Commit Graph

400 Commits

Author SHA1 Message Date
Changyu Bi 1c7652fcef Introduce a WriteBatchWithIndex-based implementation of ReadOnlyMemTable (#13123)
Summary:
introduce the class WBWIMemTable that implements ReadOnlyMemTable interface with data stored in a WriteBatchWithIndex object.

This PR implements the main read path: Get, MultiGet and Iterator. It only supports Put, Delete and SingleDelete operations for now. All the keys in the WBWIMemTable will be assigned a global sequence number through WBWIMemTable::SetGlobalSequenceNumber().

Planned follow up PRs:
- Create WBWIMemTable with a transaction's WBWI and ingest it into a DB during Transaction::Commit()
- Support for Merge. This will be more complicated since we can have multiple updates with the same user key for Merge.
- Support for other operations like WideColumn and other ReadOnlyMemTable methods.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/13123

Test Plan: * A mini-stress test for the read path is added as a new unit test

Reviewed By: jowlyzhang

Differential Revision: D65633419

Pulled By: cbi42

fbshipit-source-id: 0684fe47260b41f51ca39c300eb72ca5bc9c5a3b
2024-11-12 09:27:11 -08:00
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
2024-06-22 15:15:02 -07:00
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
2024-06-18 16:16:09 -07:00
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
2024-06-18 10:51:29 -07:00
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
2024-04-19 19:13:31 -07:00
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
2024-04-11 11:34:04 -07:00
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
2024-04-02 21:23:06 -07:00
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
2024-03-12 12:42:08 -07:00
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
2024-03-05 10:22:43 -08:00
Neil Ramaswamy 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
2024-01-17 17:51:36 -08:00
Radek Hubner 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
2023-12-18 13:43:01 -08:00
Radek Hubner 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
2023-11-16 15:46:31 -08:00
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
2023-11-06 07:38:42 -08:00
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
2023-10-27 15:56:48 -07:00
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
2023-10-10 11:07:33 -07:00
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
2023-09-29 08:54:50 -07:00
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
2023-09-21 20:30:53 -07:00
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
2023-08-30 12:45:52 -07:00
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
2023-05-22 14:28:58 -07:00
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
2023-05-18 13:25:01 -07:00
Hui Xiao 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
2023-05-18 09:44:15 -07:00
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
2023-03-18 09:51:58 -07:00
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
2023-03-17 20:23:49 -07:00
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
2023-03-15 17:51:44 -07:00
Changyu Bi 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
2023-02-22 12:28:18 -08:00
Peter Dillinger 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
2023-02-08 20:14:57 -08:00
Changyu Bi f515d9d203 Revert #10802 Consider range tombstone in compaction output file cutting (#11089)
Summary:
This reverts commit f02c708aa3 since it introduced several bugs (see https://github.com/facebook/rocksdb/issues/11078 and https://github.com/facebook/rocksdb/issues/11067 for attempts to fix them) and that I do not have a high confidence to fix all of them and ensure no further ones before the next release branch cut. There are also come existing issue found during bug fixing. We will work on it and try to merge it to the release after.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11089

Test Plan: existing CI.

Reviewed By: ajkr

Differential Revision: D42505972

Pulled By: cbi42

fbshipit-source-id: 2f66dcde6b85dc94977b317c2ce513872cfbc153
2023-01-13 12:28:21 -08:00
Peter Dillinger 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
2023-01-11 14:20:40 -08:00
Changyu Bi 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
2022-12-15 09:11:54 -08:00
Peter Dillinger 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
2022-11-21 16:17:36 -08:00
Peter Dillinger 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
2022-11-16 10:15:55 -08:00
Peter Dillinger 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
2022-10-17 17:10:16 -07:00
gitbw95 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
2022-08-29 21:09:36 -07:00
Jay Zhuang 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
2022-08-25 18:52:37 -07:00
Levi Tamasi 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
2022-08-25 16:45:48 -07:00
Levi Tamasi 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
2022-08-19 11:51:12 -07:00
Gang Liao 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
2022-07-18 23:26:57 -07:00
Jay Zhuang 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
2022-07-14 21:49:34 -07:00
Jay Zhuang 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
2022-07-13 20:54:49 -07:00
Levi Tamasi 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
2022-06-25 15:30:47 -07:00
Gang Liao 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
2022-06-17 15:22:59 -07:00
Peter Dillinger 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
2022-06-17 13:08:45 -07:00
Peter Dillinger 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
2022-06-16 15:51:33 -07:00
Yanqin Jin 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
2022-06-10 16:07:03 -07:00
Levi Tamasi 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
2022-06-03 20:54:48 -07:00
Yu Zhang 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
2022-05-19 18:39:41 -07:00
anand76 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
2022-05-19 15:36:27 -07:00
Peter Dillinger 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
2022-05-03 12:32:02 -07:00
Peter Dillinger 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
2022-04-26 21:59:24 -07:00
sdong 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
2022-04-15 23:24:05 -07:00