源码解析Flink源节点数据读取是如何与checkpoint串行执行

谁践踏了优雅 2024-03-23 18:54 74阅读 0赞

#### 文章目录 ####

*   *   *   *  源码解析Flink源节点数据读取是如何与checkpoint串行执行
             *   *  Checkpoint阶段
                 *   *  StreamTask类变量actionExecutor的实现和初始化
                     *  小结
                 *  数据读取阶段
                 *   *  小结
                 *  总结

##### 源码解析Flink源节点数据读取是如何与checkpoint串行执行 #####

Flink版本：1.13.6

前置知识：源节点的Checkpoint是由Checkpointcoordinate触发，具体是通过RPC调用TaskManager中对应的Task的StreamTask类的performChecpoint方法执行Checkpoint。

本文思路：本文先分析checkpoint阶段，然后再分析数据读取阶段，最后得出结论：源节点Checkpoint时和源节点读取数据时，都需要抢SourceStreamTask类中lock变量的锁，最终实现串行执行checkpoint与写数据

###### Checkpoint阶段 ######

Checkpoint在StreamTask的performCheckpoint方法中执行，该方法调用过程如下

// 在StreamTask类中 执行checkpoint操作
    private boolean performCheckpoint(
                CheckpointMetaData checkpointMetaData,
                CheckpointOptions checkpointOptions,
                CheckpointMetricsBuilder checkpointMetrics )
                throws Exception {
        
            if (isRunning) {
        
                //使用actionExecutor 同步触发checkpoint
                actionExecutor.runThrowing(
                        () -> {
        
        					....//经过一系列检查
                            subtaskCheckpointCoordinator.checkpointState(
                                    checkpointMetaData,
                                    checkpointOptions,
                                    checkpointMetrics,
                                    operatorChain,
                                    this::isRunning);
                        });
                return true;
            } else {
        
        		....
            }
        }

从上述代码可以看出，Checkpoint执行是由actionExecutor执行器执行

###### StreamTask类变量actionExecutor的实现和初始化 ######

> StreamTask类变量actionExecution的实现

通过代码注释可以知道该执行器的实现是StreamTaskActionExecutor.SynchronizedStreamTaskActionExecutor；从SynchronizedStreamTaskActionExecutor源代码可知，该执行器每次执行都需要获得mutex对象锁

/**
         * All actions outside of the task {@link #mailboxProcessor mailbox} (i.e. performed by another
         * thread) must be executed through this executor to ensure that we don't have concurrent method
         * calls that void consistent checkpoints.
         *
         * <p>CheckpointLock is superseded by {@link MailboxExecutor}, with {@link
         * StreamTaskActionExecutor.SynchronizedStreamTaskActionExecutor
         * SynchronizedStreamTaskActionExecutor} to provide lock to {@link SourceStreamTask}.
         */
    private final StreamTaskActionExecutor actionExecutor;
    
    
    class SynchronizedStreamTaskActionExecutor implements StreamTaskActionExecutor {
        
        private final Object mutex;
    
        public SynchronizedStreamTaskActionExecutor(Object mutex) {
        
            this.mutex = mutex;
        }
    
        @Override
        public void run(RunnableWithException runnable) throws Exception {
        
            synchronized (mutex) {
        
                runnable.run();
            }
        }
    }

> StreamTask变量actionExecution初始化

actionExecutor变量在StreamTask中定义，在构造方法中初始化；该构造方法由SourceStreamTask调用，并传入SynchronizedStreamTaskActionExecutor对象，代码如下所示

//   SourceStreamTask的方法
    private SourceStreamTask(Environment env, Object lock) throws Exception {
        
        //调用的StreamTask构造函数，传入SynchronizedStreamTaskActionExecutor对象
        super(
                env,
                null,
                FatalExitExceptionHandler.INSTANCE,
                //初始化actionExecutor
                StreamTaskActionExecutor.synchronizedExecutor(lock));
        //将lock对象赋值给类变量lock
        this.lock = Preconditions.checkNotNull(lock);
        this.sourceThread = new LegacySourceFunctionThread();
    
        getEnvironment().getMetricGroup().getIOMetricGroup().setEnableBusyTime(false);
    }
    
    //  StreamTask的方法
    protected StreamTask(
            Environment environment,
            @Nullable TimerService timerService,
            Thread.UncaughtExceptionHandler uncaughtExceptionHandler,
        	//初始化actionExecutor
            StreamTaskActionExecutor actionExecutor)
            throws Exception {
        
        this(
                environment,
                timerService,
                uncaughtExceptionHandler,
                actionExecutor,
                new TaskMailboxImpl(Thread.currentThread()));
    }
    
    protected StreamTask(
            Environment environment,
            @Nullable TimerService timerService,
            Thread.UncaughtExceptionHandler uncaughtExceptionHandler,
            StreamTaskActionExecutor actionExecutor,
            TaskMailbox mailbox)
            throws Exception {
        
        super(environment);
        this.configuration = new StreamConfig(getTaskConfiguration());
        this.recordWriter = createRecordWriterDelegate(configuration, environment);
        //初始化actionExecutor
        this.actionExecutor = Preconditions.checkNotNull(actionExecutor);
        this.mailboxProcessor = new MailboxProcessor(this::processInput, mailbox, actionExecutor);
        .......}

###### 小结 ######

actionExecutor执行器每次执行都需要获得mutex对象，mutex对象就是SourceStreamTask类中的lock对象；即**算子每次执行Checkpoint时都需要获得SourceStreamTask类中lock对象锁才能进行**

###### 数据读取阶段 ######

在执行Checkpoint时控制读取源端，则控制点必定是在调用SourceContext的collect方法时

@Override
    public void run(SourceContext<String> ctx) throws Exception {
        
        int i = 0;
        while (true) {
        
    		//在这个方法里处理
            ctx.collect(String.valueOf(i));
        }
    }

点击collection查看实现，选择NonTimestampContext查看代码，collect()实现如下

@Override
    public void collect(T element) {
        
        synchronized (lock) {
        
            output.collect(reuse.replace(element));
        }
    }

所以这里控制数据读取发送是通过lock来控制，lock是如何初始化的？

通过NonTimestampContext构造方法可以定位到StreamSourceContexts->getSourceContext方法；

public static <OUT> SourceFunction.SourceContext<OUT> getSourceContext(
            TimeCharacteristic timeCharacteristic,
            ProcessingTimeService processingTimeService,
            Object checkpointLock,
            StreamStatusMaintainer streamStatusMaintainer,
            Output<StreamRecord<OUT>> output,
            long watermarkInterval,
            long idleTimeout) {
        
    
        final SourceFunction.SourceContext<OUT> ctx;
        switch (timeCharacteristic) {
        
    		....
            case ProcessingTime:
                //初始化NonTimestampContext
                ctx = new NonTimestampContext<>(checkpointLock, output);
                break;
            default:
                throw new IllegalArgumentException(String.valueOf(timeCharacteristic));
        }
        return ctx;
    }

向上追踪，在StreamSource类中调用getSourceContext：

public void run(
            final Object lockingObject,
            final StreamStatusMaintainer streamStatusMaintainer,
            final Output<StreamRecord<OUT>> collector,
            final OperatorChain<?, ?> operatorChain)
            throws Exception {
        
            ....
            this.ctx =
            
            StreamSourceContexts.getSourceContext(
                    timeCharacteristic,
                    getProcessingTimeService(),
                    lockingObject,
                    streamStatusMaintainer,
                    collector,
                    watermarkInterval,
                    -1);
            ....
            }
    // 再向上最终run方法的调用点->是由内部方法run调用
    public void run(
            final Object lockingObject,
            final StreamStatusMaintainer streamStatusMaintainer,
            final OperatorChain<?, ?> operatorChain)
            throws Exception {
        
    
        run(lockingObject, streamStatusMaintainer, output, operatorChain);
    }
    
    //再向上最终run方法的调用点->SourceStreamTask 调用run 然后再代用mainOpterator run方法
    @Override
    public void run() {
        
        try {
        
            // 使用的是类变量lock
            mainOperator.run(lock, getStreamStatusMaintainer(), operatorChain);
            if (!wasStoppedExternally && !isCanceled()) {
        
                synchronized (lock) {
        
                    operatorChain.setIgnoreEndOfInput(false);
                }
            }
            completionFuture.complete(null);
        } catch (Throwable t) {
        
            // Note, t can be also an InterruptedException
            completionFuture.completeExceptionally(t);
        }
    }

###### 小结 ######

所以在源端写数据时，必须**获得SourceStreamTask中的类变量lock的锁才能进行写数据**；类变量lock刚好和执行器时同一个对象

###### 总结 ######

flink的source算子在Checkpoint时，是通过锁对象SourceStreamTask.lock，来控制源端数据产生和Checkpoint的有序进行