kafka/jmh-benchmarks
Lucas Bradstreet 577d235e11 MINOR: refactor replica last sent HW updates due to performance regression (#7671)
This change fixes a performance regression due to follower last seen highwatermark
handling introduced in 23beeea. maybeUpdateHwAndSendResponse is expensive for
brokers with high partition counts, as it requires a partition and a replica lookup for every
partition being fetched. This refactor moves the last seen watermark update into the follower
fetch state update where we have already looked up the partition and replica.

I've seen cases where maybeUpdateHwAndSendResponse is responsible 8% of CPU usage, not including the responseCallback call that is part of it.

I have benchmarked this change with `UpdateFollowerFetchStateBenchmark` and it adds 5ns
of overhead to Partition.updateFollowerFetchState, which is a rounding error compared to the
current overhead of maybeUpdateHwAndSendResponse.

Reviewers: David Arthur <mumrah@gmail.com>, Jason Gustafson <jason@confluent.io>, Ismael Juma <ismael@juma.me.uk>
2019-11-12 21:24:47 -08:00
..
src/main/java/org/apache/kafka/jmh MINOR: refactor replica last sent HW updates due to performance regression (#7671) 2019-11-12 21:24:47 -08:00
README.md MINOR: Document improvement (#6682) 2019-05-06 16:52:23 +05:30
jmh.sh KAFKA-3989; MINOR: follow-up: update script to run from kafka root 2017-08-26 16:15:40 -07:00

README.md

JMH-Benchmark module

This module contains benchmarks written using JMH from OpenJDK. Writing correct micro-benchmarks in Java (or another JVM language) is difficult and there are many non-obvious pitfalls (many due to compiler optimizations). JMH is a framework for running and analyzing benchmarks (micro or macro) written in Java (or another JVM language).

For help in writing correct JMH tests, the best place to start is the sample code provided by the JMH project.

Typically, JMH is expected to run as a separate project in Maven. The jmh-benchmarks module uses the gradle shadow jar plugin to emulate this behavior, by creating the required uber-jar file containing the benchmarking code and required JMH classes.

JMH is highly configurable and users are encouraged to look through the samples for suggestions on what options are available. A good tutorial for using JMH can be found here

Gradle Tasks / Running benchmarks in gradle

If no benchmark mode is specified, the default is used which is throughput. It is assumed that users run the gradle tasks with './gradlew' from the root of the Kafka project.

  • jmh-benchmarks:shadowJar - creates the uber jar required to run the benchmarks.

  • jmh-benchmarks:jmh - runs the clean and shadowJar tasks followed by all the benchmarks.

Using the jmh script

If you want to set specific JMH flags or only run a certain test(s) passing arguments via gradle tasks is cumbersome. Instead you can use the jhm.sh script. NOTE: It is assumed users run the jmh.sh script from the jmh-benchmarks module.

  • Run a specific test setting fork-mode (number iterations) to 2 :./jmh.sh -f 2 LRUCacheBenchmark

  • By default all JMH output goes to stdout. To run a benchmark and capture the results in a file: ./jmh.sh -f 2 -o benchmarkResults.txt LRUCacheBenchmark NOTE: For now this script needs to be run from the jmh-benchmarks directory.

Running JMH outside of gradle

The JMH benchmarks can be run outside of gradle as you would with any executable jar file: java -jar <kafka-repo-dir>/jmh-benchmarks/build/libs/kafka-jmh-benchmarks-all.jar -f2 LRUCacheBenchmark

JMH Options

Some common JMH options are:

 
   -e <regexp+>                Benchmarks to exclude from the run. 
 
   -f <int>                    How many times to fork a single benchmark. Use 0 to 
                               disable forking altogether. Warning: disabling 
                               forking may have detrimental impact on benchmark 
                               and infrastructure reliability, you might want 
                               to use different warmup mode instead. 
 
   -o <filename>               Redirect human-readable output to a given file. 
 
  
 
   -v <mode>                   Verbosity mode. Available modes are: [SILENT, NORMAL, 
                               EXTRA] 

To view all options run jmh with the -h flag.