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/*
* Copyright (c) 2015, Oracle America, Inc.
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* * Redistributions of source code must retain the above copyright notice,
* this list of conditions and the following disclaimer.
*
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
*
* * Neither the name of Oracle nor the names of its contributors may be used
* to endorse or promote products derived from this software without
* specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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* LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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package org.openjdk.jmh.samples;
import org.openjdk.jmh.annotations.*;
import org.openjdk.jmh.runner.Runner;
import org.openjdk.jmh.runner.RunnerException;
import org.openjdk.jmh.runner.options.Options;
import org.openjdk.jmh.runner.options.OptionsBuilder;
import java.util.Arrays;
import java.util.Random;
import java.util.concurrent.TimeUnit;
@BenchmarkMode(Mode.AverageTime)
@OutputTimeUnit(TimeUnit.NANOSECONDS)
@Warmup(iterations = 5, time = 1, timeUnit = TimeUnit.SECONDS)
@Measurement(iterations = 5, time = 1, timeUnit = TimeUnit.SECONDS)
@Fork(5)
public class JMHSample_38_PerInvokeSetup {
/*
* This example highlights the usual mistake in non-steady-state benchmarks.
*
* Suppose we want to test how long it takes to bubble sort an array. Naively,
* we could make the test that populates an array with random (unsorted) values,
* and calls sort on it over and over again:
*/
private void bubbleSort(byte[] b) {
boolean changed = true;
while (changed) {
changed = false;
for (int c = 0; c < b.length - 1; c++) {
if (b[c] > b[c + 1]) {
byte t = b[c];
b[c] = b[c + 1];
b[c + 1] = t;
changed = true;
}
}
}
}
// Could be an implicit State instead, but we are going to use it
// as the dependency in one of the tests below
@State(Scope.Benchmark)
public static class Data {
@Param({"1", "16", "256"})
int count;
byte[] arr;
@Setup
public void setup() {
arr = new byte[count];
Random random = new Random(1234);
random.nextBytes(arr);
}
}
@Benchmark
public byte[] measureWrong(Data d) {
bubbleSort(d.arr);
return d.arr;
}
/*
* The method above is subtly wrong: it sorts the random array on the first invocation
* only. Every subsequent call will "sort" the already sorted array. With bubble sort,
* that operation would be significantly faster!
*
* This is how we might *try* to measure it right by making a copy in Level.Invocation
* setup. However, this is susceptible to the problems described in Level.Invocation
* Javadocs, READ AND UNDERSTAND THOSE DOCS BEFORE USING THIS APPROACH.
*/
@State(Scope.Thread)
public static class DataCopy {
byte[] copy;
@Setup(Level.Invocation)
public void setup2(Data d) {
copy = Arrays.copyOf(d.arr, d.arr.length);
}
}
@Benchmark
public byte[] measureNeutral(DataCopy d) {
bubbleSort(d.copy);
return d.copy;
}
/*
* In an overwhelming majority of cases, the only sensible thing to do is to suck up
* the per-invocation setup costs into a benchmark itself. This work well in practice,
* especially when the payload costs dominate the setup costs.
*/
@Benchmark
public byte[] measureRight(Data d) {
byte[] c = Arrays.copyOf(d.arr, d.arr.length);
bubbleSort(c);
return c;
}
/*
Benchmark (count) Mode Cnt Score Error Units
JMHSample_38_PerInvokeSetup.measureWrong 1 avgt 25 2.408 ± 0.011 ns/op
JMHSample_38_PerInvokeSetup.measureWrong 16 avgt 25 8.286 ± 0.023 ns/op
JMHSample_38_PerInvokeSetup.measureWrong 256 avgt 25 73.405 ± 0.018 ns/op
JMHSample_38_PerInvokeSetup.measureNeutral 1 avgt 25 15.835 ± 0.470 ns/op
JMHSample_38_PerInvokeSetup.measureNeutral 16 avgt 25 112.552 ± 0.787 ns/op
JMHSample_38_PerInvokeSetup.measureNeutral 256 avgt 25 58343.848 ± 991.202 ns/op
JMHSample_38_PerInvokeSetup.measureRight 1 avgt 25 6.075 ± 0.018 ns/op
JMHSample_38_PerInvokeSetup.measureRight 16 avgt 25 102.390 ± 0.676 ns/op
JMHSample_38_PerInvokeSetup.measureRight 256 avgt 25 58812.411 ± 997.951 ns/op
We can clearly see that "measureWrong" provides a very weird result: it "sorts" way too fast.
"measureNeutral" is neither good or bad: while it prepares the data for each invocation correctly,
the timing overheads are clearly visible. These overheads can be overwhelming, depending on
the thread count and/or OS flavor.
*/
/*
* ============================== HOW TO RUN THIS TEST: ====================================
*
* You can run this test:
*
* a) Via the command line:
* $ mvn clean install
* $ java -jar target/benchmarks.jar JMHSample_38
*
* b) Via the Java API:
* (see the JMH homepage for possible caveats when running from IDE:
* http://openjdk.java.net/projects/code-tools/jmh/)
*/
public static void main(String[] args) throws RunnerException {
Options opt = new OptionsBuilder()
.include(".*" + JMHSample_38_PerInvokeSetup.class.getSimpleName() + ".*")
.build();
new Runner(opt).run();
}
}
