151242ce46
Summary:
**Context:**
The existing stat rocksdb.sst.read.micros does not reflect each of compaction and flush cases but aggregate them, which is not so helpful for us to understand IO read behavior of each of them.
**Summary**
- Update `StopWatch` and `RandomAccessFileReader` to record `rocksdb.sst.read.micros` and `rocksdb.file.{flush/compaction}.read.micros`
- Fixed the default histogram in `RandomAccessFileReader`
- New field `ReadOptions/IOOptions::io_activity`; Pass `ReadOptions` through paths under db open, flush and compaction to where we can prepare `IOOptions` and pass it to `RandomAccessFileReader`
- Use `thread_status_util` for assertion in `DbStressFSWrapper` for continuous testing on we are passing correct `io_activity` under db open, flush and compaction
Pull Request resolved: https://github.com/facebook/rocksdb/pull/11288
Test Plan:
- **Stress test**
- **Db bench 1: rocksdb.sst.read.micros COUNT ≈ sum of rocksdb.file.read.flush.micros's and rocksdb.file.read.compaction.micros's.** (without blob)
- May not be exactly the same due to `HistogramStat::Add` only guarantees atomic not accuracy across threads.
```
./db_bench -db=/dev/shm/testdb/ -statistics=true -benchmarks="fillseq" -key_size=32 -value_size=512 -num=50000 -write_buffer_size=655 -target_file_size_base=655 -disable_auto_compactions=false -compression_type=none -bloom_bits=3 (-use_plain_table=1 -prefix_size=10)
```
```
// BlockBasedTable
rocksdb.sst.read.micros P50 : 2.009374 P95 : 4.968548 P99 : 8.110362 P100 : 43.000000 COUNT : 40456 SUM : 114805
rocksdb.file.read.flush.micros P50 : 1.871841 P95 : 3.872407 P99 : 5.540541 P100 : 43.000000 COUNT : 2250 SUM : 6116
rocksdb.file.read.compaction.micros P50 : 2.023109 P95 : 5.029149 P99 : 8.196910 P100 : 26.000000 COUNT : 38206 SUM : 108689
// PlainTable
Does not apply
```
- **Db bench 2: performance**
**Read**
SETUP: db with 900 files
```
./db_bench -db=/dev/shm/testdb/ -benchmarks="fillseq" -key_size=32 -value_size=512 -num=50000 -write_buffer_size=655 -disable_auto_compactions=true -target_file_size_base=655 -compression_type=none
```run till convergence
```
./db_bench -seed=1678564177044286 -use_existing_db=true -db=/dev/shm/testdb -benchmarks=readrandom[-X60] -statistics=true -num=1000000 -disable_auto_compactions=true -compression_type=none -bloom_bits=3
```
Pre-change
`readrandom [AVG 60 runs] : 21568 (± 248) ops/sec`
Post-change (no regression, -0.3%)
`readrandom [AVG 60 runs] : 21486 (± 236) ops/sec`
**Compaction/Flush**run till convergence
```
./db_bench -db=/dev/shm/testdb2/ -seed=1678564177044286 -benchmarks="fillseq[-X60]" -key_size=32 -value_size=512 -num=50000 -write_buffer_size=655 -disable_auto_compactions=false -target_file_size_base=655 -compression_type=none
rocksdb.sst.read.micros COUNT : 33820
rocksdb.sst.read.flush.micros COUNT : 1800
rocksdb.sst.read.compaction.micros COUNT : 32020
```
Pre-change
`fillseq [AVG 46 runs] : 1391 (± 214) ops/sec; 0.7 (± 0.1) MB/sec`
Post-change (no regression, ~-0.4%)
`fillseq [AVG 46 runs] : 1385 (± 216) ops/sec; 0.7 (± 0.1) MB/sec`
Reviewed By: ajkr
Differential Revision: D44007011
Pulled By: hx235
fbshipit-source-id: a54c89e4846dfc9a135389edf3f3eedfea257132
|
||
|---|---|---|
| .. | ||
| CMakeLists.txt | ||
| db_basic_bench.cc | ||
| README.md | ||
| ribbon_bench.cc | ||
RocksDB Micro-Benchmark
Overview
RocksDB micro-benchmark is a set of tests for benchmarking a single component or simple DB operations. The test artificially generates input data and executes the same operation with it to collect and report performance metrics. As it's focusing on testing a single, well-defined operation, the result is more precise and reproducible, which also has its limitation of not representing a real production use case. The test author needs to carefully design the microbench to represent its true purpose.
The tests are based on Google Benchmark library, which provides a standard framework for writing benchmarks.
How to Run
Prerequisite
Install the Google Benchmark version 1.6.0 or above.
Note: Google Benchmark 1.6.x is incompatible with previous versions like 1.5.x, please make sure you're using the newer version.
Build and Run
With Makefile:
$ DEBUG_LEVEL=0 make run_microbench
Or with cmake:
$ mkdir build && cd build && cmake .. -DCMAKE_BUILD_TYPE=Release -DWITH_BENCHMARK
$ make run_microbench
Note: Please run the benchmark code in release build.
Run Single Test
Example:
$ make db_basic_bench
$ ./db_basic_bench --benchmark_filter=<TEST_NAME>
Best Practices
* Use the Same Test Directory Setting as Unittest
Most of the Micro-benchmark tests use the same test directory setup as unittest, so it could be overridden by:
$ TEST_TMPDIR=/mydata/tmp/ ./db_basic_bench --benchmark_filter=<TEST_NAME>
Please also follow that when designing new tests.
* Avoid Using Debug API
Even though micro-benchmark is a test, avoid using internal Debug API like TEST_WaitForRun() which is designed for unittest. As benchmark tests are designed for release build, don't use any of that.
* Pay Attention to Local Optimization
As a micro-benchmark is focusing on a single component or area, make sure it is a key part for impacting the overall application performance.
The compiler might be able to optimize the code that not the same way as the whole application, and if the test data input is simple and small, it may be able to all cached in CPU memory, which is leading to a wrong metric. Take these into consideration when designing the tests.
* Names of user-defined counters/metrics has to be [A-Za-z0-9_]
It's a restriction of the metrics collecting and reporting system RocksDB is using internally. It will also help integrate with more systems.
* Minimize the Metrics Variation
Try reducing the test result variation, one way to check that is running the test multiple times and check the CV (Coefficient of Variation) reported by gbenchmark.
$ ./db_basic_bench --benchmark_filter=<TEST_NAME> --benchmark_repetitions=10
...
<TEST_NAME>_cv 3.2%
RocksDB has background compaction jobs which may cause the test result to vary a lot. If the micro-benchmark is not purposely testing the operation while compaction is in progress, it should wait for the compaction to finish (db_impl->WaitForCompact()) or disable auto-compaction.