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399 commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
Andrew Kryczka
|
40944cbbdb |
Fix folly build (#12795)
Summary: - Updated pinned folly version to the latest - gcc/g++ 10 is required since https://github.com/facebook/folly/commit/2c1c617e9e so we had to modify the tests using gcc/g++ 7 - libsodium 1.0.17 is no longer downloadable from GitHub so I found it elsewhere. I will submit a PR for that upstream to folly - USE_FOLLY_LITE changes - added boost header dependency instead of commenting out the `#include`s since that approach stopped working - added "folly/lang/Exception.cpp" to the compilation Pull Request resolved: https://github.com/facebook/rocksdb/pull/12795 Reviewed By: hx235 Differential Revision: D58916693 Pulled By: ajkr fbshipit-source-id: b5f9bca2d929825846ac898b785972b071db62b1 |
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Peter Dillinger
|
71f9e6b5b3 |
Add experimental range filters to stress/crash test (#12769)
Summary: Implemented two key segment extractors that satisfy the "segment prefix property," one with variable segment widths and one with fixed. Used these to create a couple of named configs and versions that are randomly selected by the crash test. On the read side, the required table_filter is set up everywhere I found the stress test uses iterator_upper_bound. Writing filters on new SST files and applying filters on SST files to range queries are configured independently, to potentially help with isolating different sides of the functionality. Not yet implemented / possible follow-up: * Consider manipulating/skewing the query bounds to better exercise filters * Not yet using categories in the extractors * Not yet dynamically changing the filtering version Pull Request resolved: https://github.com/facebook/rocksdb/pull/12769 Test Plan: Some stress test trial runs, including with ASAN. Inserted some temporary probes to ensure code was being exercised (more or less) as intended. Reviewed By: hx235 Differential Revision: D58547462 Pulled By: pdillinger fbshipit-source-id: f7b1596dd668426268c5293ac17615f749703f52 |
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Yu Zhang
|
c73cf7a878 |
Add CompactForTieringCollector to support automatically trigger compaction for tiering use case (#12760)
Summary: This PR adds user property collector factory `CompactForTieringCollectorFactory` to support observe SST file and mark it as need compaction for fast tracking data to the proper tier. A triggering ratio `compaction_trigger_ratio_` can be configured to achieve the following: 1) Setting the ratio to be equal to or smaller than 0 disables this collector 2) Setting the ratio to be within (0, 1] will write the number of observed eligible entries into a user property and marks a file as need-compaction when aforementioned condition is met. 3) Setting the ratio to be higher than 1 can be used to just writes the user table property, and not mark any file as need compaction. For a column family that does not enable tiering feature, even if an effective configuration is provided, this collector is still disabled. For a file that is already on the last level, this collector is also disabled. Pull Request resolved: https://github.com/facebook/rocksdb/pull/12760 Test Plan: Added unit tests Reviewed By: pdillinger Differential Revision: D58734976 Pulled By: jowlyzhang fbshipit-source-id: 6daab2c4f62b5c6689c3c03e3b3907bbbe6b7a81 |
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anand76
|
d8fb849b7e |
Basic RocksDB follower implementation (#12540)
Summary: A basic implementation of RocksDB follower mode, which opens a remote database (referred to as leader) on a distributed file system by tailing its MANIFEST. It leverages the secondary instance mode, but is different in some key ways - 1. It has its own directory with links to the leader's database 2. Periodically refreshes itself 3. (Future) Snapshot support 4. (Future) Garbage collection of obsolete links 5. (Long term) Memtable replication There are two main classes implementing this functionality - `DBImplFollower` and `OnDemandFileSystem`. The former is derived from `DBImplSecondary`. Similar to `DBImplSecondary`, it implements recovery and catch up through MANIFEST tailing using the `ReactiveVersionSet`, but does not consider logs. In a future PR, we will implement memtable replication, which will eliminate the need to catch up using logs. In addition, the recovery and catch-up tries to avoid directory listing as repeated metadata operations are expensive. The second main piece is the `OnDemandFileSystem`, which plugs in as an `Env` for the follower instance and creates the illusion of the follower directory as a clone of the leader directory. It creates links to SSTs on first reference. When the follower tails the MANIFEST and attempts to create a new `Version`, it calls `VerifyFileMetadata` to verify the size of the file, and optionally the unique ID of the file. During this process, links are created which prevent the underlying files from getting deallocated even if the leader deletes the files. TODOs: Deletion of obsolete links, snapshots, robust checking against misconfigurations, better observability etc. Pull Request resolved: https://github.com/facebook/rocksdb/pull/12540 Reviewed By: jowlyzhang Differential Revision: D56315718 Pulled By: anand1976 fbshipit-source-id: d19e1aca43a6af4000cb8622a718031b69ebd97b |
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Jay Huh
|
58a98bded9 |
MultiCFIterator Refactor - CoalescingIterator & AttributeGroupIterator (#12480)
Summary:
There are a couple of reasons to modify the current implementation of the MultiCfIterator, which implements the generic `Iterator` interface.
- The default behavior of `value()`/`columns()` returning data from different Column Families for different keys can be prone to errors, even though there might be valid use cases where users do not care about the origin of the value/columns.
- The `attribute_groups()` API, which is not yet implemented, will not be useful for a single-CF iterator.
In this PR, we are implementing the following changes:
- `IteratorBase` introduced, which includes all basic iterator functions except `value()` and `columns()`.
- `Iterator`, which now inherits from `IteratorBase`, includes `value()` and `columns()`.
- New public interface `AttributeGroupIterator` inherits from `IteratorBase` and additionally includes `attribute_groups()` (to be implemented).
- Renamed former `MultiCfIterator` to `CoalescingIterator` which inherits from `Iterator`
- Existing MultiCfIteratorTest has been split into two - `CoalescingIteratorTest` and `AttributeGroupIteratorTest`.
- Moved AttributeGroup related code from `wide_columns.h` to a new file, `attribute_groups.h`.
Some Implementation Details
- `MultiCfIteratorImpl` takes two functions - `populate_func` and `reset_func` and use them to populate `value_` and `columns_` in CoalescingIterator and `attribute_groups_` in AttributeGroupIterator. In CoalescingIterator, populate_func is `Coalesce()`, in AttributeGroupIterator populate_func is `AddToAttributeGroups()`. `reset_func` clears populated value_, columns_ and attribute_groups_ accordingly.
- `Coalesce()` merge sorts columns from multiple CFs when a key exists in more than on CFs. column that appears in later CF overwrites the prior ones.
For example, if CF1 has `"key_1" ==> {"col_1": "foo", "col_2", "baz"}` and CF2 has `"key_1" ==> {"col_2": "quux", "col_3", "bla"}`, and when the iterator is at `key_1`, `columns()` will return `{"col_1": "foo", "col_2", "quux", "col_3", "bla"}`
In this example, `value()` will be empty, because none of them have values for `kDefaultColumnName`
Pull Request resolved: https://github.com/facebook/rocksdb/pull/12480
Test Plan:
## Unit Test
```
./multi_cf_iterator_test
```
## Performance Test
To make sure this change does not impact existing `Iterator` performance
**Build**
```
$> make -j64 release
```
**Setup**
```
$> TEST_TMPDIR=/dev/shm/db_bench ./db_bench -benchmarks="filluniquerandom" -key_size=32 -value_size=512 -num=1000000 -compression_type=none
```
**Run**
```
TEST_TMPDIR=/dev/shm/db_bench ./db_bench -use_existing_db=1 -benchmarks="newiterator,seekrandom" -cache_size=10485760000
```
**Before the change**
```
DB path: [/dev/shm/db_bench/dbbench]
newiterator : 0.519 micros/op 1927904 ops/sec 0.519 seconds 1000000 operations;
DB path: [/dev/shm/db_bench/dbbench]
seekrandom : 5.302 micros/op 188589 ops/sec 5.303 seconds 1000000 operations; (0 of 1000000 found)
```
**After the change**
```
DB path: [/dev/shm/db_bench/dbbench]
newiterator : 0.497 micros/op 2011012 ops/sec 0.497 seconds 1000000 operations;
DB path: [/dev/shm/db_bench/dbbench]
seekrandom : 5.252 micros/op 190405 ops/sec 5.252 seconds 1000000 operations; (0 of 1000000 found)
```
Reviewed By: ltamasi
Differential Revision: D55353909
Pulled By: jaykorean
fbshipit-source-id: 8d7786ffee09e022261ce34aa60e8633685e1946
|
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Yu Zhang
|
74d419be4d |
Add support in SstFileReader to get a raw table iterator (#12385)
Summary: This PR adds support to programmatically iterate a raw table file with an iterator returned by `SstFileReader::NewTableIterator`. For third party tools to use to observe SST files created by RocksDB. The original feature request was from this merge request: https://github.com/facebook/rocksdb/pull/12370 Since keys returned by raw table iterators are internal keys, this PR also adds a struct `ParsedEntryInfo` and util method `ParseEntry` to support user to parse internal key. `GetInternalKeyForSeek`, and `GetInternalKeyForSeekForPrev` to support users to create internal keys for seek operations with this raw table iterator. Pull Request resolved: https://github.com/facebook/rocksdb/pull/12385 Test Plan: Added unit tests Reviewed By: cbi42 Differential Revision: D55662855 Pulled By: jowlyzhang fbshipit-source-id: 0716a173ee95924fbd4e1f9b6cccf06525c40049 |
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Alan Paxton
|
d9a441113e |
JNI get_helper code sharing / multiGet() use efficient batch C++ support (#12344)
Summary: Implement RAII-based helpers for JNIGet() and multiGet() Replace JNI C++ helpers `rocksdb_get_helper, rocksdb_get_helper_direct`, `multi_get_helper`, `multi_get_helper_direct`, `multi_get_helper_release_keys`, `txn_get_helper`, and `txn_multi_get_helper`. The model is to entirely do away with a single helper, instead a number of utility methods allow each separate JNI `Get()` and `MultiGet()` method to organise their parameters efficiently, then call the underlying C++ `db->Get()`, `db->MultiGet()`, `txn->Get()`, or `txn->MultiGet()` method itself, and use further utilities to retrieve results. Roughly speaking: * get keys into C++ form * Call C++ Get() * get results and status into Java form We achieve a useful performance gain as part of this work; by using the updated C++ multiGet we immediately pick up its performance gains (batch improvements to multiGet C++ were previously implemented, but not until now used by Java/JNI). multiGetBB already uses the batched C++ multiGet(), and all other benchmarks show consistent improvement after the changes: ## Before: ``` Benchmark (columnFamilyTestType) (keyCount) (keySize) (multiGetSize) (valueSize) Mode Cnt Score Error Units MultiGetNewBenchmarks.multiGetBB200 no_column_family 10000 1024 100 256 thrpt 25 5315.459 ± 20.465 ops/s MultiGetNewBenchmarks.multiGetBB200 no_column_family 10000 1024 100 1024 thrpt 25 5673.115 ± 78.299 ops/s MultiGetNewBenchmarks.multiGetBB200 no_column_family 10000 1024 100 4096 thrpt 25 2616.860 ± 46.994 ops/s MultiGetNewBenchmarks.multiGetBB200 no_column_family 10000 1024 100 16384 thrpt 25 1700.058 ± 24.034 ops/s MultiGetNewBenchmarks.multiGetBB200 no_column_family 10000 1024 100 65536 thrpt 25 791.171 ± 13.955 ops/s MultiGetNewBenchmarks.multiGetList10 no_column_family 10000 1024 100 256 thrpt 25 6129.929 ± 94.200 ops/s MultiGetNewBenchmarks.multiGetList10 no_column_family 10000 1024 100 1024 thrpt 25 7012.405 ± 97.886 ops/s MultiGetNewBenchmarks.multiGetList10 no_column_family 10000 1024 100 4096 thrpt 25 2799.014 ± 39.352 ops/s MultiGetNewBenchmarks.multiGetList10 no_column_family 10000 1024 100 16384 thrpt 25 1417.205 ± 22.272 ops/s MultiGetNewBenchmarks.multiGetList10 no_column_family 10000 1024 100 65536 thrpt 25 655.594 ± 13.050 ops/s MultiGetNewBenchmarks.multiGetListExplicitCF20 no_column_family 10000 1024 100 256 thrpt 25 6147.247 ± 82.711 ops/s MultiGetNewBenchmarks.multiGetListExplicitCF20 no_column_family 10000 1024 100 1024 thrpt 25 7004.213 ± 79.251 ops/s MultiGetNewBenchmarks.multiGetListExplicitCF20 no_column_family 10000 1024 100 4096 thrpt 25 2715.154 ± 110.017 ops/s MultiGetNewBenchmarks.multiGetListExplicitCF20 no_column_family 10000 1024 100 16384 thrpt 25 1408.070 ± 31.714 ops/s MultiGetNewBenchmarks.multiGetListExplicitCF20 no_column_family 10000 1024 100 65536 thrpt 25 623.829 ± 57.374 ops/s MultiGetNewBenchmarks.multiGetListRandomCF30 no_column_family 10000 1024 100 256 thrpt 25 6119.243 ± 116.313 ops/s MultiGetNewBenchmarks.multiGetListRandomCF30 no_column_family 10000 1024 100 1024 thrpt 25 6931.873 ± 128.094 ops/s MultiGetNewBenchmarks.multiGetListRandomCF30 no_column_family 10000 1024 100 4096 thrpt 25 2678.253 ± 39.113 ops/s MultiGetNewBenchmarks.multiGetListRandomCF30 no_column_family 10000 1024 100 16384 thrpt 25 1337.384 ± 19.500 ops/s MultiGetNewBenchmarks.multiGetListRandomCF30 no_column_family 10000 1024 100 65536 thrpt 25 625.596 ± 14.525 ops/s ``` ## After: ``` Benchmark (columnFamilyTestType) (keyCount) (keySize) (multiGetSize) (valueSize) Mode Cnt Score Error Units MultiGetBenchmarks.multiGetBB200 no_column_family 10000 1024 100 256 thrpt 25 5191.074 ± 78.250 ops/s MultiGetBenchmarks.multiGetBB200 no_column_family 10000 1024 100 1024 thrpt 25 5378.692 ± 260.682 ops/s MultiGetBenchmarks.multiGetBB200 no_column_family 10000 1024 100 4096 thrpt 25 2590.183 ± 34.844 ops/s MultiGetBenchmarks.multiGetBB200 no_column_family 10000 1024 100 16384 thrpt 25 1634.793 ± 34.022 ops/s MultiGetBenchmarks.multiGetBB200 no_column_family 10000 1024 100 65536 thrpt 25 786.455 ± 8.462 ops/s MultiGetBenchmarks.multiGetBB200 1_column_family 10000 1024 100 256 thrpt 25 5285.055 ± 11.676 ops/s MultiGetBenchmarks.multiGetBB200 1_column_family 10000 1024 100 1024 thrpt 25 5586.758 ± 213.008 ops/s MultiGetBenchmarks.multiGetBB200 1_column_family 10000 1024 100 4096 thrpt 25 2527.172 ± 17.106 ops/s MultiGetBenchmarks.multiGetBB200 1_column_family 10000 1024 100 16384 thrpt 25 1819.547 ± 12.958 ops/s MultiGetBenchmarks.multiGetBB200 1_column_family 10000 1024 100 65536 thrpt 25 803.861 ± 9.963 ops/s MultiGetBenchmarks.multiGetBB200 20_column_families 10000 1024 100 256 thrpt 25 5253.793 ± 28.020 ops/s MultiGetBenchmarks.multiGetBB200 20_column_families 10000 1024 100 1024 thrpt 25 5705.591 ± 20.556 ops/s MultiGetBenchmarks.multiGetBB200 20_column_families 10000 1024 100 4096 thrpt 25 2523.377 ± 15.415 ops/s MultiGetBenchmarks.multiGetBB200 20_column_families 10000 1024 100 16384 thrpt 25 1815.344 ± 11.309 ops/s MultiGetBenchmarks.multiGetBB200 20_column_families 10000 1024 100 65536 thrpt 25 820.792 ± 3.192 ops/s MultiGetBenchmarks.multiGetBB200 100_column_families 10000 1024 100 256 thrpt 25 5262.184 ± 20.477 ops/s MultiGetBenchmarks.multiGetBB200 100_column_families 10000 1024 100 1024 thrpt 25 5706.959 ± 23.123 ops/s MultiGetBenchmarks.multiGetBB200 100_column_families 10000 1024 100 4096 thrpt 25 2520.362 ± 9.170 ops/s MultiGetBenchmarks.multiGetBB200 100_column_families 10000 1024 100 16384 thrpt 25 1789.185 ± 14.239 ops/s MultiGetBenchmarks.multiGetBB200 100_column_families 10000 1024 100 65536 thrpt 25 818.401 ± 12.132 ops/s MultiGetBenchmarks.multiGetList10 no_column_family 10000 1024 100 256 thrpt 25 6978.310 ± 14.084 ops/s MultiGetBenchmarks.multiGetList10 no_column_family 10000 1024 100 1024 thrpt 25 7664.242 ± 22.304 ops/s MultiGetBenchmarks.multiGetList10 no_column_family 10000 1024 100 4096 thrpt 25 2881.778 ± 81.054 ops/s MultiGetBenchmarks.multiGetList10 no_column_family 10000 1024 100 16384 thrpt 25 1599.826 ± 7.190 ops/s MultiGetBenchmarks.multiGetList10 no_column_family 10000 1024 100 65536 thrpt 25 737.520 ± 6.809 ops/s MultiGetBenchmarks.multiGetList10 1_column_family 10000 1024 100 256 thrpt 25 6974.376 ± 10.716 ops/s MultiGetBenchmarks.multiGetList10 1_column_family 10000 1024 100 1024 thrpt 25 7637.440 ± 45.877 ops/s MultiGetBenchmarks.multiGetList10 1_column_family 10000 1024 100 4096 thrpt 25 2820.472 ± 42.231 ops/s MultiGetBenchmarks.multiGetList10 1_column_family 10000 1024 100 16384 thrpt 25 1716.663 ± 8.527 ops/s MultiGetBenchmarks.multiGetList10 1_column_family 10000 1024 100 65536 thrpt 25 755.848 ± 7.514 ops/s MultiGetBenchmarks.multiGetList10 20_column_families 10000 1024 100 256 thrpt 25 6943.651 ± 20.040 ops/s MultiGetBenchmarks.multiGetList10 20_column_families 10000 1024 100 1024 thrpt 25 7679.415 ± 9.114 ops/s MultiGetBenchmarks.multiGetList10 20_column_families 10000 1024 100 4096 thrpt 25 2844.564 ± 13.388 ops/s MultiGetBenchmarks.multiGetList10 20_column_families 10000 1024 100 16384 thrpt 25 1729.545 ± 5.983 ops/s MultiGetBenchmarks.multiGetList10 20_column_families 10000 1024 100 65536 thrpt 25 783.218 ± 1.530 ops/s MultiGetBenchmarks.multiGetList10 100_column_families 10000 1024 100 256 thrpt 25 6944.276 ± 29.995 ops/s MultiGetBenchmarks.multiGetList10 100_column_families 10000 1024 100 1024 thrpt 25 7670.301 ± 8.986 ops/s MultiGetBenchmarks.multiGetList10 100_column_families 10000 1024 100 4096 thrpt 25 2839.828 ± 12.421 ops/s MultiGetBenchmarks.multiGetList10 100_column_families 10000 1024 100 16384 thrpt 25 1730.005 ± 9.209 ops/s MultiGetBenchmarks.multiGetList10 100_column_families 10000 1024 100 65536 thrpt 25 787.096 ± 1.977 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 no_column_family 10000 1024 100 256 thrpt 25 6896.944 ± 21.530 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 no_column_family 10000 1024 100 1024 thrpt 25 7622.407 ± 12.824 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 no_column_family 10000 1024 100 4096 thrpt 25 2927.538 ± 19.792 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 no_column_family 10000 1024 100 16384 thrpt 25 1598.041 ± 4.312 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 no_column_family 10000 1024 100 65536 thrpt 25 744.564 ± 9.236 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 1_column_family 10000 1024 100 256 thrpt 25 6853.760 ± 78.041 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 1_column_family 10000 1024 100 1024 thrpt 25 7360.917 ± 355.365 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 1_column_family 10000 1024 100 4096 thrpt 25 2848.774 ± 13.409 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 1_column_family 10000 1024 100 16384 thrpt 25 1727.688 ± 3.329 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 1_column_family 10000 1024 100 65536 thrpt 25 776.088 ± 7.517 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 20_column_families 10000 1024 100 256 thrpt 25 6910.339 ± 14.366 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 20_column_families 10000 1024 100 1024 thrpt 25 7633.660 ± 10.830 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 20_column_families 10000 1024 100 4096 thrpt 25 2787.799 ± 81.775 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 20_column_families 10000 1024 100 16384 thrpt 25 1726.517 ± 6.830 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 20_column_families 10000 1024 100 65536 thrpt 25 787.597 ± 3.362 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 100_column_families 10000 1024 100 256 thrpt 25 6922.445 ± 10.493 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 100_column_families 10000 1024 100 1024 thrpt 25 7604.710 ± 48.043 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 100_column_families 10000 1024 100 4096 thrpt 25 2848.788 ± 15.783 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 100_column_families 10000 1024 100 16384 thrpt 25 1730.837 ± 6.497 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 100_column_families 10000 1024 100 65536 thrpt 25 794.557 ± 1.869 ops/s MultiGetBenchmarks.multiGetListRandomCF30 no_column_family 10000 1024 100 256 thrpt 25 6918.716 ± 15.766 ops/s MultiGetBenchmarks.multiGetListRandomCF30 no_column_family 10000 1024 100 1024 thrpt 25 7626.692 ± 9.394 ops/s MultiGetBenchmarks.multiGetListRandomCF30 no_column_family 10000 1024 100 4096 thrpt 25 2871.382 ± 72.155 ops/s MultiGetBenchmarks.multiGetListRandomCF30 no_column_family 10000 1024 100 16384 thrpt 25 1598.786 ± 4.819 ops/s MultiGetBenchmarks.multiGetListRandomCF30 no_column_family 10000 1024 100 65536 thrpt 25 748.469 ± 7.234 ops/s MultiGetBenchmarks.multiGetListRandomCF30 1_column_family 10000 1024 100 256 thrpt 25 6922.666 ± 17.131 ops/s MultiGetBenchmarks.multiGetListRandomCF30 1_column_family 10000 1024 100 1024 thrpt 25 7623.890 ± 8.805 ops/s MultiGetBenchmarks.multiGetListRandomCF30 1_column_family 10000 1024 100 4096 thrpt 25 2850.698 ± 18.004 ops/s MultiGetBenchmarks.multiGetListRandomCF30 1_column_family 10000 1024 100 16384 thrpt 25 1727.623 ± 4.868 ops/s MultiGetBenchmarks.multiGetListRandomCF30 1_column_family 10000 1024 100 65536 thrpt 25 774.534 ± 10.025 ops/s MultiGetBenchmarks.multiGetListRandomCF30 20_column_families 10000 1024 100 256 thrpt 25 5486.251 ± 13.582 ops/s MultiGetBenchmarks.multiGetListRandomCF30 20_column_families 10000 1024 100 1024 thrpt 25 4920.656 ± 44.557 ops/s MultiGetBenchmarks.multiGetListRandomCF30 20_column_families 10000 1024 100 4096 thrpt 25 3922.913 ± 25.686 ops/s MultiGetBenchmarks.multiGetListRandomCF30 20_column_families 10000 1024 100 16384 thrpt 25 2873.106 ± 4.336 ops/s MultiGetBenchmarks.multiGetListRandomCF30 20_column_families 10000 1024 100 65536 thrpt 25 802.404 ± 8.967 ops/s MultiGetBenchmarks.multiGetListRandomCF30 100_column_families 10000 1024 100 256 thrpt 25 4817.996 ± 18.042 ops/s MultiGetBenchmarks.multiGetListRandomCF30 100_column_families 10000 1024 100 1024 thrpt 25 4243.922 ± 13.929 ops/s MultiGetBenchmarks.multiGetListRandomCF30 100_column_families 10000 1024 100 4096 thrpt 25 3175.998 ± 7.773 ops/s MultiGetBenchmarks.multiGetListRandomCF30 100_column_families 10000 1024 100 16384 thrpt 25 2321.990 ± 12.501 ops/s MultiGetBenchmarks.multiGetListRandomCF30 100_column_families 10000 1024 100 65536 thrpt 25 1753.028 ± 7.130 ops/s ``` Closes https://github.com/facebook/rocksdb/issues/11518 Pull Request resolved: https://github.com/facebook/rocksdb/pull/12344 Reviewed By: cbi42 Differential Revision: D54809714 Pulled By: pdillinger fbshipit-source-id: bee3b949720abac073bce043b59ce976a11e99eb |
||
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Jay Huh
|
3412195367 |
Introduce MultiCfIterator (#12153)
Summary: This PR introduces a new implementation of `Iterator` via a new public API called `NewMultiCfIterator()`. The new API takes a vector of column family handles to build a cross-column-family iterator, which internally maintains multiple `DBIter`s as child iterators from a consistent database state. When a key exists in multiple column families, the iterator selects the value (and wide columns) from the first column family containing the key, following the order provided in the `column_families` parameter. Similar to the merging iterator, a min heap is used to iterate across the child iterators. Backward iteration and direction change functionalities will be implemented in future PRs. The comparator used to compare keys across different column families will be derived from the iterator of the first column family specified in `column_families`. This comparator will be checked against the comparators from all other column families that the iterator will traverse. If there's a mismatch with any of the comparators, the initialization of the iterator will fail. Please note that this PR is not enough for users to start using `MultiCfIterator`. The `MultiCfIterator` and related APIs are still marked as "**DO NOT USE - UNDER CONSTRUCTION**". This PR is just the first of many PRs that will follow soon. This PR includes the following: - Introduction and partial implementation of the `MultiCfIterator`, which implements the generic `Iterator` interface. The implementation includes the construction of the iterator, `SeekToFirst()`, `Next()`, `Valid()`, `key()`, `value()`, and `columns()`. - Unit tests to verify iteration across multiple column families in two distinct scenarios: (1) keys are unique across all column families, and (2) the same keys exist in multiple column families. Pull Request resolved: https://github.com/facebook/rocksdb/pull/12153 Reviewed By: pdillinger Differential Revision: D52308697 Pulled By: jaykorean fbshipit-source-id: b03e69f13b40af5a8f0598d0f43a0bec01ef8294 |
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Neil Ramaswamy
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4835c11cce |
Add native logger support to RocksJava (#12213)
Summary: ## Overview In this PR, we introduce support for setting the RocksDB native logger through Java. As mentioned in the discussion on the [Google Group discussion](https://groups.google.com/g/rocksdb/c/xYmbEs4sqRM/m/e73E4whJAQAJ), this work is primarily motivated by the JDK 17 [performance regression in JNI thread attach/detach calls](https://bugs.openjdk.org/browse/JDK-8314859): the only existing RocksJava logging configuration call, `setLogger`, invokes the provided logger over the JNI. ## Changes Specifically, these changes add support for the `devnull` and `stderr` native loggers. For the `stderr` logger, we add the ability to prefix every log with a `logPrefix`, so that it becomes possible know which database a particular log is coming from (if multiple databases are in use). The API looks like the following: ```java Options opts = new Options(); NativeLogger stderrNativeLogger = NativeLogger.newStderrLogger( InfoLogLevel.DEBUG_LEVEL, "[my prefix here]"); options.setLogger(stderrNativeLogger); try (final RocksDB db = RocksDB.open(options, ...)) {...} // Cleanup stderrNativeLogger.close() opts.close(); ``` Note that the API to set the logger is the same, via `Options::setLogger` (or `DBOptions::setLogger`). However, it will set the RocksDB logger to be native when the provided logger is an instance of `NativeLogger`. ## Testing Two tests have been added in `NativeLoggerTest.java`. The first test creates both the `devnull` and `stderr` loggers, and sets them on the associated `Options`. However, to avoid polluting the testing output with logs from `stderr`, only the `devnull` logger is actually used in the test. The second test does the same logic, but for `DBOptions`. It is possible to manually verify the `stderr` logger by modifying the tests slightly, and observing that the console indeed gets cluttered with logs from `stderr`. Pull Request resolved: https://github.com/facebook/rocksdb/pull/12213 Reviewed By: cbi42 Differential Revision: D52772306 Pulled By: ajkr fbshipit-source-id: 4026895f78f9cc250daf6bfa57427957e2d8b053 |
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Radek Hubner
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f7486ff6a3 |
Add deletion-triggered compaction to RocksJava (#12028)
Summary: Pull Request resolved: https://github.com/facebook/rocksdb/pull/12028 Reviewed By: akankshamahajan15 Differential Revision: D52264983 Pulled By: ajkr fbshipit-source-id: 02d08015b4bffac06d889dc1be50a51d03f891b3 |
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Radek Hubner
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2f9ea8193f |
Add HyperClockCache Java API. (#12065)
Summary: Fix https://github.com/facebook/rocksdb/issues/11510 Pull Request resolved: https://github.com/facebook/rocksdb/pull/12065 Reviewed By: ajkr Differential Revision: D51406695 Pulled By: cbi42 fbshipit-source-id: b9e32da5f9bcafb5365e4349f7295be90d5aa7ba |
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马越
|
19768a923a |
Add jni Support for API CreateColumnFamilyWithImport (#11646)
Summary: - Add the following missing options to src/main/java/org/rocksdb/ImportColumnFamilyOptions.java and in java/rocksjni/import_column_family_options.cc in RocksJava. - Add the struct to src/main/java/org/rocksdb/ExportImportFilesMetaData.java and in java/rocksjni/export_import_files_metadatajni.cc in RocksJava. - Add New Java API `createColumnFamilyWithImport` to src/main/java/org/rocksdb/RocksDB.java - Add New Java API `exportColumnFamily` to src/main/java/org/rocksdb/Checkpoint.java Pull Request resolved: https://github.com/facebook/rocksdb/pull/11646 Test Plan: - added unit tests for exportColumnFamily in org.rocksdb.CheckpointTest - added unit tests for createColumnFamilyWithImport to org.rocksdb.ImportColumnFamilyTest Reviewed By: ajkr Differential Revision: D50889700 Pulled By: cbi42 fbshipit-source-id: d623b35e445bba62a0d3c007d74352e937678f6c |
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|
Jay Huh
|
e230e4d248 |
Make OffpeakTimeInfo available in VersionSet (#12018)
Summary: As mentioned in https://github.com/facebook/rocksdb/issues/11893, we are going to use the offpeak time information to pre-process TTL-based compactions. To do so, we need to access `daily_offpeak_time_utc` in `VersionStorageInfo::ComputeCompactionScore()` where we pick the files to compact. This PR is to make the offpeak time information available at the time of compaction-scoring. We are not changing any compaction scoring logic just yet. Will follow up in a separate PR. There were two ways to achieve what we want. 1. Make `MutableDBOptions` available in `ColumnFamilyData` and `ComputeCompactionScore()` take `MutableDBOptions` along with `ImmutableOptions` and `MutableCFOptions`. 2. Make `daily_offpeak_time_utc` and `IsNowOffpeak()` available in `VersionStorageInfo`. We chose the latter as it involves smaller changes. This change includes the following - Introduction of `OffpeakTimeInfo` and `IsNowOffpeak()` has been moved from `MutableDBOptions` - `OffpeakTimeInfo` added to `VersionSet` and it can be set during construction and by `ChangeOffpeakTimeInfo()` - During `SetDBOptions()`, if offpeak time info needs to change, it calls `MaybeScheduleFlushOrCompaction()` to re-compute compaction scores and process compactions as needed Pull Request resolved: https://github.com/facebook/rocksdb/pull/12018 Test Plan: - `DBOptionsTest::OffpeakTimes` changed to include checks for `MaybeScheduleFlushOrCompaction()` calls and `VersionSet`'s OffpeakTimeInfo value change during `SetDBOptions()`. - `VersionSetTest::OffpeakTimeInfoTest` added to test `ChangeOffpeakTimeInfo()`. `IsNowOffpeak()` tests moved from `DBOptionsTest::OffpeakTimes` Reviewed By: pdillinger Differential Revision: D50723881 Pulled By: jaykorean fbshipit-source-id: 3cff0291936f3729c0e9c7750834b9378fb435f6 |
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|
Radek Hubner
|
98ab2d80fa |
Add PerfContext API in Java (#11805)
Summary: This PR expose RocksDB C++ API for performance measurement in Java. It's initial implementation and it doesn't support ```level_to_perf_context``` Pull Request resolved: https://github.com/facebook/rocksdb/pull/11805 Reviewed By: akankshamahajan15 Differential Revision: D50128356 Pulled By: ltamasi fbshipit-source-id: afb35980a89129a30d4a6b4cce12352c9de186b6 |
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|
Levi Tamasi
|
01e2d33565 |
Add the wide-column aware merge API to the stress tests (#11906)
Summary: Pull Request resolved: https://github.com/facebook/rocksdb/pull/11906 The patch adds stress test coverage for the wide-column aware `FullMergeV3` API by implementing a new `DBStressWideMergeOperator`. This operator is similar to `PutOperator` / `PutOperatorV2` in the sense that its result is based on the last merge operand; however, the merge result can be either a plain value or a wide-column entity, depending on the value base encoded into the operand and the value of the `use_put_entity_one_in` stress test parameter. Following the same rule for merge results that we do for writes ensures that the queries issued by the validation logic receive the expected results. The new operator is used instead of `PutOperatorV2` whenever `use_put_entity_one_in` is positive. Note that the patch also makes it possible to set `use_put_entity_one_in` and `use_merge` (but not `use_full_merge_v1`) at the same time, giving `use_put_entity_one_in` precedence, so the stress test will use `PutEntity` for writes passing the `use_put_entity_one_in` check described above and `Merge` for any other writes. Reviewed By: jaykorean Differential Revision: D49760024 fbshipit-source-id: 3893602c3e7935381b484f4f5026f1983e3a04a9 |
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anand76
|
269478ee46 |
Support compressed and local flash secondary cache stacking (#11812)
Summary: This PR implements support for a three tier cache - primary block cache, compressed secondary cache, and a nvm (local flash) secondary cache. This allows more effective utilization of the nvm cache, and minimizes the number of reads from local flash by caching compressed blocks in the compressed secondary cache. The basic design is as follows - 1. A new secondary cache implementation, ```TieredSecondaryCache```, is introduced. It keeps the compressed and nvm secondary caches and manages the movement of blocks between them and the primary block cache. To setup a three tier cache, we allocate a ```CacheWithSecondaryAdapter```, with a ```TieredSecondaryCache``` instance as the secondary cache. 2. The table reader passes both the uncompressed and compressed block to ```FullTypedCacheInterface::InsertFull```, allowing the block cache to optionally store the compressed block. 3. When there's a miss, the block object is constructed and inserted in the primary cache, and the compressed block is inserted into the nvm cache by calling ```InsertSaved```. This avoids the overhead of recompressing the block, as well as avoiding putting more memory pressure on the compressed secondary cache. 4. When there's a hit in the nvm cache, we attempt to insert the block in the compressed secondary cache and the primary cache, subject to the admission policy of those caches (i.e admit on second access). Blocks/items evicted from any tier are simply discarded. We can easily implement additional admission policies if desired. Todo (In a subsequent PR): 1. Add to db_bench and run benchmarks 2. Add to db_stress Pull Request resolved: https://github.com/facebook/rocksdb/pull/11812 Reviewed By: pdillinger Differential Revision: D49461842 Pulled By: anand1976 fbshipit-source-id: b40ac1330ef7cd8c12efa0a3ca75128e602e3a0b |
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|
Jay Huh
|
ea9a5b2914 |
Wide Column support in ldb (#11754)
Summary: wide_columns can now be pretty-printed in the following commands - `./ldb dump_wal` - `./ldb dump` - `./ldb idump` - `./ldb dump_live_files` - `./ldb scan` - `./sst_dump --command=scan` There are opportunities to refactor to reduce some nearly identical code. This PR is initial change to add wide column support in `ldb` and `sst_dump` tool. More PRs to come for the refactor. Pull Request resolved: https://github.com/facebook/rocksdb/pull/11754 Test Plan: **New Tests added** - `WideColumnsHelperTest::DumpWideColumns` - `WideColumnsHelperTest::DumpSliceAsWideColumns` **Changes added to existing tests** - `ExternalSSTFileTest::BasicMixed` added to cover mixed case (This test should have been added in https://github.com/facebook/rocksdb/issues/11688). This test does not verify the ldb or sst_dump output. This test was used to create test SST files having some rows with wide columns and some without and the generated SST files were used to manually test sst_dump_tool. - `createSST()` in `sst_dump_test` now takes `wide_column_one_in` to add wide column value in SST **dump_wal** ``` ./ldb dump_wal --walfile=/tmp/rocksdbtest-226125/db_wide_basic_test_2675429_2308393776696827948/000004.log --print_value --header ``` ``` Sequence,Count,ByteSize,Physical Offset,Key(s) : value 1,1,59,0,PUT_ENTITY(0) : 0x:0x68656C6C6F 0x617474725F6E616D6531:0x666F6F 0x617474725F6E616D6532:0x626172 2,1,34,42,PUT_ENTITY(0) : 0x617474725F6F6E65:0x74776F 0x617474725F7468726565:0x666F7572 3,1,17,7d,PUT(0) : 0x7468697264 : 0x62617A ``` **idump** ``` ./ldb --db=/tmp/rocksdbtest-226125/db_wide_basic_test_3481961_2308393776696827948/ idump ``` ``` 'first' seq:1, type:22 => :hello attr_name1:foo attr_name2:bar 'second' seq:2, type:22 => attr_one:two attr_three:four 'third' seq:3, type:1 => baz Internal keys in range: 3 ``` **SST Dump from dump_live_files** ``` ./ldb --db=/tmp/rocksdbtest-226125/db_wide_basic_test_3481961_2308393776696827948/ compact ./ldb --db=/tmp/rocksdbtest-226125/db_wide_basic_test_3481961_2308393776696827948/ dump_live_files ``` ``` ... ============================== SST Files ============================== /tmp/rocksdbtest-226125/db_wide_basic_test_3481961_2308393776696827948/000013.sst level:1 ------------------------------ Process /tmp/rocksdbtest-226125/db_wide_basic_test_3481961_2308393776696827948/000013.sst Sst file format: block-based 'first' seq:0, type:22 => :hello attr_name1:foo attr_name2:bar 'second' seq:0, type:22 => attr_one:two attr_three:four 'third' seq:0, type:1 => baz ... ``` **dump** ``` ./ldb --db=/tmp/rocksdbtest-226125/db_wide_basic_test_3481961_2308393776696827948/ dump ``` ``` first ==> :hello attr_name1:foo attr_name2:bar second ==> attr_one:two attr_three:four third ==> baz Keys in range: 3 ``` **scan** ``` ./ldb --db=/tmp/rocksdbtest-226125/db_wide_basic_test_3481961_2308393776696827948/ scan ``` ``` first : :hello attr_name1:foo attr_name2:bar second : attr_one:two attr_three:four third : baz ``` **sst_dump** ``` ./sst_dump --file=/tmp/rocksdbtest-226125/db_wide_basic_test_3481961_2308393776696827948/000013.sst --command=scan ``` ``` options.env is 0x7ff54b296000 Process /tmp/rocksdbtest-226125/db_wide_basic_test_3481961_2308393776696827948/000013.sst Sst file format: block-based from [] to [] 'first' seq:0, type:22 => :hello attr_name1:foo attr_name2:bar 'second' seq:0, type:22 => attr_one:two attr_three:four 'third' seq:0, type:1 => baz ``` Reviewed By: ltamasi Differential Revision: D48837999 Pulled By: jaykorean fbshipit-source-id: b0280f0589d2b9716bb9b50530ffcabb397d140f |
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|
Yu Zhang
|
11ebddb1d4 |
Add utils to use for handling user defined timestamp size record in WAL (#11451)
Summary: Add a util method `HandleWriteBatchTimestampSizeDifference` to handle a `WriteBatch` read from WAL log when user-defined timestamp size record is written and read. Two check modes are added: `kVerifyConsistency` that just verifies the recorded timestamp size are consistent with the running ones. This mode is to be used by `db_impl_secondary` for opening a DB as secondary instance. It will also be used by `db_impl_open` before the user comparator switch support is added to make a column switch between enabling/disable UDT feature. The other mode `kReconcileInconsistency` will be used by `db_impl_open` later when user comparator can be changed. Another change is to extract a method `CollectColumnFamilyIdsFromWriteBatch` in db_secondary_impl.h into its standalone util file so it can be shared. Pull Request resolved: https://github.com/facebook/rocksdb/pull/11451 Test Plan: ``` make check ./udt_util_test ``` Reviewed By: ltamasi Differential Revision: D45894386 Pulled By: jowlyzhang fbshipit-source-id: b96790777f154cddab6d45d9ba2e5d20ebc6fe9d |
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|
mayue.fight
|
8d8eb0e77e |
Support Clip DB to KeyRange (#11379)
Summary: This PR is part of the request https://github.com/facebook/rocksdb/issues/11317. (Another part is https://github.com/facebook/rocksdb/pull/11378) ClipDB() will clip the entries in the CF according to the range [begin_key, end_key). All the entries outside this range will be completely deleted (including tombstones). This feature is mainly used to ensure that there is no overlapping Key when calling CreateColumnFamilyWithImports() to import multiple CFs. When Calling ClipDB [begin, end), there are the following steps 1. Quickly and directly delete files without overlap DeleteFilesInRanges(nullptr, begin) + DeleteFilesInRanges(end, nullptr) 2. Delete the Key outside the range Delete[smallest_key, begin) + Delete[end, largest_key] 3. Delete the tombstone through Manul Compact CompactRange(option, nullptr, nullptr) Pull Request resolved: https://github.com/facebook/rocksdb/pull/11379 Reviewed By: ajkr Differential Revision: D45840358 Pulled By: cbi42 fbshipit-source-id: 54152e8a45fd8ede137f99787eb252f0b51440a4 |
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Hui Xiao
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7263f51d50 |
Improve comment of ExpectedValue in db stress (#11456)
Summary: **Context/Summary:** https://github.com/facebook/rocksdb/pull/11424 made me realize there are a couple gaps in my `ExpectedValue` comments so I updated them, along with separating `ExpectedValue` into separate files so it's clearer that `ExpectedValue` can be used without updating `ExpectedState` (e.g, TestMultiGet() where we care about value base of expected value but not updating the ExpectedState). Pull Request resolved: https://github.com/facebook/rocksdb/pull/11456 Test Plan: CI Reviewed By: jowlyzhang Differential Revision: D45965070 Pulled By: hx235 fbshipit-source-id: dcee690c13b00a3119757ea9d43b646f9644e1a9 |
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Hui Xiao
|
cb58477185 |
New stat rocksdb.{cf|db}-write-stall-stats exposed in a structural way (#11300)
Summary: **Context/Summary:** Users are interested in figuring out what has caused write stall. - Refactor write stall related stats from property `kCFStats` into its own db property `rocksdb.cf-write-stall-stats` as a map or string. For now, this only contains count of different combination of (CF-scope `WriteStallCause`) + (`WriteStallCondition`) - Add new `WriteStallCause::kWriteBufferManagerLimit` to reflect write stall caused by write buffer manager - Add new `rocksdb.db-write-stall-stats`. For now, this only contains `WriteStallCause::kWriteBufferManagerLimit` + `WriteStallCondition::kStopped` - Expose functions in new class `WriteStallStatsMapKeys` for examining the above two properties returned as map - Misc: rename/comment some write stall InternalStats for clarity Pull Request resolved: https://github.com/facebook/rocksdb/pull/11300 Test Plan: - New UT - Stress test `python3 tools/db_crashtest.py blackbox --simple --get_property_one_in=1` - Perf test: Both converge very slowly at similar rates but post-change has higher average ops/sec than pre-change even though they are run at the same time. ``` ./db_bench -seed=1679014417652004 -db=/dev/shm/testdb/ -statistics=false -benchmarks="fillseq[-X60]" -key_size=32 -value_size=512 -num=100000 -db_write_buffer_size=655 -target_file_size_base=655 -disable_auto_compactions=false -compression_type=none -bloom_bits=3 ``` pre-change: ``` fillseq [AVG 15 runs] : 1176 (± 732) ops/sec; 0.6 (± 0.4) MB/sec fillseq : 1052.671 micros/op 949 ops/sec 105.267 seconds 100000 operations; 0.5 MB/s fillseq [AVG 16 runs] : 1162 (± 685) ops/sec; 0.6 (± 0.4) MB/sec fillseq : 1387.330 micros/op 720 ops/sec 138.733 seconds 100000 operations; 0.4 MB/s fillseq [AVG 17 runs] : 1136 (± 646) ops/sec; 0.6 (± 0.3) MB/sec fillseq : 1232.011 micros/op 811 ops/sec 123.201 seconds 100000 operations; 0.4 MB/s fillseq [AVG 18 runs] : 1118 (± 610) ops/sec; 0.6 (± 0.3) MB/sec fillseq : 1282.567 micros/op 779 ops/sec 128.257 seconds 100000 operations; 0.4 MB/s fillseq [AVG 19 runs] : 1100 (± 578) ops/sec; 0.6 (± 0.3) MB/sec fillseq : 1914.336 micros/op 522 ops/sec 191.434 seconds 100000 operations; 0.3 MB/s fillseq [AVG 20 runs] : 1071 (± 551) ops/sec; 0.6 (± 0.3) MB/sec fillseq : 1227.510 micros/op 814 ops/sec 122.751 seconds 100000 operations; 0.4 MB/s fillseq [AVG 21 runs] : 1059 (± 525) ops/sec; 0.5 (± 0.3) MB/sec ``` post-change: ``` fillseq [AVG 15 runs] : 1226 (± 732) ops/sec; 0.6 (± 0.4) MB/sec fillseq : 1323.825 micros/op 755 ops/sec 132.383 seconds 100000 operations; 0.4 MB/s fillseq [AVG 16 runs] : 1196 (± 687) ops/sec; 0.6 (± 0.4) MB/sec fillseq : 1223.905 micros/op 817 ops/sec 122.391 seconds 100000 operations; 0.4 MB/s fillseq [AVG 17 runs] : 1174 (± 647) ops/sec; 0.6 (± 0.3) MB/sec fillseq : 1168.996 micros/op 855 ops/sec 116.900 seconds 100000 operations; 0.4 MB/s fillseq [AVG 18 runs] : 1156 (± 611) ops/sec; 0.6 (± 0.3) MB/sec fillseq : 1348.729 micros/op 741 ops/sec 134.873 seconds 100000 operations; 0.4 MB/s fillseq [AVG 19 runs] : 1134 (± 579) ops/sec; 0.6 (± 0.3) MB/sec fillseq : 1196.887 micros/op 835 ops/sec 119.689 seconds 100000 operations; 0.4 MB/s fillseq [AVG 20 runs] : 1119 (± 550) ops/sec; 0.6 (± 0.3) MB/sec fillseq : 1193.697 micros/op 837 ops/sec 119.370 seconds 100000 operations; 0.4 MB/s fillseq [AVG 21 runs] : 1106 (± 524) ops/sec; 0.6 (± 0.3) MB/sec ``` Reviewed By: ajkr Differential Revision: D44159541 Pulled By: hx235 fbshipit-source-id: 8d29efb70001fdc52d34535eeb3364fc3e71e40b |
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|
Peter Dillinger
|
204fcff751 |
HyperClockCache support for SecondaryCache, with refactoring (#11301)
Summary:
Internally refactors SecondaryCache integration out of LRUCache specifically and into a wrapper/adapter class that works with various Cache implementations. Notably, this relies on separating the notion of async lookup handles from other cache handles, so that HyperClockCache doesn't have to deal with the problem of allocating handles from the hash table for lookups that might fail anyway, and might be on the same key without support for coalescing. (LRUCache's hash table can incorporate previously allocated handles thanks to its pointer indirection.) Specifically, I'm worried about the case in which hundreds of threads try to access the same block and probing in the hash table degrades to linear search on the pile of entries with the same key.
This change is a big step in the direction of supporting stacked SecondaryCaches, but there are obstacles to completing that. Especially, there is no SecondaryCache hook for evictions to pass from one to the next. It has been proposed that evictions be transmitted simply as the persisted data (as in SaveToCallback), but given the current structure provided by the CacheItemHelpers, that would require an extra copy of the block data, because there's intentionally no way to ask for a contiguous Slice of the data (to allow for flexibility in storage). `AsyncLookupHandle` and the re-worked `WaitAll()` should be essentially prepared for stacked SecondaryCaches, but several "TODO with stacked secondaries" issues remain in various places.
It could be argued that the stacking instead be done as a SecondaryCache adapter that wraps two (or more) SecondaryCaches, but at least with the current API that would require an extra heap allocation on SecondaryCache Lookup for a wrapper SecondaryCacheResultHandle that can transfer a Lookup between secondaries. We could also consider trying to unify the Cache and SecondaryCache APIs, though that might be difficult if `AsyncLookupHandle` is kept a fixed struct.
## cache.h (public API)
Moves `secondary_cache` option from LRUCacheOptions to ShardedCacheOptions so that it is applicable to HyperClockCache.
## advanced_cache.h (advanced public API)
* Add `Cache::CreateStandalone()` so that the SecondaryCache support wrapper can use it.
* Add `SetEvictionCallback()` / `eviction_callback_` so that the SecondaryCache support wrapper can use it. Only a single callback is supported for efficiency. If there is ever a need for more than one, hopefully that can be handled with a broadcast callback wrapper.
These are essentially the two "extra" pieces of `Cache` for pulling out specific SecondaryCache support from the `Cache` implementation. I think it's a good trade-off as these are reasonable, limited, and reusable "cut points" into the `Cache` implementations.
* Remove async capability from standard `Lookup()` (getting rid of awkward restrictions on pending Handles) and add `AsyncLookupHandle` and `StartAsyncLookup()`. As noted in the comments, the full struct of `AsyncLookupHandle` is exposed so that it can be stack allocated, for efficiency, though more data is being copied around than before, which could impact performance. (Lookup info -> AsyncLookupHandle -> Handle vs. Lookup info -> Handle)
I could foresee a future in which a Cache internally saves a pointer to the AsyncLookupHandle, which means it's dangerous to allow it to be copyable or even movable. It also means it's not compatible with std::vector (which I don't like requiring as an API parameter anyway), so `WaitAll()` expects any contiguous array of AsyncLookupHandles. I believe this is best for common case efficiency, while behaving well in other cases also. For example, `WaitAll()` has no effect on default-constructed AsyncLookupHandles, which look like a completed cache miss.
## cacheable_entry.h
A couple of functions are obsolete because Cache::Handle can no longer be pending.
## cache.cc
Provides default implementations for new or revamped Cache functions, especially appropriate for non-blocking caches.
## secondary_cache_adapter.{h,cc}
The full details of the Cache wrapper adding SecondaryCache support. Essentially replicates the SecondaryCache handling that was in LRUCache, but obviously refactored. There is a bit of logic duplication, where Lookup() is essentially a manually optimized version of StartAsyncLookup() and Wait(), but it's roughly a dozen lines of code.
## sharded_cache.h, typed_cache.h, charged_cache.{h,cc}, sim_cache.cc
Simply updated for Cache API changes.
## lru_cache.{h,cc}
Carefully remove SecondaryCache logic, implement `CreateStandalone` and eviction handler functionality.
## clock_cache.{h,cc}
Expose existing `CreateStandalone` functionality, add eviction handler functionality. Light refactoring.
## block_based_table_reader*
Mostly re-worked the only usage of async Lookup, which is in BlockBasedTable::MultiGet. Used arrays in place of autovector in some places for efficiency. Simplified some logic by not trying to process some cache results before they're all ready.
Created new function `BlockBasedTable::GetCachePriority()` to reduce some pre-existing code duplication (and avoid making it worse).
Fixed at least one small bug from the prior confusing mixture of async and sync Lookups. In MaybeReadBlockAndLoadToCache(), called by RetrieveBlock(), called by MultiGet() with wait=false, is_cache_hit for the block_cache_tracer entry would not be set to true if the handle was pending after Lookup and before Wait.
## Intended follow-up work
* Figure out if there are any missing stats or block_cache_tracer work in refactored BlockBasedTable::MultiGet
* Stacked secondary caches (see above discussion)
* See if we can make up for the small MultiGet performance regression.
* Study more performance with SecondaryCache
* Items evicted from over-full LRUCache in Release were not being demoted to SecondaryCache, and still aren't to minimize unit test churn. Ideally they would be demoted, but it's an exceptional case so not a big deal.
* Use CreateStandalone for cache reservations (save unnecessary hash table operations). Not a big deal, but worthy cleanup.
* Somehow I got the contract for SecondaryCache::Insert wrong in #10945. (Doesn't take ownership!) That API comment needs to be fixed, but didn't want to mingle that in here.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/11301
Test Plan:
## Unit tests
Generally updated to include HCC in SecondaryCache tests, though HyperClockCache has some different, less strict behaviors that leads to some tests not really being set up to work with it. Some of the tests remain disabled with it, but I think we have good coverage without them.
## Crash/stress test
Updated to use the new combination.
## Performance
First, let's check for regression on caches without secondary cache configured. Adding support for the eviction callback is likely to have a tiny effect, but it shouldn't be worrisome. LRUCache could benefit slightly from less logic around SecondaryCache handling. We can test with cache_bench default settings, built with DEBUG_LEVEL=0 and PORTABLE=0.
```
(while :; do base/cache_bench --cache_type=hyper_clock_cache | grep Rough; done) | awk '{ sum += $9; count++; print $0; print "Average: " int(sum / count) }'
```
**Before** this and #11299 (which could also have a small effect), running for about an hour, before & after running concurrently for each cache type:
HyperClockCache: 3168662 (average parallel ops/sec)
LRUCache: 2940127
**After** this and #11299, running for about an hour:
HyperClockCache: 3164862 (average parallel ops/sec) (0.12% slower)
LRUCache: 2940928 (0.03% faster)
This is an acceptable difference IMHO.
Next, let's consider essentially the worst case of new CPU overhead affecting overall performance. MultiGet uses the async lookup interface regardless of whether SecondaryCache or folly are used. We can configure a benchmark where all block cache queries are for data blocks, and all are hits.
Create DB and test (before and after tests running simultaneously):
```
TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=fillrandom -num=30000000 -disable_wal=1 -bloom_bits=16
TEST_TMPDIR=/dev/shm base/db_bench -benchmarks=multireadrandom[-X30] -readonly -multiread_batched -batch_size=32 -num=30000000 -bloom_bits=16 -cache_size=6789000000 -duration 20 -threads=16
```
**Before**:
multireadrandom [AVG 30 runs] : 3444202 (± 57049) ops/sec; 240.9 (± 4.0) MB/sec
multireadrandom [MEDIAN 30 runs] : 3514443 ops/sec; 245.8 MB/sec
**After**:
multireadrandom [AVG 30 runs] : 3291022 (± 58851) ops/sec; 230.2 (± 4.1) MB/sec
multireadrandom [MEDIAN 30 runs] : 3366179 ops/sec; 235.4 MB/sec
So that's roughly a 3% regression, on kind of a *worst case* test of MultiGet CPU. Similar story with HyperClockCache:
**Before**:
multireadrandom [AVG 30 runs] : 3933777 (± 41840) ops/sec; 275.1 (± 2.9) MB/sec
multireadrandom [MEDIAN 30 runs] : 3970667 ops/sec; 277.7 MB/sec
**After**:
multireadrandom [AVG 30 runs] : 3755338 (± 30391) ops/sec; 262.6 (± 2.1) MB/sec
multireadrandom [MEDIAN 30 runs] : 3785696 ops/sec; 264.8 MB/sec
Roughly a 4-5% regression. Not ideal, but not the whole story, fortunately.
Let's also look at Get() in db_bench:
```
TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=readrandom[-X30] -readonly -num=30000000 -bloom_bits=16 -cache_size=6789000000 -duration 20 -threads=16
```
**Before**:
readrandom [AVG 30 runs] : 2198685 (± 13412) ops/sec; 153.8 (± 0.9) MB/sec
readrandom [MEDIAN 30 runs] : 2209498 ops/sec; 154.5 MB/sec
**After**:
readrandom [AVG 30 runs] : 2292814 (± 43508) ops/sec; 160.3 (± 3.0) MB/sec
readrandom [MEDIAN 30 runs] : 2365181 ops/sec; 165.4 MB/sec
That's showing roughly a 4% improvement, perhaps because of the secondary cache code that is no longer part of LRUCache. But weirdly, HyperClockCache is also showing 2-3% improvement:
**Before**:
readrandom [AVG 30 runs] : 2272333 (± 9992) ops/sec; 158.9 (± 0.7) MB/sec
readrandom [MEDIAN 30 runs] : 2273239 ops/sec; 159.0 MB/sec
**After**:
readrandom [AVG 30 runs] : 2332407 (± 11252) ops/sec; 163.1 (± 0.8) MB/sec
readrandom [MEDIAN 30 runs] : 2335329 ops/sec; 163.3 MB/sec
Reviewed By: ltamasi
Differential Revision: D44177044
Pulled By: pdillinger
fbshipit-source-id: e808e48ff3fe2f792a79841ba617be98e48689f5
|
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Peter Dillinger
|
ccaa3225b0 |
Simplify tracking entries already in SecondaryCache (#11299)
Summary: In preparation for factoring secondary cache support out of individual Cache implementations, we can get rid of the "in secondary cache" flag on entries through a workable hack: when an entry is promoted from secondary, it is inserted in primary using a helper that lacks secondary cache support, thus preventing re-insertion into secondary cache through existing logic. This adds to the complexity of building CacheItemHelpers, because you always have to be able to get to an equivalent helper without secondary cache support, but that complexity is reasonably isolated within RocksDB typed_cache.h and test code. gcc-7 seems to have problems with constexpr constructor referencing `this` so removed constexpr support on CacheItemHelper. Also refactored some related test code to share common code / functionality. Pull Request resolved: https://github.com/facebook/rocksdb/pull/11299 Test Plan: existing tests Reviewed By: anand1976 Differential Revision: D44101453 Pulled By: pdillinger fbshipit-source-id: 7a59d0a3938ee40159c90c3e65d7004f6a272345 |
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Changyu Bi
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229297d1b8 |
Refactor AddRangeDels() + consider range tombstone during compaction file cutting (#11113)
Summary: A second attempt after https://github.com/facebook/rocksdb/issues/10802, with bug fixes and refactoring. This PR updates compaction logic to take range tombstones into account when determining whether to cut the current compaction output file (https://github.com/facebook/rocksdb/issues/4811). Before this change, only point keys were considered, and range tombstones could cause large compactions. For example, if the current compaction outputs is a range tombstone [a, b) and 2 point keys y, z, they would be added to the same file, and may overlap with too many files in the next level and cause a large compaction in the future. This PR also includes ajkr's effort to simplify the logic to add range tombstones to compaction output files in `AddRangeDels()` ([https://github.com/facebook/rocksdb/issues/11078](https://github.com/facebook/rocksdb/pull/11078#issuecomment-1386078861)). The main change is for `CompactionIterator` to emit range tombstone start keys to be processed by `CompactionOutputs`. A new class `CompactionMergingIterator` is introduced to replace `MergingIterator` under `CompactionIterator` to enable emitting of range tombstone start keys. Further improvement after this PR include cutting compaction output at some grandparent boundary key (instead of the next output key) when cutting within a range tombstone to reduce overlap with grandparents. Pull Request resolved: https://github.com/facebook/rocksdb/pull/11113 Test Plan: * added unit test in db_range_del_test * crash test with a small key range: `python3 tools/db_crashtest.py blackbox --simple --max_key=100 --interval=600 --write_buffer_size=262144 --target_file_size_base=256 --max_bytes_for_level_base=262144 --block_size=128 --value_size_mult=33 --subcompactions=10 --use_multiget=1 --delpercent=3 --delrangepercent=2 --verify_iterator_with_expected_state_one_in=2 --num_iterations=10` Reviewed By: ajkr Differential Revision: D42655709 Pulled By: cbi42 fbshipit-source-id: 8367e36ef5640e8f21c14a3855d4a8d6e360a34c |
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Peter Dillinger
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34bb3ddc43 |
Improve SmallEnumSet (#11178)
Summary: In anticipation of using this to represent sets of CacheEntryRole for including or excluding kinds of blocks in block cache tiers, add significant new features to SmallEnumSet, including at least: * List initialization * Applicative constexpr operations * copy/move/equality ops * begin/end/const_iterator for iteration * Better comments Pull Request resolved: https://github.com/facebook/rocksdb/pull/11178 Test Plan: unit tests added/expanded Reviewed By: ltamasi Differential Revision: D42973723 Pulled By: pdillinger fbshipit-source-id: 40783486feda931c3f7c6fcc9a300acd6a4b0a0a |
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Changyu Bi
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f515d9d203 |
Revert #10802 Consider range tombstone in compaction output file cutting (#11089)
Summary:
This reverts commit
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Peter Dillinger
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9f7801c5f1 |
Major Cache refactoring, CPU efficiency improvement (#10975)
Summary: This is several refactorings bundled into one to avoid having to incrementally re-modify uses of Cache several times. Overall, there are breaking changes to Cache class, and it becomes more of low-level interface for implementing caches, especially block cache. New internal APIs make using Cache cleaner than before, and more insulated from block cache evolution. Hopefully, this is the last really big block cache refactoring, because of rather effectively decoupling the implementations from the uses. This change also removes the EXPERIMENTAL designation on the SecondaryCache support in Cache. It seems reasonably mature at this point but still subject to change/evolution (as I warn in the API docs for Cache). The high-level motivation for this refactoring is to minimize code duplication / compounding complexity in adding SecondaryCache support to HyperClockCache (in a later PR). Other benefits listed below. * static_cast lines of code +29 -35 (net removed 6) * reinterpret_cast lines of code +6 -32 (net removed 26) ## cache.h and secondary_cache.h * Always use CacheItemHelper with entries instead of just a Deleter. There are several motivations / justifications: * Simpler for implementations to deal with just one Insert and one Lookup. * Simpler and more efficient implementation because we don't have to track which entries are using helpers and which are using deleters * Gets rid of hack to classify cache entries by their deleter. Instead, the CacheItemHelper includes a CacheEntryRole. This simplifies a lot of code (cache_entry_roles.h almost eliminated). Fixes https://github.com/facebook/rocksdb/issues/9428. * Makes it trivial to adjust SecondaryCache behavior based on kind of block (e.g. don't re-compress filter blocks). * It is arguably less convenient for many direct users of Cache, but direct users of Cache are now rare with introduction of typed_cache.h (below). * I considered and rejected an alternative approach in which we reduce customizability by assuming each secondary cache compatible value starts with a Slice referencing the uncompressed block contents (already true or mostly true), but we apparently intend to stack secondary caches. Saving an entry from a compressed secondary to a lower tier requires custom handling offered by SaveToCallback, etc. * Make CreateCallback part of the helper and introduce CreateContext to work with it (alternative to https://github.com/facebook/rocksdb/issues/10562). This cleans up the interface while still allowing context to be provided for loading/parsing values into primary cache. This model works for async lookup in BlockBasedTable reader (reader owns a CreateContext) under the assumption that it always waits on secondary cache operations to finish. (Otherwise, the CreateContext could be destroyed while async operation depending on it continues.) This likely contributes most to the observed performance improvement because it saves an std::function backed by a heap allocation. * Use char* for serialized data, e.g. in SaveToCallback, where void* was confusingly used. (We use `char*` for serialized byte data all over RocksDB, with many advantages over `void*`. `memcpy` etc. are legacy APIs that should not be mimicked.) * Add a type alias Cache::ObjectPtr = void*, so that we can better indicate the intent of the void* when it is to be the object associated with a Cache entry. Related: started (but did not complete) a refactoring to move away from "value" of a cache entry toward "object" or "obj". (It is confusing to call Cache a key-value store (like DB) when it is really storing arbitrary in-memory objects, not byte strings.) * Remove unnecessary key param from DeleterFn. This is good for efficiency in HyperClockCache, which does not directly store the cache key in memory. (Alternative to https://github.com/facebook/rocksdb/issues/10774) * Add allocator to Cache DeleterFn. This is a kind of future-proofing change in case we get more serious about using the Cache allocator for memory tracked by the Cache. Right now, only the uncompressed block contents are allocated using the allocator, and a pointer to that allocator is saved as part of the cached object so that the deleter can use it. (See CacheAllocationPtr.) If in the future we are able to "flatten out" our Cache objects some more, it would be good not to have to track the allocator as part of each object. * Removes legacy `ApplyToAllCacheEntries` and changes `ApplyToAllEntries` signature for Deleter->CacheItemHelper change. ## typed_cache.h Adds various "typed" interfaces to the Cache as internal APIs, so that most uses of Cache can use simple type safe code without casting and without explicit deleters, etc. Almost all of the non-test, non-glue code uses of Cache have been migrated. (Follow-up work: CompressedSecondaryCache deserves deeper attention to migrate.) This change expands RocksDB's internal usage of metaprogramming and SFINAE (https://en.cppreference.com/w/cpp/language/sfinae). The existing usages of Cache are divided up at a high level into these new interfaces. See updated existing uses of Cache for examples of how these are used. * PlaceholderCacheInterface - Used for making cache reservations, with entries that have a charge but no value. * BasicTypedCacheInterface<TValue> - Used for primary cache storage of objects of type TValue, which can be cleaned up with std::default_delete<TValue>. The role is provided by TValue::kCacheEntryRole or given in an optional template parameter. * FullTypedCacheInterface<TValue, TCreateContext> - Used for secondary cache compatible storage of objects of type TValue. In addition to BasicTypedCacheInterface constraints, we require TValue::ContentSlice() to return persistable data. This simplifies usage for the normal case of simple secondary cache compatibility (can give you a Slice to the data already in memory). In addition to TCreateContext performing the role of Cache::CreateContext, it is also expected to provide a factory function for creating TValue. * For each of these, there's a "Shared" version (e.g. FullTypedSharedCacheInterface) that holds a shared_ptr to the Cache, rather than assuming external ownership by holding only a raw `Cache*`. These interfaces introduce specific handle types for each interface instantiation, so that it's easy to see what kind of object is controlled by a handle. (Ultimately, this might not be worth the extra complexity, but it seems OK so far.) Note: I attempted to make the cache 'charge' automatically inferred from the cache object type, such as by expecting an ApproximateMemoryUsage() function, but this is not so clean because there are cases where we need to compute the charge ahead of time and don't want to re-compute it. ## block_cache.h This header is essentially the replacement for the old block_like_traits.h. It includes various things to support block cache access with typed_cache.h for block-based table. ## block_based_table_reader.cc Before this change, accessing the block cache here was an awkward mix of static polymorphism (template TBlocklike) and switch-case on a dynamic BlockType value. This change mostly unifies on static polymorphism, relying on minor hacks in block_cache.h to distinguish variants of Block. We still check BlockType in some places (especially for stats, which could be improved in follow-up work) but at least the BlockType is a static constant from the template parameter. (No more awkward partial redundancy between static and dynamic info.) This likely contributes to the overall performance improvement, but hasn't been tested in isolation. The other key source of simplification here is a more unified system of creating block cache objects: for directly populating from primary cache and for promotion from secondary cache. Both use BlockCreateContext, for context and for factory functions. ## block_based_table_builder.cc, cache_dump_load_impl.cc Before this change, warming caches was super ugly code. Both of these source files had switch statements to basically transition from the dynamic BlockType world to the static TBlocklike world. None of that mess is needed anymore as there's a new, untyped WarmInCache function that handles all the details just as promotion from SecondaryCache would. (Fixes `TODO akanksha: Dedup below code` in block_based_table_builder.cc.) ## Everything else Mostly just updating Cache users to use new typed APIs when reasonably possible, or changed Cache APIs when not. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10975 Test Plan: tests updated Performance test setup similar to https://github.com/facebook/rocksdb/issues/10626 (by cache size, LRUCache when not "hyper" for HyperClockCache): 34MB 1thread base.hyper -> kops/s: 0.745 io_bytes/op: 2.52504e+06 miss_ratio: 0.140906 max_rss_mb: 76.4844 34MB 1thread new.hyper -> kops/s: 0.751 io_bytes/op: 2.5123e+06 miss_ratio: 0.140161 max_rss_mb: 79.3594 34MB 1thread base -> kops/s: 0.254 io_bytes/op: 1.36073e+07 miss_ratio: 0.918818 max_rss_mb: 45.9297 34MB 1thread new -> kops/s: 0.252 io_bytes/op: 1.36157e+07 miss_ratio: 0.918999 max_rss_mb: 44.1523 34MB 32thread base.hyper -> kops/s: 7.272 io_bytes/op: 2.88323e+06 miss_ratio: 0.162532 max_rss_mb: 516.602 34MB 32thread new.hyper -> kops/s: 7.214 io_bytes/op: 2.99046e+06 miss_ratio: 0.168818 max_rss_mb: 518.293 34MB 32thread base -> kops/s: 3.528 io_bytes/op: 1.35722e+07 miss_ratio: 0.914691 max_rss_mb: 264.926 34MB 32thread new -> kops/s: 3.604 io_bytes/op: 1.35744e+07 miss_ratio: 0.915054 max_rss_mb: 264.488 233MB 1thread base.hyper -> kops/s: 53.909 io_bytes/op: 2552.35 miss_ratio: 0.0440566 max_rss_mb: 241.984 233MB 1thread new.hyper -> kops/s: 62.792 io_bytes/op: 2549.79 miss_ratio: 0.044043 max_rss_mb: 241.922 233MB 1thread base -> kops/s: 1.197 io_bytes/op: 2.75173e+06 miss_ratio: 0.103093 max_rss_mb: 241.559 233MB 1thread new -> kops/s: 1.199 io_bytes/op: 2.73723e+06 miss_ratio: 0.10305 max_rss_mb: 240.93 233MB 32thread base.hyper -> kops/s: 1298.69 io_bytes/op: 2539.12 miss_ratio: 0.0440307 max_rss_mb: 371.418 233MB 32thread new.hyper -> kops/s: 1421.35 io_bytes/op: 2538.75 miss_ratio: 0.0440307 max_rss_mb: 347.273 233MB 32thread base -> kops/s: 9.693 io_bytes/op: 2.77304e+06 miss_ratio: 0.103745 max_rss_mb: 569.691 233MB 32thread new -> kops/s: 9.75 io_bytes/op: 2.77559e+06 miss_ratio: 0.103798 max_rss_mb: 552.82 1597MB 1thread base.hyper -> kops/s: 58.607 io_bytes/op: 1449.14 miss_ratio: 0.0249324 max_rss_mb: 1583.55 1597MB 1thread new.hyper -> kops/s: 69.6 io_bytes/op: 1434.89 miss_ratio: 0.0247167 max_rss_mb: 1584.02 1597MB 1thread base -> kops/s: 60.478 io_bytes/op: 1421.28 miss_ratio: 0.024452 max_rss_mb: 1589.45 1597MB 1thread new -> kops/s: 63.973 io_bytes/op: 1416.07 miss_ratio: 0.0243766 max_rss_mb: 1589.24 1597MB 32thread base.hyper -> kops/s: 1436.2 io_bytes/op: 1357.93 miss_ratio: 0.0235353 max_rss_mb: 1692.92 1597MB 32thread new.hyper -> kops/s: 1605.03 io_bytes/op: 1358.04 miss_ratio: 0.023538 max_rss_mb: 1702.78 1597MB 32thread base -> kops/s: 280.059 io_bytes/op: 1350.34 miss_ratio: 0.023289 max_rss_mb: 1675.36 1597MB 32thread new -> kops/s: 283.125 io_bytes/op: 1351.05 miss_ratio: 0.0232797 max_rss_mb: 1703.83 Almost uniformly improving over base revision, especially for hot paths with HyperClockCache, up to 12% higher throughput seen (1597MB, 32thread, hyper). The improvement for that is likely coming from much simplified code for providing context for secondary cache promotion (CreateCallback/CreateContext), and possibly from less branching in block_based_table_reader. And likely a small improvement from not reconstituting key for DeleterFn. Reviewed By: anand1976 Differential Revision: D42417818 Pulled By: pdillinger fbshipit-source-id: f86bfdd584dce27c028b151ba56818ad14f7a432 |
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Changyu Bi
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f02c708aa3 |
Consider range tombstone in compaction output file cutting (#10802)
Summary: This PR is the first step for Issue https://github.com/facebook/rocksdb/issues/4811. Currently compaction output files are cut at point keys, and the decision is made mainly in `CompactionOutputs::ShouldStopBefore()`. This makes it possible for range tombstones to cause large compactions that does not respect `max_compaction_bytes`. For example, we can have a large range tombstone that overlaps with too many files from the next level. Another example is when there is a gap between a range tombstone and another key. The first issue may be more acceptable, as a lot of data is deleted. This PR address the second issue by calling `ShouldStopBefore()` for range tombstone start keys. The main change is for `CompactionIterator` to emit range tombstone start keys to be processed by `CompactionOutputs`. A new `CompactionMergingIterator` is introduced and only used under `CompactionIterator` for this purpose. Further improvement after this PR include 1) cut compaction output at some grandparent boundary key instead of at the next point key or range tombstone start key and 2) cut compaction output file within a large range tombstone (it may be easier and reasonable to only do it for range tombstones at the end of a compaction output). Pull Request resolved: https://github.com/facebook/rocksdb/pull/10802 Test Plan: - added unit tests in db_range_del_test. - stress test: `python3 tools/db_crashtest.py whitebox --[simple|enable_ts] --verify_iterator_with_expected_state_one_in=5 --delrangepercent=5 --prefixpercent=2 --writepercent=58 --readpercen=21 --duration=36000 --range_deletion_width=1000000` Reviewed By: ajkr, jay-zhuang Differential Revision: D40308827 Pulled By: cbi42 fbshipit-source-id: a8fd6f70a3f09d0ef7a40e006f6c964bba8c00df |
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Peter Dillinger
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e079d562af |
Add a SecondaryCache::InsertSaved() API, use in CacheDumper impl (#10945)
Summary: Can simplify some ugly code in cache_dump_load_impl.cc by having an API in SecondaryCache that can directly consume persisted data. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10945 Test Plan: existing tests for CacheDumper, added basic unit test Reviewed By: anand1976 Differential Revision: D41231497 Pulled By: pdillinger fbshipit-source-id: b8ec993ef7d3e7efd68aae8602fd3f858da58068 |
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Peter Dillinger
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32520df1d9 |
Remove prototype FastLRUCache (#10954)
Summary: This was just a stepping stone to what eventually became HyperClockCache, and is now just more code to maintain. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10954 Test Plan: tests updated Reviewed By: akankshamahajan15 Differential Revision: D41310123 Pulled By: pdillinger fbshipit-source-id: 618ee148a1a0a29ee756ba8fe28359617b7cd67c |
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Peter Dillinger
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8367f0d2d7 |
Improve / refactor anonymous mmap capabilities (#10810)
Summary: The motivation for this change is a planned feature (related to HyperClockCache) that will depend on a large array that can essentially grow automatically, up to some bound, without the pointer address changing and with guaranteed zero-initialization of the data. Anonymous mmaps provide such functionality, and this change provides an internal API for that. The other existing use of anonymous mmap in RocksDB is for allocating in huge pages. That code and other related Arena code used some awkward non-RAII and pre-C++11 idioms, so I cleaned up much of that as well, with RAII, move semantics, constexpr, etc. More specifcs: * Minimize conditional compilation * Add Windows support for anonymous mmaps * Use std::deque instead of std::vector for more efficient bag Pull Request resolved: https://github.com/facebook/rocksdb/pull/10810 Test Plan: unit test added for new functionality Reviewed By: riversand963 Differential Revision: D40347204 Pulled By: pdillinger fbshipit-source-id: ca83fcc47e50fabf7595069380edd2954f4f879c |
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gitbw95
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6cd8133035 |
Fix an import issue in fbcode. (#10604)
Summary: This should fix an import issue detected in meta internal tests. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10604 Test Plan: Unit Tests. Reviewed By: hx235 Differential Revision: D39120414 Pulled By: gitbw95 fbshipit-source-id: dbd016d7f47b9f54aab5ea61e8d3cd79734f46af |
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Jay Zhuang
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d9e71fb2c5 |
Fix periodic_task unable to re-register the same task type (#10379)
Summary: Timer has a limitation that it cannot re-register a task with the same name, because the cancel only mark the task as invalid and wait for the Timer thread to clean it up later, before the task is cleaned up, the same task name cannot be added. Which makes the task option update likely to fail, which basically cancel and re-register the same task name. Change the periodic task name to a random unique id and store it in periodic_task_scheduler. Also refactor the `periodic_work` to `periodic_task` to make each job function as a `task`. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10379 Test Plan: unittests Reviewed By: ajkr Differential Revision: D38000615 Pulled By: jay-zhuang fbshipit-source-id: e4135f9422e3b53aaec8eda54f4e18ce633a279e |
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Levi Tamasi
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3f57d84af4 |
Introduce a dedicated class to represent blob values (#10571)
Summary: The patch introduces a new class called `BlobContents`, which represents a single uncompressed blob value. We currently use `std::string` for this purpose; `BlobContents` is somewhat smaller but the primary reason for a dedicated class is that it enables certain improvements and optimizations like eliding a copy when inserting a blob into the cache, using custom allocators, or more control over and better accounting of the memory usage of cached blobs (see https://github.com/facebook/rocksdb/issues/10484). (We plan to implement these in subsequent PRs.) Pull Request resolved: https://github.com/facebook/rocksdb/pull/10571 Test Plan: `make check` Reviewed By: riversand963 Differential Revision: D39000965 Pulled By: ltamasi fbshipit-source-id: f296eddf9dec4fc3e11cad525b462bdf63c78f96 |
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Levi Tamasi
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81388b36e0 |
Add support for wide-column point lookups (#10540)
Summary: The patch adds a new API `GetEntity` that can be used to perform wide-column point lookups. It also extends the `Get` code path and the `MemTable` / `MemTableList` and `Version` / `GetContext` logic accordingly so that wide-column entities can be served from both memtables and SSTs. If the result of a lookup is a wide-column entity (`kTypeWideColumnEntity`), it is passed to the application in deserialized form; if it is a plain old key-value (`kTypeValue`), it is presented as a wide-column entity with a single default (anonymous) column. (In contrast, regular `Get` returns plain old key-values as-is, and returns the value of the default column for wide-column entities, see https://github.com/facebook/rocksdb/issues/10483 .) The result of `GetEntity` is a self-contained `PinnableWideColumns` object. `PinnableWideColumns` contains a `PinnableSlice`, which either stores the underlying data in its own buffer or holds on to a cache handle. It also contains a `WideColumns` instance, which indexes the contents of the `PinnableSlice`, so applications can access the values of columns efficiently. There are several pieces of functionality which are currently not supported for wide-column entities: there is currently no `MultiGetEntity` or wide-column iterator; also, `Merge` and `GetMergeOperands` are not supported, and there is no `GetEntity` implementation for read-only and secondary instances. We plan to implement these in future PRs. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10540 Test Plan: `make check` Reviewed By: akankshamahajan15 Differential Revision: D38847474 Pulled By: ltamasi fbshipit-source-id: 42311a34ccdfe88b3775e847a5e2a5296e002b5b |
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Gang Liao
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0b6bc101ba |
Charge blob cache usage against the global memory limit (#10321)
Summary: To help service owners to manage their memory budget effectively, we have been working towards counting all major memory users inside RocksDB towards a single global memory limit (see e.g. https://github.com/facebook/rocksdb/wiki/Write-Buffer-Manager#cost-memory-used-in-memtable-to-block-cache). The global limit is specified by the capacity of the block-based table's block cache, and is technically implemented by inserting dummy entries ("reservations") into the block cache. The goal of this task is to support charging the memory usage of the new blob cache against this global memory limit when the backing cache of the blob cache and the block cache are different. This PR is a part of https://github.com/facebook/rocksdb/issues/10156 Pull Request resolved: https://github.com/facebook/rocksdb/pull/10321 Reviewed By: ltamasi Differential Revision: D37913590 Pulled By: gangliao fbshipit-source-id: eaacf23907f82dc7d18964a3f24d7039a2937a72 |
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Jay Zhuang
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a3acf2ef87 |
Add seqno to time mapping (#10338)
Summary: Which will be used for tiered storage to preclude hot data from compacting to the cold tier (the last level). Internally, adding seqno to time mapping. A periodic_task is scheduled to record the current_seqno -> current_time in certain cadence. When memtable flush, the mapping informaiton is stored in sstable property. During compaction, the mapping information are merged and get the approximate time of sequence number, which is used to determine if a key is recently inserted or not and preclude it from the last level if it's recently inserted (within the `preclude_last_level_data_seconds`). Pull Request resolved: https://github.com/facebook/rocksdb/pull/10338 Test Plan: CI Reviewed By: siying Differential Revision: D37810187 Pulled By: jay-zhuang fbshipit-source-id: 6953be7a18a99de8b1cb3b162d712f79c2b4899f |
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Jay Zhuang
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6ce0b2ca34 |
Tiered Compaction: per key placement support (#9964)
Summary: Support per_key_placement for last level compaction, which will be used for tiered compaction. * compaction iterator reports which level a key should output to; * compaction get the output level information and check if it's safe to output the data to penultimate level; * all compaction output files will be installed. * extra internal compaction stats added for penultimate level. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9964 Test Plan: * Unittest * db_bench, no significate difference: https://gist.github.com/jay-zhuang/3645f8fb97ec0ab47c10704bb39fd6e4 * microbench manual compaction no significate difference: https://gist.github.com/jay-zhuang/ba679b3e89e24992615ee9eef310e6dd * run the db_stress multiple times (not covering the new feature) looks good (internal: https://fburl.com/sandcastle/9w84pp2m) Reviewed By: ajkr Differential Revision: D36249494 Pulled By: jay-zhuang fbshipit-source-id: a96da57c8031c1df83e4a7a8567b657a112b80a3 |
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Levi Tamasi
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c73d2a9d18 |
Add API for writing wide-column entities (#10242)
Summary: The patch builds on https://github.com/facebook/rocksdb/pull/9915 and adds a new API called `PutEntity` that can be used to write a wide-column entity to the database. The new API is added to both `DB` and `WriteBatch`. Note that currently there is no way to retrieve these entities; more precisely, all read APIs (`Get`, `MultiGet`, and iterator) return `NotSupported` when they encounter a wide-column entity that is required to answer a query. Read-side support (as well as other missing functionality like `Merge`, compaction filter, and timestamp support) will be added in later PRs. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10242 Test Plan: `make check` Reviewed By: riversand963 Differential Revision: D37369748 Pulled By: ltamasi fbshipit-source-id: 7f5e412359ed7a400fd80b897dae5599dbcd685d |
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Gang Liao
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c965c9ef65 |
Read blob from blob cache if exists when GetBlob() (#10178)
Summary: There is currently no caching mechanism for blobs, which is not ideal especially when the database resides on remote storage (where we cannot rely on the OS page cache). As part of this task, we would like to make it possible for the application to configure a blob cache. In this task, we added a new abstraction layer `BlobSource` to retrieve blobs from either blob cache or raw blob file. Note: For simplicity, the current PR only includes `GetBlob()`. `MultiGetBlob()` will be included in the next PR. This PR is a part of https://github.com/facebook/rocksdb/issues/10156 Pull Request resolved: https://github.com/facebook/rocksdb/pull/10178 Reviewed By: ltamasi Differential Revision: D37250507 Pulled By: gangliao fbshipit-source-id: 3fc4a55a0cea955a3147bdc7dba06430e377259b |
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Peter Dillinger
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1aac814578 |
Use optimized folly DistributedMutex in LRUCache when available (#10179)
Summary: folly DistributedMutex is faster than standard mutexes though imposes some static obligations on usage. See https://github.com/facebook/folly/blob/main/folly/synchronization/DistributedMutex.h for details. Here we use this alternative for our Cache implementations (especially LRUCache) for better locking performance, when RocksDB is compiled with folly. Also added information about which distributed mutex implementation is being used to cache_bench output and to DB LOG. Intended follow-up: * Use DMutex in more places, perhaps improving API to support non-scoped locking * Fix linking with fbcode compiler (needs ROCKSDB_NO_FBCODE=1 currently) Credit: Thanks Siying for reminding me about this line of work that was previously left unfinished. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10179 Test Plan: for correctness, existing tests. CircleCI config updated. Also Meta-internal buck build updated. For performance, ran simultaneous before & after cache_bench. Out of three comparison runs, the middle improvement to ops/sec was +21%: Baseline: USE_CLANG=1 DEBUG_LEVEL=0 make -j24 cache_bench (fbcode compiler) ``` Complete in 20.201 s; Rough parallel ops/sec = 1584062 Thread ops/sec = 107176 Operation latency (ns): Count: 32000000 Average: 9257.9421 StdDev: 122412.04 Min: 134 Median: 3623.0493 Max: 56918500 Percentiles: P50: 3623.05 P75: 10288.02 P99: 30219.35 P99.9: 683522.04 P99.99: 7302791.63 ``` New: (add USE_FOLLY=1) ``` Complete in 16.674 s; Rough parallel ops/sec = 1919135 (+21%) Thread ops/sec = 135487 Operation latency (ns): Count: 32000000 Average: 7304.9294 StdDev: 108530.28 Min: 132 Median: 3777.6012 Max: 91030902 Percentiles: P50: 3777.60 P75: 10169.89 P99: 24504.51 P99.9: 59721.59 P99.99: 1861151.83 ``` Reviewed By: anand1976 Differential Revision: D37182983 Pulled By: pdillinger fbshipit-source-id: a17eb05f25b832b6a2c1356f5c657e831a5af8d1 |
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Peter Dillinger
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126c223714 |
Remove deprecated block-based filter (#10184)
Summary: In https://github.com/facebook/rocksdb/issues/9535, release 7.0, we hid the old block-based filter from being created using the public API, because of its inefficiency. Although we normally maintain read compatibility on old DBs forever, filters are not required for reading a DB, only for optimizing read performance. Thus, it should be acceptable to remove this code and the substantial maintenance burden it carries as useful features are developed and validated (such as user timestamp). This change completely removes the code for reading and writing the old block-based filters, net removing about 1370 lines of code no longer needed. Options removed from testing / benchmarking tools. The prior existence is only evident in a couple of places: * `CacheEntryRole::kDeprecatedFilterBlock` - We can update this public API enum in a major release to minimize source code incompatibilities. * A warning is logged when an old table file is opened that used the old block-based filter. This is provided as a courtesy, and would be a pain to unit test, so manual testing should suffice. Unfortunately, sst_dump does not tell you whether a file uses block-based filter, and the structure of the code makes it very difficult to fix. * To detect that case, `kObsoleteFilterBlockPrefix` (renamed from `kFilterBlockPrefix`) for metaindex is maintained (for now). Other notes: * In some cases where numbers are associated with filter configurations, we have had to update the assigned numbers so that they all correspond to something that exists. * Fixed potential stat counting bug by assuming `filter_checked = false` for cases like `filter == nullptr` rather than assuming `filter_checked = true` * Removed obsolete `block_offset` and `prefix_extractor` parameters from several functions. * Removed some unnecessary checks `if (!table_prefix_extractor() && !prefix_extractor)` because the caller guarantees the prefix extractor exists and is compatible Pull Request resolved: https://github.com/facebook/rocksdb/pull/10184 Test Plan: tests updated, manually test new warning in LOG using base version to generate a DB Reviewed By: riversand963 Differential Revision: D37212647 Pulled By: pdillinger fbshipit-source-id: 06ee020d8de3b81260ffc36ad0c1202cbf463a80 |
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Yanqin Jin
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1777e5f7e9 |
Snapshots with user-specified timestamps (#9879)
Summary: In RocksDB, keys are associated with (internal) sequence numbers which denote when the keys are written to the database. Sequence numbers in different RocksDB instances are unrelated, thus not comparable. It is nice if we can associate sequence numbers with their corresponding actual timestamps. One thing we can do is to support user-defined timestamp, which allows the applications to specify the format of custom timestamps and encode a timestamp with each key. More details can be found at https://github.com/facebook/rocksdb/wiki/User-defined-Timestamp-%28Experimental%29. This PR provides a different but complementary approach. We can associate rocksdb snapshots (defined in https://github.com/facebook/rocksdb/blob/7.2.fb/include/rocksdb/snapshot.h#L20) with **user-specified** timestamps. Since a snapshot is essentially an object representing a sequence number, this PR establishes a bi-directional mapping between sequence numbers and timestamps. In the past, snapshots are usually taken by readers. The current super-version is grabbed, and a `rocksdb::Snapshot` object is created with the last published sequence number of the super-version. You can see that the reader actually has no good idea of what timestamp to assign to this snapshot, because by the time the `GetSnapshot()` is called, an arbitrarily long period of time may have already elapsed since the last write, which is when the last published sequence number is written. This observation motivates the creation of "timestamped" snapshots on the write path. Currently, this functionality is exposed only to the layer of `TransactionDB`. Application can tell RocksDB to create a snapshot when a transaction commits, effectively associating the last sequence number with a timestamp. It is also assumed that application will ensure any two snapshots with timestamps should satisfy the following: ``` snapshot1.seq < snapshot2.seq iff. snapshot1.ts < snapshot2.ts ``` If the application can guarantee that when a reader takes a timestamped snapshot, there is no active writes going on in the database, then we also allow the user to use a new API `TransactionDB::CreateTimestampedSnapshot()` to create a snapshot with associated timestamp. Code example ```cpp // Create a timestamped snapshot when committing transaction. txn->SetCommitTimestamp(100); txn->SetSnapshotOnNextOperation(); txn->Commit(); // A wrapper API for convenience Status Transaction::CommitAndTryCreateSnapshot( std::shared_ptr<TransactionNotifier> notifier, TxnTimestamp ts, std::shared_ptr<const Snapshot>* ret); // Create a timestamped snapshot if caller guarantees no concurrent writes std::pair<Status, std::shared_ptr<const Snapshot>> snapshot = txn_db->CreateTimestampedSnapshot(100); ``` The snapshots created in this way will be managed by RocksDB with ref-counting and potentially shared with other readers. We provide the following APIs for readers to retrieve a snapshot given a timestamp. ```cpp // Return the timestamped snapshot correponding to given timestamp. If ts is // kMaxTxnTimestamp, then we return the latest timestamped snapshot if present. // Othersise, we return the snapshot whose timestamp is equal to `ts`. If no // such snapshot exists, then we return null. std::shared_ptr<const Snapshot> TransactionDB::GetTimestampedSnapshot(TxnTimestamp ts) const; // Return the latest timestamped snapshot if present. std::shared_ptr<const Snapshot> TransactionDB::GetLatestTimestampedSnapshot() const; ``` We also provide two additional APIs for stats collection and reporting purposes. ```cpp Status TransactionDB::GetAllTimestampedSnapshots( std::vector<std::shared_ptr<const Snapshot>>& snapshots) const; // Return timestamped snapshots whose timestamps fall in [ts_lb, ts_ub) and store them in `snapshots`. Status TransactionDB::GetTimestampedSnapshots( TxnTimestamp ts_lb, TxnTimestamp ts_ub, std::vector<std::shared_ptr<const Snapshot>>& snapshots) const; ``` To prevent the number of timestamped snapshots from growing infinitely, we provide the following API to release timestamped snapshots whose timestamps are older than or equal to a given threshold. ```cpp void TransactionDB::ReleaseTimestampedSnapshotsOlderThan(TxnTimestamp ts); ``` Before shutdown, RocksDB will release all timestamped snapshots. Comparison with user-defined timestamp and how they can be combined: User-defined timestamp persists every key with a timestamp, while timestamped snapshots maintain a volatile mapping between snapshots (sequence numbers) and timestamps. Different internal keys with the same user key but different timestamps will be treated as different by compaction, thus a newer version will not hide older versions (with smaller timestamps) unless they are eligible for garbage collection. In contrast, taking a timestamped snapshot at a certain sequence number and timestamp prevents all the keys visible in this snapshot from been dropped by compaction. Here, visible means (seq < snapshot and most recent). The timestamped snapshot supports the semantics of reading at an exact point in time. Timestamped snapshots can also be used with user-defined timestamp. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9879 Test Plan: ``` make check TEST_TMPDIR=/dev/shm make crash_test_with_txn ``` Reviewed By: siying Differential Revision: D35783919 Pulled By: riversand963 fbshipit-source-id: 586ad905e169189e19d3bfc0cb0177a7239d1bd4 |
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Levi Tamasi
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e9c74bc474 |
Add wide column serialization primitives (#9915)
Summary: The patch adds some low-level logic that can be used to serialize/deserialize a sorted vector of wide columns to/from a simple binary searchable string representation. Currently, there is no user-facing API; this will be implemented in subsequent stages. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9915 Test Plan: `make check` Reviewed By: siying Differential Revision: D35978076 Pulled By: ltamasi fbshipit-source-id: 33f5f6628ec3bcd8c8beab363b1978ac047a8788 |
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Yu Zhang
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16bdb1f999 |
Add timestamp support to DBImplReadOnly (#10004)
Summary: This PR adds timestamp support to a read only DB instance opened as `DBImplReadOnly`. A follow up PR will add the same support to `CompactedDBImpl`. With this, read only database has these timestamp related APIs: `ReadOptions.timestamp` : read should return the latest data visible to this specified timestamp `Iterator::timestamp()` : returns the timestamp associated with the key, value `DB:Get(..., std::string* timestamp)` : returns the timestamp associated with the key, value in `timestamp` Test plan (on devserver): ``` $COMPILE_WITH_ASAN=1 make -j24 all $./db_with_timestamp_basic_test --gtest_filter=DBBasicTestWithTimestamp.ReadOnlyDB* ``` Pull Request resolved: https://github.com/facebook/rocksdb/pull/10004 Reviewed By: riversand963 Differential Revision: D36434422 Pulled By: jowlyzhang fbshipit-source-id: 5d949e65b1ffb845758000e2b310fdd4aae71cfb |
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anand76
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57997ddaaf |
Multi file concurrency in MultiGet using coroutines and async IO (#9968)
Summary: This PR implements a coroutine version of batched MultiGet in order to concurrently read from multiple SST files in a level using async IO, thus reducing the latency of the MultiGet. The API from the user perspective is still synchronous and single threaded, with the RocksDB part of the processing happening in the context of the caller's thread. In Version::MultiGet, the decision is made whether to call synchronous or coroutine code. A good way to review this PR is to review the first 4 commits in order - de773b3, 70c2f70, 10b50e1, and 377a597 - before reviewing the rest. TODO: 1. Figure out how to build it in CircleCI (requires some dependencies to be installed) 2. Do some stress testing with coroutines enabled No regression in synchronous MultiGet between this branch and main - ``` ./db_bench -use_existing_db=true --db=/data/mysql/rocksdb/prefix_scan -benchmarks="readseq,multireadrandom" -key_size=32 -value_size=512 -num=5000000 -batch_size=64 -multiread_batched=true -use_direct_reads=false -duration=60 -ops_between_duration_checks=1 -readonly=true -adaptive_readahead=true -threads=16 -cache_size=10485760000 -async_io=false -multiread_stride=40000 -statistics ``` Branch - ```multireadrandom : 4.025 micros/op 3975111 ops/sec 60.001 seconds 238509056 operations; 2062.3 MB/s (14767808 of 14767808 found)``` Main - ```multireadrandom : 3.987 micros/op 4013216 ops/sec 60.001 seconds 240795392 operations; 2082.1 MB/s (15231040 of 15231040 found)``` More benchmarks in various scenarios are given below. The measurements were taken with ```async_io=false``` (no coroutines) and ```async_io=true``` (use coroutines). For an IO bound workload (with every key requiring an IO), the coroutines version shows a clear benefit, being ~2.6X faster. For CPU bound workloads, the coroutines version has ~6-15% higher CPU utilization, depending on how many keys overlap an SST file. 1. Single thread IO bound workload on remote storage with sparse MultiGet batch keys (~1 key overlap/file) - No coroutines - ```multireadrandom : 831.774 micros/op 1202 ops/sec 60.001 seconds 72136 operations; 0.6 MB/s (72136 of 72136 found)``` Using coroutines - ```multireadrandom : 318.742 micros/op 3137 ops/sec 60.003 seconds 188248 operations; 1.6 MB/s (188248 of 188248 found)``` 2. Single thread CPU bound workload (all data cached) with ~1 key overlap/file - No coroutines - ```multireadrandom : 4.127 micros/op 242322 ops/sec 60.000 seconds 14539384 operations; 125.7 MB/s (14539384 of 14539384 found)``` Using coroutines - ```multireadrandom : 4.741 micros/op 210935 ops/sec 60.000 seconds 12656176 operations; 109.4 MB/s (12656176 of 12656176 found)``` 3. Single thread CPU bound workload with ~2 key overlap/file - No coroutines - ```multireadrandom : 3.717 micros/op 269000 ops/sec 60.000 seconds 16140024 operations; 139.6 MB/s (16140024 of 16140024 found)``` Using coroutines - ```multireadrandom : 4.146 micros/op 241204 ops/sec 60.000 seconds 14472296 operations; 125.1 MB/s (14472296 of 14472296 found)``` 4. CPU bound multi-threaded (16 threads) with ~4 key overlap/file - No coroutines - ```multireadrandom : 4.534 micros/op 3528792 ops/sec 60.000 seconds 211728728 operations; 1830.7 MB/s (12737024 of 12737024 found) ``` Using coroutines - ```multireadrandom : 4.872 micros/op 3283812 ops/sec 60.000 seconds 197030096 operations; 1703.6 MB/s (12548032 of 12548032 found) ``` Pull Request resolved: https://github.com/facebook/rocksdb/pull/9968 Reviewed By: akankshamahajan15 Differential Revision: D36348563 Pulled By: anand1976 fbshipit-source-id: c0ce85a505fd26ebfbb09786cbd7f25202038696 |
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Peter Dillinger
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bb87164db3 |
Fork and simplify LRUCache for developing enhancements (#9917)
Summary: To support a project to prototype and evaluate algorithmic enhancments and alternatives to LRUCache, here I have separated out LRUCache into internal-only "FastLRUCache" and cut it down to essentials, so that details like secondary cache handling and priorities do not interfere with prototyping. These can be re-integrated later as needed, along with refactoring to minimize code duplication (which would slow down prototyping for now). Pull Request resolved: https://github.com/facebook/rocksdb/pull/9917 Test Plan: unit tests updated to ensure basic functionality has (likely) been preserved Reviewed By: anand1976 Differential Revision: D35995554 Pulled By: pdillinger fbshipit-source-id: d67b20b7ada3b5d3bfe56d897a73885894a1d9db |
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Peter Dillinger
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9d0cae7104 |
Eliminate unnecessary (slow) block cache Ref()ing in MultiGet (#9899)
Summary: When MultiGet() determines that multiple query keys can be served by examining the same data block in block cache (one Lookup()), each PinnableSlice referring to data in that data block needs to hold on to the block in cache so that they can be released at arbitrary times by the API user. Historically this is accomplished with extra calls to Ref() on the Handle from Lookup(), with each PinnableSlice cleanup calling Release() on the Handle, but this creates extra contention on the block cache for the extra Ref()s and Release()es, especially because they hit the same cache shard repeatedly. In the case of merge operands (possibly more cases?), the problem was compounded by doing an extra Ref()+eventual Release() for each merge operand for a key reusing a block (which could be the same key!), rather than one Ref() per key. (Note: the non-shared case with `biter` was already one per key.) This change optimizes MultiGet not to rely on these extra, contentious Ref()+Release() calls by instead, in the shared block case, wrapping the cache Release() cleanup in a refcounted object referenced by the PinnableSlices, such that after the last wrapped reference is released, the cache entry is Release()ed. Relaxed atomic refcounts should be much faster than mutex-guarded Ref() and Release(), and much less prone to a performance cliff when MultiGet() does a lot of block sharing. Note that I did not use std::shared_ptr, because that would require an extra indirection object (shared_ptr itself new/delete) in order to associate a ref increment/decrement with a Cleanable cleanup entry. (If I assumed it was the size of two pointers, I could do some hackery to make it work without the extra indirection, but that's too fragile.) Some details: * Fixed (removed) extra block cache tracing entries in cases of cache entry reuse in MultiGet, but it's likely that in some other cases traces are missing (XXX comment inserted) * Moved existing implementations for cleanable.h from iterator.cc to new cleanable.cc * Improved API comments on Cleanable * Added a public SharedCleanablePtr class to cleanable.h in case others could benefit from the same pattern (potentially many Cleanables and/or smart pointers referencing a shared Cleanable) * Add a typedef for MultiGetContext::Mask * Some variable renaming for clarity Pull Request resolved: https://github.com/facebook/rocksdb/pull/9899 Test Plan: Added unit tests for SharedCleanablePtr. Greatly enhanced ability of existing tests to detect cache use-after-free. * Release PinnableSlices from MultiGet as they are read rather than in bulk (in db_test_util wrapper). * In ASAN build, default to using a trivially small LRUCache for block_cache so that entries are immediately erased when unreferenced. (Updated two tests that depend on caching.) New ASAN testsuite running time seems OK to me. If I introduce a bug into my implementation where we skip the shared cleanups on block reuse, ASAN detects the bug in `db_basic_test *MultiGet*`. If I remove either of the above testing enhancements, the bug is not detected. Consider for follow-up work: manipulate or randomize ordering of PinnableSlice use and release from MultiGet db_test_util wrapper. But in typical cases, natural ordering gives pretty good functional coverage. Performance test: In the extreme (but possible) case of MultiGetting the same or adjacent keys in a batch, throughput can improve by an order of magnitude. `./db_bench -benchmarks=multireadrandom -db=/dev/shm/testdb -readonly -num=5 -duration=10 -threads=20 -multiread_batched -batch_size=200` Before ops/sec, num=5: 1,384,394 Before ops/sec, num=500: 6,423,720 After ops/sec, num=500: 10,658,794 After ops/sec, num=5: 16,027,257 Also note that previously, with high parallelism, having query keys concentrated in a single block was worse than spreading them out a bit. Now concentrated in a single block is faster than spread out, which is hopefully consistent with natural expectation. Random query performance: with num=1000000, over 999 x 10s runs running before & after simultaneously (each -threads=12): Before: multireadrandom [AVG 999 runs] : 1088699 (± 7344) ops/sec; 120.4 (± 0.8 ) MB/sec After: multireadrandom [AVG 999 runs] : 1090402 (± 7230) ops/sec; 120.6 (± 0.8 ) MB/sec Possibly better, possibly in the noise. Reviewed By: anand1976 Differential Revision: D35907003 Pulled By: pdillinger fbshipit-source-id: bbd244d703649a8ca12d476f2d03853ed9d1a17e |
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sdong
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4f9c0fd083 |
Add Aggregation Merge Operator (#9780)
Summary: Add a merge operator that allows users to register specific aggregation function so that they can does aggregation based per key using different aggregation types. See comments of function CreateAggMergeOperator() for actual usage. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9780 Test Plan: Add a unit test to coverage various cases. Reviewed By: ltamasi Differential Revision: D35267444 fbshipit-source-id: 5b02f31c4f3e17e96dd4025cdc49fca8c2868628 |
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Peter Dillinger
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efd035164b |
Meta-internal folly integration with F14FastMap (#9546)
Summary: Especially after updating to C++17, I don't see a compelling case for *requiring* any folly components in RocksDB. I was able to purge the existing hard dependencies, and it can be quite difficult to strip out non-trivial components from folly for use in RocksDB. (The prospect of doing that on F14 has changed my mind on the best approach here.) But this change creates an optional integration where we can plug in components from folly at compile time, starting here with F14FastMap to replace std::unordered_map when possible (probably no public APIs for example). I have replaced the biggest CPU users of std::unordered_map with compile-time pluggable UnorderedMap which will use F14FastMap when USE_FOLLY is set. USE_FOLLY is always set in the Meta-internal buck build, and a simulation of that is in the Makefile for public CI testing. A full folly build is not needed, but checking out the full folly repo is much simpler for getting the dependency, and anything else we might want to optionally integrate in the future. Some picky details: * I don't think the distributed mutex stuff is actually used, so it was easy to remove. * I implemented an alternative to `folly::constexpr_log2` (which is much easier in C++17 than C++11) so that I could pull out the hard dependencies on `ConstexprMath.h` * I had to add noexcept move constructors/operators to some types to make F14's complainUnlessNothrowMoveAndDestroy check happy, and I added a macro to make that easier in some common cases. * Updated Meta-internal buck build to use folly F14Map (always) No updates to HISTORY.md nor INSTALL.md as this is not (yet?) considered a production integration for open source users. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9546 Test Plan: CircleCI tests updated so that a couple of them use folly. Most internal unit & stress/crash tests updated to use Meta-internal latest folly. (Note: they should probably use buck but they currently use Makefile.) Example performance improvement: when filter partitions are pinned in cache, they are tracked by PartitionedFilterBlockReader::filter_map_ and we can build a test that exercises that heavily. Build DB with ``` TEST_TMPDIR=/dev/shm/rocksdb ./db_bench -benchmarks=fillrandom -num=10000000 -disable_wal=1 -write_buffer_size=30000000 -bloom_bits=16 -compaction_style=2 -fifo_compaction_max_table_files_size_mb=10000 -fifo_compaction_allow_compaction=0 -partition_index_and_filters ``` and test with (simultaneous runs with & without folly, ~20 times each to see convergence) ``` TEST_TMPDIR=/dev/shm/rocksdb ./db_bench_folly -readonly -use_existing_db -benchmarks=readrandom -num=10000000 -bloom_bits=16 -compaction_style=2 -fifo_compaction_max_table_files_size_mb=10000 -fifo_compaction_allow_compaction=0 -partition_index_and_filters -duration=40 -pin_l0_filter_and_index_blocks_in_cache ``` Average ops/s no folly: 26229.2 Average ops/s with folly: 26853.3 (+2.4%) Reviewed By: ajkr Differential Revision: D34181736 Pulled By: pdillinger fbshipit-source-id: ffa6ad5104c2880321d8a1aa7187e00ab0d02e94 |