java – 了解Streams API的ForEachTask中的主循环

看来 Java Streams的并行化核心是ForEachTask.了解其逻辑似乎对于获取预期针对Streams API编写的客户端代码的并发行为所必需的心理模型至关重要.然而,我发现我的预期与实际行为相矛盾.

作为参考,这里是关键的compute()方法(java / util / streams / ForEachOps.java：253)：

public void compute() {
  Spliterator<S> rightSplit = spliterator,leftSplit;
  long sizeEstimate = rightSplit.estimateSize(),sizeThreshold;
  if ((sizeThreshold = targetSize) == 0L)
    targetSize = sizeThreshold = AbstractTask.suggestTargetSize(sizeEstimate);
  boolean isShortCircuit = StreamOpFlag.SHORT_CIRCUIT.isKnown(helper.getStreamAndOpFlags());
  boolean forkRight = false;
  Sink<S> taskSink = sink;
  ForEachTask<S,T> task = this;
  while (!isShortCircuit || !taskSink.cancellationRequested()) {
    if (sizeEstimate <= sizeThreshold ||
        (leftSplit = rightSplit.trySplit()) == null) {
      task.helper.copyInto(taskSink,rightSplit);
      break;
    }
    ForEachTask<S,T> leftTask = new ForEachTask<>(task,leftSplit);
    task.addToPendingCount(1);
    ForEachTask<S,T> taskToFork;
    if (forkRight) {
      forkRight = false;
      rightSplit = leftSplit;
      taskToFork = task;
      task = leftTask;
    }
    else {
      forkRight = true;
      taskToFork = leftTask;
    }
    taskToFork.fork();
    sizeEstimate = rightSplit.estimateSize();
  }
  task.spliterator = null;
  task.propagateCompletion();
}

在高级描述中,主循环不断分解分离器,交替地去除块的处理并内联处理,直到分割器拒绝进一步分割或剩余大小低于计算的阈值.

现在考虑上述算法在未定义的流的情况下,其中整体不被分割成大致相等的一半;而是从流的头部重复地取出预定尺寸的块.在这种情况下,块的“建议的目标大小”异常大,这主要意味着块不会重新分割成较小的块.

因此,该算法似乎交替地分离一个块,然后一个内联处理.如果每个组块需要相同的时间进行处理,则应该使用不超过两个内核.但是,实际的行为是我机器上的所有四个内核都被占用.显然,我使用该算法缺少一个重要的难题.

我失踪了什么？

附录：测试代码

这是一个独立的代码,可用于测试这个问题的主题的行为：

package test;

import static java.util.concurrent.TimeUnit.NANOSECONDS;
import static java.util.concurrent.TimeUnit.SECONDS;
import static test.FixedBatchSpliteratorWrapper.withFixedSplits;

import java.io.IOException;
import java.io.PrintWriter;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.Paths;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.atomic.AtomicLong;

public class Parallelization {
  static final AtomicLong totalTime = new AtomicLong();
  static final ExecutorService pool = Executors.newFixedThreadPool(4);

  public static void main(String[] args) throws IOException {
    final long start = System.nanoTime();
    final Path inputPath = createInput();
    System.out.println("Start processing");
    try (PrintWriter w = new PrintWriter(Files.newBufferedWriter(Paths.get("output.txt")))) {
      withFixedSplits(Files.newBufferedReader(inputPath).lines(),200).map(Parallelization::processLine)
      .forEach(w::println);
    }
    final double cpuTime = totalTime.get(),realTime = System.nanoTime() - start;
    final int cores = Runtime.getRuntime().availableProcessors();
    System.out.println("          Cores: " + cores);
    System.out.format("       CPU time: %.2f sn",cpuTime / SECONDS.toNanos(1));
    System.out.format("      Real time: %.2f sn",realTime / SECONDS.toNanos(1));
    System.out.format("CPU utilization: %.2f%%",100.0 * cpuTime / realTime / cores);
  }
  private static String processLine(String line) {
    final long localStart = System.nanoTime();
    double ret = 0;
    for (int i = 0; i < line.length(); i++)
      for (int j = 0; j < line.length(); j++)
        ret += Math.pow(line.charAt(i),line.charAt(j) / 32.0);
    final long took = System.nanoTime() - localStart;
    totalTime.getAndAdd(took);
    return NANOSECONDS.toMillis(took) + " " + ret;
  }
  private static Path createInput() throws IOException {
    final Path inputPath = Paths.get("input.txt");
    try (PrintWriter w = new PrintWriter(Files.newBufferedWriter(inputPath))) {
      for (int i = 0; i < 6_000; i++) {
        final String text = String.valueOf(System.nanoTime());
        for (int j = 0; j < 20; j++)
          w.print(text);
        w.println();
      }
    }
    return inputPath;
  }
}

package test;

import static java.util.Spliterators.spliterator;
import static java.util.stream.StreamSupport.stream;

import java.util.Comparator;
import java.util.Spliterator;
import java.util.function.Consumer;
import java.util.stream.Stream;

public class FixedBatchSpliteratorWrapper<T> implements Spliterator<T> {
  private final Spliterator<T> spliterator;
  private final int batchSize;
  private final int characteristics;
  private long est;

  public FixedBatchSpliteratorWrapper(Spliterator<T> toWrap,long est,int batchSize) {
    final int c = toWrap.characteristics();
    this.characteristics = (c & SIZED) != 0 ? c | SUBSIZED : c;
    this.spliterator = toWrap;
    this.batchSize = batchSize;
    this.est = est;
  }
  public FixedBatchSpliteratorWrapper(Spliterator<T> toWrap,int batchSize) {
    this(toWrap,toWrap.estimateSize(),batchSize);
  }

  public static <T> Stream<T> withFixedSplits(Stream<T> in,int batchSize) {
    return stream(new FixedBatchSpliteratorWrapper<>(in.spliterator(),batchSize),true);
  }

  @Override public Spliterator<T> trySplit() {
    final HoldingConsumer<T> holder = new HoldingConsumer<>();
    if (!spliterator.tryAdvance(holder)) return null;
    final Object[] a = new Object[batchSize];
    int j = 0;
    do a[j] = holder.value; while (++j < batchSize && tryAdvance(holder));
    if (est != Long.MAX_VALUE) est -= j;
    return spliterator(a,j,characteristics());
  }
  @Override public boolean tryAdvance(Consumer<? super T> action) {
    return spliterator.tryAdvance(action);
  }
  @Override public void forEachRemaining(Consumer<? super T> action) {
    spliterator.forEachRemaining(action);
  }
  @Override public Comparator<? super T> getComparator() {
    if (hasCharacteristics(SORTED)) return null;
    throw new IllegalStateException();
  }
  @Override public long estimateSize() { return est; }
  @Override public int characteristics() { return characteristics; }

  static final class HoldingConsumer<T> implements Consumer<T> {
    Object value;
    @Override public void accept(T value) { this.value = value; }
  }
}

解决方法

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