opensearch-benchmark 1.0.0

Macrobenchmarking framework for OpenSearch

OpenSearch Benchmark

OpenSearch Benchmark is the macrobenchmarking framework for OpenSearch.

What is OpenSearch Benchmark?

If you are looking to performance test OpenSearch, then OpenSearch Benchmark is for you. It can help you with the following tasks:

• Running performance benchmarks and recording results
• Setting up and tearing down OpenSearch clusters for benchmarking
• Managing benchmark data and specifications across OpenSearch versions
• Discovering performance problems by attaching so-called telemetry devices
• Comparing performance results
• Creating customized workloads

We have also put considerable effort into OpenSearch Benchmark to ensure that benchmarking data are reproducible.

Quick Start

OpenSearch Benchmark is developed for Unix and is actively tested on Linux, Ubuntu, and MacOS. OpenSearch Benchmark supports benchmarking OpenSearch clusters running on Windows but OpenSearch Benchmark itself needs to be installed on machines running Unix.

Installing OpenSearch Benchmark

Note: If you actively develop on OpenSearch, we recommend that you install OpenSearch Benchmark in development mode instead as OpenSearch is fast moving and OpenSearch Benchmark always adapts accordingly to the latest main version.

Install Python 3.8+ including pip3, git 1.9+ and an appropriate JDK to run OpenSearch Be sure that JAVA_HOME points to that JDK and that the corresponding Java executable in $JAVA_HOME/bin is picked up via your PATH environment variable. Then run the following command, optionally prefixed by sudo if necessary:

python3 -m pip install opensearch-benchmark

If you have any trouble or need more detailed instructions, please look in the detailed installation guide.

Run your first test execution

Now we're ready to run our first test execution:

opensearch-benchmark execute-test --distribution-version=1.0.0 --workload=geonames --test-mode

This will download OpenSearch 1.0.0 and run one of OpenSearch Benchmark's official workloads - the geonames workload - against it. Note that this uses the --test-mode argument to only run a single instance of each operation in order to reduce the time needed for a test execution. This argument is used as a sanity check and should be removed in an actual benchmarking scenario. After the test execution, a summary report is written to the command line:

------------------------------------------------------
    _______             __   _____
   / ____(_)___  ____ _/ /  / ___/_________  ________
  / /_  / / __ \/ __ `/ /   \__ \/ ___/ __ \/ ___/ _ \
 / __/ / / / / / /_/ / /   ___/ / /__/ /_/ / /  /  __/
/_/   /_/_/ /_/\__,_/_/   /____/\___/\____/_/   \___/
------------------------------------------------------

|                         Metric |                 Task |     Value |   Unit |
|-------------------------------:|---------------------:|----------:|-------:|
|            Total indexing time |                      |   28.0997 |    min |
|               Total merge time |                      |   6.84378 |    min |
|             Total refresh time |                      |   3.06045 |    min |
|               Total flush time |                      |  0.106517 |    min |
|      Total merge throttle time |                      |   1.28193 |    min |
|               Median CPU usage |                      |     471.6 |      % |
|             Total Young Gen GC |                      |    16.237 |      s |
|               Total Old Gen GC |                      |     1.796 |      s |
|                     Index size |                      |   2.60124 |     GB |
|                  Total written |                      |   11.8144 |     GB |
|         Heap used for segments |                      |   14.7326 |     MB |
|       Heap used for doc values |                      |  0.115917 |     MB |
|            Heap used for terms |                      |   13.3203 |     MB |
|            Heap used for norms |                      | 0.0734253 |     MB |
|           Heap used for points |                      |    0.5793 |     MB |
|    Heap used for stored fields |                      |  0.643608 |     MB |
|                  Segment count |                      |        97 |        |
|                 Min Throughput |         index-append |   31925.2 | docs/s |
|              Median Throughput |         index-append |   39137.5 | docs/s |
|                 Max Throughput |         index-append |   39633.6 | docs/s |
|      50.0th percentile latency |         index-append |   872.513 |     ms |
|      90.0th percentile latency |         index-append |   1457.13 |     ms |
|      99.0th percentile latency |         index-append |   1874.89 |     ms |
|       100th percentile latency |         index-append |   2711.71 |     ms |
| 50.0th percentile service time |         index-append |   872.513 |     ms |
| 90.0th percentile service time |         index-append |   1457.13 |     ms |
| 99.0th percentile service time |         index-append |   1874.89 |     ms |
|  100th percentile service time |         index-append |   2711.71 |     ms |
|                           ...  |                  ... |       ... |    ... |
|                           ...  |                  ... |       ... |    ... |
|                 Min Throughput |     painless_dynamic |   2.53292 |  ops/s |
|              Median Throughput |     painless_dynamic |   2.53813 |  ops/s |
|                 Max Throughput |     painless_dynamic |   2.54401 |  ops/s |
|      50.0th percentile latency |     painless_dynamic |    172208 |     ms |
|      90.0th percentile latency |     painless_dynamic |    310401 |     ms |
|      99.0th percentile latency |     painless_dynamic |    341341 |     ms |
|      99.9th percentile latency |     painless_dynamic |    344404 |     ms |
|       100th percentile latency |     painless_dynamic |    344754 |     ms |
| 50.0th percentile service time |     painless_dynamic |    393.02 |     ms |
| 90.0th percentile service time |     painless_dynamic |   407.579 |     ms |
| 99.0th percentile service time |     painless_dynamic |   430.806 |     ms |
| 99.9th percentile service time |     painless_dynamic |   457.352 |     ms |
|  100th percentile service time |     painless_dynamic |   459.474 |     ms |

----------------------------------
[INFO] SUCCESS (took 2634 seconds)
----------------------------------

Creating Your Own Workloads

For more information on how users can create their own workloads, see the Create Workload Guide

Getting help

• Quick help: opensearch-benchmark --help
• Look in OpenSearch Benchmark's user guide for more information
• For any questions or answers, visit our community forum.
• File improvements or bug reports in our Github repo.

How to Contribute

See all details in the contributor guidelines.

License

This software is licensed under the Apache License, version 2 ("ALv2"), quoted below.

Copyright 2015-2022 OpenSearch https://opensearch.org/

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.