java - JMH 基准迭代中的随机峰

Question

我正在尝试一个非常快的方法(~20 us/op)，它似乎工作得很好，除了一些随机很长的迭代:

Iteration  63: 14.319 us/op
Iteration  64: 13.128 us/op
Iteration  65: 15.198 us/op
Iteration  66: 20.822 us/op
Iteration  67: 21.669 us/op
Iteration  68: 21.439 us/op
Iteration  69: 15.946 us/op
Iteration  70: 18.793 us/op
Iteration  71: 19.212 us/op
Iteration  72: 816.129 us/op  // oopsy
Iteration  73: 22.115 us/op
Iteration  74: 15.143 us/op
Iteration  75: 18.423 us/op
Iteration  76: 15.238 us/op

Result "benchmark.StuffBench.run_bench":
  20.629 ±(99.9%) 9.164 us/op [Average]
  (min, avg, max) = (12.689, 20.629, 816.129), stdev = 47.763
  CI (99.9%): [11.464, 29.793] (assumes normal distribution)

它可能是 GC，但 shouldDoGc(false) 不会改变任何东西:

final Options options = new OptionsBuilder()
                .include(StuffBench.class.getSimpleName())
                .shouldDoGC(false)
                .build();
Collection<RunResult> runResults = new Runner(options).run();

基准类:

@Fork(value = 2)
@Threads(1)
@Warmup(iterations = 1000, time = 50, timeUnit = TimeUnit.MICROSECONDS)
@Measurement(iterations = 150, time = 50, timeUnit = TimeUnit.MICROSECONDS)
@Timeout(time = 50, timeUnit = TimeUnit.MICROSECONDS)
@OutputTimeUnit(TimeUnit.MICROSECONDS)
@BenchmarkMode(Mode.AverageTime)
@State(Scope.Benchmark)
public class StuffBench {
    private Stuff stuff;

    @Setup
    public void initialize() {
        stuff = new Stuff();
    }

    @Benchmark
    public void run_bench() {
        stuff.run();
    }
}

Answer 1

为了解决此类问题，我使用了所谓的抖动采样器。您有一个线程设置时间戳、运行代码、重置时间戳并暂停以防止 CPU 过载。第二个线程对时间戳进行采样，如果它处于 Activity 状态并且时间太长，例如20 us，你打印它正在做什么的堆栈跟踪。例如Thread.getStackTrace() 结合最常见的堆栈跟踪，你就有了一个可以指向问题的安全点(或问题之后的第一个安全点)它更像是艺术而不是科学；)