level_at_creation` to be passed in as an argument in `IntTblPropCollectorFactory::CreateIntTblPropCollector()` and `UserKeyTablePropertiesCollectorFactory::CreateIntTblPropCollector()`, the latter of which is an internal wrapper of user's passed-in `TablePropertiesCollectorFactory::CreateTablePropertiesCollector()` used in table-building process - Called `IntTblPropCollectorFactory::CreateIntTblPropCollector()` with `level_at_creation` passed into both `BlockBasedTableBuilder` and `PlainTableBuilder` - `PlainTableBuilder` previously did not capture `level_at_creation` from `TableBuilderOptions` in `PlainTableFactory`. In order for it to call the method with this parameter, this PR also made `PlainTableBuilder` capture `level_at_creation` as a required parameter - Called `IntTblPropCollectorFactory::CreateIntTblPropCollector()` with `level_at_creation` its overridden functions in its derived classes, including `RegularKeysStartWithAFactory::CreateIntTblPropCollector()` in `table_properties_collector_test.cc`, `SstFileWriterPropertiesCollectorFactory::CreateIntTblPropCollector()` in `sst_file_writer_collectors.h` Pull Request resolved: https://github.com/facebook/rocksdb/pull/8919 Test Plan: - Passed the added assertion for `context.level_at_creation` - Passed existing tests - Run `Make` to make sure adding a required parameter to `PlainTableBuilder`'s constructor does not break anything Reviewed By: anand1976 Differential Revision: D30951729 Pulled By: hx235 fbshipit-source-id: c4a0173b0d9344a4cf47e1b987d759c1c73cb474
3 years ago
factory->CreateIntTblPropCollector(tbo.column_family_id,
tbo.level_at_creation));
TablePropertiesCollectorFactory Summary: This diff addresses task #4296714 and rethinks how users provide us with TablePropertiesCollectors as part of Options. Here's description of task #4296714: I'm debugging #4295529 and noticed that our count of user properties kDeletedKeys is wrong. We're sharing one single InternalKeyPropertiesCollector with all Table Builders. In LOG Files, we're outputting number of kDeletedKeys as connected with a single table, while it's actually the total count of deleted keys since creation of the DB. For example, this table has 3155 entries and 1391828 deleted keys. The problem with current approach that we call methods on a single TablePropertiesCollector for all the tables we create. Even worse, we could do it from multiple threads at the same time and TablePropertiesCollector has no way of knowing which table we're calling it for. Good part: Looks like nobody inside Facebook is using Options::table_properties_collectors. This means we should be able to painfully change the API. In this change, I introduce TablePropertiesCollectorFactory. For every table we create, we call `CreateTablePropertiesCollector`, which creates a TablePropertiesCollector for a single table. We then use it sequentially from a single thread, which means it doesn't have to be thread-safe. Test Plan: Added a test in table_properties_collector_test that fails on master (build two tables, assert that kDeletedKeys count is correct for the second one). Also, all other tests Reviewers: sdong, dhruba, haobo, kailiu Reviewed By: kailiu CC: leveldb Differential Revision: https://reviews.facebook.net/D18579
11 years ago
}
table_properties_collectors.emplace_back(
new BlockBasedTablePropertiesCollector(
table_options.index_type, table_options.whole_key_filtering,
moptions.prefix_extractor != nullptr));
const Comparator* ucmp = tbo.internal_comparator.user_comparator();
assert(ucmp);
if (ucmp->timestamp_size() > 0) {
table_properties_collectors.emplace_back(
new TimestampTablePropertiesCollector(ucmp));
}
if (table_options.verify_compression) {
for (uint32_t i = 0; i < compression_opts.parallel_threads; i++) {
verify_ctxs[i].reset(new UncompressionContext(compression_type));
}
}
Embed original file number in SST table properties (#8686) Summary: I very recently realized that with https://github.com/facebook/rocksdb/issues/8669 we cannot later add file numbers to external SST files (so that more can share db session ids for better uniqueness properties), because of forward compatibility. We would have a version of RocksDB that assumes session IDs are unique on external SST files and therefore can't really break that invariant in future files. This change adds a table property for "orig_file_number" which is populated by normal SST files and also external SST files generated by SstFileWriter. SstFileWriter now keeps a db_session_id for life of the object and increments its own file numbers for embedding in table properties. (They are arguably "fake" file numbers because these numbers and not embedded in the file name.) While updating block_based_table_builder, I removed several unnecessary fields from Rep, because following the pattern would have created another unnecessary field. This change also updates block_based_table_reader to use this new property when available, which means that for newer SST files, we can determine the stable/original <db_session_id,file_number> unique identifier using just the file contents, not the file name. (It's a bit complicated; detailed comments in block_based_table_reader.) Also added DB host id to properties listing by sst_dump, which could be useful in debugging. Pull Request resolved: https://github.com/facebook/rocksdb/pull/8686 Test Plan: majorly overhauled StableCacheKeys test for this change Reviewed By: zhichao-cao Differential Revision: D30457742 Pulled By: pdillinger fbshipit-source-id: 2e5ae7dddeb94fb9d8eac8a928486aed8b8cd445
3 years ago
// These are only needed for populating table properties
props.column_family_id = tbo.column_family_id;
props.column_family_name = tbo.column_family_name;
props.oldest_key_time = tbo.oldest_key_time;
props.file_creation_time = tbo.file_creation_time;
props.orig_file_number = tbo.cur_file_num;
props.db_id = tbo.db_id;
props.db_session_id = tbo.db_session_id;
props.db_host_id = ioptions.db_host_id;
if (!ReifyDbHostIdProperty(ioptions.env, &props.db_host_id).ok()) {
ROCKS_LOG_INFO(ioptions.logger, "db_host_id property will not be set");
}
}
Rep(const Rep&) = delete;
Rep& operator=(const Rep&) = delete;
private:
// Synchronize status & io_status accesses across threads from main thread,
// compression thread and write thread in parallel compression.
std::mutex status_mutex;
std::atomic<bool> status_ok;
Status status;
std::mutex io_status_mutex;
std::atomic<bool> io_status_ok;
IOStatus io_status;
};
struct BlockBasedTableBuilder::ParallelCompressionRep {
// Keys is a wrapper of vector of strings avoiding
// releasing string memories during vector clear()
// in order to save memory allocation overhead
class Keys {
public:
Keys() : keys_(kKeysInitSize), size_(0) {}
void PushBack(const Slice& key) {
if (size_ == keys_.size()) {
keys_.emplace_back(key.data(), key.size());
} else {
keys_[size_].assign(key.data(), key.size());
}
size_++;
}
void SwapAssign(std::vector<std::string>& keys) {
size_ = keys.size();
std::swap(keys_, keys);
}
void Clear() { size_ = 0; }
size_t Size() { return size_; }
std::string& Back() { return keys_[size_ - 1]; }
std::string& operator[](size_t idx) {
assert(idx < size_);
return keys_[idx];
}
private:
const size_t kKeysInitSize = 32;
std::vector<std::string> keys_;
size_t size_;
};
std::unique_ptr<Keys> curr_block_keys;
class BlockRepSlot;
// BlockRep instances are fetched from and recycled to
// block_rep_pool during parallel compression.
struct BlockRep {
Slice contents;
Slice compressed_contents;
std::unique_ptr<std::string> data;
std::unique_ptr<std::string> compressed_data;
CompressionType compression_type;
std::unique_ptr<std::string> first_key_in_next_block;
std::unique_ptr<Keys> keys;
std::unique_ptr<BlockRepSlot> slot;
Status status;
};
// Use a vector of BlockRep as a buffer for a determined number
// of BlockRep structures. All data referenced by pointers in
// BlockRep will be freed when this vector is destructed.
using BlockRepBuffer = std::vector<BlockRep>;
BlockRepBuffer block_rep_buf;
// Use a thread-safe queue for concurrent access from block
// building thread and writer thread.
using BlockRepPool = WorkQueue<BlockRep*>;
BlockRepPool block_rep_pool;
// Use BlockRepSlot to keep block order in write thread.
// slot_ will pass references to BlockRep
class BlockRepSlot {
public:
BlockRepSlot() : slot_(1) {}
template <typename T>
void Fill(T&& rep) {
slot_.push(std::forward<T>(rep));
};
void Take(BlockRep*& rep) { slot_.pop(rep); }
private:
// slot_ will pass references to BlockRep in block_rep_buf,
// and those references are always valid before the destruction of
// block_rep_buf.
WorkQueue<BlockRep*> slot_;
};
// Compression queue will pass references to BlockRep in block_rep_buf,
// and those references are always valid before the destruction of
// block_rep_buf.
using CompressQueue = WorkQueue<BlockRep*>;
CompressQueue compress_queue;
std::vector<port::Thread> compress_thread_pool;
// Write queue will pass references to BlockRep::slot in block_rep_buf,
// and those references are always valid before the corresponding
// BlockRep::slot is destructed, which is before the destruction of
// block_rep_buf.
using WriteQueue = WorkQueue<BlockRepSlot*>;
WriteQueue write_queue;
std::unique_ptr<port::Thread> write_thread;
// Estimate output file size when parallel compression is enabled. This is
// necessary because compression & flush are no longer synchronized,
// and BlockBasedTableBuilder::FileSize() is no longer accurate.
// memory_order_relaxed suffices because accurate statistics is not required.
class FileSizeEstimator {
public:
explicit FileSizeEstimator()
: raw_bytes_compressed(0),
raw_bytes_curr_block(0),
raw_bytes_curr_block_set(false),
raw_bytes_inflight(0),
blocks_inflight(0),
curr_compression_ratio(0),
estimated_file_size(0) {}
// Estimate file size when a block is about to be emitted to
// compression thread
void EmitBlock(uint64_t raw_block_size, uint64_t curr_file_size) {
uint64_t new_raw_bytes_inflight =
raw_bytes_inflight.fetch_add(raw_block_size,
std::memory_order_relaxed) +
raw_block_size;
uint64_t new_blocks_inflight =
blocks_inflight.fetch_add(1, std::memory_order_relaxed) + 1;
estimated_file_size.store(
curr_file_size +
static_cast<uint64_t>(
static_cast<double>(new_raw_bytes_inflight) *
curr_compression_ratio.load(std::memory_order_relaxed)) +
new_blocks_inflight * kBlockTrailerSize,
std::memory_order_relaxed);
}
// Estimate file size when a block is already reaped from
// compression thread
void ReapBlock(uint64_t compressed_block_size, uint64_t curr_file_size) {
assert(raw_bytes_curr_block_set);
uint64_t new_raw_bytes_compressed =
raw_bytes_compressed + raw_bytes_curr_block;
assert(new_raw_bytes_compressed > 0);
curr_compression_ratio.store(
(curr_compression_ratio.load(std::memory_order_relaxed) *
raw_bytes_compressed +
compressed_block_size) /
static_cast<double>(new_raw_bytes_compressed),
std::memory_order_relaxed);
raw_bytes_compressed = new_raw_bytes_compressed;
uint64_t new_raw_bytes_inflight =
raw_bytes_inflight.fetch_sub(raw_bytes_curr_block,
std::memory_order_relaxed) -
raw_bytes_curr_block;
uint64_t new_blocks_inflight =
blocks_inflight.fetch_sub(1, std::memory_order_relaxed) - 1;
estimated_file_size.store(
curr_file_size +
static_cast<uint64_t>(
static_cast<double>(new_raw_bytes_inflight) *
curr_compression_ratio.load(std::memory_order_relaxed)) +
new_blocks_inflight * kBlockTrailerSize,
std::memory_order_relaxed);
raw_bytes_curr_block_set = false;
}
void SetEstimatedFileSize(uint64_t size) {
estimated_file_size.store(size, std::memory_order_relaxed);
}
uint64_t GetEstimatedFileSize() {
return estimated_file_size.load(std::memory_order_relaxed);
}
void SetCurrBlockRawSize(uint64_t size) {
raw_bytes_curr_block = size;
raw_bytes_curr_block_set = true;
}
private:
// Raw bytes compressed so far.
uint64_t raw_bytes_compressed;
// Size of current block being appended.
uint64_t raw_bytes_curr_block;
// Whether raw_bytes_curr_block has been set for next
// ReapBlock call.
bool raw_bytes_curr_block_set;
// Raw bytes under compression and not appended yet.
std::atomic<uint64_t> raw_bytes_inflight;
// Number of blocks under compression and not appended yet.
std::atomic<uint64_t> blocks_inflight;
// Current compression ratio, maintained by BGWorkWriteRawBlock.
std::atomic<double> curr_compression_ratio;
// Estimated SST file size.
std::atomic<uint64_t> estimated_file_size;
};
FileSizeEstimator file_size_estimator;
// Facilities used for waiting first block completion. Need to Wait for
// the completion of first block compression and flush to get a non-zero
// compression ratio.
std::atomic<bool> first_block_processed;
std::condition_variable first_block_cond;
std::mutex first_block_mutex;
explicit ParallelCompressionRep(uint32_t parallel_threads)
: curr_block_keys(new Keys()),
block_rep_buf(parallel_threads),
block_rep_pool(parallel_threads),
compress_queue(parallel_threads),
write_queue(parallel_threads),
first_block_processed(false) {
for (uint32_t i = 0; i < parallel_threads; i++) {
block_rep_buf[i].contents = Slice();
block_rep_buf[i].compressed_contents = Slice();
block_rep_buf[i].data.reset(new std::string());
block_rep_buf[i].compressed_data.reset(new std::string());
block_rep_buf[i].compression_type = CompressionType();
block_rep_buf[i].first_key_in_next_block.reset(new std::string());
block_rep_buf[i].keys.reset(new Keys());
block_rep_buf[i].slot.reset(new BlockRepSlot());
block_rep_buf[i].status = Status::OK();
block_rep_pool.push(&block_rep_buf[i]);
}
}
~ParallelCompressionRep() { block_rep_pool.finish(); }
// Make a block prepared to be emitted to compression thread
// Used in non-buffered mode
BlockRep* PrepareBlock(CompressionType compression_type,
const Slice* first_key_in_next_block,
BlockBuilder* data_block) {
BlockRep* block_rep =
PrepareBlockInternal(compression_type, first_key_in_next_block);
assert(block_rep != nullptr);
data_block->SwapAndReset(*(block_rep->data));
block_rep->contents = *(block_rep->data);
std::swap(block_rep->keys, curr_block_keys);
curr_block_keys->Clear();
return block_rep;
}
// Used in EnterUnbuffered
BlockRep* PrepareBlock(CompressionType compression_type,
const Slice* first_key_in_next_block,
std::string* data_block,
std::vector<std::string>* keys) {
BlockRep* block_rep =
PrepareBlockInternal(compression_type, first_key_in_next_block);
assert(block_rep != nullptr);
std::swap(*(block_rep->data), *data_block);
block_rep->contents = *(block_rep->data);
block_rep->keys->SwapAssign(*keys);
return block_rep;
}
// Emit a block to compression thread
void EmitBlock(BlockRep* block_rep) {
assert(block_rep != nullptr);
assert(block_rep->status.ok());
if (!write_queue.push(block_rep->slot.get())) {
return;
}
if (!compress_queue.push(block_rep)) {
return;
}
if (!first_block_processed.load(std::memory_order_relaxed)) {
std::unique_lock<std::mutex> lock(first_block_mutex);
first_block_cond.wait(lock, [this] {
return first_block_processed.load(std::memory_order_relaxed);
});
}
}
// Reap a block from compression thread
void ReapBlock(BlockRep* block_rep) {
assert(block_rep != nullptr);
block_rep->compressed_data->clear();
block_rep_pool.push(block_rep);
if (!first_block_processed.load(std::memory_order_relaxed)) {
std::lock_guard<std::mutex> lock(first_block_mutex);
first_block_processed.store(true, std::memory_order_relaxed);
first_block_cond.notify_one();
}
}
private:
BlockRep* PrepareBlockInternal(CompressionType compression_type,
const Slice* first_key_in_next_block) {
BlockRep* block_rep = nullptr;
block_rep_pool.pop(block_rep);
assert(block_rep != nullptr);
assert(block_rep->data);
block_rep->compression_type = compression_type;
if (first_key_in_next_block == nullptr) {
block_rep->first_key_in_next_block.reset(nullptr);
} else {
block_rep->first_key_in_next_block->assign(
first_key_in_next_block->data(), first_key_in_next_block->size());
}
return block_rep;
}
};
BlockBasedTableBuilder::BlockBasedTableBuilder(
const BlockBasedTableOptions& table_options, const TableBuilderOptions& tbo,
WritableFileWriter* file) {
BlockBasedTableOptions sanitized_table_options(table_options);
if (sanitized_table_options.format_version == 0 &&
sanitized_table_options.checksum != kCRC32c) {
ROCKS_LOG_WARN(
tbo.ioptions.logger,
"Silently converting format_version to 1 because checksum is "
"non-default");
// silently convert format_version to 1 to keep consistent with current
// behavior
sanitized_table_options.format_version = 1;
}
rep_ = new Rep(sanitized_table_options, tbo, file);
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
TEST_SYNC_POINT_CALLBACK(
"BlockBasedTableBuilder::BlockBasedTableBuilder:PreSetupBaseCacheKey",
const_cast<TableProperties*>(&rep_->props));
// Extremely large files use atypical cache key encoding, and we don't
// know ahead of time how big the file will be. But assuming it's less
// than 4TB, we will correctly predict the cache keys.
BlockBasedTable::SetupBaseCacheKey(
&rep_->props, tbo.db_session_id, tbo.cur_file_num,
BlockBasedTable::kMaxFileSizeStandardEncoding, &rep_->base_cache_key);
if (rep_->IsParallelCompressionEnabled()) {
StartParallelCompression();
}
}
BlockBasedTableBuilder::~BlockBasedTableBuilder() {
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
// Catch errors where caller forgot to call Finish()
assert(rep_->state == Rep::State::kClosed);
delete rep_;
}
void BlockBasedTableBuilder::Add(const Slice& key, const Slice& value) {
Rep* r = rep_;
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
assert(rep_->state != Rep::State::kClosed);
if (!ok()) return;
ValueType value_type = ExtractValueType(key);
if (IsValueType(value_type)) {
#ifndef NDEBUG
if (r->props.num_entries > r->props.num_range_deletions) {
assert(r->internal_comparator.Compare(key, Slice(r->last_key)) > 0);
}
#endif // !NDEBUG
auto should_flush = r->flush_block_policy->Update(key, value);
if (should_flush) {
assert(!r->data_block.empty());
r->first_key_in_next_block = &key;
Flush();
if (r->state == Rep::State::kBuffered) {
bool exceeds_buffer_limit =
(r->buffer_limit != 0 && r->data_begin_offset > r->buffer_limit);
bool exceeds_global_block_cache_limit = false;
Rewrite memory-charging feature's option API (#9926) Summary: **Context:** Previous PR https://github.com/facebook/rocksdb/pull/9748, https://github.com/facebook/rocksdb/pull/9073, https://github.com/facebook/rocksdb/pull/8428 added separate flag for each charged memory area. Such API design is not scalable as we charge more and more memory areas. Also, we foresee an opportunity to consolidate this feature with other cache usage related features such as `cache_index_and_filter_blocks` using `CacheEntryRole`. Therefore we decided to consolidate all these flags with `CacheUsageOptions cache_usage_options` and this PR serves as the first step by consolidating memory-charging related flags. **Summary:** - Replaced old API reference with new ones, including making `kCompressionDictionaryBuildingBuffer` opt-out and added a unit test for that - Added missing db bench/stress test for some memory charging features - Renamed related test suite to indicate they are under the same theme of memory charging - Refactored a commonly used mocked cache component in memory charging related tests to reduce code duplication - Replaced the phrases "memory tracking" / "cache reservation" (other than CacheReservationManager-related ones) with "memory charging" for standard description of this feature. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9926 Test Plan: - New unit test for opt-out `kCompressionDictionaryBuildingBuffer` `TEST_F(ChargeCompressionDictionaryBuildingBufferTest, Basic)` - New unit test for option validation/sanitization `TEST_F(CacheUsageOptionsOverridesTest, SanitizeAndValidateOptions)` - CI - db bench (in case querying new options introduces regression) **+0.5% micros/op**: `TEST_TMPDIR=/dev/shm/testdb ./db_bench -benchmarks=fillseq -db=$TEST_TMPDIR -charge_compression_dictionary_building_buffer=1(remove this for comparison) -compression_max_dict_bytes=10000 -disable_auto_compactions=1 -write_buffer_size=100000 -num=4000000 | egrep 'fillseq'` #-run | (pre-PR) avg micros/op | std micros/op | (post-PR) micros/op | std micros/op | change (%) -- | -- | -- | -- | -- | -- 10 | 3.9711 | 0.264408 | 3.9914 | 0.254563 | 0.5111933721 20 | 3.83905 | 0.0664488 | 3.8251 | 0.0695456 | **-0.3633711465** 40 | 3.86625 | 0.136669 | 3.8867 | 0.143765 | **0.5289363078** - db_stress: `python3 tools/db_crashtest.py blackbox -charge_compression_dictionary_building_buffer=1 -charge_filter_construction=1 -charge_table_reader=1 -cache_size=1` killed as normal Reviewed By: ajkr Differential Revision: D36054712 Pulled By: hx235 fbshipit-source-id: d406e90f5e0c5ea4dbcb585a484ad9302d4302af
3 years ago
// Increase cache charging for the last buffered data block
// only if the block is not going to be unbuffered immediately
// and there exists a cache reservation manager
if (!exceeds_buffer_limit &&
r->compression_dict_buffer_cache_res_mgr != nullptr) {
Status s =
Account memory of big memory users in BlockBasedTable in global memory limit (#9748) Summary: **Context:** Through heap profiling, we discovered that `BlockBasedTableReader` objects can accumulate and lead to high memory usage (e.g, `max_open_file = -1`). These memories are currently not saved, not tracked, not constrained and not cache evict-able. As a first step to improve this, similar to https://github.com/facebook/rocksdb/pull/8428, this PR is to track an estimate of `BlockBasedTableReader` object's memory in block cache and fail future creation if the memory usage exceeds the available space of cache at the time of creation. **Summary:** - Approximate big memory users (`BlockBasedTable::Rep` and `TableProperties` )' memory usage in addition to the existing estimated ones (filter block/index block/un-compression dictionary) - Charge all of these memory usages to block cache on `BlockBasedTable::Open()` and release them on `~BlockBasedTable()` as there is no memory usage fluctuation of concern in between - Refactor on CacheReservationManager (and its call-sites) to add concurrent support for BlockBasedTable used in this PR. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9748 Test Plan: - New unit tests - db bench: `OpenDb` : **-0.52% in ms** - Setup `./db_bench -benchmarks=fillseq -db=/dev/shm/testdb -disable_auto_compactions=1 -write_buffer_size=1048576` - Repeated run with pre-change w/o feature and post-change with feature, benchmark `OpenDb`: `./db_bench -benchmarks=readrandom -use_existing_db=1 -db=/dev/shm/testdb -reserve_table_reader_memory=true (remove this when running w/o feature) -file_opening_threads=3 -open_files=-1 -report_open_timing=true| egrep 'OpenDb:'` #-run | (feature-off) avg milliseconds | std milliseconds | (feature-on) avg milliseconds | std milliseconds | change (%) -- | -- | -- | -- | -- | -- 10 | 11.4018 | 5.95173 | 9.47788 | 1.57538 | -16.87382694 20 | 9.23746 | 0.841053 | 9.32377 | 1.14074 | 0.9343477536 40 | 9.0876 | 0.671129 | 9.35053 | 1.11713 | 2.893283155 80 | 9.72514 | 2.28459 | 9.52013 | 1.0894 | -2.108041632 160 | 9.74677 | 0.991234 | 9.84743 | 1.73396 | 1.032752389 320 | 10.7297 | 5.11555 | 10.547 | 1.97692 | **-1.70275031** 640 | 11.7092 | 2.36565 | 11.7869 | 2.69377 | **0.6635807741** - db bench on write with cost to cache in WriteBufferManager (just in case this PR's CRM refactoring accidentally slows down anything in WBM) : `fillseq` : **+0.54% in micros/op** `./db_bench -benchmarks=fillseq -db=/dev/shm/testdb -disable_auto_compactions=1 -cost_write_buffer_to_cache=true -write_buffer_size=10000000000 | egrep 'fillseq'` #-run | (pre-PR) avg micros/op | std micros/op | (post-PR) avg micros/op | std micros/op | change (%) -- | -- | -- | -- | -- | -- 10 | 6.15 | 0.260187 | 6.289 | 0.371192 | 2.260162602 20 | 7.28025 | 0.465402 | 7.37255 | 0.451256 | 1.267813605 40 | 7.06312 | 0.490654 | 7.13803 | 0.478676 | **1.060579461** 80 | 7.14035 | 0.972831 | 7.14196 | 0.92971 | **0.02254791432** - filter bench: `bloom filter`: **-0.78% in ms/key** - ` ./filter_bench -impl=2 -quick -reserve_table_builder_memory=true | grep 'Build avg'` #-run | (pre-PR) avg ns/key | std ns/key | (post-PR) ns/key | std ns/key | change (%) -- | -- | -- | -- | -- | -- 10 | 26.4369 | 0.442182 | 26.3273 | 0.422919 | **-0.4145720565** 20 | 26.4451 | 0.592787 | 26.1419 | 0.62451 | **-1.1465262** - Crash test `python3 tools/db_crashtest.py blackbox --reserve_table_reader_memory=1 --cache_size=1` killed as normal Reviewed By: ajkr Differential Revision: D35136549 Pulled By: hx235 fbshipit-source-id: 146978858d0f900f43f4eb09bfd3e83195e3be28
3 years ago
r->compression_dict_buffer_cache_res_mgr->UpdateCacheReservation(
r->data_begin_offset);
exceeds_global_block_cache_limit = s.IsMemoryLimit();
}
if (exceeds_buffer_limit || exceeds_global_block_cache_limit) {
EnterUnbuffered();
}
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
}
// Add item to index block.
// We do not emit the index entry for a block until we have seen the
// first key for the next data block. This allows us to use shorter
// keys in the index block. For example, consider a block boundary
// between the keys "the quick brown fox" and "the who". We can use
// "the r" as the key for the index block entry since it is >= all
// entries in the first block and < all entries in subsequent
// blocks.
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
if (ok() && r->state == Rep::State::kUnbuffered) {
if (r->IsParallelCompressionEnabled()) {
r->pc_rep->curr_block_keys->Clear();
} else {
r->index_builder->AddIndexEntry(&r->last_key, &key,
r->pending_handle);
}
}
}
// Note: PartitionedFilterBlockBuilder requires key being added to filter
// builder after being added to index builder.
if (r->state == Rep::State::kUnbuffered) {
if (r->IsParallelCompressionEnabled()) {
r->pc_rep->curr_block_keys->PushBack(key);
} else {
if (r->filter_builder != nullptr) {
size_t ts_sz =
r->internal_comparator.user_comparator()->timestamp_size();
r->filter_builder->Add(ExtractUserKeyAndStripTimestamp(key, ts_sz));
}
}
}
r->data_block.AddWithLastKey(key, value, r->last_key);
r->last_key.assign(key.data(), key.size());
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
if (r->state == Rep::State::kBuffered) {
// Buffered keys will be replayed from data_block_buffers during
// `Finish()` once compression dictionary has been finalized.
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
} else {
if (!r->IsParallelCompressionEnabled()) {
r->index_builder->OnKeyAdded(key);
}
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
}
// TODO offset passed in is not accurate for parallel compression case
NotifyCollectTableCollectorsOnAdd(key, value, r->get_offset(),
r->table_properties_collectors,
r->ioptions.logger);
} else if (value_type == kTypeRangeDeletion) {
r->range_del_block.Add(key, value);
// TODO offset passed in is not accurate for parallel compression case
NotifyCollectTableCollectorsOnAdd(key, value, r->get_offset(),
r->table_properties_collectors,
r->ioptions.logger);
} else {
assert(false);
}
r->props.num_entries++;
r->props.raw_key_size += key.size();
r->props.raw_value_size += value.size();
if (value_type == kTypeDeletion || value_type == kTypeSingleDeletion) {
r->props.num_deletions++;
} else if (value_type == kTypeRangeDeletion) {
r->props.num_deletions++;
r->props.num_range_deletions++;
} else if (value_type == kTypeMerge) {
r->props.num_merge_operands++;
}
}
void BlockBasedTableBuilder::Flush() {
Rep* r = rep_;
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
assert(rep_->state != Rep::State::kClosed);
if (!ok()) return;
if (r->data_block.empty()) return;
if (r->IsParallelCompressionEnabled() &&
r->state == Rep::State::kUnbuffered) {
r->data_block.Finish();
ParallelCompressionRep::BlockRep* block_rep = r->pc_rep->PrepareBlock(
r->compression_type, r->first_key_in_next_block, &(r->data_block));
assert(block_rep != nullptr);
r->pc_rep->file_size_estimator.EmitBlock(block_rep->data->size(),
r->get_offset());
r->pc_rep->EmitBlock(block_rep);
} else {
WriteBlock(&r->data_block, &r->pending_handle, BlockType::kData);
}
}
void BlockBasedTableBuilder::WriteBlock(BlockBuilder* block,
BlockHandle* handle,
BlockType block_type) {
Limit buffering for collecting samples for compression dictionary (#7970) Summary: For dictionary compression, we need to collect some representative samples of the data to be compressed, which we use to either generate or train (when `CompressionOptions::zstd_max_train_bytes > 0`) a dictionary. Previously, the strategy was to buffer all the data blocks during flush, and up to the target file size during compaction. That strategy allowed us to randomly pick samples from as wide a range as possible that'd be guaranteed to land in a single output file. However, some users try to make huge files in memory-constrained environments, where this strategy can cause OOM. This PR introduces an option, `CompressionOptions::max_dict_buffer_bytes`, that limits how much data blocks are buffered before we switch to unbuffered mode (which means creating the per-SST dictionary, writing out the buffered data, and compressing/writing new blocks as soon as they are built). It is not strict as we currently buffer more than just data blocks -- also keys are buffered. But it does make a step towards giving users predictable memory usage. Related changes include: - Changed sampling for dictionary compression to select unique data blocks when there is limited availability of data blocks - Made use of `BlockBuilder::SwapAndReset()` to save an allocation+memcpy when buffering data blocks for building a dictionary - Changed `ParseBoolean()` to accept an input containing characters after the boolean. This is necessary since, with this PR, a value for `CompressionOptions::enabled` is no longer necessarily the final component in the `CompressionOptions` string. Pull Request resolved: https://github.com/facebook/rocksdb/pull/7970 Test Plan: - updated `CompressionOptions` unit tests to verify limit is respected (to the extent expected in the current implementation) in various scenarios of flush/compaction to bottommost/non-bottommost level - looked at jemalloc heap profiles right before and after switching to unbuffered mode during flush/compaction. Verified memory usage in buffering is proportional to the limit set. Reviewed By: pdillinger Differential Revision: D26467994 Pulled By: ajkr fbshipit-source-id: 3da4ef9fba59974e4ef40e40c01611002c861465
4 years ago
block->Finish();
std::string raw_block_contents;
raw_block_contents.reserve(rep_->table_options.block_size);
Limit buffering for collecting samples for compression dictionary (#7970) Summary: For dictionary compression, we need to collect some representative samples of the data to be compressed, which we use to either generate or train (when `CompressionOptions::zstd_max_train_bytes > 0`) a dictionary. Previously, the strategy was to buffer all the data blocks during flush, and up to the target file size during compaction. That strategy allowed us to randomly pick samples from as wide a range as possible that'd be guaranteed to land in a single output file. However, some users try to make huge files in memory-constrained environments, where this strategy can cause OOM. This PR introduces an option, `CompressionOptions::max_dict_buffer_bytes`, that limits how much data blocks are buffered before we switch to unbuffered mode (which means creating the per-SST dictionary, writing out the buffered data, and compressing/writing new blocks as soon as they are built). It is not strict as we currently buffer more than just data blocks -- also keys are buffered. But it does make a step towards giving users predictable memory usage. Related changes include: - Changed sampling for dictionary compression to select unique data blocks when there is limited availability of data blocks - Made use of `BlockBuilder::SwapAndReset()` to save an allocation+memcpy when buffering data blocks for building a dictionary - Changed `ParseBoolean()` to accept an input containing characters after the boolean. This is necessary since, with this PR, a value for `CompressionOptions::enabled` is no longer necessarily the final component in the `CompressionOptions` string. Pull Request resolved: https://github.com/facebook/rocksdb/pull/7970 Test Plan: - updated `CompressionOptions` unit tests to verify limit is respected (to the extent expected in the current implementation) in various scenarios of flush/compaction to bottommost/non-bottommost level - looked at jemalloc heap profiles right before and after switching to unbuffered mode during flush/compaction. Verified memory usage in buffering is proportional to the limit set. Reviewed By: pdillinger Differential Revision: D26467994 Pulled By: ajkr fbshipit-source-id: 3da4ef9fba59974e4ef40e40c01611002c861465
4 years ago
block->SwapAndReset(raw_block_contents);
if (rep_->state == Rep::State::kBuffered) {
assert(block_type == BlockType::kData);
rep_->data_block_buffers.emplace_back(std::move(raw_block_contents));
rep_->data_begin_offset += rep_->data_block_buffers.back().size();
Limit buffering for collecting samples for compression dictionary (#7970) Summary: For dictionary compression, we need to collect some representative samples of the data to be compressed, which we use to either generate or train (when `CompressionOptions::zstd_max_train_bytes > 0`) a dictionary. Previously, the strategy was to buffer all the data blocks during flush, and up to the target file size during compaction. That strategy allowed us to randomly pick samples from as wide a range as possible that'd be guaranteed to land in a single output file. However, some users try to make huge files in memory-constrained environments, where this strategy can cause OOM. This PR introduces an option, `CompressionOptions::max_dict_buffer_bytes`, that limits how much data blocks are buffered before we switch to unbuffered mode (which means creating the per-SST dictionary, writing out the buffered data, and compressing/writing new blocks as soon as they are built). It is not strict as we currently buffer more than just data blocks -- also keys are buffered. But it does make a step towards giving users predictable memory usage. Related changes include: - Changed sampling for dictionary compression to select unique data blocks when there is limited availability of data blocks - Made use of `BlockBuilder::SwapAndReset()` to save an allocation+memcpy when buffering data blocks for building a dictionary - Changed `ParseBoolean()` to accept an input containing characters after the boolean. This is necessary since, with this PR, a value for `CompressionOptions::enabled` is no longer necessarily the final component in the `CompressionOptions` string. Pull Request resolved: https://github.com/facebook/rocksdb/pull/7970 Test Plan: - updated `CompressionOptions` unit tests to verify limit is respected (to the extent expected in the current implementation) in various scenarios of flush/compaction to bottommost/non-bottommost level - looked at jemalloc heap profiles right before and after switching to unbuffered mode during flush/compaction. Verified memory usage in buffering is proportional to the limit set. Reviewed By: pdillinger Differential Revision: D26467994 Pulled By: ajkr fbshipit-source-id: 3da4ef9fba59974e4ef40e40c01611002c861465
4 years ago
return;
}
WriteBlock(raw_block_contents, handle, block_type);
}
void BlockBasedTableBuilder::WriteBlock(const Slice& raw_block_contents,
BlockHandle* handle,
BlockType block_type) {
Rep* r = rep_;
Limit buffering for collecting samples for compression dictionary (#7970) Summary: For dictionary compression, we need to collect some representative samples of the data to be compressed, which we use to either generate or train (when `CompressionOptions::zstd_max_train_bytes > 0`) a dictionary. Previously, the strategy was to buffer all the data blocks during flush, and up to the target file size during compaction. That strategy allowed us to randomly pick samples from as wide a range as possible that'd be guaranteed to land in a single output file. However, some users try to make huge files in memory-constrained environments, where this strategy can cause OOM. This PR introduces an option, `CompressionOptions::max_dict_buffer_bytes`, that limits how much data blocks are buffered before we switch to unbuffered mode (which means creating the per-SST dictionary, writing out the buffered data, and compressing/writing new blocks as soon as they are built). It is not strict as we currently buffer more than just data blocks -- also keys are buffered. But it does make a step towards giving users predictable memory usage. Related changes include: - Changed sampling for dictionary compression to select unique data blocks when there is limited availability of data blocks - Made use of `BlockBuilder::SwapAndReset()` to save an allocation+memcpy when buffering data blocks for building a dictionary - Changed `ParseBoolean()` to accept an input containing characters after the boolean. This is necessary since, with this PR, a value for `CompressionOptions::enabled` is no longer necessarily the final component in the `CompressionOptions` string. Pull Request resolved: https://github.com/facebook/rocksdb/pull/7970 Test Plan: - updated `CompressionOptions` unit tests to verify limit is respected (to the extent expected in the current implementation) in various scenarios of flush/compaction to bottommost/non-bottommost level - looked at jemalloc heap profiles right before and after switching to unbuffered mode during flush/compaction. Verified memory usage in buffering is proportional to the limit set. Reviewed By: pdillinger Differential Revision: D26467994 Pulled By: ajkr fbshipit-source-id: 3da4ef9fba59974e4ef40e40c01611002c861465
4 years ago
assert(r->state == Rep::State::kUnbuffered);
Slice block_contents;
CompressionType type;
Status compress_status;
bool is_data_block = block_type == BlockType::kData;
CompressAndVerifyBlock(raw_block_contents, is_data_block,
*(r->compression_ctxs[0]), r->verify_ctxs[0].get(),
&(r->compressed_output), &(block_contents), &type,
&compress_status);
r->SetStatus(compress_status);
if (!ok()) {
return;
}
WriteRawBlock(block_contents, type, handle, block_type, &raw_block_contents);
r->compressed_output.clear();
if (is_data_block) {
r->props.data_size = r->get_offset();
++r->props.num_data_blocks;
}
}
void BlockBasedTableBuilder::BGWorkCompression(
const CompressionContext& compression_ctx,
UncompressionContext* verify_ctx) {
ParallelCompressionRep::BlockRep* block_rep = nullptr;
while (rep_->pc_rep->compress_queue.pop(block_rep)) {
assert(block_rep != nullptr);
CompressAndVerifyBlock(block_rep->contents, true, /* is_data_block*/
compression_ctx, verify_ctx,
block_rep->compressed_data.get(),
&block_rep->compressed_contents,
&(block_rep->compression_type), &block_rep->status);
block_rep->slot->Fill(block_rep);
}
}
void BlockBasedTableBuilder::CompressAndVerifyBlock(
const Slice& raw_block_contents, bool is_data_block,
const CompressionContext& compression_ctx, UncompressionContext* verify_ctx,
std::string* compressed_output, Slice* block_contents,
CompressionType* type, Status* out_status) {
// File format contains a sequence of blocks where each block has:
// block_data: uint8[n]
// type: uint8
// crc: uint32
Rep* r = rep_;
bool is_status_ok = ok();
if (!r->IsParallelCompressionEnabled()) {
assert(is_status_ok);
}
*type = r->compression_type;
uint64_t sample_for_compression = r->sample_for_compression;
bool abort_compression = false;
StopWatchNano timer(
r->ioptions.clock,
ShouldReportDetailedTime(r->ioptions.env, r->ioptions.stats));
if (is_status_ok && raw_block_contents.size() < kCompressionSizeLimit) {
if (is_data_block) {
r->compressible_input_data_bytes.fetch_add(raw_block_contents.size(),
std::memory_order_relaxed);
}
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
const CompressionDict* compression_dict;
if (!is_data_block || r->compression_dict == nullptr) {
compression_dict = &CompressionDict::GetEmptyDict();
} else {
compression_dict = r->compression_dict.get();
}
assert(compression_dict != nullptr);
CompressionInfo compression_info(r->compression_opts, compression_ctx,
*compression_dict, *type,
sample_for_compression);
std::string sampled_output_fast;
std::string sampled_output_slow;
*block_contents = CompressBlock(
raw_block_contents, compression_info, type,
r->table_options.format_version, is_data_block /* do_sample */,
compressed_output, &sampled_output_fast, &sampled_output_slow);
if (sampled_output_slow.size() > 0 || sampled_output_fast.size() > 0) {
// Currently compression sampling is only enabled for data block.
assert(is_data_block);
r->sampled_input_data_bytes.fetch_add(raw_block_contents.size(),
std::memory_order_relaxed);
r->sampled_output_slow_data_bytes.fetch_add(sampled_output_slow.size(),
std::memory_order_relaxed);
r->sampled_output_fast_data_bytes.fetch_add(sampled_output_fast.size(),
std::memory_order_relaxed);
}
// notify collectors on block add
NotifyCollectTableCollectorsOnBlockAdd(
r->table_properties_collectors, raw_block_contents.size(),
sampled_output_fast.size(), sampled_output_slow.size());
// Some of the compression algorithms are known to be unreliable. If
// the verify_compression flag is set then try to de-compress the
// compressed data and compare to the input.
if (*type != kNoCompression && r->table_options.verify_compression) {
// Retrieve the uncompressed contents into a new buffer
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
const UncompressionDict* verify_dict;
if (!is_data_block || r->verify_dict == nullptr) {
verify_dict = &UncompressionDict::GetEmptyDict();
} else {
verify_dict = r->verify_dict.get();
}
assert(verify_dict != nullptr);
BlockContents contents;
UncompressionInfo uncompression_info(*verify_ctx, *verify_dict,
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
r->compression_type);
Status stat = UncompressBlockContentsForCompressionType(
uncompression_info, block_contents->data(), block_contents->size(),
&contents, r->table_options.format_version, r->ioptions);
if (stat.ok()) {
bool compressed_ok = contents.data.compare(raw_block_contents) == 0;
if (!compressed_ok) {
// The result of the compression was invalid. abort.
abort_compression = true;
ROCKS_LOG_ERROR(r->ioptions.logger,
"Decompressed block did not match raw block");
*out_status =
Status::Corruption("Decompressed block did not match raw block");
}
} else {
// Decompression reported an error. abort.
*out_status = Status::Corruption(std::string("Could not decompress: ") +
stat.getState());
abort_compression = true;
}
}
} else {
// Block is too big to be compressed.
if (is_data_block) {
r->uncompressible_input_data_bytes.fetch_add(raw_block_contents.size(),
std::memory_order_relaxed);
}
abort_compression = true;
}
if (is_data_block) {
r->uncompressible_input_data_bytes.fetch_add(kBlockTrailerSize,
std::memory_order_relaxed);
}
// Abort compression if the block is too big, or did not pass
// verification.
if (abort_compression) {
RecordTick(r->ioptions.stats, NUMBER_BLOCK_NOT_COMPRESSED);
*type = kNoCompression;
*block_contents = raw_block_contents;
} else if (*type != kNoCompression) {
if (ShouldReportDetailedTime(r->ioptions.env, r->ioptions.stats)) {
RecordTimeToHistogram(r->ioptions.stats, COMPRESSION_TIMES_NANOS,
timer.ElapsedNanos());
}
RecordInHistogram(r->ioptions.stats, BYTES_COMPRESSED,
raw_block_contents.size());
RecordTick(r->ioptions.stats, NUMBER_BLOCK_COMPRESSED);
} else if (*type != r->compression_type) {
RecordTick(r->ioptions.stats, NUMBER_BLOCK_NOT_COMPRESSED);
}
}
void BlockBasedTableBuilder::WriteRawBlock(const Slice& block_contents,
CompressionType type,
BlockHandle* handle,
BlockType block_type,
const Slice* raw_block_contents) {
Rep* r = rep_;
bool is_data_block = block_type == BlockType::kData;
StopWatch sw(r->ioptions.clock, r->ioptions.stats, WRITE_RAW_BLOCK_MICROS);
handle->set_offset(r->get_offset());
handle->set_size(block_contents.size());
assert(status().ok());
assert(io_status().ok());
{
IOStatus io_s = r->file->Append(block_contents);
if (!io_s.ok()) {
r->SetIOStatus(io_s);
return;
}
}
std::array<char, kBlockTrailerSize> trailer;
trailer[0] = type;
uint32_t checksum = ComputeBuiltinChecksumWithLastByte(
r->table_options.checksum, block_contents.data(), block_contents.size(),
/*last_byte*/ type);
Detect (new) Bloom/Ribbon Filter construction corruption (#9342) Summary: Note: rebase on and merge after https://github.com/facebook/rocksdb/pull/9349, https://github.com/facebook/rocksdb/pull/9345, (optional) https://github.com/facebook/rocksdb/pull/9393 **Context:** (Quoted from pdillinger) Layers of information during new Bloom/Ribbon Filter construction in building block-based tables includes the following: a) set of keys to add to filter b) set of hashes to add to filter (64-bit hash applied to each key) c) set of Bloom indices to set in filter, with duplicates d) set of Bloom indices to set in filter, deduplicated e) final filter and its checksum This PR aims to detect corruption (e.g, unexpected hardware/software corruption on data structures residing in the memory for a long time) from b) to e) and leave a) as future works for application level. - b)'s corruption is detected by verifying the xor checksum of the hash entries calculated as the entries accumulate before being added to the filter. (i.e, `XXPH3FilterBitsBuilder::MaybeVerifyHashEntriesChecksum()`) - c) - e)'s corruption is detected by verifying the hash entries indeed exists in the constructed filter by re-querying these hash entries in the filter (i.e, `FilterBitsBuilder::MaybePostVerify()`) after computing the block checksum (except for PartitionFilter, which is done right after each `FilterBitsBuilder::Finish` for impl simplicity - see code comment for more). For this stage of detection, we assume hash entries are not corrupted after checking on b) since the time interval from b) to c) is relatively short IMO. Option to enable this feature of detection is `BlockBasedTableOptions::detect_filter_construct_corruption` which is false by default. **Summary:** - Implemented new functions `XXPH3FilterBitsBuilder::MaybeVerifyHashEntriesChecksum()` and `FilterBitsBuilder::MaybePostVerify()` - Ensured hash entries, final filter and banding and their [cache reservation ](https://github.com/facebook/rocksdb/issues/9073) are released properly despite corruption - See [Filter.construction.artifacts.release.point.pdf ](https://github.com/facebook/rocksdb/files/7923487/Design.Filter.construction.artifacts.release.point.pdf) for high-level design - Bundled and refactored hash entries's related artifact in XXPH3FilterBitsBuilder into `HashEntriesInfo` for better control on lifetime of these artifact during `SwapEntires`, `ResetEntries` - Ensured RocksDB block-based table builder calls `FilterBitsBuilder::MaybePostVerify()` after constructing the filter by `FilterBitsBuilder::Finish()` - When encountering such filter construction corruption, stop writing the filter content to files and mark such a block-based table building non-ok by storing the corruption status in the builder. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9342 Test Plan: - Added new unit test `DBFilterConstructionCorruptionTestWithParam.DetectCorruption` - Included this new feature in `DBFilterConstructionReserveMemoryTestWithParam.ReserveMemory` as this feature heavily touch ReserveMemory's impl - For fallback case, I run `./filter_bench -impl=3 -detect_filter_construct_corruption=true -reserve_table_builder_memory=true -strict_capacity_limit=true -quick -runs 10 | grep 'Build avg'` to make sure nothing break. - Added to `filter_bench`: increased filter construction time by **30%**, mostly by `MaybePostVerify()` - FastLocalBloom - Before change: `./filter_bench -impl=2 -quick -runs 10 | grep 'Build avg'`: **28.86643s** - After change: - `./filter_bench -impl=2 -detect_filter_construct_corruption=false -quick -runs 10 | grep 'Build avg'` (expect a tiny increase due to MaybePostVerify is always called regardless): **27.6644s (-4% perf improvement might be due to now we don't drop bloom hash entry in `AddAllEntries` along iteration but in bulk later, same with the bypassing-MaybePostVerify case below)** - `./filter_bench -impl=2 -detect_filter_construct_corruption=true -quick -runs 10 | grep 'Build avg'` (expect acceptable increase): **34.41159s (+20%)** - `./filter_bench -impl=2 -detect_filter_construct_corruption=true -quick -runs 10 | grep 'Build avg'` (by-passing MaybePostVerify, expect minor increase): **27.13431s (-6%)** - Standard128Ribbon - Before change: `./filter_bench -impl=3 -quick -runs 10 | grep 'Build avg'`: **122.5384s** - After change: - `./filter_bench -impl=3 -detect_filter_construct_corruption=false -quick -runs 10 | grep 'Build avg'` (expect a tiny increase due to MaybePostVerify is always called regardless - verified by removing MaybePostVerify under this case and found only +-1ns difference): **124.3588s (+2%)** - `./filter_bench -impl=3 -detect_filter_construct_corruption=true -quick -runs 10 | grep 'Build avg'`(expect acceptable increase): **159.4946s (+30%)** - `./filter_bench -impl=3 -detect_filter_construct_corruption=true -quick -runs 10 | grep 'Build avg'`(by-passing MaybePostVerify, expect minor increase) : **125.258s (+2%)** - Added to `db_stress`: `make crash_test`, `./db_stress --detect_filter_construct_corruption=true` - Manually smoke-tested: manually corrupted the filter construction in some db level tests with basic PUT and background flush. As expected, the error did get returned to users in subsequent PUT and Flush status. Reviewed By: pdillinger Differential Revision: D33746928 Pulled By: hx235 fbshipit-source-id: cb056426be5a7debc1cd16f23bc250f36a08ca57
3 years ago
if (block_type == BlockType::kFilter) {
Status s = r->filter_builder->MaybePostVerifyFilter(block_contents);
if (!s.ok()) {
r->SetStatus(s);
return;
}
}
EncodeFixed32(trailer.data() + 1, checksum);
TEST_SYNC_POINT_CALLBACK(
"BlockBasedTableBuilder::WriteRawBlock:TamperWithChecksum",
trailer.data());
{
IOStatus io_s = r->file->Append(Slice(trailer.data(), trailer.size()));
if (!io_s.ok()) {
r->SetIOStatus(io_s);
return;
}
}
{
Status s = Status::OK();
bool warm_cache;
switch (r->table_options.prepopulate_block_cache) {
case BlockBasedTableOptions::PrepopulateBlockCache::kFlushOnly:
warm_cache = (r->reason == TableFileCreationReason::kFlush);
break;
case BlockBasedTableOptions::PrepopulateBlockCache::kDisable:
warm_cache = false;
break;
default:
// missing case
assert(false);
warm_cache = false;
}
if (warm_cache) {
if (type == kNoCompression) {
s = InsertBlockInCacheHelper(block_contents, handle, block_type);
} else if (raw_block_contents != nullptr) {
s = InsertBlockInCacheHelper(*raw_block_contents, handle, block_type);
}
if (!s.ok()) {
r->SetStatus(s);
return;
}
}
s = InsertBlockInCompressedCache(block_contents, type, handle);
if (!s.ok()) {
r->SetStatus(s);
return;
}
}
r->set_offset(r->get_offset() + block_contents.size() + kBlockTrailerSize);
if (r->table_options.block_align && is_data_block) {
size_t pad_bytes =
(r->alignment -
((block_contents.size() + kBlockTrailerSize) & (r->alignment - 1))) &
(r->alignment - 1);
IOStatus io_s = r->file->Pad(pad_bytes);
if (io_s.ok()) {
r->set_offset(r->get_offset() + pad_bytes);
} else {
r->SetIOStatus(io_s);
return;
}
}
if (r->IsParallelCompressionEnabled()) {
if (is_data_block) {
r->pc_rep->file_size_estimator.ReapBlock(block_contents.size(),
r->get_offset());
} else {
r->pc_rep->file_size_estimator.SetEstimatedFileSize(r->get_offset());
}
}
}
void BlockBasedTableBuilder::BGWorkWriteRawBlock() {
Rep* r = rep_;
ParallelCompressionRep::BlockRepSlot* slot = nullptr;
ParallelCompressionRep::BlockRep* block_rep = nullptr;
while (r->pc_rep->write_queue.pop(slot)) {
assert(slot != nullptr);
slot->Take(block_rep);
assert(block_rep != nullptr);
if (!block_rep->status.ok()) {
r->SetStatus(block_rep->status);
// Reap block so that blocked Flush() can finish
// if there is one, and Flush() will notice !ok() next time.
block_rep->status = Status::OK();
r->pc_rep->ReapBlock(block_rep);
continue;
}
for (size_t i = 0; i < block_rep->keys->Size(); i++) {
auto& key = (*block_rep->keys)[i];
if (r->filter_builder != nullptr) {
size_t ts_sz =
r->internal_comparator.user_comparator()->timestamp_size();
r->filter_builder->Add(ExtractUserKeyAndStripTimestamp(key, ts_sz));
}
r->index_builder->OnKeyAdded(key);
}
r->pc_rep->file_size_estimator.SetCurrBlockRawSize(block_rep->data->size());
WriteRawBlock(block_rep->compressed_contents, block_rep->compression_type,
&r->pending_handle, BlockType::kData, &block_rep->contents);
if (!ok()) {
break;
}
r->props.data_size = r->get_offset();
++r->props.num_data_blocks;
if (block_rep->first_key_in_next_block == nullptr) {
r->index_builder->AddIndexEntry(&(block_rep->keys->Back()), nullptr,
r->pending_handle);
} else {
Slice first_key_in_next_block =
Slice(*block_rep->first_key_in_next_block);
r->index_builder->AddIndexEntry(&(block_rep->keys->Back()),
&first_key_in_next_block,
r->pending_handle);
}
r->pc_rep->ReapBlock(block_rep);
}
}
void BlockBasedTableBuilder::StartParallelCompression() {
rep_->pc_rep.reset(
new ParallelCompressionRep(rep_->compression_opts.parallel_threads));
rep_->pc_rep->compress_thread_pool.reserve(
rep_->compression_opts.parallel_threads);
for (uint32_t i = 0; i < rep_->compression_opts.parallel_threads; i++) {
rep_->pc_rep->compress_thread_pool.emplace_back([this, i] {
BGWorkCompression(*(rep_->compression_ctxs[i]),
rep_->verify_ctxs[i].get());
});
}
rep_->pc_rep->write_thread.reset(
new port::Thread([this] { BGWorkWriteRawBlock(); }));
}
void BlockBasedTableBuilder::StopParallelCompression() {
rep_->pc_rep->compress_queue.finish();
for (auto& thread : rep_->pc_rep->compress_thread_pool) {
thread.join();
}
rep_->pc_rep->write_queue.finish();
rep_->pc_rep->write_thread->join();
}
Status BlockBasedTableBuilder::status() const { return rep_->GetStatus(); }
IOStatus BlockBasedTableBuilder::io_status() const {
return rep_->GetIOStatus();
}
namespace {
// Delete the entry resided in the cache.
template <class Entry>
void DeleteEntryCached(const Slice& /*key*/, void* value) {
auto entry = reinterpret_cast<Entry*>(value);
delete entry;
}
} // namespace
//
// Make a copy of the block contents and insert into compressed block cache
//
Status BlockBasedTableBuilder::InsertBlockInCompressedCache(
const Slice& block_contents, const CompressionType type,
const BlockHandle* handle) {
Rep* r = rep_;
Cache* block_cache_compressed = r->table_options.block_cache_compressed.get();
Status s;
if (type != kNoCompression && block_cache_compressed != nullptr) {
size_t size = block_contents.size();
auto ubuf =
AllocateBlock(size + 1, block_cache_compressed->memory_allocator());
memcpy(ubuf.get(), block_contents.data(), size);
ubuf[size] = type;
BlockContents* block_contents_to_cache =
new BlockContents(std::move(ubuf), size);
#ifndef NDEBUG
block_contents_to_cache->is_raw_block = true;
#endif // NDEBUG
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
CacheKey key = BlockBasedTable::GetCacheKey(rep_->base_cache_key, *handle);
s = block_cache_compressed->Insert(
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
key.AsSlice(), block_contents_to_cache,
block_contents_to_cache->ApproximateMemoryUsage(),
&DeleteEntryCached<BlockContents>);
if (s.ok()) {
RecordTick(rep_->ioptions.stats, BLOCK_CACHE_COMPRESSED_ADD);
} else {
RecordTick(rep_->ioptions.stats, BLOCK_CACHE_COMPRESSED_ADD_FAILURES);
}
// Invalidate OS cache.
r->file->InvalidateCache(static_cast<size_t>(r->get_offset()), size)
.PermitUncheckedError();
}
return s;
}
Status BlockBasedTableBuilder::InsertBlockInCacheHelper(
const Slice& block_contents, const BlockHandle* handle,
BlockType block_type) {
Status s;
switch (block_type) {
case BlockType::kData:
case BlockType::kIndex:
case BlockType::kFilterPartitionIndex:
s = InsertBlockInCache<Block>(block_contents, handle, block_type);
break;
case BlockType::kFilter:
s = InsertBlockInCache<ParsedFullFilterBlock>(block_contents, handle,
block_type);
break;
case BlockType::kCompressionDictionary:
s = InsertBlockInCache<UncompressionDict>(block_contents, handle,
block_type);
break;
default:
// no-op / not cached
break;
}
return s;
}
template <typename TBlocklike>
Status BlockBasedTableBuilder::InsertBlockInCache(const Slice& block_contents,
const BlockHandle* handle,
BlockType block_type) {
// Uncompressed regular block cache
Cache* block_cache = rep_->table_options.block_cache.get();
Status s;
if (block_cache != nullptr) {
size_t size = block_contents.size();
auto buf = AllocateBlock(size, block_cache->memory_allocator());
memcpy(buf.get(), block_contents.data(), size);
BlockContents results(std::move(buf), size);
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
CacheKey key = BlockBasedTable::GetCacheKey(rep_->base_cache_key, *handle);
const size_t read_amp_bytes_per_bit =
rep_->table_options.read_amp_bytes_per_bit;
// TODO akanksha:: Dedup below code by calling
// BlockBasedTable::PutDataBlockToCache.
std::unique_ptr<TBlocklike> block_holder(
BlocklikeTraits<TBlocklike>::Create(
std::move(results), read_amp_bytes_per_bit,
rep_->ioptions.statistics.get(),
false /*rep_->blocks_definitely_zstd_compressed*/,
rep_->table_options.filter_policy.get()));
assert(block_holder->own_bytes());
size_t charge = block_holder->ApproximateMemoryUsage();
s = block_cache->Insert(
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
key.AsSlice(), block_holder.get(),
BlocklikeTraits<TBlocklike>::GetCacheItemHelper(block_type), charge,
nullptr, Cache::Priority::LOW);
if (s.ok()) {
// Release ownership of block_holder.
block_holder.release();
BlockBasedTable::UpdateCacheInsertionMetrics(
block_type, nullptr /*get_context*/, charge, s.IsOkOverwritten(),
rep_->ioptions.stats);
} else {
RecordTick(rep_->ioptions.stats, BLOCK_CACHE_ADD_FAILURES);
}
}
return s;
}
void BlockBasedTableBuilder::WriteFilterBlock(
MetaIndexBuilder* meta_index_builder) {
if (rep_->filter_builder == nullptr || rep_->filter_builder->IsEmpty()) {
// No filter block needed
return;
}
BlockHandle filter_block_handle;
bool is_partitioned_filter = rep_->table_options.partition_filters;
if (ok()) {
rep_->props.num_filter_entries +=
rep_->filter_builder->EstimateEntriesAdded();
Status s = Status::Incomplete();
while (ok() && s.IsIncomplete()) {
Deallocate payload of BlockBasedTableBuilder::Rep::FilterBlockBuilder earlier for Full/PartitionedFilter (#9070) Summary: Note: This PR is the 1st part of a bigger PR stack (https://github.com/facebook/rocksdb/pull/9073). Context: Previously, the payload (i.e, filter data) within `BlockBasedTableBuilder::Rep::FilterBlockBuilder` object is not deallocated until `BlockBasedTableBuilder` is deallocated, despite it is no longer useful after its related `filter_content` being written. - Transferred the payload (i.e, the filter data) out of `BlockBasedTableBuilder::Rep::FilterBlockBuilder` object - For PartitionedFilter: - Unified `filters` and `filter_gc` lists into one `std::deque<FilterEntry> filters` by adding a new field `last_filter_entry_key` and storing the `std::unique_ptr filter_data` with the `Slice filter` in the same entry - Reset `last_filter_data` in the case where `filters` is empty, which should be as by then we would've finish using all the `Slice filter` - Deallocated the payload by going out of scope as soon as we're done with using the `filter_content` associated with the payload - This is an internal interface change at the level of `FilterBlockBuilder::Finish()`, which leads to touching the inherited interface in `BlockBasedFilterBlockBuilder`. But for that, the payload transferring is ignored. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9070 Test Plan: - The main focus is to catch segment fault error during `FilterBlockBuilder::Finish()` and `BlockBasedTableBuilder::Finish()` and interface mismatch. Relying on existing CI tests is enough as `assert(false)` was temporarily added to verify the new logic of transferring ownership indeed run Reviewed By: pdillinger Differential Revision: D31884933 Pulled By: hx235 fbshipit-source-id: f73ecfbea13788d4fc058013ace27230110b52f4
3 years ago
// filter_data is used to store the transferred filter data payload from
// FilterBlockBuilder and deallocate the payload by going out of scope.
// Otherwise, the payload will unnecessarily remain until
// BlockBasedTableBuilder is deallocated.
//
// See FilterBlockBuilder::Finish() for more on the difference in
// transferred filter data payload among different FilterBlockBuilder
// subtypes.
std::unique_ptr<const char[]> filter_data;
Slice filter_content =
Deallocate payload of BlockBasedTableBuilder::Rep::FilterBlockBuilder earlier for Full/PartitionedFilter (#9070) Summary: Note: This PR is the 1st part of a bigger PR stack (https://github.com/facebook/rocksdb/pull/9073). Context: Previously, the payload (i.e, filter data) within `BlockBasedTableBuilder::Rep::FilterBlockBuilder` object is not deallocated until `BlockBasedTableBuilder` is deallocated, despite it is no longer useful after its related `filter_content` being written. - Transferred the payload (i.e, the filter data) out of `BlockBasedTableBuilder::Rep::FilterBlockBuilder` object - For PartitionedFilter: - Unified `filters` and `filter_gc` lists into one `std::deque<FilterEntry> filters` by adding a new field `last_filter_entry_key` and storing the `std::unique_ptr filter_data` with the `Slice filter` in the same entry - Reset `last_filter_data` in the case where `filters` is empty, which should be as by then we would've finish using all the `Slice filter` - Deallocated the payload by going out of scope as soon as we're done with using the `filter_content` associated with the payload - This is an internal interface change at the level of `FilterBlockBuilder::Finish()`, which leads to touching the inherited interface in `BlockBasedFilterBlockBuilder`. But for that, the payload transferring is ignored. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9070 Test Plan: - The main focus is to catch segment fault error during `FilterBlockBuilder::Finish()` and `BlockBasedTableBuilder::Finish()` and interface mismatch. Relying on existing CI tests is enough as `assert(false)` was temporarily added to verify the new logic of transferring ownership indeed run Reviewed By: pdillinger Differential Revision: D31884933 Pulled By: hx235 fbshipit-source-id: f73ecfbea13788d4fc058013ace27230110b52f4
3 years ago
rep_->filter_builder->Finish(filter_block_handle, &s, &filter_data);
Detect (new) Bloom/Ribbon Filter construction corruption (#9342) Summary: Note: rebase on and merge after https://github.com/facebook/rocksdb/pull/9349, https://github.com/facebook/rocksdb/pull/9345, (optional) https://github.com/facebook/rocksdb/pull/9393 **Context:** (Quoted from pdillinger) Layers of information during new Bloom/Ribbon Filter construction in building block-based tables includes the following: a) set of keys to add to filter b) set of hashes to add to filter (64-bit hash applied to each key) c) set of Bloom indices to set in filter, with duplicates d) set of Bloom indices to set in filter, deduplicated e) final filter and its checksum This PR aims to detect corruption (e.g, unexpected hardware/software corruption on data structures residing in the memory for a long time) from b) to e) and leave a) as future works for application level. - b)'s corruption is detected by verifying the xor checksum of the hash entries calculated as the entries accumulate before being added to the filter. (i.e, `XXPH3FilterBitsBuilder::MaybeVerifyHashEntriesChecksum()`) - c) - e)'s corruption is detected by verifying the hash entries indeed exists in the constructed filter by re-querying these hash entries in the filter (i.e, `FilterBitsBuilder::MaybePostVerify()`) after computing the block checksum (except for PartitionFilter, which is done right after each `FilterBitsBuilder::Finish` for impl simplicity - see code comment for more). For this stage of detection, we assume hash entries are not corrupted after checking on b) since the time interval from b) to c) is relatively short IMO. Option to enable this feature of detection is `BlockBasedTableOptions::detect_filter_construct_corruption` which is false by default. **Summary:** - Implemented new functions `XXPH3FilterBitsBuilder::MaybeVerifyHashEntriesChecksum()` and `FilterBitsBuilder::MaybePostVerify()` - Ensured hash entries, final filter and banding and their [cache reservation ](https://github.com/facebook/rocksdb/issues/9073) are released properly despite corruption - See [Filter.construction.artifacts.release.point.pdf ](https://github.com/facebook/rocksdb/files/7923487/Design.Filter.construction.artifacts.release.point.pdf) for high-level design - Bundled and refactored hash entries's related artifact in XXPH3FilterBitsBuilder into `HashEntriesInfo` for better control on lifetime of these artifact during `SwapEntires`, `ResetEntries` - Ensured RocksDB block-based table builder calls `FilterBitsBuilder::MaybePostVerify()` after constructing the filter by `FilterBitsBuilder::Finish()` - When encountering such filter construction corruption, stop writing the filter content to files and mark such a block-based table building non-ok by storing the corruption status in the builder. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9342 Test Plan: - Added new unit test `DBFilterConstructionCorruptionTestWithParam.DetectCorruption` - Included this new feature in `DBFilterConstructionReserveMemoryTestWithParam.ReserveMemory` as this feature heavily touch ReserveMemory's impl - For fallback case, I run `./filter_bench -impl=3 -detect_filter_construct_corruption=true -reserve_table_builder_memory=true -strict_capacity_limit=true -quick -runs 10 | grep 'Build avg'` to make sure nothing break. - Added to `filter_bench`: increased filter construction time by **30%**, mostly by `MaybePostVerify()` - FastLocalBloom - Before change: `./filter_bench -impl=2 -quick -runs 10 | grep 'Build avg'`: **28.86643s** - After change: - `./filter_bench -impl=2 -detect_filter_construct_corruption=false -quick -runs 10 | grep 'Build avg'` (expect a tiny increase due to MaybePostVerify is always called regardless): **27.6644s (-4% perf improvement might be due to now we don't drop bloom hash entry in `AddAllEntries` along iteration but in bulk later, same with the bypassing-MaybePostVerify case below)** - `./filter_bench -impl=2 -detect_filter_construct_corruption=true -quick -runs 10 | grep 'Build avg'` (expect acceptable increase): **34.41159s (+20%)** - `./filter_bench -impl=2 -detect_filter_construct_corruption=true -quick -runs 10 | grep 'Build avg'` (by-passing MaybePostVerify, expect minor increase): **27.13431s (-6%)** - Standard128Ribbon - Before change: `./filter_bench -impl=3 -quick -runs 10 | grep 'Build avg'`: **122.5384s** - After change: - `./filter_bench -impl=3 -detect_filter_construct_corruption=false -quick -runs 10 | grep 'Build avg'` (expect a tiny increase due to MaybePostVerify is always called regardless - verified by removing MaybePostVerify under this case and found only +-1ns difference): **124.3588s (+2%)** - `./filter_bench -impl=3 -detect_filter_construct_corruption=true -quick -runs 10 | grep 'Build avg'`(expect acceptable increase): **159.4946s (+30%)** - `./filter_bench -impl=3 -detect_filter_construct_corruption=true -quick -runs 10 | grep 'Build avg'`(by-passing MaybePostVerify, expect minor increase) : **125.258s (+2%)** - Added to `db_stress`: `make crash_test`, `./db_stress --detect_filter_construct_corruption=true` - Manually smoke-tested: manually corrupted the filter construction in some db level tests with basic PUT and background flush. As expected, the error did get returned to users in subsequent PUT and Flush status. Reviewed By: pdillinger Differential Revision: D33746928 Pulled By: hx235 fbshipit-source-id: cb056426be5a7debc1cd16f23bc250f36a08ca57
3 years ago
assert(s.ok() || s.IsIncomplete() || s.IsCorruption());
if (s.IsCorruption()) {
rep_->SetStatus(s);
break;
}
rep_->props.filter_size += filter_content.size();
Remove deprecated block-based filter (#10184) Summary: In https://github.com/facebook/rocksdb/issues/9535, release 7.0, we hid the old block-based filter from being created using the public API, because of its inefficiency. Although we normally maintain read compatibility on old DBs forever, filters are not required for reading a DB, only for optimizing read performance. Thus, it should be acceptable to remove this code and the substantial maintenance burden it carries as useful features are developed and validated (such as user timestamp). This change completely removes the code for reading and writing the old block-based filters, net removing about 1370 lines of code no longer needed. Options removed from testing / benchmarking tools. The prior existence is only evident in a couple of places: * `CacheEntryRole::kDeprecatedFilterBlock` - We can update this public API enum in a major release to minimize source code incompatibilities. * A warning is logged when an old table file is opened that used the old block-based filter. This is provided as a courtesy, and would be a pain to unit test, so manual testing should suffice. Unfortunately, sst_dump does not tell you whether a file uses block-based filter, and the structure of the code makes it very difficult to fix. * To detect that case, `kObsoleteFilterBlockPrefix` (renamed from `kFilterBlockPrefix`) for metaindex is maintained (for now). Other notes: * In some cases where numbers are associated with filter configurations, we have had to update the assigned numbers so that they all correspond to something that exists. * Fixed potential stat counting bug by assuming `filter_checked = false` for cases like `filter == nullptr` rather than assuming `filter_checked = true` * Removed obsolete `block_offset` and `prefix_extractor` parameters from several functions. * Removed some unnecessary checks `if (!table_prefix_extractor() && !prefix_extractor)` because the caller guarantees the prefix extractor exists and is compatible Pull Request resolved: https://github.com/facebook/rocksdb/pull/10184 Test Plan: tests updated, manually test new warning in LOG using base version to generate a DB Reviewed By: riversand963 Differential Revision: D37212647 Pulled By: pdillinger fbshipit-source-id: 06ee020d8de3b81260ffc36ad0c1202cbf463a80
3 years ago
BlockType btype = is_partitioned_filter && /* last */ s.ok()
? BlockType::kFilterPartitionIndex
: BlockType::kFilter;
WriteRawBlock(filter_content, kNoCompression, &filter_block_handle, btype,
nullptr /*raw_contents*/);
}
Account Bloom/Ribbon filter construction memory in global memory limit (#9073) Summary: Note: This PR is the 4th part of a bigger PR stack (https://github.com/facebook/rocksdb/pull/9073) and will rebase/merge only after the first three PRs (https://github.com/facebook/rocksdb/pull/9070, https://github.com/facebook/rocksdb/pull/9071, https://github.com/facebook/rocksdb/pull/9130) merge. **Context:** Similar to https://github.com/facebook/rocksdb/pull/8428, this PR is to track memory usage during (new) Bloom Filter (i.e,FastLocalBloom) and Ribbon Filter (i.e, Ribbon128) construction, moving toward the goal of [single global memory limit using block cache capacity](https://github.com/facebook/rocksdb/wiki/Projects-Being-Developed#improving-memory-efficiency). It also constrains the size of the banding portion of Ribbon Filter during construction by falling back to Bloom Filter if that banding is, at some point, larger than the available space in the cache under `LRUCacheOptions::strict_capacity_limit=true`. The option to turn on this feature is `BlockBasedTableOptions::reserve_table_builder_memory = true` which by default is set to `false`. We [decided](https://github.com/facebook/rocksdb/pull/9073#discussion_r741548409) not to have separate option for separate memory user in table building therefore their memory accounting are all bundled under one general option. **Summary:** - Reserved/released cache for creation/destruction of three main memory users with the passed-in `FilterBuildingContext::cache_res_mgr` during filter construction: - hash entries (i.e`hash_entries`.size(), we bucket-charge hash entries during insertion for performance), - banding (Ribbon Filter only, `bytes_coeff_rows` +`bytes_result_rows` + `bytes_backtrack`), - final filter (i.e, `mutable_buf`'s size). - Implementation details: in order to use `CacheReservationManager::CacheReservationHandle` to account final filter's memory, we have to store the `CacheReservationManager` object and `CacheReservationHandle` for final filter in `XXPH3BitsFilterBuilder` as well as explicitly delete the filter bits builder when done with the final filter in block based table. - Added option fo run `filter_bench` with this memory reservation feature Pull Request resolved: https://github.com/facebook/rocksdb/pull/9073 Test Plan: - Added new tests in `db_bloom_filter_test` to verify filter construction peak cache reservation under combination of `BlockBasedTable::Rep::FilterType` (e.g, `kFullFilter`, `kPartitionedFilter`), `BloomFilterPolicy::Mode`(e.g, `kFastLocalBloom`, `kStandard128Ribbon`, `kDeprecatedBlock`) and `BlockBasedTableOptions::reserve_table_builder_memory` - To address the concern for slow test: tests with memory reservation under `kFullFilter` + `kStandard128Ribbon` and `kPartitionedFilter` take around **3000 - 6000 ms** and others take around **1500 - 2000 ms**, in total adding **20000 - 25000 ms** to the test suit running locally - Added new test in `bloom_test` to verify Ribbon Filter fallback on large banding in FullFilter - Added test in `filter_bench` to verify that this feature does not significantly slow down Bloom/Ribbon Filter construction speed. Local result averaged over **20** run as below: - FastLocalBloom - baseline `./filter_bench -impl=2 -quick -runs 20 | grep 'Build avg'`: - **Build avg ns/key: 29.56295** (DEBUG_LEVEL=1), **29.98153** (DEBUG_LEVEL=0) - new feature (expected to be similar as above)`./filter_bench -impl=2 -quick -runs 20 -reserve_table_builder_memory=true | grep 'Build avg'`: - **Build avg ns/key: 30.99046** (DEBUG_LEVEL=1), **30.48867** (DEBUG_LEVEL=0) - new feature of RibbonFilter with fallback (expected to be similar as above) `./filter_bench -impl=2 -quick -runs 20 -reserve_table_builder_memory=true -strict_capacity_limit=true | grep 'Build avg'` : - **Build avg ns/key: 31.146975** (DEBUG_LEVEL=1), **30.08165** (DEBUG_LEVEL=0) - Ribbon128 - baseline `./filter_bench -impl=3 -quick -runs 20 | grep 'Build avg'`: - **Build avg ns/key: 129.17585** (DEBUG_LEVEL=1), **130.5225** (DEBUG_LEVEL=0) - new feature (expected to be similar as above) `./filter_bench -impl=3 -quick -runs 20 -reserve_table_builder_memory=true | grep 'Build avg' `: - **Build avg ns/key: 131.61645** (DEBUG_LEVEL=1), **132.98075** (DEBUG_LEVEL=0) - new feature of RibbonFilter with fallback (expected to be a lot faster than above due to fallback) `./filter_bench -impl=3 -quick -runs 20 -reserve_table_builder_memory=true -strict_capacity_limit=true | grep 'Build avg'` : - **Build avg ns/key: 52.032965** (DEBUG_LEVEL=1), **52.597825** (DEBUG_LEVEL=0) - And the warning message of `"Cache reservation for Ribbon filter banding failed due to cache full"` is indeed logged to console. Reviewed By: pdillinger Differential Revision: D31991348 Pulled By: hx235 fbshipit-source-id: 9336b2c60f44d530063da518ceaf56dac5f9df8e
3 years ago
rep_->filter_builder->ResetFilterBitsBuilder();
}
if (ok()) {
// Add mapping from "<filter_block_prefix>.Name" to location
// of filter data.
std::string key;
Remove deprecated block-based filter (#10184) Summary: In https://github.com/facebook/rocksdb/issues/9535, release 7.0, we hid the old block-based filter from being created using the public API, because of its inefficiency. Although we normally maintain read compatibility on old DBs forever, filters are not required for reading a DB, only for optimizing read performance. Thus, it should be acceptable to remove this code and the substantial maintenance burden it carries as useful features are developed and validated (such as user timestamp). This change completely removes the code for reading and writing the old block-based filters, net removing about 1370 lines of code no longer needed. Options removed from testing / benchmarking tools. The prior existence is only evident in a couple of places: * `CacheEntryRole::kDeprecatedFilterBlock` - We can update this public API enum in a major release to minimize source code incompatibilities. * A warning is logged when an old table file is opened that used the old block-based filter. This is provided as a courtesy, and would be a pain to unit test, so manual testing should suffice. Unfortunately, sst_dump does not tell you whether a file uses block-based filter, and the structure of the code makes it very difficult to fix. * To detect that case, `kObsoleteFilterBlockPrefix` (renamed from `kFilterBlockPrefix`) for metaindex is maintained (for now). Other notes: * In some cases where numbers are associated with filter configurations, we have had to update the assigned numbers so that they all correspond to something that exists. * Fixed potential stat counting bug by assuming `filter_checked = false` for cases like `filter == nullptr` rather than assuming `filter_checked = true` * Removed obsolete `block_offset` and `prefix_extractor` parameters from several functions. * Removed some unnecessary checks `if (!table_prefix_extractor() && !prefix_extractor)` because the caller guarantees the prefix extractor exists and is compatible Pull Request resolved: https://github.com/facebook/rocksdb/pull/10184 Test Plan: tests updated, manually test new warning in LOG using base version to generate a DB Reviewed By: riversand963 Differential Revision: D37212647 Pulled By: pdillinger fbshipit-source-id: 06ee020d8de3b81260ffc36ad0c1202cbf463a80
3 years ago
key = is_partitioned_filter ? BlockBasedTable::kPartitionedFilterBlockPrefix
: BlockBasedTable::kFullFilterBlockPrefix;
Fix a major performance bug in 7.0 re: filter compatibility (#9736) Summary: Bloom filters generated by pre-7.0 releases are not read by 7.0.x releases (and vice-versa) due to changes to FilterPolicy::Name() in https://github.com/facebook/rocksdb/issues/9590. This can severely impact read performance and read I/O on upgrade or downgrade with existing DB, but not data correctness. To fix, we go back using the old, unified name in SST metadata but (for a while anyway) recognize the aliases that could be generated by early 7.0.x releases. This unfortunately requires a public API change to avoid interfering with all the good changes from https://github.com/facebook/rocksdb/issues/9590, but the API change only affects users with custom FilterPolicy, which should be very few. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9736 Test Plan: manual Generate DBs with ``` ./db_bench.7.0 -db=/dev/shm/rocksdb.7.0 -bloom_bits=10 -cache_index_and_filter_blocks=1 -benchmarks=fillrandom -num=10000000 -compaction_style=2 -fifo_compaction_max_table_files_size_mb=10000 -fifo_compaction_allow_compaction=0 ``` and similar. Compare with ``` for IMPL in 6.29 7.0 fixed; do for DB in 6.29 7.0 fixed; do echo "Testing $IMPL on $DB:"; ./db_bench.$IMPL -db=/dev/shm/rocksdb.$DB -use_existing_db -readonly -bloom_bits=10 -benchmarks=readrandom -num=10000000 -compaction_style=2 -fifo_compaction_max_table_files_size_mb=10000 -fifo_compaction_allow_compaction=0 -duration=10 2>&1 | grep micros/op; done; done ``` Results: ``` Testing 6.29 on 6.29: readrandom : 34.381 micros/op 29085 ops/sec; 3.2 MB/s (291999 of 291999 found) Testing 6.29 on 7.0: readrandom : 190.443 micros/op 5249 ops/sec; 0.6 MB/s (52999 of 52999 found) Testing 6.29 on fixed: readrandom : 40.148 micros/op 24907 ops/sec; 2.8 MB/s (249999 of 249999 found) Testing 7.0 on 6.29: readrandom : 229.430 micros/op 4357 ops/sec; 0.5 MB/s (43999 of 43999 found) Testing 7.0 on 7.0: readrandom : 33.348 micros/op 29986 ops/sec; 3.3 MB/s (299999 of 299999 found) Testing 7.0 on fixed: readrandom : 152.734 micros/op 6546 ops/sec; 0.7 MB/s (65999 of 65999 found) Testing fixed on 6.29: readrandom : 32.024 micros/op 31224 ops/sec; 3.5 MB/s (312999 of 312999 found) Testing fixed on 7.0: readrandom : 33.990 micros/op 29390 ops/sec; 3.3 MB/s (294999 of 294999 found) Testing fixed on fixed: readrandom : 28.714 micros/op 34825 ops/sec; 3.9 MB/s (348999 of 348999 found) ``` Just paying attention to order of magnitude of ops/sec (short test durations, lots of noise), it's clear that with the fix we can read <= 6.29 & >= 7.0 at full speed, where neither 6.29 nor 7.0 can on both. And 6.29 release can properly read fixed DB at full speed. Reviewed By: siying, ajkr Differential Revision: D35057844 Pulled By: pdillinger fbshipit-source-id: a46893a6af4bf084375ebe4728066d00eb08f050
3 years ago
key.append(rep_->table_options.filter_policy->CompatibilityName());
meta_index_builder->Add(key, filter_block_handle);
}
}
void BlockBasedTableBuilder::WriteIndexBlock(
MetaIndexBuilder* meta_index_builder, BlockHandle* index_block_handle) {
if (!ok()) {
return;
}
IndexBuilder::IndexBlocks index_blocks;
auto index_builder_status = rep_->index_builder->Finish(&index_blocks);
if (index_builder_status.IsIncomplete()) {
// We we have more than one index partition then meta_blocks are not
// supported for the index. Currently meta_blocks are used only by
// HashIndexBuilder which is not multi-partition.
assert(index_blocks.meta_blocks.empty());
} else if (ok() && !index_builder_status.ok()) {
rep_->SetStatus(index_builder_status);
}
if (ok()) {
for (const auto& item : index_blocks.meta_blocks) {
BlockHandle block_handle;
WriteBlock(item.second, &block_handle, BlockType::kIndex);
if (!ok()) {
break;
Implement full filter for block based table. Summary: 1. Make filter_block.h a base class. Derive block_based_filter_block and full_filter_block. The previous one is the traditional filter block. The full_filter_block is newly added. It would generate a filter block that contain all the keys in SST file. 2. When querying a key, table would first check if full_filter is available. If not, it would go to the exact data block and check using block_based filter. 3. User could choose to use full_filter or tradional(block_based_filter). They would be stored in SST file with different meta index name. "filter.filter_policy" or "full_filter.filter_policy". Then, Table reader is able to know the fllter block type. 4. Some optimizations have been done for full_filter_block, thus it requires a different interface compared to the original one in filter_policy.h. 5. Actual implementation of filter bits coding/decoding is placed in util/bloom_impl.cc Benchmark: base commit 1d23b5c470844c1208301311f0889eca750431c0 Command: db_bench --db=/dev/shm/rocksdb --num_levels=6 --key_size=20 --prefix_size=20 --keys_per_prefix=0 --value_size=100 --write_buffer_size=134217728 --max_write_buffer_number=2 --target_file_size_base=33554432 --max_bytes_for_level_base=1073741824 --verify_checksum=false --max_background_compactions=4 --use_plain_table=0 --memtablerep=prefix_hash --open_files=-1 --mmap_read=1 --mmap_write=0 --bloom_bits=10 --bloom_locality=1 --memtable_bloom_bits=500000 --compression_type=lz4 --num=393216000 --use_hash_search=1 --block_size=1024 --block_restart_interval=16 --use_existing_db=1 --threads=1 --benchmarks=readrandom —disable_auto_compactions=1 Read QPS increase for about 30% from 2230002 to 2991411. Test Plan: make all check valgrind db_test db_stress --use_block_based_filter = 0 ./auto_sanity_test.sh Reviewers: igor, yhchiang, ljin, sdong Reviewed By: sdong Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D20979
10 years ago
}
meta_index_builder->Add(item.first, block_handle);
}
}
if (ok()) {
if (rep_->table_options.enable_index_compression) {
WriteBlock(index_blocks.index_block_contents, index_block_handle,
BlockType::kIndex);
} else {
WriteRawBlock(index_blocks.index_block_contents, kNoCompression,
index_block_handle, BlockType::kIndex);
}
}
// If there are more index partitions, finish them and write them out
if (index_builder_status.IsIncomplete()) {
bool index_building_finished = false;
while (ok() && !index_building_finished) {
Status s =
rep_->index_builder->Finish(&index_blocks, *index_block_handle);
if (s.ok()) {
index_building_finished = true;
} else if (s.IsIncomplete()) {
// More partitioned index after this one
assert(!index_building_finished);
} else {
// Error
rep_->SetStatus(s);
return;
}
if (rep_->table_options.enable_index_compression) {
WriteBlock(index_blocks.index_block_contents, index_block_handle,
BlockType::kIndex);
} else {
WriteRawBlock(index_blocks.index_block_contents, kNoCompression,
index_block_handle, BlockType::kIndex);
}
// The last index_block_handle will be for the partition index block
}
}
}
void BlockBasedTableBuilder::WritePropertiesBlock(
MetaIndexBuilder* meta_index_builder) {
BlockHandle properties_block_handle;
if (ok()) {
PropertyBlockBuilder property_block_builder;
rep_->props.filter_policy_name =
rep_->table_options.filter_policy != nullptr
? rep_->table_options.filter_policy->Name()
: "";
rep_->props.index_size =
rep_->index_builder->IndexSize() + kBlockTrailerSize;
rep_->props.comparator_name = rep_->ioptions.user_comparator != nullptr
? rep_->ioptions.user_comparator->Name()
: "nullptr";
rep_->props.merge_operator_name =
rep_->ioptions.merge_operator != nullptr
? rep_->ioptions.merge_operator->Name()
: "nullptr";
rep_->props.compression_name =
CompressionTypeToString(rep_->compression_type);
add compression options to table properties (#5081) Summary: Since we are planning to use dictionary compression and to use different compression level, it is quite useful to add compression options to TableProperties. For example, in MyRocks, if the feature is available, we can query from information_schema.rocksdb_sst_props to see if all sst files are converted to ZSTD dictionary compressions. Resolves https://github.com/facebook/rocksdb/issues/4992 With this PR, user can query table properties through `GetPropertiesOfAllTables` API and get compression options as std::string: `window_bits=-14; level=32767; strategy=0; max_dict_bytes=0; zstd_max_train_bytes=0; enabled=0;` or table_properties->ToString() will also contain it `# data blocks=1; # entries=13; # deletions=0; # merge operands=0; # range deletions=0; raw key size=143; raw average key size=11.000000; raw value size=39; raw average value size=3.000000; data block size=120; index block size (user-key? 0, delta-value? 0)=27; filter block size=0; (estimated) table size=147; filter policy name=N/A; prefix extractor name=nullptr; column family ID=0; column family name=default; comparator name=leveldb.BytewiseComparator; merge operator name=nullptr; property collectors names=[]; SST file compression algo=Snappy; SST file compression options=window_bits=-14; level=32767; strategy=0; max_dict_bytes=0; zstd_max_train_bytes=0; enabled=0; ; creation time=1552946632; time stamp of earliest key=1552946632;` Pull Request resolved: https://github.com/facebook/rocksdb/pull/5081 Differential Revision: D14716692 Pulled By: miasantreble fbshipit-source-id: 7d2f2cf84e052bff876e71b4212cfdebf5be32dd
6 years ago
rep_->props.compression_options =
CompressionOptionsToString(rep_->compression_opts);
rep_->props.prefix_extractor_name =
rep_->moptions.prefix_extractor != nullptr
? rep_->moptions.prefix_extractor->AsString()
: "nullptr";
std::string property_collectors_names = "[";
for (size_t i = 0;
i < rep_->ioptions.table_properties_collector_factories.size(); ++i) {
if (i != 0) {
property_collectors_names += ",";
}
property_collectors_names +=
rep_->ioptions.table_properties_collector_factories[i]->Name();
}
property_collectors_names += "]";
rep_->props.property_collectors_names = property_collectors_names;
if (rep_->table_options.index_type ==
BlockBasedTableOptions::kTwoLevelIndexSearch) {
assert(rep_->p_index_builder_ != nullptr);
rep_->props.index_partitions = rep_->p_index_builder_->NumPartitions();
rep_->props.top_level_index_size =
rep_->p_index_builder_->TopLevelIndexSize(rep_->offset);
}
rep_->props.index_key_is_user_key =
!rep_->index_builder->seperator_is_key_plus_seq();
rep_->props.index_value_is_delta_encoded =
rep_->use_delta_encoding_for_index_values;
if (rep_->sampled_input_data_bytes > 0) {
rep_->props.slow_compression_estimated_data_size = static_cast<uint64_t>(
static_cast<double>(rep_->sampled_output_slow_data_bytes) /
rep_->sampled_input_data_bytes *
rep_->compressible_input_data_bytes +
rep_->uncompressible_input_data_bytes + 0.5);
rep_->props.fast_compression_estimated_data_size = static_cast<uint64_t>(
static_cast<double>(rep_->sampled_output_fast_data_bytes) /
rep_->sampled_input_data_bytes *
rep_->compressible_input_data_bytes +
rep_->uncompressible_input_data_bytes + 0.5);
} else if (rep_->sample_for_compression > 0) {
// We tried to sample but none were found. Assume worst-case (compression
// ratio 1.0) so data is complete and aggregatable.
rep_->props.slow_compression_estimated_data_size =
rep_->compressible_input_data_bytes +
rep_->uncompressible_input_data_bytes;
rep_->props.fast_compression_estimated_data_size =
rep_->compressible_input_data_bytes +
rep_->uncompressible_input_data_bytes;
}
// Add basic properties
property_block_builder.AddTableProperty(rep_->props);
// Add use collected properties
NotifyCollectTableCollectorsOnFinish(rep_->table_properties_collectors,
rep_->ioptions.logger,
&property_block_builder);
Slice block_data = property_block_builder.Finish();
TEST_SYNC_POINT_CALLBACK(
"BlockBasedTableBuilder::WritePropertiesBlock:BlockData", &block_data);
WriteRawBlock(block_data, kNoCompression, &properties_block_handle,
BlockType::kProperties);
}
if (ok()) {
#ifndef NDEBUG
{
uint64_t props_block_offset = properties_block_handle.offset();
uint64_t props_block_size = properties_block_handle.size();
TEST_SYNC_POINT_CALLBACK(
"BlockBasedTableBuilder::WritePropertiesBlock:GetPropsBlockOffset",
&props_block_offset);
TEST_SYNC_POINT_CALLBACK(
"BlockBasedTableBuilder::WritePropertiesBlock:GetPropsBlockSize",
&props_block_size);
}
#endif // !NDEBUG
Improve / clean up meta block code & integrity (#9163) Summary: * Checksums are now checked on meta blocks unless specifically suppressed or not applicable (e.g. plain table). (Was other way around.) This means a number of cases that were not checking checksums now are, including direct read TableProperties in Version::GetTableProperties (fixed in meta_blocks ReadTableProperties), reading any block from PersistentCache (fixed in BlockFetcher), read TableProperties in SstFileDumper (ldb/sst_dump/BackupEngine) before table reader open, maybe more. * For that to work, I moved the global_seqno+TableProperties checksum logic to the shared table/ code, because that is used by many utilies such as SstFileDumper. * Also for that to work, we have to know when we're dealing with a block that has a checksum (trailer), so added that capability to Footer based on magic number, and from there BlockFetcher. * Knowledge of trailer presence has also fixed a problem where other table formats were reading blocks including bytes for a non-existant trailer--and awkwardly kind-of not using them, e.g. no shared code checking checksums. (BlockFetcher compression type was populated incorrectly.) Now we only read what is needed. * Minimized code duplication and differing/incompatible/awkward abstractions in meta_blocks.{cc,h} (e.g. SeekTo in metaindex block without parsing block handle) * Moved some meta block handling code from table_properties*.* * Moved some code specific to block-based table from shared table/ code to BlockBasedTable class. The checksum stuff means we can't completely separate it, but things that don't need to be in shared table/ code should not be. * Use unique_ptr rather than raw ptr in more places. (Note: you can std::move from unique_ptr to shared_ptr.) Without enhancements to GetPropertiesOfAllTablesTest (see below), net reduction of roughly 100 lines of code. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9163 Test Plan: existing tests and * Enhanced DBTablePropertiesTest.GetPropertiesOfAllTablesTest to verify that checksums are now checked on direct read of table properties by TableCache (new test would fail before this change) * Also enhanced DBTablePropertiesTest.GetPropertiesOfAllTablesTest to test putting table properties under old meta name * Also generally enhanced that same test to actually test what it was supposed to be testing already, by kicking things out of table cache when we don't want them there. Reviewed By: ajkr, mrambacher Differential Revision: D32514757 Pulled By: pdillinger fbshipit-source-id: 507964b9311d186ae8d1131182290cbd97a99fa9
3 years ago
const std::string* properties_block_meta = &kPropertiesBlockName;
Improve / clean up meta block code & integrity (#9163) Summary: * Checksums are now checked on meta blocks unless specifically suppressed or not applicable (e.g. plain table). (Was other way around.) This means a number of cases that were not checking checksums now are, including direct read TableProperties in Version::GetTableProperties (fixed in meta_blocks ReadTableProperties), reading any block from PersistentCache (fixed in BlockFetcher), read TableProperties in SstFileDumper (ldb/sst_dump/BackupEngine) before table reader open, maybe more. * For that to work, I moved the global_seqno+TableProperties checksum logic to the shared table/ code, because that is used by many utilies such as SstFileDumper. * Also for that to work, we have to know when we're dealing with a block that has a checksum (trailer), so added that capability to Footer based on magic number, and from there BlockFetcher. * Knowledge of trailer presence has also fixed a problem where other table formats were reading blocks including bytes for a non-existant trailer--and awkwardly kind-of not using them, e.g. no shared code checking checksums. (BlockFetcher compression type was populated incorrectly.) Now we only read what is needed. * Minimized code duplication and differing/incompatible/awkward abstractions in meta_blocks.{cc,h} (e.g. SeekTo in metaindex block without parsing block handle) * Moved some meta block handling code from table_properties*.* * Moved some code specific to block-based table from shared table/ code to BlockBasedTable class. The checksum stuff means we can't completely separate it, but things that don't need to be in shared table/ code should not be. * Use unique_ptr rather than raw ptr in more places. (Note: you can std::move from unique_ptr to shared_ptr.) Without enhancements to GetPropertiesOfAllTablesTest (see below), net reduction of roughly 100 lines of code. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9163 Test Plan: existing tests and * Enhanced DBTablePropertiesTest.GetPropertiesOfAllTablesTest to verify that checksums are now checked on direct read of table properties by TableCache (new test would fail before this change) * Also enhanced DBTablePropertiesTest.GetPropertiesOfAllTablesTest to test putting table properties under old meta name * Also generally enhanced that same test to actually test what it was supposed to be testing already, by kicking things out of table cache when we don't want them there. Reviewed By: ajkr, mrambacher Differential Revision: D32514757 Pulled By: pdillinger fbshipit-source-id: 507964b9311d186ae8d1131182290cbd97a99fa9
3 years ago
TEST_SYNC_POINT_CALLBACK(
"BlockBasedTableBuilder::WritePropertiesBlock:Meta",
&properties_block_meta);
meta_index_builder->Add(*properties_block_meta, properties_block_handle);
}
}
void BlockBasedTableBuilder::WriteCompressionDictBlock(
MetaIndexBuilder* meta_index_builder) {
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
if (rep_->compression_dict != nullptr &&
rep_->compression_dict->GetRawDict().size()) {
BlockHandle compression_dict_block_handle;
if (ok()) {
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
WriteRawBlock(rep_->compression_dict->GetRawDict(), kNoCompression,
&compression_dict_block_handle,
BlockType::kCompressionDictionary);
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
#ifndef NDEBUG
Slice compression_dict = rep_->compression_dict->GetRawDict();
TEST_SYNC_POINT_CALLBACK(
"BlockBasedTableBuilder::WriteCompressionDictBlock:RawDict",
&compression_dict);
#endif // NDEBUG
}
if (ok()) {
meta_index_builder->Add(kCompressionDictBlockName,
compression_dict_block_handle);
}
}
}
void BlockBasedTableBuilder::WriteRangeDelBlock(
MetaIndexBuilder* meta_index_builder) {
if (ok() && !rep_->range_del_block.empty()) {
BlockHandle range_del_block_handle;
WriteRawBlock(rep_->range_del_block.Finish(), kNoCompression,
&range_del_block_handle, BlockType::kRangeDeletion);
meta_index_builder->Add(kRangeDelBlockName, range_del_block_handle);
}
}
void BlockBasedTableBuilder::WriteFooter(BlockHandle& metaindex_block_handle,
BlockHandle& index_block_handle) {
Rep* r = rep_;
// this is guaranteed by BlockBasedTableBuilder's constructor
assert(r->table_options.checksum == kCRC32c ||
r->table_options.format_version != 0);
assert(ok());
FooterBuilder footer;
footer.Build(kBlockBasedTableMagicNumber, r->table_options.format_version,
r->get_offset(), r->table_options.checksum,
metaindex_block_handle, index_block_handle);
IOStatus ios = r->file->Append(footer.GetSlice());
if (ios.ok()) {
r->set_offset(r->get_offset() + footer.GetSlice().size());
} else {
r->SetIOStatus(ios);
}
}
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
void BlockBasedTableBuilder::EnterUnbuffered() {
Rep* r = rep_;
assert(r->state == Rep::State::kBuffered);
r->state = Rep::State::kUnbuffered;
const size_t kSampleBytes = r->compression_opts.zstd_max_train_bytes > 0
? r->compression_opts.zstd_max_train_bytes
: r->compression_opts.max_dict_bytes;
const size_t kNumBlocksBuffered = r->data_block_buffers.size();
if (kNumBlocksBuffered == 0) {
// The below code is neither safe nor necessary for handling zero data
// blocks.
return;
}
Limit buffering for collecting samples for compression dictionary (#7970) Summary: For dictionary compression, we need to collect some representative samples of the data to be compressed, which we use to either generate or train (when `CompressionOptions::zstd_max_train_bytes > 0`) a dictionary. Previously, the strategy was to buffer all the data blocks during flush, and up to the target file size during compaction. That strategy allowed us to randomly pick samples from as wide a range as possible that'd be guaranteed to land in a single output file. However, some users try to make huge files in memory-constrained environments, where this strategy can cause OOM. This PR introduces an option, `CompressionOptions::max_dict_buffer_bytes`, that limits how much data blocks are buffered before we switch to unbuffered mode (which means creating the per-SST dictionary, writing out the buffered data, and compressing/writing new blocks as soon as they are built). It is not strict as we currently buffer more than just data blocks -- also keys are buffered. But it does make a step towards giving users predictable memory usage. Related changes include: - Changed sampling for dictionary compression to select unique data blocks when there is limited availability of data blocks - Made use of `BlockBuilder::SwapAndReset()` to save an allocation+memcpy when buffering data blocks for building a dictionary - Changed `ParseBoolean()` to accept an input containing characters after the boolean. This is necessary since, with this PR, a value for `CompressionOptions::enabled` is no longer necessarily the final component in the `CompressionOptions` string. Pull Request resolved: https://github.com/facebook/rocksdb/pull/7970 Test Plan: - updated `CompressionOptions` unit tests to verify limit is respected (to the extent expected in the current implementation) in various scenarios of flush/compaction to bottommost/non-bottommost level - looked at jemalloc heap profiles right before and after switching to unbuffered mode during flush/compaction. Verified memory usage in buffering is proportional to the limit set. Reviewed By: pdillinger Differential Revision: D26467994 Pulled By: ajkr fbshipit-source-id: 3da4ef9fba59974e4ef40e40c01611002c861465
4 years ago
// Abstract algebra teaches us that a finite cyclic group (such as the
// additive group of integers modulo N) can be generated by a number that is
// coprime with N. Since N is variable (number of buffered data blocks), we
// must then pick a prime number in order to guarantee coprimeness with any N.
//
// One downside of this approach is the spread will be poor when
// `kPrimeGeneratorRemainder` is close to zero or close to
// `kNumBlocksBuffered`.
//
// Picked a random number between one and one trillion and then chose the
// next prime number greater than or equal to it.
const uint64_t kPrimeGenerator = 545055921143ull;
// Can avoid repeated division by just adding the remainder repeatedly.
const size_t kPrimeGeneratorRemainder = static_cast<size_t>(
kPrimeGenerator % static_cast<uint64_t>(kNumBlocksBuffered));
const size_t kInitSampleIdx = kNumBlocksBuffered / 2;
Limit buffering for collecting samples for compression dictionary (#7970) Summary: For dictionary compression, we need to collect some representative samples of the data to be compressed, which we use to either generate or train (when `CompressionOptions::zstd_max_train_bytes > 0`) a dictionary. Previously, the strategy was to buffer all the data blocks during flush, and up to the target file size during compaction. That strategy allowed us to randomly pick samples from as wide a range as possible that'd be guaranteed to land in a single output file. However, some users try to make huge files in memory-constrained environments, where this strategy can cause OOM. This PR introduces an option, `CompressionOptions::max_dict_buffer_bytes`, that limits how much data blocks are buffered before we switch to unbuffered mode (which means creating the per-SST dictionary, writing out the buffered data, and compressing/writing new blocks as soon as they are built). It is not strict as we currently buffer more than just data blocks -- also keys are buffered. But it does make a step towards giving users predictable memory usage. Related changes include: - Changed sampling for dictionary compression to select unique data blocks when there is limited availability of data blocks - Made use of `BlockBuilder::SwapAndReset()` to save an allocation+memcpy when buffering data blocks for building a dictionary - Changed `ParseBoolean()` to accept an input containing characters after the boolean. This is necessary since, with this PR, a value for `CompressionOptions::enabled` is no longer necessarily the final component in the `CompressionOptions` string. Pull Request resolved: https://github.com/facebook/rocksdb/pull/7970 Test Plan: - updated `CompressionOptions` unit tests to verify limit is respected (to the extent expected in the current implementation) in various scenarios of flush/compaction to bottommost/non-bottommost level - looked at jemalloc heap profiles right before and after switching to unbuffered mode during flush/compaction. Verified memory usage in buffering is proportional to the limit set. Reviewed By: pdillinger Differential Revision: D26467994 Pulled By: ajkr fbshipit-source-id: 3da4ef9fba59974e4ef40e40c01611002c861465
4 years ago
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
std::string compression_dict_samples;
std::vector<size_t> compression_dict_sample_lens;
size_t buffer_idx = kInitSampleIdx;
for (size_t i = 0;
i < kNumBlocksBuffered && compression_dict_samples.size() < kSampleBytes;
++i) {
size_t copy_len = std::min(kSampleBytes - compression_dict_samples.size(),
r->data_block_buffers[buffer_idx].size());
compression_dict_samples.append(r->data_block_buffers[buffer_idx], 0,
copy_len);
compression_dict_sample_lens.emplace_back(copy_len);
buffer_idx += kPrimeGeneratorRemainder;
if (buffer_idx >= kNumBlocksBuffered) {
buffer_idx -= kNumBlocksBuffered;
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
}
}
// final data block flushed, now we can generate dictionary from the samples.
// OK if compression_dict_samples is empty, we'll just get empty dictionary.
std::string dict;
if (r->compression_opts.zstd_max_train_bytes > 0) {
Support using ZDICT_finalizeDictionary to generate zstd dictionary (#9857) Summary: An untrained dictionary is currently simply the concatenation of several samples. The ZSTD API, ZDICT_finalizeDictionary(), can improve such a dictionary's effectiveness at low cost. This PR changes how dictionary is created by calling the ZSTD ZDICT_finalizeDictionary() API instead of creating raw content dictionary (when max_dict_buffer_bytes > 0), and pass in all buffered uncompressed data blocks as samples. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9857 Test Plan: #### db_bench test for cpu/memory of compression+decompression and space saving on synthetic data: Set up: change the parameter [here](https://github.com/facebook/rocksdb/blob/fb9a167a55e0970b1ef6f67c1600c8d9c4c6114f/tools/db_bench_tool.cc#L1766) to 16384 to make synthetic data more compressible. ``` # linked local ZSTD with version 1.5.2 # DEBUG_LEVEL=0 ROCKSDB_NO_FBCODE=1 ROCKSDB_DISABLE_ZSTD=1 EXTRA_CXXFLAGS="-DZSTD_STATIC_LINKING_ONLY -DZSTD -I/data/users/changyubi/install/include/" EXTRA_LDFLAGS="-L/data/users/changyubi/install/lib/ -l:libzstd.a" make -j32 db_bench dict_bytes=16384 train_bytes=1048576 echo "========== No Dictionary ==========" TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=filluniquerandom,compact -num=10000000 -compression_type=zstd -compression_max_dict_bytes=0 -block_size=4096 -max_background_jobs=24 -memtablerep=vector -allow_concurrent_memtable_write=false -disable_wal=true -max_write_buffer_number=8 >/dev/null 2>&1 TEST_TMPDIR=/dev/shm /usr/bin/time ./db_bench -use_existing_db=true -benchmarks=compact -compression_type=zstd -compression_max_dict_bytes=0 -block_size=4096 2>&1 | grep elapsed du -hc /dev/shm/dbbench/*sst | grep total echo "========== Raw Content Dictionary ==========" TEST_TMPDIR=/dev/shm ./db_bench_main -benchmarks=filluniquerandom,compact -num=10000000 -compression_type=zstd -compression_max_dict_bytes=$dict_bytes -block_size=4096 -max_background_jobs=24 -memtablerep=vector -allow_concurrent_memtable_write=false -disable_wal=true -max_write_buffer_number=8 >/dev/null 2>&1 TEST_TMPDIR=/dev/shm /usr/bin/time ./db_bench_main -use_existing_db=true -benchmarks=compact -compression_type=zstd -compression_max_dict_bytes=$dict_bytes -block_size=4096 2>&1 | grep elapsed du -hc /dev/shm/dbbench/*sst | grep total echo "========== FinalizeDictionary ==========" TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=filluniquerandom,compact -num=10000000 -compression_type=zstd -compression_max_dict_bytes=$dict_bytes -compression_zstd_max_train_bytes=$train_bytes -compression_use_zstd_dict_trainer=false -block_size=4096 -max_background_jobs=24 -memtablerep=vector -allow_concurrent_memtable_write=false -disable_wal=true -max_write_buffer_number=8 >/dev/null 2>&1 TEST_TMPDIR=/dev/shm /usr/bin/time ./db_bench -use_existing_db=true -benchmarks=compact -compression_type=zstd -compression_max_dict_bytes=$dict_bytes -compression_zstd_max_train_bytes=$train_bytes -compression_use_zstd_dict_trainer=false -block_size=4096 2>&1 | grep elapsed du -hc /dev/shm/dbbench/*sst | grep total echo "========== TrainDictionary ==========" TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=filluniquerandom,compact -num=10000000 -compression_type=zstd -compression_max_dict_bytes=$dict_bytes -compression_zstd_max_train_bytes=$train_bytes -block_size=4096 -max_background_jobs=24 -memtablerep=vector -allow_concurrent_memtable_write=false -disable_wal=true -max_write_buffer_number=8 >/dev/null 2>&1 TEST_TMPDIR=/dev/shm /usr/bin/time ./db_bench -use_existing_db=true -benchmarks=compact -compression_type=zstd -compression_max_dict_bytes=$dict_bytes -compression_zstd_max_train_bytes=$train_bytes -block_size=4096 2>&1 | grep elapsed du -hc /dev/shm/dbbench/*sst | grep total # Result: TrainDictionary is much better on space saving, but FinalizeDictionary seems to use less memory. # before compression data size: 1.2GB dict_bytes=16384 max_dict_buffer_bytes = 1048576 space cpu/memory No Dictionary 468M 14.93user 1.00system 0:15.92elapsed 100%CPU (0avgtext+0avgdata 23904maxresident)k Raw Dictionary 251M 15.81user 0.80system 0:16.56elapsed 100%CPU (0avgtext+0avgdata 156808maxresident)k FinalizeDictionary 236M 11.93user 0.64system 0:12.56elapsed 100%CPU (0avgtext+0avgdata 89548maxresident)k TrainDictionary 84M 7.29user 0.45system 0:07.75elapsed 100%CPU (0avgtext+0avgdata 97288maxresident)k ``` #### Benchmark on 10 sample SST files for spacing saving and CPU time on compression: FinalizeDictionary is comparable to TrainDictionary in terms of space saving, and takes less time in compression. ``` dict_bytes=16384 train_bytes=1048576 for sst_file in `ls ../temp/myrock-sst/` do echo "********** $sst_file **********" echo "========== No Dictionary ==========" ./sst_dump --file="../temp/myrock-sst/$sst_file" --command=recompress --compression_level_from=6 --compression_level_to=6 --compression_types=kZSTD echo "========== Raw Content Dictionary ==========" ./sst_dump --file="../temp/myrock-sst/$sst_file" --command=recompress --compression_level_from=6 --compression_level_to=6 --compression_types=kZSTD --compression_max_dict_bytes=$dict_bytes echo "========== FinalizeDictionary ==========" ./sst_dump --file="../temp/myrock-sst/$sst_file" --command=recompress --compression_level_from=6 --compression_level_to=6 --compression_types=kZSTD --compression_max_dict_bytes=$dict_bytes --compression_zstd_max_train_bytes=$train_bytes --compression_use_zstd_finalize_dict echo "========== TrainDictionary ==========" ./sst_dump --file="../temp/myrock-sst/$sst_file" --command=recompress --compression_level_from=6 --compression_level_to=6 --compression_types=kZSTD --compression_max_dict_bytes=$dict_bytes --compression_zstd_max_train_bytes=$train_bytes done 010240.sst (Size/Time) 011029.sst 013184.sst 021552.sst 185054.sst 185137.sst 191666.sst 7560381.sst 7604174.sst 7635312.sst No Dictionary 28165569 / 2614419 32899411 / 2976832 32977848 / 3055542 31966329 / 2004590 33614351 / 1755877 33429029 / 1717042 33611933 / 1776936 33634045 / 2771417 33789721 / 2205414 33592194 / 388254 Raw Content Dictionary 28019950 / 2697961 33748665 / 3572422 33896373 / 3534701 26418431 / 2259658 28560825 / 1839168 28455030 / 1846039 28494319 / 1861349 32391599 / 3095649 33772142 / 2407843 33592230 / 474523 FinalizeDictionary 27896012 / 2650029 33763886 / 3719427 33904283 / 3552793 26008225 / 2198033 28111872 / 1869530 28014374 / 1789771 28047706 / 1848300 32296254 / 3204027 33698698 / 2381468 33592344 / 517433 TrainDictionary 28046089 / 2740037 33706480 / 3679019 33885741 / 3629351 25087123 / 2204558 27194353 / 1970207 27234229 / 1896811 27166710 / 1903119 32011041 / 3322315 32730692 / 2406146 33608631 / 570593 ``` #### Decompression/Read test: With FinalizeDictionary/TrainDictionary, some data structure used for decompression are in stored in dictionary, so they are expected to be faster in terms of decompression/reads. ``` dict_bytes=16384 train_bytes=1048576 echo "No Dictionary" TEST_TMPDIR=/dev/shm/ ./db_bench -benchmarks=filluniquerandom,compact -compression_type=zstd -compression_max_dict_bytes=0 > /dev/null 2>&1 TEST_TMPDIR=/dev/shm/ ./db_bench -use_existing_db=true -benchmarks=readrandom -cache_size=0 -compression_type=zstd -compression_max_dict_bytes=0 2>&1 | grep MB/s echo "Raw Dictionary" TEST_TMPDIR=/dev/shm/ ./db_bench -benchmarks=filluniquerandom,compact -compression_type=zstd -compression_max_dict_bytes=$dict_bytes > /dev/null 2>&1 TEST_TMPDIR=/dev/shm/ ./db_bench -use_existing_db=true -benchmarks=readrandom -cache_size=0 -compression_type=zstd -compression_max_dict_bytes=$dict_bytes 2>&1 | grep MB/s echo "FinalizeDict" TEST_TMPDIR=/dev/shm/ ./db_bench -benchmarks=filluniquerandom,compact -compression_type=zstd -compression_max_dict_bytes=$dict_bytes -compression_zstd_max_train_bytes=$train_bytes -compression_use_zstd_dict_trainer=false > /dev/null 2>&1 TEST_TMPDIR=/dev/shm/ ./db_bench -use_existing_db=true -benchmarks=readrandom -cache_size=0 -compression_type=zstd -compression_max_dict_bytes=$dict_bytes -compression_zstd_max_train_bytes=$train_bytes -compression_use_zstd_dict_trainer=false 2>&1 | grep MB/s echo "Train Dictionary" TEST_TMPDIR=/dev/shm/ ./db_bench -benchmarks=filluniquerandom,compact -compression_type=zstd -compression_max_dict_bytes=$dict_bytes -compression_zstd_max_train_bytes=$train_bytes > /dev/null 2>&1 TEST_TMPDIR=/dev/shm/ ./db_bench -use_existing_db=true -benchmarks=readrandom -cache_size=0 -compression_type=zstd -compression_max_dict_bytes=$dict_bytes -compression_zstd_max_train_bytes=$train_bytes 2>&1 | grep MB/s No Dictionary readrandom : 12.183 micros/op 82082 ops/sec 12.183 seconds 1000000 operations; 9.1 MB/s (1000000 of 1000000 found) Raw Dictionary readrandom : 12.314 micros/op 81205 ops/sec 12.314 seconds 1000000 operations; 9.0 MB/s (1000000 of 1000000 found) FinalizeDict readrandom : 9.787 micros/op 102180 ops/sec 9.787 seconds 1000000 operations; 11.3 MB/s (1000000 of 1000000 found) Train Dictionary readrandom : 9.698 micros/op 103108 ops/sec 9.699 seconds 1000000 operations; 11.4 MB/s (1000000 of 1000000 found) ``` Reviewed By: ajkr Differential Revision: D35720026 Pulled By: cbi42 fbshipit-source-id: 24d230fdff0fd28a1bb650658798f00dfcfb2a1f
3 years ago
if (r->compression_opts.use_zstd_dict_trainer) {
dict = ZSTD_TrainDictionary(compression_dict_samples,
compression_dict_sample_lens,
r->compression_opts.max_dict_bytes);
} else {
dict = ZSTD_FinalizeDictionary(
compression_dict_samples, compression_dict_sample_lens,
r->compression_opts.max_dict_bytes, r->compression_opts.level);
}
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
} else {
dict = std::move(compression_dict_samples);
}
r->compression_dict.reset(new CompressionDict(dict, r->compression_type,
r->compression_opts.level));
r->verify_dict.reset(new UncompressionDict(
dict, r->compression_type == kZSTD ||
r->compression_type == kZSTDNotFinalCompression));
auto get_iterator_for_block = [&r](size_t i) {
auto& data_block = r->data_block_buffers[i];
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
assert(!data_block.empty());
Block reader{BlockContents{data_block}};
DataBlockIter* iter = reader.NewDataIterator(
r->internal_comparator.user_comparator(), kDisableGlobalSequenceNumber);
iter->SeekToFirst();
assert(iter->Valid());
return std::unique_ptr<DataBlockIter>(iter);
};
std::unique_ptr<DataBlockIter> iter = nullptr, next_block_iter = nullptr;
for (size_t i = 0; ok() && i < r->data_block_buffers.size(); ++i) {
if (iter == nullptr) {
iter = get_iterator_for_block(i);
assert(iter != nullptr);
};
if (i + 1 < r->data_block_buffers.size()) {
next_block_iter = get_iterator_for_block(i + 1);
}
auto& data_block = r->data_block_buffers[i];
if (r->IsParallelCompressionEnabled()) {
Slice first_key_in_next_block;
const Slice* first_key_in_next_block_ptr = &first_key_in_next_block;
if (i + 1 < r->data_block_buffers.size()) {
assert(next_block_iter != nullptr);
first_key_in_next_block = next_block_iter->key();
} else {
first_key_in_next_block_ptr = r->first_key_in_next_block;
}
std::vector<std::string> keys;
for (; iter->Valid(); iter->Next()) {
keys.emplace_back(iter->key().ToString());
}
ParallelCompressionRep::BlockRep* block_rep = r->pc_rep->PrepareBlock(
r->compression_type, first_key_in_next_block_ptr, &data_block, &keys);
assert(block_rep != nullptr);
r->pc_rep->file_size_estimator.EmitBlock(block_rep->data->size(),
r->get_offset());
r->pc_rep->EmitBlock(block_rep);
} else {
for (; iter->Valid(); iter->Next()) {
Slice key = iter->key();
if (r->filter_builder != nullptr) {
size_t ts_sz =
r->internal_comparator.user_comparator()->timestamp_size();
r->filter_builder->Add(ExtractUserKeyAndStripTimestamp(key, ts_sz));
}
r->index_builder->OnKeyAdded(key);
}
WriteBlock(Slice(data_block), &r->pending_handle, BlockType::kData);
if (ok() && i + 1 < r->data_block_buffers.size()) {
assert(next_block_iter != nullptr);
Slice first_key_in_next_block = next_block_iter->key();
Slice* first_key_in_next_block_ptr = &first_key_in_next_block;
iter->SeekToLast();
std::string last_key = iter->key().ToString();
r->index_builder->AddIndexEntry(&last_key, first_key_in_next_block_ptr,
r->pending_handle);
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
}
}
std::swap(iter, next_block_iter);
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
}
r->data_block_buffers.clear();
r->data_begin_offset = 0;
// Release all reserved cache for data block buffers
if (r->compression_dict_buffer_cache_res_mgr != nullptr) {
Account memory of big memory users in BlockBasedTable in global memory limit (#9748) Summary: **Context:** Through heap profiling, we discovered that `BlockBasedTableReader` objects can accumulate and lead to high memory usage (e.g, `max_open_file = -1`). These memories are currently not saved, not tracked, not constrained and not cache evict-able. As a first step to improve this, similar to https://github.com/facebook/rocksdb/pull/8428, this PR is to track an estimate of `BlockBasedTableReader` object's memory in block cache and fail future creation if the memory usage exceeds the available space of cache at the time of creation. **Summary:** - Approximate big memory users (`BlockBasedTable::Rep` and `TableProperties` )' memory usage in addition to the existing estimated ones (filter block/index block/un-compression dictionary) - Charge all of these memory usages to block cache on `BlockBasedTable::Open()` and release them on `~BlockBasedTable()` as there is no memory usage fluctuation of concern in between - Refactor on CacheReservationManager (and its call-sites) to add concurrent support for BlockBasedTable used in this PR. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9748 Test Plan: - New unit tests - db bench: `OpenDb` : **-0.52% in ms** - Setup `./db_bench -benchmarks=fillseq -db=/dev/shm/testdb -disable_auto_compactions=1 -write_buffer_size=1048576` - Repeated run with pre-change w/o feature and post-change with feature, benchmark `OpenDb`: `./db_bench -benchmarks=readrandom -use_existing_db=1 -db=/dev/shm/testdb -reserve_table_reader_memory=true (remove this when running w/o feature) -file_opening_threads=3 -open_files=-1 -report_open_timing=true| egrep 'OpenDb:'` #-run | (feature-off) avg milliseconds | std milliseconds | (feature-on) avg milliseconds | std milliseconds | change (%) -- | -- | -- | -- | -- | -- 10 | 11.4018 | 5.95173 | 9.47788 | 1.57538 | -16.87382694 20 | 9.23746 | 0.841053 | 9.32377 | 1.14074 | 0.9343477536 40 | 9.0876 | 0.671129 | 9.35053 | 1.11713 | 2.893283155 80 | 9.72514 | 2.28459 | 9.52013 | 1.0894 | -2.108041632 160 | 9.74677 | 0.991234 | 9.84743 | 1.73396 | 1.032752389 320 | 10.7297 | 5.11555 | 10.547 | 1.97692 | **-1.70275031** 640 | 11.7092 | 2.36565 | 11.7869 | 2.69377 | **0.6635807741** - db bench on write with cost to cache in WriteBufferManager (just in case this PR's CRM refactoring accidentally slows down anything in WBM) : `fillseq` : **+0.54% in micros/op** `./db_bench -benchmarks=fillseq -db=/dev/shm/testdb -disable_auto_compactions=1 -cost_write_buffer_to_cache=true -write_buffer_size=10000000000 | egrep 'fillseq'` #-run | (pre-PR) avg micros/op | std micros/op | (post-PR) avg micros/op | std micros/op | change (%) -- | -- | -- | -- | -- | -- 10 | 6.15 | 0.260187 | 6.289 | 0.371192 | 2.260162602 20 | 7.28025 | 0.465402 | 7.37255 | 0.451256 | 1.267813605 40 | 7.06312 | 0.490654 | 7.13803 | 0.478676 | **1.060579461** 80 | 7.14035 | 0.972831 | 7.14196 | 0.92971 | **0.02254791432** - filter bench: `bloom filter`: **-0.78% in ms/key** - ` ./filter_bench -impl=2 -quick -reserve_table_builder_memory=true | grep 'Build avg'` #-run | (pre-PR) avg ns/key | std ns/key | (post-PR) ns/key | std ns/key | change (%) -- | -- | -- | -- | -- | -- 10 | 26.4369 | 0.442182 | 26.3273 | 0.422919 | **-0.4145720565** 20 | 26.4451 | 0.592787 | 26.1419 | 0.62451 | **-1.1465262** - Crash test `python3 tools/db_crashtest.py blackbox --reserve_table_reader_memory=1 --cache_size=1` killed as normal Reviewed By: ajkr Differential Revision: D35136549 Pulled By: hx235 fbshipit-source-id: 146978858d0f900f43f4eb09bfd3e83195e3be28
3 years ago
Status s = r->compression_dict_buffer_cache_res_mgr->UpdateCacheReservation(
r->data_begin_offset);
s.PermitUncheckedError();
}
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
}
Status BlockBasedTableBuilder::Finish() {
Rep* r = rep_;
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
assert(r->state != Rep::State::kClosed);
bool empty_data_block = r->data_block.empty();
r->first_key_in_next_block = nullptr;
Flush();
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
if (r->state == Rep::State::kBuffered) {
EnterUnbuffered();
}
if (r->IsParallelCompressionEnabled()) {
StopParallelCompression();
#ifndef NDEBUG
for (const auto& br : r->pc_rep->block_rep_buf) {
assert(br.status.ok());
}
#endif // !NDEBUG
} else {
// To make sure properties block is able to keep the accurate size of index
// block, we will finish writing all index entries first.
if (ok() && !empty_data_block) {
r->index_builder->AddIndexEntry(
&r->last_key, nullptr /* no next data block */, r->pending_handle);
}
}
// Write meta blocks, metaindex block and footer in the following order.
// 1. [meta block: filter]
// 2. [meta block: index]
// 3. [meta block: compression dictionary]
// 4. [meta block: range deletion tombstone]
// 5. [meta block: properties]
// 6. [metaindex block]
// 7. Footer
BlockHandle metaindex_block_handle, index_block_handle;
MetaIndexBuilder meta_index_builder;
WriteFilterBlock(&meta_index_builder);
WriteIndexBlock(&meta_index_builder, &index_block_handle);
WriteCompressionDictBlock(&meta_index_builder);
WriteRangeDelBlock(&meta_index_builder);
WritePropertiesBlock(&meta_index_builder);
if (ok()) {
// flush the meta index block
WriteRawBlock(meta_index_builder.Finish(), kNoCompression,
&metaindex_block_handle, BlockType::kMetaIndex);
}
if (ok()) {
WriteFooter(metaindex_block_handle, index_block_handle);
}
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
r->state = Rep::State::kClosed;
r->SetStatus(r->CopyIOStatus());
Status ret_status = r->CopyStatus();
assert(!ret_status.ok() || io_status().ok());
return ret_status;
}
void BlockBasedTableBuilder::Abandon() {
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
assert(rep_->state != Rep::State::kClosed);
if (rep_->IsParallelCompressionEnabled()) {
StopParallelCompression();
}
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
rep_->state = Rep::State::kClosed;
rep_->CopyStatus().PermitUncheckedError();
rep_->CopyIOStatus().PermitUncheckedError();
}
uint64_t BlockBasedTableBuilder::NumEntries() const {
return rep_->props.num_entries;
}
bool BlockBasedTableBuilder::IsEmpty() const {
return rep_->props.num_entries == 0 && rep_->props.num_range_deletions == 0;
}
Reduce scope of compression dictionary to single SST (#4952) Summary: Our previous approach was to train one compression dictionary per compaction, using the first output SST to train a dictionary, and then applying it on subsequent SSTs in the same compaction. While this was great for minimizing CPU/memory/I/O overhead, it did not achieve good compression ratios in practice. In our most promising potential use case, moderate reductions in a dictionary's scope make a major difference on compression ratio. So, this PR changes compression dictionary to be scoped per-SST. It accepts the tradeoff during table building to use more memory and CPU. Important changes include: - The `BlockBasedTableBuilder` has a new state when dictionary compression is in-use: `kBuffered`. In that state it accumulates uncompressed data in-memory whenever `Add` is called. - After accumulating target file size bytes or calling `BlockBasedTableBuilder::Finish`, a `BlockBasedTableBuilder` moves to the `kUnbuffered` state. The transition (`EnterUnbuffered()`) involves sampling the buffered data, training a dictionary, and compressing/writing out all buffered data. In the `kUnbuffered` state, a `BlockBasedTableBuilder` behaves the same as before -- blocks are compressed/written out as soon as they fill up. - Samples are now whole uncompressed data blocks, except the final sample may be a partial data block so we don't breach the user's configured `max_dict_bytes` or `zstd_max_train_bytes`. The dictionary trainer is supposed to work better when we pass it real units of compression. Previously we were passing 64-byte KV samples which was not realistic. Pull Request resolved: https://github.com/facebook/rocksdb/pull/4952 Differential Revision: D13967980 Pulled By: ajkr fbshipit-source-id: 82bea6f7537e1529c7a1a4cdee84585f5949300f
6 years ago
uint64_t BlockBasedTableBuilder::FileSize() const { return rep_->offset; }
uint64_t BlockBasedTableBuilder::EstimatedFileSize() const {
if (rep_->IsParallelCompressionEnabled()) {
// Use compression ratio so far and inflight raw bytes to estimate
// final SST size.
return rep_->pc_rep->file_size_estimator.GetEstimatedFileSize();
} else {
return FileSize();
}
}
bool BlockBasedTableBuilder::NeedCompact() const {
for (const auto& collector : rep_->table_properties_collectors) {
if (collector->NeedCompact()) {
return true;
}
}
return false;
}
TableProperties BlockBasedTableBuilder::GetTableProperties() const {
TableProperties ret = rep_->props;
for (const auto& collector : rep_->table_properties_collectors) {
for (const auto& prop : collector->GetReadableProperties()) {
ret.readable_properties.insert(prop);
}
collector->Finish(&ret.user_collected_properties).PermitUncheckedError();
}
return ret;
}
std::string BlockBasedTableBuilder::GetFileChecksum() const {
if (rep_->file != nullptr) {
return rep_->file->GetFileChecksum();
} else {
return kUnknownFileChecksum;
}
}
const char* BlockBasedTableBuilder::GetFileChecksumFuncName() const {
if (rep_->file != nullptr) {
return rep_->file->GetFileChecksumFuncName();
} else {
return kUnknownFileChecksumFuncName;
}
}
void BlockBasedTableBuilder::SetSeqnoTimeTableProperties(
const std::string& encoded_seqno_to_time_mapping,
uint64_t oldest_ancestor_time) {
rep_->props.seqno_to_time_mapping = encoded_seqno_to_time_mapping;
rep_->props.creation_time = oldest_ancestor_time;
}
Remove deprecated block-based filter (#10184) Summary: In https://github.com/facebook/rocksdb/issues/9535, release 7.0, we hid the old block-based filter from being created using the public API, because of its inefficiency. Although we normally maintain read compatibility on old DBs forever, filters are not required for reading a DB, only for optimizing read performance. Thus, it should be acceptable to remove this code and the substantial maintenance burden it carries as useful features are developed and validated (such as user timestamp). This change completely removes the code for reading and writing the old block-based filters, net removing about 1370 lines of code no longer needed. Options removed from testing / benchmarking tools. The prior existence is only evident in a couple of places: * `CacheEntryRole::kDeprecatedFilterBlock` - We can update this public API enum in a major release to minimize source code incompatibilities. * A warning is logged when an old table file is opened that used the old block-based filter. This is provided as a courtesy, and would be a pain to unit test, so manual testing should suffice. Unfortunately, sst_dump does not tell you whether a file uses block-based filter, and the structure of the code makes it very difficult to fix. * To detect that case, `kObsoleteFilterBlockPrefix` (renamed from `kFilterBlockPrefix`) for metaindex is maintained (for now). Other notes: * In some cases where numbers are associated with filter configurations, we have had to update the assigned numbers so that they all correspond to something that exists. * Fixed potential stat counting bug by assuming `filter_checked = false` for cases like `filter == nullptr` rather than assuming `filter_checked = true` * Removed obsolete `block_offset` and `prefix_extractor` parameters from several functions. * Removed some unnecessary checks `if (!table_prefix_extractor() && !prefix_extractor)` because the caller guarantees the prefix extractor exists and is compatible Pull Request resolved: https://github.com/facebook/rocksdb/pull/10184 Test Plan: tests updated, manually test new warning in LOG using base version to generate a DB Reviewed By: riversand963 Differential Revision: D37212647 Pulled By: pdillinger fbshipit-source-id: 06ee020d8de3b81260ffc36ad0c1202cbf463a80
3 years ago
const std::string BlockBasedTable::kObsoleteFilterBlockPrefix = "filter.";
Implement full filter for block based table. Summary: 1. Make filter_block.h a base class. Derive block_based_filter_block and full_filter_block. The previous one is the traditional filter block. The full_filter_block is newly added. It would generate a filter block that contain all the keys in SST file. 2. When querying a key, table would first check if full_filter is available. If not, it would go to the exact data block and check using block_based filter. 3. User could choose to use full_filter or tradional(block_based_filter). They would be stored in SST file with different meta index name. "filter.filter_policy" or "full_filter.filter_policy". Then, Table reader is able to know the fllter block type. 4. Some optimizations have been done for full_filter_block, thus it requires a different interface compared to the original one in filter_policy.h. 5. Actual implementation of filter bits coding/decoding is placed in util/bloom_impl.cc Benchmark: base commit 1d23b5c470844c1208301311f0889eca750431c0 Command: db_bench --db=/dev/shm/rocksdb --num_levels=6 --key_size=20 --prefix_size=20 --keys_per_prefix=0 --value_size=100 --write_buffer_size=134217728 --max_write_buffer_number=2 --target_file_size_base=33554432 --max_bytes_for_level_base=1073741824 --verify_checksum=false --max_background_compactions=4 --use_plain_table=0 --memtablerep=prefix_hash --open_files=-1 --mmap_read=1 --mmap_write=0 --bloom_bits=10 --bloom_locality=1 --memtable_bloom_bits=500000 --compression_type=lz4 --num=393216000 --use_hash_search=1 --block_size=1024 --block_restart_interval=16 --use_existing_db=1 --threads=1 --benchmarks=readrandom —disable_auto_compactions=1 Read QPS increase for about 30% from 2230002 to 2991411. Test Plan: make all check valgrind db_test db_stress --use_block_based_filter = 0 ./auto_sanity_test.sh Reviewers: igor, yhchiang, ljin, sdong Reviewed By: sdong Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D20979
10 years ago
const std::string BlockBasedTable::kFullFilterBlockPrefix = "fullfilter.";
const std::string BlockBasedTable::kPartitionedFilterBlockPrefix =
"partitionedfilter.";
} // namespace ROCKSDB_NAMESPACE