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rocksdb/options/options.cc

717 lines
30 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 "rocksdb/options.h"
#include <cinttypes>
#include <limits>
#include "logging/logging.h"
#include "monitoring/statistics.h"
#include "options/db_options.h"
#include "options/options_helper.h"
#include "rocksdb/cache.h"
#include "rocksdb/compaction_filter.h"
#include "rocksdb/comparator.h"
#include "rocksdb/env.h"
#include "rocksdb/filter_policy.h"
#include "rocksdb/memtablerep.h"
#include "rocksdb/merge_operator.h"
#include "rocksdb/slice.h"
#include "rocksdb/slice_transform.h"
#include "rocksdb/sst_file_manager.h"
#include "rocksdb/sst_partitioner.h"
#include "rocksdb/table.h"
#include "rocksdb/table_properties.h"
#include "rocksdb/wal_filter.h"
#include "table/block_based/block_based_table_factory.h"
#include "util/compression.h"
namespace ROCKSDB_NAMESPACE {
AdvancedColumnFamilyOptions::AdvancedColumnFamilyOptions() {
assert(memtable_factory.get() != nullptr);
}
AdvancedColumnFamilyOptions::AdvancedColumnFamilyOptions(const Options& options)
: max_write_buffer_number(options.max_write_buffer_number),
min_write_buffer_number_to_merge(
options.min_write_buffer_number_to_merge),
Support saving history in memtable_list Summary: For transactions, we are using the memtables to validate that there are no write conflicts. But after flushing, we don't have any memtables, and transactions could fail to commit. So we want to someone keep around some extra history to use for conflict checking. In addition, we want to provide a way to increase the size of this history if too many transactions fail to commit. After chatting with people, it seems like everyone prefers just using Memtables to store this history (instead of a separate history structure). It seems like the best place for this is abstracted inside the memtable_list. I decide to create a separate list in MemtableListVersion as using the same list complicated the flush/installalflushresults logic too much. This diff adds a new parameter to control how much memtable history to keep around after flushing. However, it sounds like people aren't too fond of adding new parameters. So I am making the default size of flushed+not-flushed memtables be set to max_write_buffers. This should not change the maximum amount of memory used, but make it more likely we're using closer the the limit. (We are now postponing deleting flushed memtables until the max_write_buffer limit is reached). So while we might use more memory on average, we are still obeying the limit set (and you could argue it's better to go ahead and use up memory now instead of waiting for a write stall to happen to test this limit). However, if people are opposed to this default behavior, we can easily set it to 0 and require this parameter be set in order to use transactions. Test Plan: Added a xfunc test to play around with setting different values of this parameter in all tests. Added testing in memtablelist_test and planning on adding more testing here. Reviewers: sdong, rven, igor Reviewed By: igor Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D37443
10 years ago
max_write_buffer_number_to_maintain(
options.max_write_buffer_number_to_maintain),
Refactor trimming logic for immutable memtables (#5022) Summary: MyRocks currently sets `max_write_buffer_number_to_maintain` in order to maintain enough history for transaction conflict checking. The effectiveness of this approach depends on the size of memtables. When memtables are small, it may not keep enough history; when memtables are large, this may consume too much memory. We are proposing a new way to configure memtable list history: by limiting the memory usage of immutable memtables. The new option is `max_write_buffer_size_to_maintain` and it will take precedence over the old `max_write_buffer_number_to_maintain` if they are both set to non-zero values. The new option accounts for the total memory usage of flushed immutable memtables and mutable memtable. When the total usage exceeds the limit, RocksDB may start dropping immutable memtables (which is also called trimming history), starting from the oldest one. The semantics of the old option actually works both as an upper bound and lower bound. History trimming will start if number of immutable memtables exceeds the limit, but it will never go below (limit-1) due to history trimming. In order the mimic the behavior with the new option, history trimming will stop if dropping the next immutable memtable causes the total memory usage go below the size limit. For example, assuming the size limit is set to 64MB, and there are 3 immutable memtables with sizes of 20, 30, 30. Although the total memory usage is 80MB > 64MB, dropping the oldest memtable will reduce the memory usage to 60MB < 64MB, so in this case no memtable will be dropped. Pull Request resolved: https://github.com/facebook/rocksdb/pull/5022 Differential Revision: D14394062 Pulled By: miasantreble fbshipit-source-id: 60457a509c6af89d0993f988c9b5c2aa9e45f5c5
5 years ago
max_write_buffer_size_to_maintain(
options.max_write_buffer_size_to_maintain),
inplace_update_support(options.inplace_update_support),
inplace_update_num_locks(options.inplace_update_num_locks),
Dynamically changeable `MemPurge` option (#10011) Summary: **Summary** Make the mempurge option flag a Mutable Column Family option flag. Therefore, the mempurge feature can be dynamically toggled. **Motivation** RocksDB users prefer having the ability to switch features on and off without having to close and reopen the DB. This is particularly important if the feature causes issues and needs to be turned off. Dynamically changing a DB option flag does not seem currently possible. Moreover, with this new change, the MemPurge feature can be toggled on or off independently between column families, which we see as a major improvement. **Content of this PR** This PR includes removal of the `experimental_mempurge_threshold` flag as a DB option flag, and its re-introduction as a `MutableCFOption` flag. I updated the code to handle dynamic changes of the flag (in particular inside the `FlushJob` file). Additionally, this PR includes a new test to demonstrate the capacity of the code to toggle the MemPurge feature on and off, as well as the addition in the `db_stress` module of 2 different mempurge threshold values (0.0 and 1.0) that can be randomly changed with the `set_option_one_in` flag. This is useful to stress test the dynamic changes. **Benchmarking** I will add numbers to prove that there is no performance impact within the next 12 hours. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10011 Reviewed By: pdillinger Differential Revision: D36462357 Pulled By: bjlemaire fbshipit-source-id: 5e3d63bdadf085c0572ecc2349e7dd9729ce1802
3 years ago
experimental_mempurge_threshold(options.experimental_mempurge_threshold),
inplace_callback(options.inplace_callback),
memtable_prefix_bloom_size_ratio(
options.memtable_prefix_bloom_size_ratio),
memtable_whole_key_filtering(options.memtable_whole_key_filtering),
memtable_huge_page_size(options.memtable_huge_page_size),
memtable_insert_with_hint_prefix_extractor(
options.memtable_insert_with_hint_prefix_extractor),
bloom_locality(options.bloom_locality),
arena_block_size(options.arena_block_size),
compression_per_level(options.compression_per_level),
num_levels(options.num_levels),
level0_slowdown_writes_trigger(options.level0_slowdown_writes_trigger),
level0_stop_writes_trigger(options.level0_stop_writes_trigger),
target_file_size_base(options.target_file_size_base),
target_file_size_multiplier(options.target_file_size_multiplier),
level_compaction_dynamic_level_bytes(
options.level_compaction_dynamic_level_bytes),
max_bytes_for_level_multiplier(options.max_bytes_for_level_multiplier),
max_bytes_for_level_multiplier_additional(
options.max_bytes_for_level_multiplier_additional),
max_compaction_bytes(options.max_compaction_bytes),
soft_pending_compaction_bytes_limit(
options.soft_pending_compaction_bytes_limit),
hard_pending_compaction_bytes_limit(
options.hard_pending_compaction_bytes_limit),
compaction_style(options.compaction_style),
compaction_pri(options.compaction_pri),
compaction_options_universal(options.compaction_options_universal),
compaction_options_fifo(options.compaction_options_fifo),
max_sequential_skip_in_iterations(
options.max_sequential_skip_in_iterations),
memtable_factory(options.memtable_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_collector_factories(
options.table_properties_collector_factories),
max_successive_merges(options.max_successive_merges),
optimize_filters_for_hits(options.optimize_filters_for_hits),
paranoid_file_checks(options.paranoid_file_checks),
force_consistency_checks(options.force_consistency_checks),
report_bg_io_stats(options.report_bg_io_stats),
ttl(options.ttl),
Periodic Compactions (#5166) Summary: Introducing Periodic Compactions. This feature allows all the files in a CF to be periodically compacted. It could help in catching any corruptions that could creep into the DB proactively as every file is constantly getting re-compacted. And also, of course, it helps to cleanup data older than certain threshold. - Introduced a new option `periodic_compaction_time` to control how long a file can live without being compacted in a CF. - This works across all levels. - The files are put in the same level after going through the compaction. (Related files in the same level are picked up as `ExpandInputstoCleanCut` is used). - Compaction filters, if any, are invoked as usual. - A new table property, `file_creation_time`, is introduced to implement this feature. This property is set to the time at which the SST file was created (and that time is given by the underlying Env/OS). This feature can be enabled on its own, or in conjunction with `ttl`. It is possible to set a different time threshold for the bottom level when used in conjunction with ttl. Since `ttl` works only on 0 to last but one levels, you could set `ttl` to, say, 1 day, and `periodic_compaction_time` to, say, 7 days. Since `ttl < periodic_compaction_time` all files in last but one levels keep getting picked up based on ttl, and almost never based on periodic_compaction_time. The files in the bottom level get picked up for compaction based on `periodic_compaction_time`. Pull Request resolved: https://github.com/facebook/rocksdb/pull/5166 Differential Revision: D14884441 Pulled By: sagar0 fbshipit-source-id: 408426cbacb409c06386a98632dcf90bfa1bda47
6 years ago
periodic_compaction_seconds(options.periodic_compaction_seconds),
sample_for_compression(options.sample_for_compression),
enable_blob_files(options.enable_blob_files),
min_blob_size(options.min_blob_size),
blob_file_size(options.blob_file_size),
blob_compression_type(options.blob_compression_type),
enable_blob_garbage_collection(options.enable_blob_garbage_collection),
blob_garbage_collection_age_cutoff(
Make it possible to force the garbage collection of the oldest blob files (#8994) Summary: The current BlobDB garbage collection logic works by relocating the valid blobs from the oldest blob files as they are encountered during compaction, and cleaning up blob files once they contain nothing but garbage. However, with sufficiently skewed workloads, it is theoretically possible to end up in a situation when few or no compactions get scheduled for the SST files that contain references to the oldest blob files, which can lead to increased space amp due to the lack of GC. In order to efficiently handle such workloads, the patch adds a new BlobDB configuration option called `blob_garbage_collection_force_threshold`, which signals to BlobDB to schedule targeted compactions for the SST files that keep alive the oldest batch of blob files if the overall ratio of garbage in the given blob files meets the threshold *and* all the given blob files are eligible for GC based on `blob_garbage_collection_age_cutoff`. (For example, if the new option is set to 0.9, targeted compactions will get scheduled if the sum of garbage bytes meets or exceeds 90% of the sum of total bytes in the oldest blob files, assuming all affected blob files are below the age-based cutoff.) The net result of these targeted compactions is that the valid blobs in the oldest blob files are relocated and the oldest blob files themselves cleaned up (since *all* SST files that rely on them get compacted away). These targeted compactions are similar to periodic compactions in the sense that they force certain SST files that otherwise would not get picked up to undergo compaction and also in the sense that instead of merging files from multiple levels, they target a single file. (Note: such compactions might still include neighboring files from the same level due to the need of having a "clean cut" boundary but they never include any files from any other level.) This functionality is currently only supported with the leveled compaction style and is inactive by default (since the default value is set to 1.0, i.e. 100%). Pull Request resolved: https://github.com/facebook/rocksdb/pull/8994 Test Plan: Ran `make check` and tested using `db_bench` and the stress/crash tests. Reviewed By: riversand963 Differential Revision: D31489850 Pulled By: ltamasi fbshipit-source-id: 44057d511726a0e2a03c5d9313d7511b3f0c4eab
3 years ago
options.blob_garbage_collection_age_cutoff),
blob_garbage_collection_force_threshold(
options.blob_garbage_collection_force_threshold),
Make it possible to enable blob files starting from a certain LSM tree level (#10077) Summary: Currently, if blob files are enabled (i.e. `enable_blob_files` is true), large values are extracted both during flush/recovery (when SST files are written into level 0 of the LSM tree) and during compaction into any LSM tree level. For certain use cases that have a mix of short-lived and long-lived values, it might make sense to support extracting large values only during compactions whose output level is greater than or equal to a specified LSM tree level (e.g. compactions into L1/L2/... or above). This could reduce the space amplification caused by large values that are turned into garbage shortly after being written at the price of some write amplification incurred by long-lived values whose extraction to blob files is delayed. In order to achieve this, we would like to do the following: - Add a new configuration option `blob_file_starting_level` (default: 0) to `AdvancedColumnFamilyOptions` (and `MutableCFOptions` and extend the related logic) - Instantiate `BlobFileBuilder` in `BuildTable` (used during flush and recovery, where the LSM tree level is L0) and `CompactionJob` iff `enable_blob_files` is set and the LSM tree level is `>= blob_file_starting_level` - Add unit tests for the new functionality, and add the new option to our stress tests (`db_stress` and `db_crashtest.py` ) - Add the new option to our benchmarking tool `db_bench` and the BlobDB benchmark script `run_blob_bench.sh` - Add the new option to the `ldb` tool (see https://github.com/facebook/rocksdb/wiki/Administration-and-Data-Access-Tool) - Ideally extend the C and Java bindings with the new option - Update the BlobDB wiki to document the new option. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10077 Reviewed By: ltamasi Differential Revision: D36884156 Pulled By: gangliao fbshipit-source-id: 942bab025f04633edca8564ed64791cb5e31627d
3 years ago
blob_compaction_readahead_size(options.blob_compaction_readahead_size),
blob_file_starting_level(options.blob_file_starting_level),
blob_cache(options.blob_cache) {
assert(memtable_factory.get() != nullptr);
if (max_bytes_for_level_multiplier_additional.size() <
static_cast<unsigned int>(num_levels)) {
max_bytes_for_level_multiplier_additional.resize(num_levels, 1);
}
}
ColumnFamilyOptions::ColumnFamilyOptions()
: compression(Snappy_Supported() ? kSnappyCompression : kNoCompression),
table_factory(
std::shared_ptr<TableFactory>(new BlockBasedTableFactory())) {}
ColumnFamilyOptions::ColumnFamilyOptions(const Options& options)
: ColumnFamilyOptions(*static_cast<const ColumnFamilyOptions*>(&options)) {}
DBOptions::DBOptions() {}
DBOptions::DBOptions(const Options& options)
: DBOptions(*static_cast<const DBOptions*>(&options)) {}
void DBOptions::Dump(Logger* log) const {
ImmutableDBOptions(*this).Dump(log);
MutableDBOptions(*this).Dump(log);
} // DBOptions::Dump
void ColumnFamilyOptions::Dump(Logger* log) const {
ROCKS_LOG_HEADER(log, " Options.comparator: %s",
comparator->Name());
ROCKS_LOG_HEADER(log, " Options.merge_operator: %s",
merge_operator ? merge_operator->Name() : "None");
ROCKS_LOG_HEADER(log, " Options.compaction_filter: %s",
compaction_filter ? compaction_filter->Name() : "None");
ROCKS_LOG_HEADER(
log, " Options.compaction_filter_factory: %s",
compaction_filter_factory ? compaction_filter_factory->Name() : "None");
ROCKS_LOG_HEADER(
log, " Options.sst_partitioner_factory: %s",
sst_partitioner_factory ? sst_partitioner_factory->Name() : "None");
ROCKS_LOG_HEADER(log, " Options.memtable_factory: %s",
memtable_factory->Name());
ROCKS_LOG_HEADER(log, " Options.table_factory: %s",
table_factory->Name());
ROCKS_LOG_HEADER(log, " table_factory options: %s",
table_factory->GetPrintableOptions().c_str());
ROCKS_LOG_HEADER(log, " Options.write_buffer_size: %" ROCKSDB_PRIszt,
write_buffer_size);
ROCKS_LOG_HEADER(log, " Options.max_write_buffer_number: %d",
max_write_buffer_number);
if (!compression_per_level.empty()) {
for (unsigned int i = 0; i < compression_per_level.size(); i++) {
ROCKS_LOG_HEADER(
log, " Options.compression[%d]: %s", i,
CompressionTypeToString(compression_per_level[i]).c_str());
}
Allow having different compression algorithms on different levels. Summary: The leveldb API is enhanced to support different compression algorithms at different levels. This adds the option min_level_to_compress to db_bench that specifies the minimum level for which compression should be done when compression is enabled. This can be used to disable compression for levels 0 and 1 which are likely to suffer from stalls because of the CPU load for memtable flushes and (L0,L1) compaction. Level 0 is special as it gets frequent memtable flushes. Level 1 is special as it frequently gets all:all file compactions between it and level 0. But all other levels could be the same. For any level N where N > 1, the rate of sequential IO for that level should be the same. The last level is the exception because it might not be full and because files from it are not read to compact with the next larger level. The same amount of time will be spent doing compaction at any level N excluding N=0, 1 or the last level. By this standard all of those levels should use the same compression. The difference is that the loss (using more disk space) from a faster compression algorithm is less significant for N=2 than for N=3. So we might be willing to trade disk space for faster write rates with no compression for L0 and L1, snappy for L2, zlib for L3. Using a faster compression algorithm for the mid levels also allows us to reclaim some cpu without trading off much loss in disk space overhead. Also note that little is to be gained by compressing levels 0 and 1. For a 4-level tree they account for 10% of the data. For a 5-level tree they account for 1% of the data. With compression enabled: * memtable flush rate is ~18MB/second * (L0,L1) compaction rate is ~30MB/second With compression enabled but min_level_to_compress=2 * memtable flush rate is ~320MB/second * (L0,L1) compaction rate is ~560MB/second This practicaly takes the same code from https://reviews.facebook.net/D6225 but makes the leveldb api more general purpose with a few additional lines of code. Test Plan: make check Differential Revision: https://reviews.facebook.net/D6261
12 years ago
} else {
ROCKS_LOG_HEADER(log, " Options.compression: %s",
CompressionTypeToString(compression).c_str());
Allow having different compression algorithms on different levels. Summary: The leveldb API is enhanced to support different compression algorithms at different levels. This adds the option min_level_to_compress to db_bench that specifies the minimum level for which compression should be done when compression is enabled. This can be used to disable compression for levels 0 and 1 which are likely to suffer from stalls because of the CPU load for memtable flushes and (L0,L1) compaction. Level 0 is special as it gets frequent memtable flushes. Level 1 is special as it frequently gets all:all file compactions between it and level 0. But all other levels could be the same. For any level N where N > 1, the rate of sequential IO for that level should be the same. The last level is the exception because it might not be full and because files from it are not read to compact with the next larger level. The same amount of time will be spent doing compaction at any level N excluding N=0, 1 or the last level. By this standard all of those levels should use the same compression. The difference is that the loss (using more disk space) from a faster compression algorithm is less significant for N=2 than for N=3. So we might be willing to trade disk space for faster write rates with no compression for L0 and L1, snappy for L2, zlib for L3. Using a faster compression algorithm for the mid levels also allows us to reclaim some cpu without trading off much loss in disk space overhead. Also note that little is to be gained by compressing levels 0 and 1. For a 4-level tree they account for 10% of the data. For a 5-level tree they account for 1% of the data. With compression enabled: * memtable flush rate is ~18MB/second * (L0,L1) compaction rate is ~30MB/second With compression enabled but min_level_to_compress=2 * memtable flush rate is ~320MB/second * (L0,L1) compaction rate is ~560MB/second This practicaly takes the same code from https://reviews.facebook.net/D6225 but makes the leveldb api more general purpose with a few additional lines of code. Test Plan: make check Differential Revision: https://reviews.facebook.net/D6261
12 years ago
}
ROCKS_LOG_HEADER(
log, " Options.bottommost_compression: %s",
bottommost_compression == kDisableCompressionOption
? "Disabled"
: CompressionTypeToString(bottommost_compression).c_str());
ROCKS_LOG_HEADER(
log, " Options.prefix_extractor: %s",
prefix_extractor == nullptr ? "nullptr" : prefix_extractor->Name());
ROCKS_LOG_HEADER(log,
" Options.memtable_insert_with_hint_prefix_extractor: %s",
memtable_insert_with_hint_prefix_extractor == nullptr
? "nullptr"
: memtable_insert_with_hint_prefix_extractor->Name());
ROCKS_LOG_HEADER(log, " Options.num_levels: %d", num_levels);
ROCKS_LOG_HEADER(log, " Options.min_write_buffer_number_to_merge: %d",
min_write_buffer_number_to_merge);
ROCKS_LOG_HEADER(log, " Options.max_write_buffer_number_to_maintain: %d",
max_write_buffer_number_to_maintain);
Refactor trimming logic for immutable memtables (#5022) Summary: MyRocks currently sets `max_write_buffer_number_to_maintain` in order to maintain enough history for transaction conflict checking. The effectiveness of this approach depends on the size of memtables. When memtables are small, it may not keep enough history; when memtables are large, this may consume too much memory. We are proposing a new way to configure memtable list history: by limiting the memory usage of immutable memtables. The new option is `max_write_buffer_size_to_maintain` and it will take precedence over the old `max_write_buffer_number_to_maintain` if they are both set to non-zero values. The new option accounts for the total memory usage of flushed immutable memtables and mutable memtable. When the total usage exceeds the limit, RocksDB may start dropping immutable memtables (which is also called trimming history), starting from the oldest one. The semantics of the old option actually works both as an upper bound and lower bound. History trimming will start if number of immutable memtables exceeds the limit, but it will never go below (limit-1) due to history trimming. In order the mimic the behavior with the new option, history trimming will stop if dropping the next immutable memtable causes the total memory usage go below the size limit. For example, assuming the size limit is set to 64MB, and there are 3 immutable memtables with sizes of 20, 30, 30. Although the total memory usage is 80MB > 64MB, dropping the oldest memtable will reduce the memory usage to 60MB < 64MB, so in this case no memtable will be dropped. Pull Request resolved: https://github.com/facebook/rocksdb/pull/5022 Differential Revision: D14394062 Pulled By: miasantreble fbshipit-source-id: 60457a509c6af89d0993f988c9b5c2aa9e45f5c5
5 years ago
ROCKS_LOG_HEADER(log,
" Options.max_write_buffer_size_to_maintain: %" PRIu64,
max_write_buffer_size_to_maintain);
ROCKS_LOG_HEADER(
log, " Options.bottommost_compression_opts.window_bits: %d",
bottommost_compression_opts.window_bits);
ROCKS_LOG_HEADER(
log, " Options.bottommost_compression_opts.level: %d",
bottommost_compression_opts.level);
ROCKS_LOG_HEADER(
log, " Options.bottommost_compression_opts.strategy: %d",
bottommost_compression_opts.strategy);
ROCKS_LOG_HEADER(
log,
" Options.bottommost_compression_opts.max_dict_bytes: "
"%" PRIu32,
bottommost_compression_opts.max_dict_bytes);
ROCKS_LOG_HEADER(
log,
" Options.bottommost_compression_opts.zstd_max_train_bytes: "
"%" PRIu32,
bottommost_compression_opts.zstd_max_train_bytes);
ROCKS_LOG_HEADER(
log,
" Options.bottommost_compression_opts.parallel_threads: "
"%" PRIu32,
bottommost_compression_opts.parallel_threads);
ROCKS_LOG_HEADER(
log, " Options.bottommost_compression_opts.enabled: %s",
bottommost_compression_opts.enabled ? "true" : "false");
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
ROCKS_LOG_HEADER(
log,
" Options.bottommost_compression_opts.max_dict_buffer_bytes: "
"%" PRIu64,
bottommost_compression_opts.max_dict_buffer_bytes);
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
ROCKS_LOG_HEADER(
log,
" Options.bottommost_compression_opts.use_zstd_dict_trainer: %s",
bottommost_compression_opts.use_zstd_dict_trainer ? "true" : "false");
ROCKS_LOG_HEADER(log, " Options.compression_opts.window_bits: %d",
compression_opts.window_bits);
ROCKS_LOG_HEADER(log, " Options.compression_opts.level: %d",
compression_opts.level);
ROCKS_LOG_HEADER(log, " Options.compression_opts.strategy: %d",
compression_opts.strategy);
ROCKS_LOG_HEADER(
log,
" Options.compression_opts.max_dict_bytes: %" PRIu32,
compression_opts.max_dict_bytes);
ROCKS_LOG_HEADER(log,
" Options.compression_opts.zstd_max_train_bytes: "
"%" PRIu32,
compression_opts.zstd_max_train_bytes);
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
ROCKS_LOG_HEADER(
log, " Options.compression_opts.use_zstd_dict_trainer: %s",
compression_opts.use_zstd_dict_trainer ? "true" : "false");
ROCKS_LOG_HEADER(log,
" Options.compression_opts.parallel_threads: "
"%" PRIu32,
compression_opts.parallel_threads);
ROCKS_LOG_HEADER(log,
" Options.compression_opts.enabled: %s",
compression_opts.enabled ? "true" : "false");
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
ROCKS_LOG_HEADER(log,
" Options.compression_opts.max_dict_buffer_bytes: "
"%" PRIu64,
compression_opts.max_dict_buffer_bytes);
ROCKS_LOG_HEADER(log, " Options.level0_file_num_compaction_trigger: %d",
level0_file_num_compaction_trigger);
ROCKS_LOG_HEADER(log, " Options.level0_slowdown_writes_trigger: %d",
level0_slowdown_writes_trigger);
ROCKS_LOG_HEADER(log, " Options.level0_stop_writes_trigger: %d",
level0_stop_writes_trigger);
ROCKS_LOG_HEADER(
log, " Options.target_file_size_base: %" PRIu64,
target_file_size_base);
ROCKS_LOG_HEADER(log, " Options.target_file_size_multiplier: %d",
target_file_size_multiplier);
ROCKS_LOG_HEADER(
log, " Options.max_bytes_for_level_base: %" PRIu64,
max_bytes_for_level_base);
ROCKS_LOG_HEADER(log, "Options.level_compaction_dynamic_level_bytes: %d",
level_compaction_dynamic_level_bytes);
ROCKS_LOG_HEADER(log, " Options.max_bytes_for_level_multiplier: %f",
max_bytes_for_level_multiplier);
for (size_t i = 0; i < max_bytes_for_level_multiplier_additional.size();
i++) {
ROCKS_LOG_HEADER(
log, "Options.max_bytes_for_level_multiplier_addtl[%" ROCKSDB_PRIszt
"]: %d",
i, max_bytes_for_level_multiplier_additional[i]);
}
ROCKS_LOG_HEADER(
log, " Options.max_sequential_skip_in_iterations: %" PRIu64,
max_sequential_skip_in_iterations);
ROCKS_LOG_HEADER(
log, " Options.max_compaction_bytes: %" PRIu64,
max_compaction_bytes);
ROCKS_LOG_HEADER(
log,
" Options.arena_block_size: %" ROCKSDB_PRIszt,
arena_block_size);
ROCKS_LOG_HEADER(log,
" Options.soft_pending_compaction_bytes_limit: %" PRIu64,
soft_pending_compaction_bytes_limit);
ROCKS_LOG_HEADER(log,
" Options.hard_pending_compaction_bytes_limit: %" PRIu64,
hard_pending_compaction_bytes_limit);
ROCKS_LOG_HEADER(log, " Options.disable_auto_compactions: %d",
disable_auto_compactions);
const auto& it_compaction_style =
compaction_style_to_string.find(compaction_style);
std::string str_compaction_style;
if (it_compaction_style == compaction_style_to_string.end()) {
assert(false);
str_compaction_style = "unknown_" + std::to_string(compaction_style);
} else {
str_compaction_style = it_compaction_style->second;
}
ROCKS_LOG_HEADER(log,
" Options.compaction_style: %s",
str_compaction_style.c_str());
const auto& it_compaction_pri =
compaction_pri_to_string.find(compaction_pri);
std::string str_compaction_pri;
if (it_compaction_pri == compaction_pri_to_string.end()) {
assert(false);
str_compaction_pri = "unknown_" + std::to_string(compaction_pri);
} else {
str_compaction_pri = it_compaction_pri->second;
}
ROCKS_LOG_HEADER(log,
" Options.compaction_pri: %s",
str_compaction_pri.c_str());
ROCKS_LOG_HEADER(log,
"Options.compaction_options_universal.size_ratio: %u",
compaction_options_universal.size_ratio);
ROCKS_LOG_HEADER(log,
"Options.compaction_options_universal.min_merge_width: %u",
compaction_options_universal.min_merge_width);
ROCKS_LOG_HEADER(log,
"Options.compaction_options_universal.max_merge_width: %u",
compaction_options_universal.max_merge_width);
ROCKS_LOG_HEADER(
log,
"Options.compaction_options_universal."
"max_size_amplification_percent: %u",
compaction_options_universal.max_size_amplification_percent);
ROCKS_LOG_HEADER(
log,
"Options.compaction_options_universal.compression_size_percent: %d",
compaction_options_universal.compression_size_percent);
const auto& it_compaction_stop_style = compaction_stop_style_to_string.find(
compaction_options_universal.stop_style);
std::string str_compaction_stop_style;
if (it_compaction_stop_style == compaction_stop_style_to_string.end()) {
assert(false);
str_compaction_stop_style =
"unknown_" + std::to_string(compaction_options_universal.stop_style);
} else {
str_compaction_stop_style = it_compaction_stop_style->second;
}
ROCKS_LOG_HEADER(log,
"Options.compaction_options_universal.stop_style: %s",
str_compaction_stop_style.c_str());
ROCKS_LOG_HEADER(
log, "Options.compaction_options_fifo.max_table_files_size: %" PRIu64,
compaction_options_fifo.max_table_files_size);
ROCKS_LOG_HEADER(log,
"Options.compaction_options_fifo.allow_compaction: %d",
compaction_options_fifo.allow_compaction);
std::ostringstream collector_info;
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
for (const auto& collector_factory : table_properties_collector_factories) {
collector_info << collector_factory->ToString() << ';';
}
ROCKS_LOG_HEADER(
log, " Options.table_properties_collectors: %s",
collector_info.str().c_str());
ROCKS_LOG_HEADER(log,
" Options.inplace_update_support: %d",
inplace_update_support);
ROCKS_LOG_HEADER(
log,
" Options.inplace_update_num_locks: %" ROCKSDB_PRIszt,
inplace_update_num_locks);
// TODO: easier config for bloom (maybe based on avg key/value size)
ROCKS_LOG_HEADER(
log, " Options.memtable_prefix_bloom_size_ratio: %f",
memtable_prefix_bloom_size_ratio);
ROCKS_LOG_HEADER(log,
" Options.memtable_whole_key_filtering: %d",
memtable_whole_key_filtering);
ROCKS_LOG_HEADER(log, " Options.memtable_huge_page_size: %" ROCKSDB_PRIszt,
memtable_huge_page_size);
ROCKS_LOG_HEADER(log,
" Options.bloom_locality: %d",
bloom_locality);
ROCKS_LOG_HEADER(
log,
" Options.max_successive_merges: %" ROCKSDB_PRIszt,
max_successive_merges);
ROCKS_LOG_HEADER(log,
" Options.optimize_filters_for_hits: %d",
optimize_filters_for_hits);
ROCKS_LOG_HEADER(log, " Options.paranoid_file_checks: %d",
paranoid_file_checks);
ROCKS_LOG_HEADER(log, " Options.force_consistency_checks: %d",
force_consistency_checks);
ROCKS_LOG_HEADER(log, " Options.report_bg_io_stats: %d",
report_bg_io_stats);
ROCKS_LOG_HEADER(log, " Options.ttl: %" PRIu64,
ttl);
Periodic Compactions (#5166) Summary: Introducing Periodic Compactions. This feature allows all the files in a CF to be periodically compacted. It could help in catching any corruptions that could creep into the DB proactively as every file is constantly getting re-compacted. And also, of course, it helps to cleanup data older than certain threshold. - Introduced a new option `periodic_compaction_time` to control how long a file can live without being compacted in a CF. - This works across all levels. - The files are put in the same level after going through the compaction. (Related files in the same level are picked up as `ExpandInputstoCleanCut` is used). - Compaction filters, if any, are invoked as usual. - A new table property, `file_creation_time`, is introduced to implement this feature. This property is set to the time at which the SST file was created (and that time is given by the underlying Env/OS). This feature can be enabled on its own, or in conjunction with `ttl`. It is possible to set a different time threshold for the bottom level when used in conjunction with ttl. Since `ttl` works only on 0 to last but one levels, you could set `ttl` to, say, 1 day, and `periodic_compaction_time` to, say, 7 days. Since `ttl < periodic_compaction_time` all files in last but one levels keep getting picked up based on ttl, and almost never based on periodic_compaction_time. The files in the bottom level get picked up for compaction based on `periodic_compaction_time`. Pull Request resolved: https://github.com/facebook/rocksdb/pull/5166 Differential Revision: D14884441 Pulled By: sagar0 fbshipit-source-id: 408426cbacb409c06386a98632dcf90bfa1bda47
6 years ago
ROCKS_LOG_HEADER(log,
" Options.periodic_compaction_seconds: %" PRIu64,
periodic_compaction_seconds);
Make it possible to force the garbage collection of the oldest blob files (#8994) Summary: The current BlobDB garbage collection logic works by relocating the valid blobs from the oldest blob files as they are encountered during compaction, and cleaning up blob files once they contain nothing but garbage. However, with sufficiently skewed workloads, it is theoretically possible to end up in a situation when few or no compactions get scheduled for the SST files that contain references to the oldest blob files, which can lead to increased space amp due to the lack of GC. In order to efficiently handle such workloads, the patch adds a new BlobDB configuration option called `blob_garbage_collection_force_threshold`, which signals to BlobDB to schedule targeted compactions for the SST files that keep alive the oldest batch of blob files if the overall ratio of garbage in the given blob files meets the threshold *and* all the given blob files are eligible for GC based on `blob_garbage_collection_age_cutoff`. (For example, if the new option is set to 0.9, targeted compactions will get scheduled if the sum of garbage bytes meets or exceeds 90% of the sum of total bytes in the oldest blob files, assuming all affected blob files are below the age-based cutoff.) The net result of these targeted compactions is that the valid blobs in the oldest blob files are relocated and the oldest blob files themselves cleaned up (since *all* SST files that rely on them get compacted away). These targeted compactions are similar to periodic compactions in the sense that they force certain SST files that otherwise would not get picked up to undergo compaction and also in the sense that instead of merging files from multiple levels, they target a single file. (Note: such compactions might still include neighboring files from the same level due to the need of having a "clean cut" boundary but they never include any files from any other level.) This functionality is currently only supported with the leveled compaction style and is inactive by default (since the default value is set to 1.0, i.e. 100%). Pull Request resolved: https://github.com/facebook/rocksdb/pull/8994 Test Plan: Ran `make check` and tested using `db_bench` and the stress/crash tests. Reviewed By: riversand963 Differential Revision: D31489850 Pulled By: ltamasi fbshipit-source-id: 44057d511726a0e2a03c5d9313d7511b3f0c4eab
3 years ago
ROCKS_LOG_HEADER(log, " Options.enable_blob_files: %s",
enable_blob_files ? "true" : "false");
Make it possible to force the garbage collection of the oldest blob files (#8994) Summary: The current BlobDB garbage collection logic works by relocating the valid blobs from the oldest blob files as they are encountered during compaction, and cleaning up blob files once they contain nothing but garbage. However, with sufficiently skewed workloads, it is theoretically possible to end up in a situation when few or no compactions get scheduled for the SST files that contain references to the oldest blob files, which can lead to increased space amp due to the lack of GC. In order to efficiently handle such workloads, the patch adds a new BlobDB configuration option called `blob_garbage_collection_force_threshold`, which signals to BlobDB to schedule targeted compactions for the SST files that keep alive the oldest batch of blob files if the overall ratio of garbage in the given blob files meets the threshold *and* all the given blob files are eligible for GC based on `blob_garbage_collection_age_cutoff`. (For example, if the new option is set to 0.9, targeted compactions will get scheduled if the sum of garbage bytes meets or exceeds 90% of the sum of total bytes in the oldest blob files, assuming all affected blob files are below the age-based cutoff.) The net result of these targeted compactions is that the valid blobs in the oldest blob files are relocated and the oldest blob files themselves cleaned up (since *all* SST files that rely on them get compacted away). These targeted compactions are similar to periodic compactions in the sense that they force certain SST files that otherwise would not get picked up to undergo compaction and also in the sense that instead of merging files from multiple levels, they target a single file. (Note: such compactions might still include neighboring files from the same level due to the need of having a "clean cut" boundary but they never include any files from any other level.) This functionality is currently only supported with the leveled compaction style and is inactive by default (since the default value is set to 1.0, i.e. 100%). Pull Request resolved: https://github.com/facebook/rocksdb/pull/8994 Test Plan: Ran `make check` and tested using `db_bench` and the stress/crash tests. Reviewed By: riversand963 Differential Revision: D31489850 Pulled By: ltamasi fbshipit-source-id: 44057d511726a0e2a03c5d9313d7511b3f0c4eab
3 years ago
ROCKS_LOG_HEADER(
log, " Options.min_blob_size: %" PRIu64,
min_blob_size);
ROCKS_LOG_HEADER(
log, " Options.blob_file_size: %" PRIu64,
blob_file_size);
ROCKS_LOG_HEADER(log, " Options.blob_compression_type: %s",
CompressionTypeToString(blob_compression_type).c_str());
Make it possible to force the garbage collection of the oldest blob files (#8994) Summary: The current BlobDB garbage collection logic works by relocating the valid blobs from the oldest blob files as they are encountered during compaction, and cleaning up blob files once they contain nothing but garbage. However, with sufficiently skewed workloads, it is theoretically possible to end up in a situation when few or no compactions get scheduled for the SST files that contain references to the oldest blob files, which can lead to increased space amp due to the lack of GC. In order to efficiently handle such workloads, the patch adds a new BlobDB configuration option called `blob_garbage_collection_force_threshold`, which signals to BlobDB to schedule targeted compactions for the SST files that keep alive the oldest batch of blob files if the overall ratio of garbage in the given blob files meets the threshold *and* all the given blob files are eligible for GC based on `blob_garbage_collection_age_cutoff`. (For example, if the new option is set to 0.9, targeted compactions will get scheduled if the sum of garbage bytes meets or exceeds 90% of the sum of total bytes in the oldest blob files, assuming all affected blob files are below the age-based cutoff.) The net result of these targeted compactions is that the valid blobs in the oldest blob files are relocated and the oldest blob files themselves cleaned up (since *all* SST files that rely on them get compacted away). These targeted compactions are similar to periodic compactions in the sense that they force certain SST files that otherwise would not get picked up to undergo compaction and also in the sense that instead of merging files from multiple levels, they target a single file. (Note: such compactions might still include neighboring files from the same level due to the need of having a "clean cut" boundary but they never include any files from any other level.) This functionality is currently only supported with the leveled compaction style and is inactive by default (since the default value is set to 1.0, i.e. 100%). Pull Request resolved: https://github.com/facebook/rocksdb/pull/8994 Test Plan: Ran `make check` and tested using `db_bench` and the stress/crash tests. Reviewed By: riversand963 Differential Revision: D31489850 Pulled By: ltamasi fbshipit-source-id: 44057d511726a0e2a03c5d9313d7511b3f0c4eab
3 years ago
ROCKS_LOG_HEADER(log, " Options.enable_blob_garbage_collection: %s",
enable_blob_garbage_collection ? "true" : "false");
Make it possible to force the garbage collection of the oldest blob files (#8994) Summary: The current BlobDB garbage collection logic works by relocating the valid blobs from the oldest blob files as they are encountered during compaction, and cleaning up blob files once they contain nothing but garbage. However, with sufficiently skewed workloads, it is theoretically possible to end up in a situation when few or no compactions get scheduled for the SST files that contain references to the oldest blob files, which can lead to increased space amp due to the lack of GC. In order to efficiently handle such workloads, the patch adds a new BlobDB configuration option called `blob_garbage_collection_force_threshold`, which signals to BlobDB to schedule targeted compactions for the SST files that keep alive the oldest batch of blob files if the overall ratio of garbage in the given blob files meets the threshold *and* all the given blob files are eligible for GC based on `blob_garbage_collection_age_cutoff`. (For example, if the new option is set to 0.9, targeted compactions will get scheduled if the sum of garbage bytes meets or exceeds 90% of the sum of total bytes in the oldest blob files, assuming all affected blob files are below the age-based cutoff.) The net result of these targeted compactions is that the valid blobs in the oldest blob files are relocated and the oldest blob files themselves cleaned up (since *all* SST files that rely on them get compacted away). These targeted compactions are similar to periodic compactions in the sense that they force certain SST files that otherwise would not get picked up to undergo compaction and also in the sense that instead of merging files from multiple levels, they target a single file. (Note: such compactions might still include neighboring files from the same level due to the need of having a "clean cut" boundary but they never include any files from any other level.) This functionality is currently only supported with the leveled compaction style and is inactive by default (since the default value is set to 1.0, i.e. 100%). Pull Request resolved: https://github.com/facebook/rocksdb/pull/8994 Test Plan: Ran `make check` and tested using `db_bench` and the stress/crash tests. Reviewed By: riversand963 Differential Revision: D31489850 Pulled By: ltamasi fbshipit-source-id: 44057d511726a0e2a03c5d9313d7511b3f0c4eab
3 years ago
ROCKS_LOG_HEADER(log, " Options.blob_garbage_collection_age_cutoff: %f",
blob_garbage_collection_age_cutoff);
Make it possible to force the garbage collection of the oldest blob files (#8994) Summary: The current BlobDB garbage collection logic works by relocating the valid blobs from the oldest blob files as they are encountered during compaction, and cleaning up blob files once they contain nothing but garbage. However, with sufficiently skewed workloads, it is theoretically possible to end up in a situation when few or no compactions get scheduled for the SST files that contain references to the oldest blob files, which can lead to increased space amp due to the lack of GC. In order to efficiently handle such workloads, the patch adds a new BlobDB configuration option called `blob_garbage_collection_force_threshold`, which signals to BlobDB to schedule targeted compactions for the SST files that keep alive the oldest batch of blob files if the overall ratio of garbage in the given blob files meets the threshold *and* all the given blob files are eligible for GC based on `blob_garbage_collection_age_cutoff`. (For example, if the new option is set to 0.9, targeted compactions will get scheduled if the sum of garbage bytes meets or exceeds 90% of the sum of total bytes in the oldest blob files, assuming all affected blob files are below the age-based cutoff.) The net result of these targeted compactions is that the valid blobs in the oldest blob files are relocated and the oldest blob files themselves cleaned up (since *all* SST files that rely on them get compacted away). These targeted compactions are similar to periodic compactions in the sense that they force certain SST files that otherwise would not get picked up to undergo compaction and also in the sense that instead of merging files from multiple levels, they target a single file. (Note: such compactions might still include neighboring files from the same level due to the need of having a "clean cut" boundary but they never include any files from any other level.) This functionality is currently only supported with the leveled compaction style and is inactive by default (since the default value is set to 1.0, i.e. 100%). Pull Request resolved: https://github.com/facebook/rocksdb/pull/8994 Test Plan: Ran `make check` and tested using `db_bench` and the stress/crash tests. Reviewed By: riversand963 Differential Revision: D31489850 Pulled By: ltamasi fbshipit-source-id: 44057d511726a0e2a03c5d9313d7511b3f0c4eab
3 years ago
ROCKS_LOG_HEADER(log, "Options.blob_garbage_collection_force_threshold: %f",
blob_garbage_collection_force_threshold);
ROCKS_LOG_HEADER(
log, " Options.blob_compaction_readahead_size: %" PRIu64,
blob_compaction_readahead_size);
Make it possible to enable blob files starting from a certain LSM tree level (#10077) Summary: Currently, if blob files are enabled (i.e. `enable_blob_files` is true), large values are extracted both during flush/recovery (when SST files are written into level 0 of the LSM tree) and during compaction into any LSM tree level. For certain use cases that have a mix of short-lived and long-lived values, it might make sense to support extracting large values only during compactions whose output level is greater than or equal to a specified LSM tree level (e.g. compactions into L1/L2/... or above). This could reduce the space amplification caused by large values that are turned into garbage shortly after being written at the price of some write amplification incurred by long-lived values whose extraction to blob files is delayed. In order to achieve this, we would like to do the following: - Add a new configuration option `blob_file_starting_level` (default: 0) to `AdvancedColumnFamilyOptions` (and `MutableCFOptions` and extend the related logic) - Instantiate `BlobFileBuilder` in `BuildTable` (used during flush and recovery, where the LSM tree level is L0) and `CompactionJob` iff `enable_blob_files` is set and the LSM tree level is `>= blob_file_starting_level` - Add unit tests for the new functionality, and add the new option to our stress tests (`db_stress` and `db_crashtest.py` ) - Add the new option to our benchmarking tool `db_bench` and the BlobDB benchmark script `run_blob_bench.sh` - Add the new option to the `ldb` tool (see https://github.com/facebook/rocksdb/wiki/Administration-and-Data-Access-Tool) - Ideally extend the C and Java bindings with the new option - Update the BlobDB wiki to document the new option. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10077 Reviewed By: ltamasi Differential Revision: D36884156 Pulled By: gangliao fbshipit-source-id: 942bab025f04633edca8564ed64791cb5e31627d
3 years ago
ROCKS_LOG_HEADER(log, " Options.blob_file_starting_level: %d",
blob_file_starting_level);
if (blob_cache) {
ROCKS_LOG_HEADER(log, " Options.blob_cache: %s",
blob_cache->Name());
ROCKS_LOG_HEADER(log, " blob_cache options: %s",
blob_cache->GetPrintableOptions().c_str());
}
Dynamically changeable `MemPurge` option (#10011) Summary: **Summary** Make the mempurge option flag a Mutable Column Family option flag. Therefore, the mempurge feature can be dynamically toggled. **Motivation** RocksDB users prefer having the ability to switch features on and off without having to close and reopen the DB. This is particularly important if the feature causes issues and needs to be turned off. Dynamically changing a DB option flag does not seem currently possible. Moreover, with this new change, the MemPurge feature can be toggled on or off independently between column families, which we see as a major improvement. **Content of this PR** This PR includes removal of the `experimental_mempurge_threshold` flag as a DB option flag, and its re-introduction as a `MutableCFOption` flag. I updated the code to handle dynamic changes of the flag (in particular inside the `FlushJob` file). Additionally, this PR includes a new test to demonstrate the capacity of the code to toggle the MemPurge feature on and off, as well as the addition in the `db_stress` module of 2 different mempurge threshold values (0.0 and 1.0) that can be randomly changed with the `set_option_one_in` flag. This is useful to stress test the dynamic changes. **Benchmarking** I will add numbers to prove that there is no performance impact within the next 12 hours. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10011 Reviewed By: pdillinger Differential Revision: D36462357 Pulled By: bjlemaire fbshipit-source-id: 5e3d63bdadf085c0572ecc2349e7dd9729ce1802
3 years ago
ROCKS_LOG_HEADER(log, "Options.experimental_mempurge_threshold: %f",
experimental_mempurge_threshold);
} // ColumnFamilyOptions::Dump
void Options::Dump(Logger* log) const {
DBOptions::Dump(log);
ColumnFamilyOptions::Dump(log);
Dynamically changeable `MemPurge` option (#10011) Summary: **Summary** Make the mempurge option flag a Mutable Column Family option flag. Therefore, the mempurge feature can be dynamically toggled. **Motivation** RocksDB users prefer having the ability to switch features on and off without having to close and reopen the DB. This is particularly important if the feature causes issues and needs to be turned off. Dynamically changing a DB option flag does not seem currently possible. Moreover, with this new change, the MemPurge feature can be toggled on or off independently between column families, which we see as a major improvement. **Content of this PR** This PR includes removal of the `experimental_mempurge_threshold` flag as a DB option flag, and its re-introduction as a `MutableCFOption` flag. I updated the code to handle dynamic changes of the flag (in particular inside the `FlushJob` file). Additionally, this PR includes a new test to demonstrate the capacity of the code to toggle the MemPurge feature on and off, as well as the addition in the `db_stress` module of 2 different mempurge threshold values (0.0 and 1.0) that can be randomly changed with the `set_option_one_in` flag. This is useful to stress test the dynamic changes. **Benchmarking** I will add numbers to prove that there is no performance impact within the next 12 hours. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10011 Reviewed By: pdillinger Differential Revision: D36462357 Pulled By: bjlemaire fbshipit-source-id: 5e3d63bdadf085c0572ecc2349e7dd9729ce1802
3 years ago
} // Options::Dump
void Options::DumpCFOptions(Logger* log) const {
ColumnFamilyOptions::Dump(log);
} // Options::DumpCFOptions
//
// The goal of this method is to create a configuration that
// allows an application to write all files into L0 and
// then do a single compaction to output all files into L1.
Options*
Options::PrepareForBulkLoad()
{
// never slowdown ingest.
level0_file_num_compaction_trigger = (1<<30);
level0_slowdown_writes_trigger = (1<<30);
level0_stop_writes_trigger = (1<<30);
soft_pending_compaction_bytes_limit = 0;
hard_pending_compaction_bytes_limit = 0;
// no auto compactions please. The application should issue a
// manual compaction after all data is loaded into L0.
disable_auto_compactions = true;
// A manual compaction run should pick all files in L0 in
// a single compaction run.
max_compaction_bytes = (static_cast<uint64_t>(1) << 60);
// It is better to have only 2 levels, otherwise a manual
// compaction would compact at every possible level, thereby
// increasing the total time needed for compactions.
num_levels = 2;
// Need to allow more write buffers to allow more parallism
// of flushes.
max_write_buffer_number = 6;
min_write_buffer_number_to_merge = 1;
// When compaction is disabled, more parallel flush threads can
// help with write throughput.
max_background_flushes = 4;
// Prevent a memtable flush to automatically promote files
// to L1. This is helpful so that all files that are
// input to the manual compaction are all at L0.
max_background_compactions = 2;
// The compaction would create large files in L1.
target_file_size_base = 256 * 1024 * 1024;
return this;
}
Options* Options::OptimizeForSmallDb() {
// 16MB block cache
std::shared_ptr<Cache> cache = NewLRUCache(16 << 20);
ColumnFamilyOptions::OptimizeForSmallDb(&cache);
DBOptions::OptimizeForSmallDb(&cache);
return this;
}
Options* Options::DisableExtraChecks() {
// See https://github.com/facebook/rocksdb/issues/9354
force_consistency_checks = false;
// Considered but no clear performance impact seen:
// * check_flush_compaction_key_order
// * paranoid_checks
// * flush_verify_memtable_count
// By current API contract, not including
// * verify_checksums
// because checking storage data integrity is a more standard practice.
return this;
}
Options* Options::OldDefaults(int rocksdb_major_version,
int rocksdb_minor_version) {
ColumnFamilyOptions::OldDefaults(rocksdb_major_version,
rocksdb_minor_version);
DBOptions::OldDefaults(rocksdb_major_version, rocksdb_minor_version);
return this;
}
DBOptions* DBOptions::OldDefaults(int rocksdb_major_version,
int rocksdb_minor_version) {
if (rocksdb_major_version < 4 ||
(rocksdb_major_version == 4 && rocksdb_minor_version < 7)) {
max_file_opening_threads = 1;
table_cache_numshardbits = 4;
}
if (rocksdb_major_version < 5 ||
(rocksdb_major_version == 5 && rocksdb_minor_version < 2)) {
delayed_write_rate = 2 * 1024U * 1024U;
} else if (rocksdb_major_version < 5 ||
(rocksdb_major_version == 5 && rocksdb_minor_version < 6)) {
delayed_write_rate = 16 * 1024U * 1024U;
}
max_open_files = 5000;
wal_recovery_mode = WALRecoveryMode::kTolerateCorruptedTailRecords;
return this;
}
ColumnFamilyOptions* ColumnFamilyOptions::OldDefaults(
int rocksdb_major_version, int rocksdb_minor_version) {
if (rocksdb_major_version < 5 ||
(rocksdb_major_version == 5 && rocksdb_minor_version <= 18)) {
compaction_pri = CompactionPri::kByCompensatedSize;
}
if (rocksdb_major_version < 4 ||
(rocksdb_major_version == 4 && rocksdb_minor_version < 7)) {
write_buffer_size = 4 << 20;
target_file_size_base = 2 * 1048576;
max_bytes_for_level_base = 10 * 1048576;
soft_pending_compaction_bytes_limit = 0;
hard_pending_compaction_bytes_limit = 0;
}
if (rocksdb_major_version < 5) {
level0_stop_writes_trigger = 24;
} else if (rocksdb_major_version == 5 && rocksdb_minor_version < 2) {
level0_stop_writes_trigger = 30;
}
return this;
}
// Optimization functions
DBOptions* DBOptions::OptimizeForSmallDb(std::shared_ptr<Cache>* cache) {
max_file_opening_threads = 1;
max_open_files = 5000;
// Cost memtable to block cache too.
std::shared_ptr<ROCKSDB_NAMESPACE::WriteBufferManager> wbm =
std::make_shared<ROCKSDB_NAMESPACE::WriteBufferManager>(
0, (cache != nullptr) ? *cache : std::shared_ptr<Cache>());
write_buffer_manager = wbm;
return this;
}
ColumnFamilyOptions* ColumnFamilyOptions::OptimizeForSmallDb(
std::shared_ptr<Cache>* cache) {
write_buffer_size = 2 << 20;
target_file_size_base = 2 * 1048576;
max_bytes_for_level_base = 10 * 1048576;
soft_pending_compaction_bytes_limit = 256 * 1048576;
hard_pending_compaction_bytes_limit = 1073741824ul;
BlockBasedTableOptions table_options;
table_options.block_cache =
(cache != nullptr) ? *cache : std::shared_ptr<Cache>();
table_options.cache_index_and_filter_blocks = true;
// Two level iterator to avoid LRU cache imbalance
table_options.index_type =
BlockBasedTableOptions::IndexType::kTwoLevelIndexSearch;
table_factory.reset(new BlockBasedTableFactory(table_options));
return this;
}
#ifndef ROCKSDB_LITE
ColumnFamilyOptions* ColumnFamilyOptions::OptimizeForPointLookup(
uint64_t block_cache_size_mb) {
BlockBasedTableOptions block_based_options;
block_based_options.data_block_index_type =
BlockBasedTableOptions::kDataBlockBinaryAndHash;
block_based_options.data_block_hash_table_util_ratio = 0.75;
block_based_options.filter_policy.reset(NewBloomFilterPolicy(10));
block_based_options.block_cache =
NewLRUCache(static_cast<size_t>(block_cache_size_mb * 1024 * 1024));
table_factory.reset(new BlockBasedTableFactory(block_based_options));
memtable_prefix_bloom_size_ratio = 0.02;
memtable_whole_key_filtering = true;
return this;
}
ColumnFamilyOptions* ColumnFamilyOptions::OptimizeLevelStyleCompaction(
uint64_t memtable_memory_budget) {
write_buffer_size = static_cast<size_t>(memtable_memory_budget / 4);
// merge two memtables when flushing to L0
min_write_buffer_number_to_merge = 2;
// this means we'll use 50% extra memory in the worst case, but will reduce
// write stalls.
max_write_buffer_number = 6;
// start flushing L0->L1 as soon as possible. each file on level0 is
// (memtable_memory_budget / 2). This will flush level 0 when it's bigger than
// memtable_memory_budget.
level0_file_num_compaction_trigger = 2;
// doesn't really matter much, but we don't want to create too many files
target_file_size_base = memtable_memory_budget / 8;
// make Level1 size equal to Level0 size, so that L0->L1 compactions are fast
max_bytes_for_level_base = memtable_memory_budget;
// level style compaction
compaction_style = kCompactionStyleLevel;
// only compress levels >= 2
compression_per_level.resize(num_levels);
for (int i = 0; i < num_levels; ++i) {
if (i < 2) {
compression_per_level[i] = kNoCompression;
} else {
compression_per_level[i] =
LZ4_Supported()
? kLZ4Compression
: (Snappy_Supported() ? kSnappyCompression : kNoCompression);
}
}
return this;
}
ColumnFamilyOptions* ColumnFamilyOptions::OptimizeUniversalStyleCompaction(
uint64_t memtable_memory_budget) {
write_buffer_size = static_cast<size_t>(memtable_memory_budget / 4);
// merge two memtables when flushing to L0
min_write_buffer_number_to_merge = 2;
// this means we'll use 50% extra memory in the worst case, but will reduce
// write stalls.
max_write_buffer_number = 6;
// universal style compaction
compaction_style = kCompactionStyleUniversal;
compaction_options_universal.compression_size_percent = 80;
return this;
}
DBOptions* DBOptions::IncreaseParallelism(int total_threads) {
max_background_jobs = total_threads;
env->SetBackgroundThreads(total_threads, Env::LOW);
env->SetBackgroundThreads(1, Env::HIGH);
return this;
}
#endif // !ROCKSDB_LITE
ReadOptions::ReadOptions()
: snapshot(nullptr),
iterate_lower_bound(nullptr),
iterate_upper_bound(nullptr),
readahead_size(0),
max_skippable_internal_keys(0),
read_tier(kReadAllTier),
verify_checksums(true),
fill_cache(true),
tailing(false),
managed(false),
total_order_seek(false),
auto_prefix_mode(false),
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
prefix_same_as_start(false),
pin_data(false),
background_purge_on_iterator_cleanup(false),
Added support for differential snapshots Summary: The motivation for this PR is to add to RocksDB support for differential (incremental) snapshots, as snapshot of the DB changes between two points in time (one can think of it as diff between to sequence numbers, or the diff D which can be thought of as an SST file or just set of KVs that can be applied to sequence number S1 to get the database to the state at sequence number S2). This feature would be useful for various distributed storages layers built on top of RocksDB, as it should help reduce resources (time and network bandwidth) needed to recover and rebuilt DB instances as replicas in the context of distributed storages. From the API standpoint that would like client app requesting iterator between (start seqnum) and current DB state, and reading the "diff". This is a very draft PR for initial review in the discussion on the approach, i'm going to rework some parts and keep updating the PR. For now, what's done here according to initial discussions: Preserving deletes: - We want to be able to optionally preserve recent deletes for some defined period of time, so that if a delete came in recently and might need to be included in the next incremental snapshot it would't get dropped by a compaction. This is done by adding new param to Options (preserve deletes flag) and new variable to DB Impl where we keep track of the sequence number after which we don't want to drop tombstones, even if they are otherwise eligible for deletion. - I also added a new API call for clients to be able to advance this cutoff seqnum after which we drop deletes; i assume it's more flexible to let clients control this, since otherwise we'd need to keep some kind of timestamp < -- > seqnum mapping inside the DB, which sounds messy and painful to support. Clients could make use of it by periodically calling GetLatestSequenceNumber(), noting the timestamp, doing some calculation and figuring out by how much we need to advance the cutoff seqnum. - Compaction codepath in compaction_iterator.cc has been modified to avoid dropping tombstones with seqnum > cutoff seqnum. Iterator changes: - couple params added to ReadOptions, to optionally allow client to request internal keys instead of user keys (so that client can get the latest value of a key, be it delete marker or a put), as well as min timestamp and min seqnum. TableCache changes: - I modified table_cache code to be able to quickly exclude SST files from iterators heep if creation_time on the file is less then iter_start_ts as passed in ReadOptions. That would help a lot in some DB settings (like reading very recent data only or using FIFO compactions), but not so much for universal compaction with more or less long iterator time span. What's left: - Still looking at how to best plug that inside DBIter codepath. So far it seems that FindNextUserKeyInternal only parses values as UserKeys, and iter->key() call generally returns user key. Can we add new API to DBIter as internal_key(), and modify this internal method to optionally set saved_key_ to point to the full internal key? I don't need to store actual seqnum there, but I do need to store type. Closes https://github.com/facebook/rocksdb/pull/2999 Differential Revision: D6175602 Pulled By: mikhail-antonov fbshipit-source-id: c779a6696ee2d574d86c69cec866a3ae095aa900
7 years ago
ignore_range_deletions(false),
make iterator return versions between timestamp bounds (#6544) Summary: (Based on Yanqin's idea) Add a new field in readoptions as lower timestamp bound for iterator. When the parameter is not supplied (nullptr), the iterator returns the latest visible version of a record. When it is supplied, the existing timestamp field is the upper bound. Together the two serves as a bounded time window. The iterator returns all versions of a record falling in the window. SeekRandom perf test (10 minutes) on the same development machine ram drive with the same DB data shows no regression (within marge of error). The test is adapted from https://github.com/facebook/rocksdb/wiki/RocksDB-In-Memory-Workload-Performance-Benchmarks. base line (commit e860f8840): seekrandom : 7.836 micros/op 4082449 ops/sec; (0 of 73481999 found) This PR: seekrandom : 7.764 micros/op 4120935 ops/sec; (0 of 71303999 found) db_bench --db=r:\rocksdb.github --num_levels=6 --key_size=20 --prefix_size=20 --keys_per_prefix=0 --value_size=100 --cache_size=2147483648 --cache_numshardbits=6 --compression_type=none --compression_ratio=1 --min_level_to_compress=-1 --disable_seek_compaction=1 --hard_rate_limit=2 --write_buffer_size=134217728 --max_write_buffer_number=2 --level0_file_num_compaction_trigger=8 --target_file_size_base=134217728 --max_bytes_for_level_base=1073741824 --disable_wal=0 --wal_dir=r:\rocksdb.github\WAL_LOG --sync=0 --verify_checksum=1 --statistics=0 --stats_per_interval=0 --stats_interval=1048576 --histogram=0 --use_plain_table=1 --open_files=-1 --memtablerep=prefix_hash --bloom_bits=10 --bloom_locality=1 --duration=600 --benchmarks=seekrandom --use_existing_db=1 --num=25000000 --threads=32 --allow_concurrent_memtable_write=0 Pull Request resolved: https://github.com/facebook/rocksdb/pull/6544 Reviewed By: ltamasi Differential Revision: D20844069 Pulled By: riversand963 fbshipit-source-id: d97f2bf38a323c8c6a68db213b2d3c694b1c1f74
5 years ago
timestamp(nullptr),
iter_start_ts(nullptr),
deadline(std::chrono::microseconds::zero()),
io_timeout(std::chrono::microseconds::zero()),
value_size_soft_limit(std::numeric_limits<uint64_t>::max()),
Provide implementation to prefetch data asynchronously in FilePrefetchBuffer (#9674) Summary: In FilePrefetchBuffer if reads are sequential, after prefetching call ReadAsync API to prefetch data asynchronously so that in next prefetching data will be available. Data prefetched asynchronously will be readahead_size/2. It uses two buffers, one for synchronous prefetching and one for asynchronous. In case, the data is overlapping, the data is copied from both buffers to third buffer to make it continuous. This feature is under ReadOptions::async_io and is under experimental. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9674 Test Plan: 1. Add new unit tests 2. Run **db_stress** to make sure nothing crashes. - Normal prefetch without `async_io` ran successfully: ``` export CRASH_TEST_EXT_ARGS=" --async_io=0" make crash_test -j ``` 3. **Run Regressions**. i) Main branch without any change for normal prefetching with async_io disabled: ``` ./db_bench -db=/tmp/prefix_scan_prefetch_main -benchmarks="fillseq" -key_size=32 -value_size=512 -num=5000000 - use_direct_io_for_flush_and_compaction=true -target_file_size_base=16777216 ``` ``` ./db_bench -use_existing_db=true -db=/tmp/prefix_scan_prefetch_main -benchmarks="seekrandom" -key_size=32 -value_size=512 -num=5000000 -use_direct_reads=true -seek_nexts=327680 -duration=120 -ops_between_duration_checks=1 Initializing RocksDB Options from the specified file Initializing RocksDB Options from command-line flags RocksDB: version 7.0 Date: Thu Mar 17 13:11:34 2022 CPU: 24 * Intel Core Processor (Broadwell) CPUCache: 16384 KB Keys: 32 bytes each (+ 0 bytes user-defined timestamp) Values: 512 bytes each (256 bytes after compression) Entries: 5000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 2594.0 MB (estimated) FileSize: 1373.3 MB (estimated) Write rate: 0 bytes/second Read rate: 0 ops/second Compression: Snappy Compression sampling rate: 0 Memtablerep: SkipListFactory Perf Level: 1 ------------------------------------------------ DB path: [/tmp/prefix_scan_prefetch_main] seekrandom : 483618.390 micros/op 2 ops/sec; 338.9 MB/s (249 of 249 found) ``` ii) normal prefetching after changes with async_io disable: ``` ./db_bench -use_existing_db=true -db=/tmp/prefix_scan_prefetch_withchange -benchmarks="seekrandom" -key_size=32 -value_size=512 -num=5000000 -use_direct_reads=true -seek_nexts=327680 -duration=120 -ops_between_duration_checks=1 Initializing RocksDB Options from the specified file Initializing RocksDB Options from command-line flags RocksDB: version 7.0 Date: Thu Mar 17 14:11:31 2022 CPU: 24 * Intel Core Processor (Broadwell) CPUCache: 16384 KB Keys: 32 bytes each (+ 0 bytes user-defined timestamp) Values: 512 bytes each (256 bytes after compression) Entries: 5000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 2594.0 MB (estimated) FileSize: 1373.3 MB (estimated) Write rate: 0 bytes/second Read rate: 0 ops/second Compression: Snappy Compression sampling rate: 0 Memtablerep: SkipListFactory Perf Level: 1 ------------------------------------------------ DB path: [/tmp/prefix_scan_prefetch_withchange] seekrandom : 471347.227 micros/op 2 ops/sec; 348.1 MB/s (255 of 255 found) ``` Reviewed By: anand1976 Differential Revision: D34731543 Pulled By: akankshamahajan15 fbshipit-source-id: 8e23aa93453d5fe3c672b9231ad582f60207937f
3 years ago
adaptive_readahead(false),
async_io(false) {}
ReadOptions::ReadOptions(bool cksum, bool cache)
: snapshot(nullptr),
iterate_lower_bound(nullptr),
iterate_upper_bound(nullptr),
readahead_size(0),
max_skippable_internal_keys(0),
read_tier(kReadAllTier),
verify_checksums(cksum),
fill_cache(cache),
tailing(false),
managed(false),
total_order_seek(false),
auto_prefix_mode(false),
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
prefix_same_as_start(false),
pin_data(false),
background_purge_on_iterator_cleanup(false),
Added support for differential snapshots Summary: The motivation for this PR is to add to RocksDB support for differential (incremental) snapshots, as snapshot of the DB changes between two points in time (one can think of it as diff between to sequence numbers, or the diff D which can be thought of as an SST file or just set of KVs that can be applied to sequence number S1 to get the database to the state at sequence number S2). This feature would be useful for various distributed storages layers built on top of RocksDB, as it should help reduce resources (time and network bandwidth) needed to recover and rebuilt DB instances as replicas in the context of distributed storages. From the API standpoint that would like client app requesting iterator between (start seqnum) and current DB state, and reading the "diff". This is a very draft PR for initial review in the discussion on the approach, i'm going to rework some parts and keep updating the PR. For now, what's done here according to initial discussions: Preserving deletes: - We want to be able to optionally preserve recent deletes for some defined period of time, so that if a delete came in recently and might need to be included in the next incremental snapshot it would't get dropped by a compaction. This is done by adding new param to Options (preserve deletes flag) and new variable to DB Impl where we keep track of the sequence number after which we don't want to drop tombstones, even if they are otherwise eligible for deletion. - I also added a new API call for clients to be able to advance this cutoff seqnum after which we drop deletes; i assume it's more flexible to let clients control this, since otherwise we'd need to keep some kind of timestamp < -- > seqnum mapping inside the DB, which sounds messy and painful to support. Clients could make use of it by periodically calling GetLatestSequenceNumber(), noting the timestamp, doing some calculation and figuring out by how much we need to advance the cutoff seqnum. - Compaction codepath in compaction_iterator.cc has been modified to avoid dropping tombstones with seqnum > cutoff seqnum. Iterator changes: - couple params added to ReadOptions, to optionally allow client to request internal keys instead of user keys (so that client can get the latest value of a key, be it delete marker or a put), as well as min timestamp and min seqnum. TableCache changes: - I modified table_cache code to be able to quickly exclude SST files from iterators heep if creation_time on the file is less then iter_start_ts as passed in ReadOptions. That would help a lot in some DB settings (like reading very recent data only or using FIFO compactions), but not so much for universal compaction with more or less long iterator time span. What's left: - Still looking at how to best plug that inside DBIter codepath. So far it seems that FindNextUserKeyInternal only parses values as UserKeys, and iter->key() call generally returns user key. Can we add new API to DBIter as internal_key(), and modify this internal method to optionally set saved_key_ to point to the full internal key? I don't need to store actual seqnum there, but I do need to store type. Closes https://github.com/facebook/rocksdb/pull/2999 Differential Revision: D6175602 Pulled By: mikhail-antonov fbshipit-source-id: c779a6696ee2d574d86c69cec866a3ae095aa900
7 years ago
ignore_range_deletions(false),
make iterator return versions between timestamp bounds (#6544) Summary: (Based on Yanqin's idea) Add a new field in readoptions as lower timestamp bound for iterator. When the parameter is not supplied (nullptr), the iterator returns the latest visible version of a record. When it is supplied, the existing timestamp field is the upper bound. Together the two serves as a bounded time window. The iterator returns all versions of a record falling in the window. SeekRandom perf test (10 minutes) on the same development machine ram drive with the same DB data shows no regression (within marge of error). The test is adapted from https://github.com/facebook/rocksdb/wiki/RocksDB-In-Memory-Workload-Performance-Benchmarks. base line (commit e860f8840): seekrandom : 7.836 micros/op 4082449 ops/sec; (0 of 73481999 found) This PR: seekrandom : 7.764 micros/op 4120935 ops/sec; (0 of 71303999 found) db_bench --db=r:\rocksdb.github --num_levels=6 --key_size=20 --prefix_size=20 --keys_per_prefix=0 --value_size=100 --cache_size=2147483648 --cache_numshardbits=6 --compression_type=none --compression_ratio=1 --min_level_to_compress=-1 --disable_seek_compaction=1 --hard_rate_limit=2 --write_buffer_size=134217728 --max_write_buffer_number=2 --level0_file_num_compaction_trigger=8 --target_file_size_base=134217728 --max_bytes_for_level_base=1073741824 --disable_wal=0 --wal_dir=r:\rocksdb.github\WAL_LOG --sync=0 --verify_checksum=1 --statistics=0 --stats_per_interval=0 --stats_interval=1048576 --histogram=0 --use_plain_table=1 --open_files=-1 --memtablerep=prefix_hash --bloom_bits=10 --bloom_locality=1 --duration=600 --benchmarks=seekrandom --use_existing_db=1 --num=25000000 --threads=32 --allow_concurrent_memtable_write=0 Pull Request resolved: https://github.com/facebook/rocksdb/pull/6544 Reviewed By: ltamasi Differential Revision: D20844069 Pulled By: riversand963 fbshipit-source-id: d97f2bf38a323c8c6a68db213b2d3c694b1c1f74
5 years ago
timestamp(nullptr),
iter_start_ts(nullptr),
deadline(std::chrono::microseconds::zero()),
io_timeout(std::chrono::microseconds::zero()),
value_size_soft_limit(std::numeric_limits<uint64_t>::max()),
Provide implementation to prefetch data asynchronously in FilePrefetchBuffer (#9674) Summary: In FilePrefetchBuffer if reads are sequential, after prefetching call ReadAsync API to prefetch data asynchronously so that in next prefetching data will be available. Data prefetched asynchronously will be readahead_size/2. It uses two buffers, one for synchronous prefetching and one for asynchronous. In case, the data is overlapping, the data is copied from both buffers to third buffer to make it continuous. This feature is under ReadOptions::async_io and is under experimental. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9674 Test Plan: 1. Add new unit tests 2. Run **db_stress** to make sure nothing crashes. - Normal prefetch without `async_io` ran successfully: ``` export CRASH_TEST_EXT_ARGS=" --async_io=0" make crash_test -j ``` 3. **Run Regressions**. i) Main branch without any change for normal prefetching with async_io disabled: ``` ./db_bench -db=/tmp/prefix_scan_prefetch_main -benchmarks="fillseq" -key_size=32 -value_size=512 -num=5000000 - use_direct_io_for_flush_and_compaction=true -target_file_size_base=16777216 ``` ``` ./db_bench -use_existing_db=true -db=/tmp/prefix_scan_prefetch_main -benchmarks="seekrandom" -key_size=32 -value_size=512 -num=5000000 -use_direct_reads=true -seek_nexts=327680 -duration=120 -ops_between_duration_checks=1 Initializing RocksDB Options from the specified file Initializing RocksDB Options from command-line flags RocksDB: version 7.0 Date: Thu Mar 17 13:11:34 2022 CPU: 24 * Intel Core Processor (Broadwell) CPUCache: 16384 KB Keys: 32 bytes each (+ 0 bytes user-defined timestamp) Values: 512 bytes each (256 bytes after compression) Entries: 5000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 2594.0 MB (estimated) FileSize: 1373.3 MB (estimated) Write rate: 0 bytes/second Read rate: 0 ops/second Compression: Snappy Compression sampling rate: 0 Memtablerep: SkipListFactory Perf Level: 1 ------------------------------------------------ DB path: [/tmp/prefix_scan_prefetch_main] seekrandom : 483618.390 micros/op 2 ops/sec; 338.9 MB/s (249 of 249 found) ``` ii) normal prefetching after changes with async_io disable: ``` ./db_bench -use_existing_db=true -db=/tmp/prefix_scan_prefetch_withchange -benchmarks="seekrandom" -key_size=32 -value_size=512 -num=5000000 -use_direct_reads=true -seek_nexts=327680 -duration=120 -ops_between_duration_checks=1 Initializing RocksDB Options from the specified file Initializing RocksDB Options from command-line flags RocksDB: version 7.0 Date: Thu Mar 17 14:11:31 2022 CPU: 24 * Intel Core Processor (Broadwell) CPUCache: 16384 KB Keys: 32 bytes each (+ 0 bytes user-defined timestamp) Values: 512 bytes each (256 bytes after compression) Entries: 5000000 Prefix: 0 bytes Keys per prefix: 0 RawSize: 2594.0 MB (estimated) FileSize: 1373.3 MB (estimated) Write rate: 0 bytes/second Read rate: 0 ops/second Compression: Snappy Compression sampling rate: 0 Memtablerep: SkipListFactory Perf Level: 1 ------------------------------------------------ DB path: [/tmp/prefix_scan_prefetch_withchange] seekrandom : 471347.227 micros/op 2 ops/sec; 348.1 MB/s (255 of 255 found) ``` Reviewed By: anand1976 Differential Revision: D34731543 Pulled By: akankshamahajan15 fbshipit-source-id: 8e23aa93453d5fe3c672b9231ad582f60207937f
3 years ago
adaptive_readahead(false),
async_io(false) {}
} // namespace ROCKSDB_NAMESPACE