[英]java micro benchmark to find average from list
我的文件帶有一些不同的字符串(大約從prod中取出100.000)。 需要找出處理該文件中每個字符串的函數的99%,99.9%。
我嘗試使用jmh編寫基准測試。 但是,我僅能找到批處理功能(處理整個文件)或僅具有一個特定字符串的必需功能所需的百分位數。
public String process1(String str){
...process...
}
public String processBatch(List<String> strings){
for (String str: strings){
process1(str)
}
}
另外,我嘗試通過@param設置整個字符串列表。 這使得jmh可以為每個字符串運行數十次迭代,但是找不到所需的結果。
jmh中是否有什么可以幫助找到所需的統計信息? 如果沒有,可以使用什么工具?
是您要找的東西嗎?
@Warmup(iterations = 1, time = 5, timeUnit = TimeUnit.SECONDS)
@Measurement(iterations = 1, time = 5, timeUnit = TimeUnit.SECONDS)
@Fork(1)
@State(Scope.Benchmark)
public class MyBenchmark {
ClassUnderBenchmark classUnderBenchmark = new ClassUnderBenchmark();
@State(Scope.Benchmark)
public static class MyTestState {
int counter = 0;
List<String> list = Arrays.asList("aaaaa", "bbbb", "ccc");
String currentString;
@Setup(Level.Invocation)
public void init() throws IOException {
this.currentString = list.get(counter++);
if (counter == 3) {
counter = 0;
}
}
}
@Benchmark
@Threads(1)
@BenchmarkMode(Mode.SampleTime)
public void test(MyBenchmark.MyTestState myTestState) {
classUnderBenchmark.toUpper(myTestState.currentString);
}
public static class ClassUnderBenchmark {
Random r = new Random();
public String toUpper(String name) {
try {
Thread.sleep(r.nextInt(100));
} catch (InterruptedException e) {
e.printStackTrace();
}
return name.toUpperCase();
}
}
public static void main(String[] args) throws RunnerException {
Options opt = new OptionsBuilder()
.include(MyBenchmark.class.getSimpleName())
.jvmArgs("-XX:+UseG1GC", "-XX:MaxGCPauseMillis=50")
.build();
new Runner(opt).run();
}
}
請參閱javadoc(org.openjdk.jmh.annotations.Mode):
/**
* <p>Sample time: samples the time for each operation.</p>
*
* <p>Runs by continuously calling {@link Benchmark} methods,
* and randomly samples the time needed for the call. This mode automatically adjusts the sampling
* frequency, but may omit some pauses which missed the sampling measurement. This mode is time-based, and it will
* run until the iteration time expires.</p>
*/
SampleTime("sample", "Sampling time"),
該測試將為您提供輸出:
Result "test":
N = 91
mean = 0,056 ±(99.9%) 0,010 s/op
Histogram, s/op:
[0,000, 0,010) = 6
[0,010, 0,020) = 9
[0,020, 0,030) = 3
[0,030, 0,040) = 11
[0,040, 0,050) = 8
[0,050, 0,060) = 11
[0,060, 0,070) = 9
[0,070, 0,080) = 9
[0,080, 0,090) = 14
Percentiles, s/op:
p(0,0000) = 0,003 s/op
p(50,0000) = 0,059 s/op
p(90,0000) = 0,092 s/op
p(95,0000) = 0,095 s/op
p(99,0000) = 0,100 s/op
p(99,9000) = 0,100 s/op
p(99,9900) = 0,100 s/op
p(99,9990) = 0,100 s/op
p(99,9999) = 0,100 s/op
p(100,0000) = 0,100 s/op
Benchmark Mode Cnt Score Error Units
MyBenchmark.test sample 91 0,056 ± 0,010 s/op
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