聊聊flink DataStream的split操作

栏目: 编程工具 · 发布时间: 5年前

内容简介:本文主要研究一下flink DataStream的split操作flink-streaming-java_2.11-1.7.0-sources.jar!/org/apache/flink/streaming/api/datastream/DataStream.javaflink-streaming-java_2.11-1.7.0-sources.jar!/org/apache/flink/streaming/api/collector/selector/OutputSelector.java

本文主要研究一下flink DataStream的split操作

实例

SplitStream<Integer> split = someDataStream.split(new OutputSelector<Integer>() {
    @Override
    public Iterable<String> select(Integer value) {
        List<String> output = new ArrayList<String>();
        if (value % 2 == 0) {
            output.add("even");
        }
        else {
            output.add("odd");
        }
        return output;
    }
});
  • 本实例将dataStream split为两个dataStream,一个outputName为even,另一个outputName为odd

DataStream.split

flink-streaming-java_2.11-1.7.0-sources.jar!/org/apache/flink/streaming/api/datastream/DataStream.java

@Public
public class DataStream<T> {

    //......

    public SplitStream<T> split(OutputSelector<T> outputSelector) {
        return new SplitStream<>(this, clean(outputSelector));
    }

    //......
}
  • DataStream的split操作接收OutputSelector参数,然后创建并返回SplitStream

OutputSelector

flink-streaming-java_2.11-1.7.0-sources.jar!/org/apache/flink/streaming/api/collector/selector/OutputSelector.java

@PublicEvolving
public interface OutputSelector<OUT> extends Serializable {

    Iterable<String> select(OUT value);

}
  • OutputSelector定义了select方法用于给element打上outputNames

SplitStream

flink-streaming-java_2.11-1.7.0-sources.jar!/org/apache/flink/streaming/api/datastream/SplitStream.java

@PublicEvolving
public class SplitStream<OUT> extends DataStream<OUT> {

    protected SplitStream(DataStream<OUT> dataStream, OutputSelector<OUT> outputSelector) {
        super(dataStream.getExecutionEnvironment(), new SplitTransformation<OUT>(dataStream.getTransformation(), outputSelector));
    }

    public DataStream<OUT> select(String... outputNames) {
        return selectOutput(outputNames);
    }

    private DataStream<OUT> selectOutput(String[] outputNames) {
        for (String outName : outputNames) {
            if (outName == null) {
                throw new RuntimeException("Selected names must not be null");
            }
        }

        SelectTransformation<OUT> selectTransform = new SelectTransformation<OUT>(this.getTransformation(), Lists.newArrayList(outputNames));
        return new DataStream<OUT>(this.getExecutionEnvironment(), selectTransform);
    }

}
  • SplitStream继承了DataStream,它定义了select方法,可以用来根据outputNames选择split出来的dataStream;select方法创建了SelectTransformation

StreamGraphGenerator

flink-streaming-java_2.11-1.7.0-sources.jar!/org/apache/flink/streaming/api/graph/StreamGraphGenerator.java

@Internal
public class StreamGraphGenerator {

    //......

    private Collection<Integer> transform(StreamTransformation<?> transform) {

        if (alreadyTransformed.containsKey(transform)) {
            return alreadyTransformed.get(transform);
        }

        LOG.debug("Transforming " + transform);

        if (transform.getMaxParallelism() <= 0) {

            // if the max parallelism hasn't been set, then first use the job wide max parallelism
            // from theExecutionConfig.
            int globalMaxParallelismFromConfig = env.getConfig().getMaxParallelism();
            if (globalMaxParallelismFromConfig > 0) {
                transform.setMaxParallelism(globalMaxParallelismFromConfig);
            }
        }

        // call at least once to trigger exceptions about MissingTypeInfo
        transform.getOutputType();

        Collection<Integer> transformedIds;
        if (transform instanceof OneInputTransformation<?, ?>) {
            transformedIds = transformOneInputTransform((OneInputTransformation<?, ?>) transform);
        } else if (transform instanceof TwoInputTransformation<?, ?, ?>) {
            transformedIds = transformTwoInputTransform((TwoInputTransformation<?, ?, ?>) transform);
        } else if (transform instanceof SourceTransformation<?>) {
            transformedIds = transformSource((SourceTransformation<?>) transform);
        } else if (transform instanceof SinkTransformation<?>) {
            transformedIds = transformSink((SinkTransformation<?>) transform);
        } else if (transform instanceof UnionTransformation<?>) {
            transformedIds = transformUnion((UnionTransformation<?>) transform);
        } else if (transform instanceof SplitTransformation<?>) {
            transformedIds = transformSplit((SplitTransformation<?>) transform);
        } else if (transform instanceof SelectTransformation<?>) {
            transformedIds = transformSelect((SelectTransformation<?>) transform);
        } else if (transform instanceof FeedbackTransformation<?>) {
            transformedIds = transformFeedback((FeedbackTransformation<?>) transform);
        } else if (transform instanceof CoFeedbackTransformation<?>) {
            transformedIds = transformCoFeedback((CoFeedbackTransformation<?>) transform);
        } else if (transform instanceof PartitionTransformation<?>) {
            transformedIds = transformPartition((PartitionTransformation<?>) transform);
        } else if (transform instanceof SideOutputTransformation<?>) {
            transformedIds = transformSideOutput((SideOutputTransformation<?>) transform);
        } else {
            throw new IllegalStateException("Unknown transformation: " + transform);
        }

        // need this check because the iterate transformation adds itself before
        // transforming the feedback edges
        if (!alreadyTransformed.containsKey(transform)) {
            alreadyTransformed.put(transform, transformedIds);
        }

        if (transform.getBufferTimeout() >= 0) {
            streamGraph.setBufferTimeout(transform.getId(), transform.getBufferTimeout());
        }
        if (transform.getUid() != null) {
            streamGraph.setTransformationUID(transform.getId(), transform.getUid());
        }
        if (transform.getUserProvidedNodeHash() != null) {
            streamGraph.setTransformationUserHash(transform.getId(), transform.getUserProvidedNodeHash());
        }

        if (transform.getMinResources() != null && transform.getPreferredResources() != null) {
            streamGraph.setResources(transform.getId(), transform.getMinResources(), transform.getPreferredResources());
        }

        return transformedIds;
    }

    private <T> Collection<Integer> transformSelect(SelectTransformation<T> select) {
        StreamTransformation<T> input = select.getInput();
        Collection<Integer> resultIds = transform(input);

        // the recursive transform might have already transformed this
        if (alreadyTransformed.containsKey(select)) {
            return alreadyTransformed.get(select);
        }

        List<Integer> virtualResultIds = new ArrayList<>();

        for (int inputId : resultIds) {
            int virtualId = StreamTransformation.getNewNodeId();
            streamGraph.addVirtualSelectNode(inputId, virtualId, select.getSelectedNames());
            virtualResultIds.add(virtualId);
        }
        return virtualResultIds;
    }

    private <T> Collection<Integer> transformSplit(SplitTransformation<T> split) {

        StreamTransformation<T> input = split.getInput();
        Collection<Integer> resultIds = transform(input);

        // the recursive transform call might have transformed this already
        if (alreadyTransformed.containsKey(split)) {
            return alreadyTransformed.get(split);
        }

        for (int inputId : resultIds) {
            streamGraph.addOutputSelector(inputId, split.getOutputSelector());
        }

        return resultIds;
    }

    //......
}
  • StreamGraphGenerator里头的transform会对SelectTransformation以及SplitTransformation进行相应的处理
  • transformSelect方法会根据select.getSelectedNames()来addVirtualSelectNode
  • transformSplit方法则根据split.getOutputSelector()来addOutputSelector

小结

  • DataStream的split操作接收OutputSelector参数,然后创建并返回SplitStream
  • OutputSelector定义了select方法用于给element打上outputNames
  • SplitStream继承了DataStream,它定义了select方法,可以用来根据outputNames选择split出来的dataStream

doc


以上所述就是小编给大家介绍的《聊聊flink DataStream的split操作》,希望对大家有所帮助,如果大家有任何疑问请给我留言,小编会及时回复大家的。在此也非常感谢大家对 码农网 的支持!

查看所有标签

猜你喜欢:

本站部分资源来源于网络,本站转载出于传递更多信息之目的,版权归原作者或者来源机构所有,如转载稿涉及版权问题,请联系我们

PWA实战

PWA实战

[美]Dean Alan Hume / 郑丰彧 / 电子工业出版社 / 2018-6 / 69

Progressive Web App(PWA)是由谷歌提出的一整套技术解决方案,它致力于为 Web 提供出色的用户体验,并完美体现了渐进增强原则。作为为数不多的实战入门用书,《PWA 实战:面向下一代的Progressive Web App》旨在通过大量清晰示例来介绍 PWA 的主要特性。全书一共由五个部分组成:第一部分介绍 PWA 的概念及解锁 PWA 应用的关键—Service Worker......一起来看看 《PWA实战》 这本书的介绍吧!

图片转BASE64编码
图片转BASE64编码

在线图片转Base64编码工具

HTML 编码/解码
HTML 编码/解码

HTML 编码/解码