例如,我有这样的方法:
public CompletableFuture<Page> getPage(int i) {
...
}
public CompletableFuture<Document> getDocument(int i) {
...
}
public CompletableFuture<Void> parseLinks(Document doc) {
...
}
我的流程:
List<CompletableFuture> list = IntStream
.range(0, 10)
.mapToObj(i -> getPage(i))
// I want method like this:
.thenApplyAndSplit(CompletableFuture<Page> page -> {
List<CompletableFuture<Document>> docs = page.getDocsId()
.stream()
.map(i -> getDocument(i))
.collect(Collectors.toList());
return docs;
})
.map(CompletableFuture<Document> future -> {
return future.thenApply(Document doc -> parseLink(doc);
})
.collect(Collectors.toList());
它应该通过flatMap()为CompletableFuture,所以我想实现这个流程:
List<Integer> -> Stream<CompletableFuture<Page>>
-> Stream<CompletableFuture<Document>>
-> parse each
UPDATE
Stream<CompletableFuture<Page>> pagesCFS = IntStream
.range(0, 10)
.mapToObj(i -> getPage(i));
Stream<CompletableFuture<Document>> documentCFS = listCFS.flatMap(page -> {
// How to return stream of Document when page finishes?
// page.thenApply( ... )
})
最佳答案 我还想尝试为CompletableFutures流实现Spliterator,所以这是我的尝试.
请注意,如果您在并行模式下使用此功能,请注意对流使用不同的ForkJoinPool以及在CompletableFuture后面运行的任务.流将等待期货完成,因此如果它们共享相同的执行程序,甚至遇到死锁,您实际上可能会失去性能.
所以这是实现:
public static <T> Stream<T> flattenStreamOfFutures(Stream<CompletableFuture<? extends T>> stream, boolean parallel) {
return StreamSupport.stream(new CompletableFutureSpliterator<T>(stream), parallel);
}
public static <T> Stream<T> flattenStreamOfFuturesOfStream(Stream<CompletableFuture<? extends Stream<T>>> stream,
boolean parallel) {
return flattenStreamOfFutures(stream, parallel).flatMap(Function.identity());
}
public static class CompletableFutureSpliterator<T> implements Spliterator<T> {
private List<CompletableFuture<? extends T>> futures;
CompletableFutureSpliterator(Stream<CompletableFuture<? extends T>> stream) {
futures = stream.collect(Collectors.toList());
}
CompletableFutureSpliterator(CompletableFuture<T>[] futures) {
this.futures = new ArrayList<>(Arrays.asList(futures));
}
CompletableFutureSpliterator(final List<CompletableFuture<? extends T>> futures) {
this.futures = new ArrayList<>(futures);
}
@Override
public boolean tryAdvance(final Consumer<? super T> action) {
if (futures.isEmpty())
return false;
CompletableFuture.anyOf(futures.stream().toArray(CompletableFuture[]::new)).join();
// now at least one of the futures has finished, get its value and remove it
ListIterator<CompletableFuture<? extends T>> it = futures.listIterator(futures.size());
while (it.hasPrevious()) {
final CompletableFuture<? extends T> future = it.previous();
if (future.isDone()) {
it.remove();
action.accept(future.join());
return true;
}
}
throw new IllegalStateException("Should not reach here");
}
@Override
public Spliterator<T> trySplit() {
if (futures.size() > 1) {
int middle = futures.size() >>> 1;
// relies on the constructor copying the list, as it gets modified in place
Spliterator<T> result = new CompletableFutureSpliterator<>(futures.subList(0, middle));
futures = futures.subList(middle, futures.size());
return result;
}
return null;
}
@Override
public long estimateSize() {
return futures.size();
}
@Override
public int characteristics() {
return IMMUTABLE | SIZED | SUBSIZED;
}
}
它通过变换给定的流< CompletableFuture< T>>来工作.进入这些期货的清单 – 假设建立流是快速的,艰苦的工作由期货本身完成,因此从中制作清单不应该是昂贵的.这也确保所有任务都已被触发,因为它强制处理源流.
为了生成输出流,它只是在流式传输其值之前等待任何未来完成.
一个简单的非并行用法示例(执行程序用于CompletableFutures,以便同时启动它们):
ExecutorService executor = Executors.newFixedThreadPool(20);
long start = System.currentTimeMillis();
flattenStreamOfFutures(IntStream.range(0, 20)
.mapToObj(i -> CompletableFuture.supplyAsync(() -> {
try {
Thread.sleep((i % 10) * 1000);
} catch (InterruptedException e) {
Thread.currentThread().interrupt();
throw new RuntimeException(e);
}
System.out.println("Finished " + i + " @ " + (System.currentTimeMillis() - start) + "ms");
return i;
}, executor)), false)
.forEach(x -> {
System.out.println(Thread.currentThread().getName() + " @ " + (System.currentTimeMillis() - start) + "ms handle result: " + x);
});
executor.shutdown();
输出:
Finished 10 @ 103ms
Finished 0 @ 105ms
main @ 114ms handle result: 10
main @ 114ms handle result: 0
Finished 1 @ 1102ms
main @ 1102ms handle result: 1
Finished 11 @ 1104ms
main @ 1104ms handle result: 11
Finished 2 @ 2102ms
main @ 2102ms handle result: 2
Finished 12 @ 2104ms
main @ 2105ms handle result: 12
Finished 3 @ 3102ms
main @ 3102ms handle result: 3
Finished 13 @ 3104ms
main @ 3105ms handle result: 13
…
正如您所看到的,即使期货未按顺序完成,流也几乎立即产生价值.
将它应用于问题中的示例,这将给出(假设parseLinks()返回CompletableFuture< String>而不是〜< Void>):
flattenStreamOfFuturesOfStream(IntStream.range(0, 10)
.mapToObj(this::getPage)
// the next map() will give a Stream<CompletableFuture<Stream<String>>>
// hence the need for flattenStreamOfFuturesOfStream()
.map(pcf -> pcf
.thenApply(page -> flattenStreamOfFutures(page
.getDocsId()
.stream()
.map(this::getDocument)
.map(docCF -> docCF.thenCompose(this::parseLinks)),
false))),
false)
.forEach(System.out::println);