OpenSearch/client/benchmark
Nik Everett 1b97652a4c
Build: Move shadow customizations into common code (#32014)
Moves the customizations to the build to produce nice shadow jars and
javadocs into common build code, mostly BuildPlugin with a little into
the root build.gradle file. This means that any project that applies the
shadow plugin will automatically be set up just like the high level rest
client:
* The non-shadow jar will not be built
* The shadow jar will not have a "classifier"
* Tests will run against the shadow jar
* Javadoc will include all of the shadowed classes
* Service files in `META-INF/services` will be merged
2018-07-17 14:20:41 -04:00
..
src/main Remove all unused imports and fix CRLF (#31207) 2018-06-11 15:12:12 +02:00
README.md Add client-benchmark-noop-api-plugin to stress clients even more in benchmarks (#20103) 2016-08-26 09:05:47 +02:00
build.gradle Build: Move shadow customizations into common code (#32014) 2018-07-17 14:20:41 -04:00

README.md

Steps to execute the benchmark

  1. Build client-benchmark-noop-api-plugin with gradle :client:client-benchmark-noop-api-plugin:assemble
  2. Install it on the target host with bin/elasticsearch-plugin install file:///full/path/to/client-benchmark-noop-api-plugin.zip
  3. Start Elasticsearch on the target host (ideally not on the same machine)
  4. Build an uberjar with gradle :client:benchmark:shadowJar and execute it.

Repeat all steps above for the other benchmark candidate.

Example benchmark

In general, you should define a few GC-related settings -Xms8192M -Xmx8192M -XX:+UseConcMarkSweepGC -verbose:gc -XX:+PrintGCDetails and keep an eye on GC activity. You can also define -XX:+PrintCompilation to see JIT activity.

Bulk indexing

Download benchmark data from http://benchmarks.elastic.co/corpora/geonames/documents.json.bz2 and decompress them.

Example command line parameters:

rest bulk 192.168.2.2 ./documents.json geonames type 8647880 5000

The parameters are in order:

  • Client type: Use either "rest" or "transport"
  • Benchmark type: Use either "bulk" or "search"
  • Benchmark target host IP (the host where Elasticsearch is running)
  • full path to the file that should be bulk indexed
  • name of the index
  • name of the (sole) type in the index
  • number of documents in the file
  • bulk size

Bulk indexing

Example command line parameters:

rest search 192.168.2.2 geonames "{ \"query\": { \"match_phrase\": { \"name\": \"Sankt Georgen\" } } }\"" 500,1000,1100,1200

The parameters are in order:

  • Client type: Use either "rest" or "transport"
  • Benchmark type: Use either "bulk" or "search"
  • Benchmark target host IP (the host where Elasticsearch is running)
  • name of the index
  • a search request body (remember to escape double quotes). The TransportClientBenchmark uses QueryBuilders.wrapperQuery() internally which automatically adds a root key query, so it must not be present in the command line parameter.
  • A comma-separated list of target throughput rates