Java 8一个流到多个映射

时间:2018-08-13 08:34:39

标签: java java-8 java-stream

让我们说我有一个巨大的Web服务器日志文件,该文件不适合内存。我需要将此文件流式传输到mapreduce方法并保存到数据库。我使用Java 8流API进行此操作。例如,在mapreduce过程之后,我得到了一个列表,例如,客户端消耗,ip消耗,内容消耗。但是,我的需求与示例中的需求不同。由于我不能共享代码,所以我只想举一个基本的例子。

通过Java 8 Stream Api,我想只读取一次文件,同时获取3个列表,而我正在并行或顺序传输文件。但是并行会很好。有什么办法吗?

2 个答案:

答案 0 :(得分:7)

通常,通过自定义Collector可以很容易地收集到除标准API之外的任何内容。就您而言,一次收集3个列表(只是一个小的示例,可以编译,因为您也无法共享代码):

private static <T> Collector<T, ?, List<List<T>>> to3Lists() {
    class Acc {

        List<T> left = new ArrayList<>();

        List<T> middle = new ArrayList<>();

        List<T> right = new ArrayList<>();

        List<List<T>> list = Arrays.asList(left, middle, right);

        void add(T elem) {
            // obviously do whatever you want here
            left.add(elem);
            middle.add(elem);
            right.add(elem);
        }

        Acc merge(Acc other) {

            left.addAll(other.left);
            middle.addAll(other.middle);
            right.addAll(other.right);

            return this;
        }

        public List<List<T>> finisher() {
            return list;
        }

    }
    return Collector.of(Acc::new, Acc::add, Acc::merge, Acc::finisher);
}

并通过以下方式使用它:

Stream.of(1, 2, 3)
      .collect(to3Lists());

很显然,这个自定义收集器没有做任何有用的事情,而只是一个如何使用它的示例。

答案 1 :(得分:4)

我已根据您的情况改编了the answer to this question。定制的Spliterator会将流“拆分”为由不同属性收集的多个流:

@SafeVarargs
public static <T> long streamForked(Stream<T> source, Consumer<Stream<T>>... consumers)
{
    return StreamSupport.stream(new ForkingSpliterator<>(source, consumers), false).count();
}

public static class ForkingSpliterator<T>
    extends AbstractSpliterator<T>
{
    private Spliterator<T>         sourceSpliterator;

    private List<BlockingQueue<T>> queues = new ArrayList<>();

    private boolean                sourceDone;

    @SafeVarargs
    private ForkingSpliterator(Stream<T> source, Consumer<Stream<T>>... consumers)
    {
        super(Long.MAX_VALUE, 0);

        sourceSpliterator = source.spliterator();

        for (Consumer<Stream<T>> fork : consumers)
        {
            LinkedBlockingQueue<T> queue = new LinkedBlockingQueue<>();
            queues.add(queue);
            new Thread(() -> fork.accept(StreamSupport.stream(new ForkedConsumer(queue), false))).start();
        }
    }

    @Override
    public boolean tryAdvance(Consumer<? super T> action)
    {
        sourceDone = !sourceSpliterator.tryAdvance(t -> queues.forEach(queue -> queue.offer(t)));
        return !sourceDone;
    }

    private class ForkedConsumer
        extends AbstractSpliterator<T>
    {
        private BlockingQueue<T> queue;

        private ForkedConsumer(BlockingQueue<T> queue)
        {
            super(Long.MAX_VALUE, 0);
            this.queue = queue;
        }

        @Override
        public boolean tryAdvance(Consumer<? super T> action)
        {
            while (queue.peek() == null)
            {
                if (sourceDone)
                {
                    // element is null, and there won't be no more, so "terminate" this sub stream
                    return false;
                }
            }

            // push to consumer pipeline
            action.accept(queue.poll());

            return true;
        }
    }
}

您可以按以下方式使用它:

streamForked(Stream.of(new Row("content1", "client1", "location1", 1),
                       new Row("content2", "client1", "location1", 2),
                       new Row("content1", "client1", "location2", 3),
                       new Row("content2", "client2", "location2", 4),
                       new Row("content1", "client2", "location2", 5)),
             rows -> System.out.println(rows.collect(Collectors.groupingBy(Row::getClient,
                                                                           Collectors.groupingBy(Row::getContent,
                                                                                                 Collectors.summingInt(Row::getConsumption))))),
             rows -> System.out.println(rows.collect(Collectors.groupingBy(Row::getClient,
                                                                           Collectors.groupingBy(Row::getLocation,
                                                                                                 Collectors.summingInt(Row::getConsumption))))),
             rows -> System.out.println(rows.collect(Collectors.groupingBy(Row::getContent,
                                                                           Collectors.groupingBy(Row::getLocation,
                                                                                                 Collectors.summingInt(Row::getConsumption))))));

// Output
// {client2={location2=9}, client1={location1=3, location2=3}}
// {client2={content2=4, content1=5}, client1={content2=2, content1=4}}
// {content2={location1=2, location2=4}, content1={location1=1, location2=8}}

请注意,使用流的副本您几乎可以做任何您想做的事情。按照您的示例,我使用了stacked groupingBy collector to group the rows by two properties,然后总结了int属性。因此结果将是Map<String, Map<String, Integer>>。但您也可以将其用于其他情况:

rows -> System.out.println(rows.count())
rows -> rows.forEach(row -> System.out.println(row))
rows -> System.out.println(rows.anyMatch(row -> row.getConsumption() > 3))