JMH microobjective recursive quicksort

Question

Hello, I am trying to perform micro-tests of various sorting algorithms, and I had a strange problem with jmh and quicksort benchmarking. Maybe something is wrong with my implementation. I would be interested if someone helps me see where the problem is. First of all, I am using ubuntu 14.04 with jdk 7 and jmh 0.9.1. Here is how I am trying to make a test:

@OutputTimeUnit(TimeUnit.MILLISECONDS)
@BenchmarkMode(Mode.AverageTime)
@Warmup(iterations = 3, time = 1)
@Measurement(iterations = 3, time = 1)
@State(Scope.Thread)
public class SortingBenchmark {

private int length = 100000;

private Distribution distribution = Distribution.RANDOM;

private int[] array;

int i = 1;

@Setup(Level.Iteration)
public void setUp() {
    array = distribution.create(length);
}

@Benchmark
public int timeQuickSort() {
    int[] sorted = Sorter.quickSort(array);
    return sorted[i];
}

@Benchmark
public int timeJDKSort() {
    Arrays.sort(array);
    return array[i];
}

public static void main(String[] args) throws RunnerException {
    Options opt = new OptionsBuilder().include(".*" + SortingBenchmark.class.getSimpleName() + ".*").forks(1)
            .build();

    new Runner(opt).run();
}
}

, , . quicksort - . ! - StackOverflowException. , - quicksort . , - ( 100000 ). , , . JDK jmh . - - ? :

public static int[] quickSort(int[] data) {
    Sorter.quickSort(data, 0, data.length - 1);
    return data;
}
private static void quickSort(int[] data, int sublistFirstIndex, int sublistLastIndex) {
    if (sublistFirstIndex < sublistLastIndex) {
        // move smaller elements before pivot and larger after
        int pivotIndex = partition(data, sublistFirstIndex, sublistLastIndex);
        // apply recursively to sub lists
        Sorter.quickSort(data, sublistFirstIndex, pivotIndex - 1);
        Sorter.quickSort(data, pivotIndex + 1, sublistLastIndex);
    }
}
private static int partition(int[] data, int sublistFirstIndex, int sublistLastIndex) {
    int pivotElement = data[sublistLastIndex];
    int pivotIndex = sublistFirstIndex - 1;
    for (int i = sublistFirstIndex; i < sublistLastIndex; i++) {
        if (data[i] <= pivotElement) {
            pivotIndex++;
            ArrayUtils.swap(data, pivotIndex, i);
        }
    }
    ArrayUtils.swap(data, pivotIndex + 1, sublistLastIndex);
    return pivotIndex + 1; // return index of pivot element
}

, - (O (n ^ 2)), . , , , jmh . , - . : https://github.com/ignl/SortingAlgos/

Answer 1

, ( , ), , .

JMH - - ( , ). @Setup (Level.Iteration) . , quicksort ( ) . .

, - @Setup (Level.Invocation). , Javadoc:

**
     * Invocation level: to be executed for each benchmark method execution.
     *
     * <p><b>WARNING: HERE BE DRAGONS! THIS IS A SHARP TOOL.
     * MAKE SURE YOU UNDERSTAND THE REASONING AND THE IMPLICATIONS
     * OF THE WARNINGS BELOW BEFORE EVEN CONSIDERING USING THIS LEVEL.</b></p>
     *
     * <p>This level is only usable for benchmarks taking more than a millisecond
     * per single {@link Benchmark} method invocation. It is a good idea to validate
     * the impact for your case on ad-hoc basis as well.</p>
     *
     * <p>WARNING #1: Since we have to subtract the setup/teardown costs from
     * the benchmark time, on this level, we have to timestamp *each* benchmark
     * invocation. If the benchmarked method is small, then we saturate the
     * system with timestamp requests, which introduce artificial latency,
     * throughput, and scalability bottlenecks.</p>
     *
     * <p>WARNING #2: Since we measure individual invocation timings with this
     * level, we probably set ourselves up for (coordinated) omission. That means
     * the hiccups in measurement can be hidden from timing measurement, and
     * can introduce surprising results. For example, when we use timings to
     * understand the benchmark throughput, the omitted timing measurement will
     * result in lower aggregate time, and fictionally *larger* throughput.</p>
     *
     * <p>WARNING #3: In order to maintain the same sharing behavior as other
     * Levels, we sometimes have to synchronize (arbitrage) the access to
     * {@link State} objects. Other levels do this outside the measurement,
     * but at this level, we have to synchronize on *critical path*, further
     * offsetting the measurement.</p>
     *
     * <p>WARNING #4: Current implementation allows the helper method execution
     * at this Level to overlap with the benchmark invocation itself in order
     * to simplify arbitrage. That matters in multi-threaded benchmarks, when
     * one worker thread executing {@link Benchmark} method may observe other
     * worker thread already calling {@link TearDown} for the same object.</p>
     */ 

, , . , .