jmh | 易学教程

Why is the StringBuilder chaining pattern sb.append(x).append(y) faster than regular sb.append(x); sb.append(y)?

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问题 I have a microbenchmark that shows very strange results: @BenchmarkMode(Mode.Throughput) @Fork(1) @State(Scope.Thread) @Warmup(iterations = 10, time = 1, timeUnit = TimeUnit.SECONDS, batchSize = 1000) @Measurement(iterations = 40, time = 1, timeUnit = TimeUnit.SECONDS, batchSize = 1000) public class Chaining { private String a1 = "111111111111111111111111"; private String a2 = "222222222222222222222222"; private String a3 = "333333333333333333333333"; @Benchmark public String typicalChaining(

How to run JMH from inside JUnit tests?

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问题 How can I run JMH benchmarks inside my existing project using JUnit tests? The official documentation recommends making a separate project, using Maven shade plugin, and launching JMH inside the main method. Is this necessary and why is it recommended? 回答1: I've been running JMH inside my existing Maven project using JUnit with no apparent ill effects. I cannot answer why the authors recommend doing things differently. I have not observed a difference in results. JMH launches a separate JVM

“No matching benchmarks” when running JMH from main in eclipse

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问题 I wanted to try out the new feature of JMH by running it as Java Application in eclipse. I imported and built jmh-samples project. Compiled classes ended in /jmh-samples/target/generated-sources/annotations, there are several JARs in /target/ and running microbenchmarks.jar from command line works as usual. However when I execute main I always get No matching benchmarks. Miss-spelled regexp? Any ideas? I am using version 0.3 回答1: jmh-dev@ is a better way to communicate this with the

Strange JIT pessimization of a loop idiom

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问题 While analyzing the results of a recent question here, I encountered a quite peculiar phenomenon: apparently an extra layer of HotSpot's JIT-optimization actually slows down execution on my machine. Here is the code I have used for the measurement: @OutputTimeUnit(TimeUnit.NANOSECONDS) @BenchmarkMode(Mode.AverageTime) @OperationsPerInvocation(Measure.ARRAY_SIZE) @Warmup(iterations = 2, time = 1) @Measurement(iterations = 5, time = 1) @State(Scope.Thread) @Threads(1) @Fork(2) public class

Erratic performance of Arrays.stream().map().sum()

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问题 I have chanced upon an instance of exceedingly erratic performance profile of a very simple map/reduce operation on primitive arrays. Here is my jmh benchmark code: @OutputTimeUnit(TimeUnit.NANOSECONDS) @BenchmarkMode(Mode.AverageTime) @OperationsPerInvocation(Measure.ARRAY_SIZE) @Warmup(iterations = 300, time = 200, timeUnit=MILLISECONDS) @Measurement(iterations = 1, time = 1000, timeUnit=MILLISECONDS) @State(Scope.Thread) @Threads(1) @Fork(1) public class Measure { static final int ARRAY