Flink Flink 源码之 Buffer Timeout优化

Posted 2022-02-06 九师兄

1.概述

转载：Flink 源码之 Buffer Timeout优化

2.Buffer Timeout 概念

Flink每个算子向下游发送数据需要两个条件：

• 输出buffer空间占满
• buffer中数据存在时间超过buffer timeout配置值（默认值为100ms）

这个配置值对Flink性能影响至关重大。配置的低，数据的延迟很小，但是会带量大量高频的网络通信，同时大幅提高CPU占用率。配置值过高buffer会经常填满，数据的延迟会增大很多。有文章表明，在大并发的情况下，如果对数据的延迟不是十分敏感，适当的调大buffer timeout（1s左右即可）可以降低CPU使用率 30% - 50%。

3.Buffer Timeout 配置

Buffer timeout有两个级别：全局级别和算子级别。

全局级别的Buffer timeout通过StreamExecutionEnvironment.setBufferTimeout方法配置。代码如下：

public StreamExecutionEnvironment setBufferTimeout(long timeoutMillis) 
    if (timeoutMillis < -1) 
        throw new IllegalArgumentException("Timeout of buffer must be non-negative or -1");
    

    this.bufferTimeout = timeoutMillis;
    return this;

StreamExecutionEnvironment中设置的bufferTimeout在构造StreamGraph的时候作为默认的buffer timeout使用。如果用户没有给算子指定专门的buffer timeout，自动采用默认的buffer timeout。

算子级别的Buffer timeout只影响这一个算子的配置。算子级别对应的是SingleOutputStreamOperator。我们查看它的setBufferTimeout方法：

public SingleOutputStreamOperator<T> setBufferTimeout(long timeoutMillis) 
    checkArgument(timeoutMillis >= -1, "timeout must be >= -1");
    transformation.setBufferTimeout(timeoutMillis);
    return this;

它为算子对应的Transformation对象设置了bufferTimeout属性。

4.Buffer Timeout 如何影响StreamGraph

Flink把Transformation翻译为StreamGraph需要用到各种各样的translator。我们查看下它的基类SimpleTransformationTranslator的configure方法片段;

// ...
StreamGraphUtils.configureBufferTimeout(
    streamGraph, transformationId, transformation, context.getDefaultBufferTimeout());
// ...

它使用了StreamGraphUtils配置StreamGraph的缓存timeout。详细内容我们需要展开分析configureBufferTimeout方法：

public static <T> void configureBufferTimeout(
    StreamGraph streamGraph,
    int nodeId,
    Transformation<T> transformation,
    long defaultBufferTimeout) 

    if (transformation.getBufferTimeout() >= 0) 
        streamGraph.setBufferTimeout(nodeId, transformation.getBufferTimeout());
     else 
        streamGraph.setBufferTimeout(nodeId, defaultBufferTimeout);
    

它接收的4个参数分别为：需要生成的streamGraph，StreamNode id，Transformation和默认的buffer timeout配置（StreamExecutionEnvironment级别的配置为默认配置）。

该方法又调用了StreamGraph的setBufferTimeout方法。我们继续跟踪。这个方法为Transformation对应的StreamNode设置bufferTimeout属性。

public void setBufferTimeout(Integer vertexID, long bufferTimeout) 
    if (getStreamNode(vertexID) != null) 
        getStreamNode(vertexID).setBufferTimeout(bufferTimeout);
    

到此位置我们得知用户为每个算子设定的buffer timeout配置最终反应到了StreamGraph中算子对应StreamNode的bufferTimeout属性。

下一章节开始分析bufferTimeout属性如何影响Flink 处理数据的行为。

5.行为

我们查看StreamEdge的构造函数：

public StreamEdge(
    StreamNode sourceVertex,
    StreamNode targetVertex,
    int typeNumber,
    StreamPartitioner<?> outputPartitioner,
    OutputTag outputTag,
    StreamExchangeMode exchangeMode) 

    this(
        sourceVertex,
        targetVertex,
        typeNumber,
        sourceVertex.getBufferTimeout(),
        outputPartitioner,
        outputTag,
        exchangeMode);

可以发现StreamEdge的bufferTimeout是由sourceVertex，即Edge上游StreamNode的bufferTimeout属性决定的。

接着追踪StreamEdge的bufferTimeout调用过程，我们找到了StreamTask.createRecordWriter方法调用：

private static <OUT>
    List<RecordWriter<SerializationDelegate<StreamRecord<OUT>>>> createRecordWriters(
    StreamConfig configuration, Environment environment) 
    List<RecordWriter<SerializationDelegate<StreamRecord<OUT>>>> recordWriters =
        new ArrayList<>();
    List<StreamEdge> outEdgesInOrder =
        configuration.getOutEdgesInOrder(
        environment.getUserCodeClassLoader().asClassLoader());

    // 遍历每个StreamEdge，逐个创建RecordWriter
    // RecordWriter的bufferTimeout为Edge的bufferTimeout
    for (int i = 0; i < outEdgesInOrder.size(); i++) 
        StreamEdge edge = outEdgesInOrder.get(i);
        recordWriters.add(
            createRecordWriter(
                edge,
                i,
                environment,
                environment.getTaskInfo().getTaskNameWithSubtasks(),
                edge.getBufferTimeout()));
    
    return recordWriters;

createRecordWriter方法内容片段如下。可知RecordWriter通过RecordWriterBuilder创建：

RecordWriter<SerializationDelegate<StreamRecord<OUT>>> output =
        new RecordWriterBuilder<SerializationDelegate<StreamRecord<OUT>>>()
                .setChannelSelector(outputPartitioner)
                .setTimeout(bufferTimeout)
                .setTaskName(taskName)
                .build(bufferWriter);

继续查看RecordWriterBuilder的build方法：

public RecordWriter<T> build(ResultPartitionWriter writer) 
    if (selector.isBroadcast()) 
        return new BroadcastRecordWriter<>(writer, timeout, taskName);
     else 
        return new ChannelSelectorRecordWriter<>(writer, selector, timeout, taskName);
    

无论创建的是BroadcastRecordWriter（广播形式写入数据到输出缓存）还是ChannelSelectorRecordWriter（把数据写入到特定channel，例如keyBy算子），他们的父类都为RecordWriter。所以接下来需要展开分析的内容为RecordWriter。

我们查看RecordWriter的构造函数，发现其中创建了一个OutputFlush对象（如果没有禁用network buffer timeout的话）：

RecordWriter(ResultPartitionWriter writer, long timeout, String taskName) 
    this.targetPartition = writer;
    this.numberOfChannels = writer.getNumberOfSubpartitions();

    this.serializer = new DataOutputSerializer(128);

    checkArgument(timeout >= ExecutionOptions.DISABLED_NETWORK_BUFFER_TIMEOUT);
    this.flushAlways = (timeout == ExecutionOptions.FLUSH_AFTER_EVERY_RECORD);
    if (timeout == ExecutionOptions.DISABLED_NETWORK_BUFFER_TIMEOUT
        || timeout == ExecutionOptions.FLUSH_AFTER_EVERY_RECORD) 
        outputFlusher = null;
     else 
        String threadName =
            taskName == null
            ? DEFAULT_OUTPUT_FLUSH_THREAD_NAME
            : DEFAULT_OUTPUT_FLUSH_THREAD_NAME + " for " + taskName;

        outputFlusher = new OutputFlusher(threadName, timeout);
        outputFlusher.start();
    

OutputFlusher使用专门的线程，异步定时调用targetPartition的flushAll()方法。调用时间间隔就是setBufferTimeout的值。

@Override
public void run() 
    try 
        while (running) 
            try 
                // 每隔timeout这么长时间，就flush所有的数据
                Thread.sleep(timeout);
             catch (InterruptedException e) 
                // propagate this if we are still running, because it should not happen
                // in that case
                if (running) 
                    throw new Exception(e);
                
            

            // any errors here should let the thread come to a halt and be
            // recognized by the writer
            flushAll();
        
     catch (Throwable t) 
        notifyFlusherException(t);
    

到此为止我们分析完了buffer timeout从配置到生成StreamGraph到如何影响Flink发送数据的完整过程。