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3 commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
Alan Paxton
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d9a441113e |
JNI get_helper code sharing / multiGet() use efficient batch C++ support (#12344)
Summary: Implement RAII-based helpers for JNIGet() and multiGet() Replace JNI C++ helpers `rocksdb_get_helper, rocksdb_get_helper_direct`, `multi_get_helper`, `multi_get_helper_direct`, `multi_get_helper_release_keys`, `txn_get_helper`, and `txn_multi_get_helper`. The model is to entirely do away with a single helper, instead a number of utility methods allow each separate JNI `Get()` and `MultiGet()` method to organise their parameters efficiently, then call the underlying C++ `db->Get()`, `db->MultiGet()`, `txn->Get()`, or `txn->MultiGet()` method itself, and use further utilities to retrieve results. Roughly speaking: * get keys into C++ form * Call C++ Get() * get results and status into Java form We achieve a useful performance gain as part of this work; by using the updated C++ multiGet we immediately pick up its performance gains (batch improvements to multiGet C++ were previously implemented, but not until now used by Java/JNI). multiGetBB already uses the batched C++ multiGet(), and all other benchmarks show consistent improvement after the changes: ## Before: ``` Benchmark (columnFamilyTestType) (keyCount) (keySize) (multiGetSize) (valueSize) Mode Cnt Score Error Units MultiGetNewBenchmarks.multiGetBB200 no_column_family 10000 1024 100 256 thrpt 25 5315.459 ± 20.465 ops/s MultiGetNewBenchmarks.multiGetBB200 no_column_family 10000 1024 100 1024 thrpt 25 5673.115 ± 78.299 ops/s MultiGetNewBenchmarks.multiGetBB200 no_column_family 10000 1024 100 4096 thrpt 25 2616.860 ± 46.994 ops/s MultiGetNewBenchmarks.multiGetBB200 no_column_family 10000 1024 100 16384 thrpt 25 1700.058 ± 24.034 ops/s MultiGetNewBenchmarks.multiGetBB200 no_column_family 10000 1024 100 65536 thrpt 25 791.171 ± 13.955 ops/s MultiGetNewBenchmarks.multiGetList10 no_column_family 10000 1024 100 256 thrpt 25 6129.929 ± 94.200 ops/s MultiGetNewBenchmarks.multiGetList10 no_column_family 10000 1024 100 1024 thrpt 25 7012.405 ± 97.886 ops/s MultiGetNewBenchmarks.multiGetList10 no_column_family 10000 1024 100 4096 thrpt 25 2799.014 ± 39.352 ops/s MultiGetNewBenchmarks.multiGetList10 no_column_family 10000 1024 100 16384 thrpt 25 1417.205 ± 22.272 ops/s MultiGetNewBenchmarks.multiGetList10 no_column_family 10000 1024 100 65536 thrpt 25 655.594 ± 13.050 ops/s MultiGetNewBenchmarks.multiGetListExplicitCF20 no_column_family 10000 1024 100 256 thrpt 25 6147.247 ± 82.711 ops/s MultiGetNewBenchmarks.multiGetListExplicitCF20 no_column_family 10000 1024 100 1024 thrpt 25 7004.213 ± 79.251 ops/s MultiGetNewBenchmarks.multiGetListExplicitCF20 no_column_family 10000 1024 100 4096 thrpt 25 2715.154 ± 110.017 ops/s MultiGetNewBenchmarks.multiGetListExplicitCF20 no_column_family 10000 1024 100 16384 thrpt 25 1408.070 ± 31.714 ops/s MultiGetNewBenchmarks.multiGetListExplicitCF20 no_column_family 10000 1024 100 65536 thrpt 25 623.829 ± 57.374 ops/s MultiGetNewBenchmarks.multiGetListRandomCF30 no_column_family 10000 1024 100 256 thrpt 25 6119.243 ± 116.313 ops/s MultiGetNewBenchmarks.multiGetListRandomCF30 no_column_family 10000 1024 100 1024 thrpt 25 6931.873 ± 128.094 ops/s MultiGetNewBenchmarks.multiGetListRandomCF30 no_column_family 10000 1024 100 4096 thrpt 25 2678.253 ± 39.113 ops/s MultiGetNewBenchmarks.multiGetListRandomCF30 no_column_family 10000 1024 100 16384 thrpt 25 1337.384 ± 19.500 ops/s MultiGetNewBenchmarks.multiGetListRandomCF30 no_column_family 10000 1024 100 65536 thrpt 25 625.596 ± 14.525 ops/s ``` ## After: ``` Benchmark (columnFamilyTestType) (keyCount) (keySize) (multiGetSize) (valueSize) Mode Cnt Score Error Units MultiGetBenchmarks.multiGetBB200 no_column_family 10000 1024 100 256 thrpt 25 5191.074 ± 78.250 ops/s MultiGetBenchmarks.multiGetBB200 no_column_family 10000 1024 100 1024 thrpt 25 5378.692 ± 260.682 ops/s MultiGetBenchmarks.multiGetBB200 no_column_family 10000 1024 100 4096 thrpt 25 2590.183 ± 34.844 ops/s MultiGetBenchmarks.multiGetBB200 no_column_family 10000 1024 100 16384 thrpt 25 1634.793 ± 34.022 ops/s MultiGetBenchmarks.multiGetBB200 no_column_family 10000 1024 100 65536 thrpt 25 786.455 ± 8.462 ops/s MultiGetBenchmarks.multiGetBB200 1_column_family 10000 1024 100 256 thrpt 25 5285.055 ± 11.676 ops/s MultiGetBenchmarks.multiGetBB200 1_column_family 10000 1024 100 1024 thrpt 25 5586.758 ± 213.008 ops/s MultiGetBenchmarks.multiGetBB200 1_column_family 10000 1024 100 4096 thrpt 25 2527.172 ± 17.106 ops/s MultiGetBenchmarks.multiGetBB200 1_column_family 10000 1024 100 16384 thrpt 25 1819.547 ± 12.958 ops/s MultiGetBenchmarks.multiGetBB200 1_column_family 10000 1024 100 65536 thrpt 25 803.861 ± 9.963 ops/s MultiGetBenchmarks.multiGetBB200 20_column_families 10000 1024 100 256 thrpt 25 5253.793 ± 28.020 ops/s MultiGetBenchmarks.multiGetBB200 20_column_families 10000 1024 100 1024 thrpt 25 5705.591 ± 20.556 ops/s MultiGetBenchmarks.multiGetBB200 20_column_families 10000 1024 100 4096 thrpt 25 2523.377 ± 15.415 ops/s MultiGetBenchmarks.multiGetBB200 20_column_families 10000 1024 100 16384 thrpt 25 1815.344 ± 11.309 ops/s MultiGetBenchmarks.multiGetBB200 20_column_families 10000 1024 100 65536 thrpt 25 820.792 ± 3.192 ops/s MultiGetBenchmarks.multiGetBB200 100_column_families 10000 1024 100 256 thrpt 25 5262.184 ± 20.477 ops/s MultiGetBenchmarks.multiGetBB200 100_column_families 10000 1024 100 1024 thrpt 25 5706.959 ± 23.123 ops/s MultiGetBenchmarks.multiGetBB200 100_column_families 10000 1024 100 4096 thrpt 25 2520.362 ± 9.170 ops/s MultiGetBenchmarks.multiGetBB200 100_column_families 10000 1024 100 16384 thrpt 25 1789.185 ± 14.239 ops/s MultiGetBenchmarks.multiGetBB200 100_column_families 10000 1024 100 65536 thrpt 25 818.401 ± 12.132 ops/s MultiGetBenchmarks.multiGetList10 no_column_family 10000 1024 100 256 thrpt 25 6978.310 ± 14.084 ops/s MultiGetBenchmarks.multiGetList10 no_column_family 10000 1024 100 1024 thrpt 25 7664.242 ± 22.304 ops/s MultiGetBenchmarks.multiGetList10 no_column_family 10000 1024 100 4096 thrpt 25 2881.778 ± 81.054 ops/s MultiGetBenchmarks.multiGetList10 no_column_family 10000 1024 100 16384 thrpt 25 1599.826 ± 7.190 ops/s MultiGetBenchmarks.multiGetList10 no_column_family 10000 1024 100 65536 thrpt 25 737.520 ± 6.809 ops/s MultiGetBenchmarks.multiGetList10 1_column_family 10000 1024 100 256 thrpt 25 6974.376 ± 10.716 ops/s MultiGetBenchmarks.multiGetList10 1_column_family 10000 1024 100 1024 thrpt 25 7637.440 ± 45.877 ops/s MultiGetBenchmarks.multiGetList10 1_column_family 10000 1024 100 4096 thrpt 25 2820.472 ± 42.231 ops/s MultiGetBenchmarks.multiGetList10 1_column_family 10000 1024 100 16384 thrpt 25 1716.663 ± 8.527 ops/s MultiGetBenchmarks.multiGetList10 1_column_family 10000 1024 100 65536 thrpt 25 755.848 ± 7.514 ops/s MultiGetBenchmarks.multiGetList10 20_column_families 10000 1024 100 256 thrpt 25 6943.651 ± 20.040 ops/s MultiGetBenchmarks.multiGetList10 20_column_families 10000 1024 100 1024 thrpt 25 7679.415 ± 9.114 ops/s MultiGetBenchmarks.multiGetList10 20_column_families 10000 1024 100 4096 thrpt 25 2844.564 ± 13.388 ops/s MultiGetBenchmarks.multiGetList10 20_column_families 10000 1024 100 16384 thrpt 25 1729.545 ± 5.983 ops/s MultiGetBenchmarks.multiGetList10 20_column_families 10000 1024 100 65536 thrpt 25 783.218 ± 1.530 ops/s MultiGetBenchmarks.multiGetList10 100_column_families 10000 1024 100 256 thrpt 25 6944.276 ± 29.995 ops/s MultiGetBenchmarks.multiGetList10 100_column_families 10000 1024 100 1024 thrpt 25 7670.301 ± 8.986 ops/s MultiGetBenchmarks.multiGetList10 100_column_families 10000 1024 100 4096 thrpt 25 2839.828 ± 12.421 ops/s MultiGetBenchmarks.multiGetList10 100_column_families 10000 1024 100 16384 thrpt 25 1730.005 ± 9.209 ops/s MultiGetBenchmarks.multiGetList10 100_column_families 10000 1024 100 65536 thrpt 25 787.096 ± 1.977 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 no_column_family 10000 1024 100 256 thrpt 25 6896.944 ± 21.530 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 no_column_family 10000 1024 100 1024 thrpt 25 7622.407 ± 12.824 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 no_column_family 10000 1024 100 4096 thrpt 25 2927.538 ± 19.792 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 no_column_family 10000 1024 100 16384 thrpt 25 1598.041 ± 4.312 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 no_column_family 10000 1024 100 65536 thrpt 25 744.564 ± 9.236 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 1_column_family 10000 1024 100 256 thrpt 25 6853.760 ± 78.041 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 1_column_family 10000 1024 100 1024 thrpt 25 7360.917 ± 355.365 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 1_column_family 10000 1024 100 4096 thrpt 25 2848.774 ± 13.409 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 1_column_family 10000 1024 100 16384 thrpt 25 1727.688 ± 3.329 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 1_column_family 10000 1024 100 65536 thrpt 25 776.088 ± 7.517 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 20_column_families 10000 1024 100 256 thrpt 25 6910.339 ± 14.366 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 20_column_families 10000 1024 100 1024 thrpt 25 7633.660 ± 10.830 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 20_column_families 10000 1024 100 4096 thrpt 25 2787.799 ± 81.775 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 20_column_families 10000 1024 100 16384 thrpt 25 1726.517 ± 6.830 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 20_column_families 10000 1024 100 65536 thrpt 25 787.597 ± 3.362 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 100_column_families 10000 1024 100 256 thrpt 25 6922.445 ± 10.493 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 100_column_families 10000 1024 100 1024 thrpt 25 7604.710 ± 48.043 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 100_column_families 10000 1024 100 4096 thrpt 25 2848.788 ± 15.783 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 100_column_families 10000 1024 100 16384 thrpt 25 1730.837 ± 6.497 ops/s MultiGetBenchmarks.multiGetListExplicitCF20 100_column_families 10000 1024 100 65536 thrpt 25 794.557 ± 1.869 ops/s MultiGetBenchmarks.multiGetListRandomCF30 no_column_family 10000 1024 100 256 thrpt 25 6918.716 ± 15.766 ops/s MultiGetBenchmarks.multiGetListRandomCF30 no_column_family 10000 1024 100 1024 thrpt 25 7626.692 ± 9.394 ops/s MultiGetBenchmarks.multiGetListRandomCF30 no_column_family 10000 1024 100 4096 thrpt 25 2871.382 ± 72.155 ops/s MultiGetBenchmarks.multiGetListRandomCF30 no_column_family 10000 1024 100 16384 thrpt 25 1598.786 ± 4.819 ops/s MultiGetBenchmarks.multiGetListRandomCF30 no_column_family 10000 1024 100 65536 thrpt 25 748.469 ± 7.234 ops/s MultiGetBenchmarks.multiGetListRandomCF30 1_column_family 10000 1024 100 256 thrpt 25 6922.666 ± 17.131 ops/s MultiGetBenchmarks.multiGetListRandomCF30 1_column_family 10000 1024 100 1024 thrpt 25 7623.890 ± 8.805 ops/s MultiGetBenchmarks.multiGetListRandomCF30 1_column_family 10000 1024 100 4096 thrpt 25 2850.698 ± 18.004 ops/s MultiGetBenchmarks.multiGetListRandomCF30 1_column_family 10000 1024 100 16384 thrpt 25 1727.623 ± 4.868 ops/s MultiGetBenchmarks.multiGetListRandomCF30 1_column_family 10000 1024 100 65536 thrpt 25 774.534 ± 10.025 ops/s MultiGetBenchmarks.multiGetListRandomCF30 20_column_families 10000 1024 100 256 thrpt 25 5486.251 ± 13.582 ops/s MultiGetBenchmarks.multiGetListRandomCF30 20_column_families 10000 1024 100 1024 thrpt 25 4920.656 ± 44.557 ops/s MultiGetBenchmarks.multiGetListRandomCF30 20_column_families 10000 1024 100 4096 thrpt 25 3922.913 ± 25.686 ops/s MultiGetBenchmarks.multiGetListRandomCF30 20_column_families 10000 1024 100 16384 thrpt 25 2873.106 ± 4.336 ops/s MultiGetBenchmarks.multiGetListRandomCF30 20_column_families 10000 1024 100 65536 thrpt 25 802.404 ± 8.967 ops/s MultiGetBenchmarks.multiGetListRandomCF30 100_column_families 10000 1024 100 256 thrpt 25 4817.996 ± 18.042 ops/s MultiGetBenchmarks.multiGetListRandomCF30 100_column_families 10000 1024 100 1024 thrpt 25 4243.922 ± 13.929 ops/s MultiGetBenchmarks.multiGetListRandomCF30 100_column_families 10000 1024 100 4096 thrpt 25 3175.998 ± 7.773 ops/s MultiGetBenchmarks.multiGetListRandomCF30 100_column_families 10000 1024 100 16384 thrpt 25 2321.990 ± 12.501 ops/s MultiGetBenchmarks.multiGetListRandomCF30 100_column_families 10000 1024 100 65536 thrpt 25 1753.028 ± 7.130 ops/s ``` Closes https://github.com/facebook/rocksdb/issues/11518 Pull Request resolved: https://github.com/facebook/rocksdb/pull/12344 Reviewed By: cbi42 Differential Revision: D54809714 Pulled By: pdillinger fbshipit-source-id: bee3b949720abac073bce043b59ce976a11e99eb |
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Alan Paxton
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c1ec0b28eb |
java / jni io_uring support (#9224)
Summary: Existing multiGet() in java calls multi_get_helper() which then calls DB::std::vector MultiGet(). This doesn't take advantage of io_uring. This change adds another JNI level method that runs a parallel code path using the DB::void MultiGet(), using ByteBuffers at the JNI level. We call it multiGetDirect(). In addition to using the io_uring path, this code internally returns pinned slices which we can copy out of into our direct byte buffers; this should reduce the overall number of copies in the code path to/from Java. Some jmh benchmark runs (100k keys, 1000 key multiGet) suggest that for value sizes > 1k, we see about a 20% performance improvement, although performance is slightly reduced for small value sizes, there's a little bit more overhead in the JNI methods. Closes https://github.com/facebook/rocksdb/issues/8407 Pull Request resolved: https://github.com/facebook/rocksdb/pull/9224 Reviewed By: mrambacher Differential Revision: D32951754 Pulled By: jay-zhuang fbshipit-source-id: 1f70df7334be2b6c42a9c8f92725f67c71631690 |
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Adam Retter
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6477075f2c |
JMH microbenchmarks for RocksJava (#6241)
Summary: This is the start of some JMH microbenchmarks for RocksJava. Such benchmarks can help us decide on performance improvements of the Java API. At the moment, I have only added benchmarks for various Comparator options, as that is one of the first areas where I want to improve performance. I plan to expand this to many more tests. Details of how to compile and run the benchmarks are in the `README.md`. A run of these on a XEON 3.5 GHz 4vCPU (QEMU Virtual CPU version 2.5+) / 8GB RAM KVM with Ubuntu 18.04, OpenJDK 1.8.0_232, and gcc 8.3.0 produced the following: ``` # Run complete. Total time: 01:43:17 REMEMBER: The numbers below are just data. To gain reusable insights, you need to follow up on why the numbers are the way they are. Use profilers (see -prof, -lprof), design factorial experiments, perform baseline and negative tests that provide experimental control, make sure the benchmarking environment is safe on JVM/OS/HW level, ask for reviews from the domain experts. Do not assume the numbers tell you what you want them to tell. Benchmark (comparatorName) Mode Cnt Score Error Units ComparatorBenchmarks.put native_bytewise thrpt 25 122373.920 ± 2200.538 ops/s ComparatorBenchmarks.put java_bytewise_adaptive_mutex thrpt 25 17388.201 ± 1444.006 ops/s ComparatorBenchmarks.put java_bytewise_non-adaptive_mutex thrpt 25 16887.150 ± 1632.204 ops/s ComparatorBenchmarks.put java_direct_bytewise_adaptive_mutex thrpt 25 15644.572 ± 1791.189 ops/s ComparatorBenchmarks.put java_direct_bytewise_non-adaptive_mutex thrpt 25 14869.601 ± 2252.135 ops/s ComparatorBenchmarks.put native_reverse_bytewise thrpt 25 116528.735 ± 4168.797 ops/s ComparatorBenchmarks.put java_reverse_bytewise_adaptive_mutex thrpt 25 10651.975 ± 545.998 ops/s ComparatorBenchmarks.put java_reverse_bytewise_non-adaptive_mutex thrpt 25 10514.224 ± 930.069 ops/s ``` Indicating a ~7x difference between comparators implemented natively (C++) and those implemented in Java. Let's see if we can't improve on that in the near future... Pull Request resolved: https://github.com/facebook/rocksdb/pull/6241 Differential Revision: D19290410 Pulled By: pdillinger fbshipit-source-id: 25d44bf3a31de265502ed0c5d8a28cf4c7cb9c0b |