1 TaskExecutor端Task退出逻辑
Task.doRun() 引导Task初始化并执行其相关代码的核心方法，
构造并实例化Task的可执行对象： AbstractInvokable invokable。
调用 AbstractInvokable.invoke() 开始启动Task包含的计算逻辑。
当AbstractInvokable.invoke()执行退出后,根据退出类型执行相应操作：
- 正常执行完毕退出：输出ResultPartition缓冲区数据，并关闭缓冲区，标记Task为Finished；
- 取消操作导致退出：标记Task为CANCELED，关闭用户代码；
- AbstractInvokable.invoke()执行过程中抛出异常退出：标记Task为FAILED，关闭用户代码，记录异常；
- AbstractInvokable.invoke()执行过程中JVM抛出错误：强制终止虚拟机，退出当前进程。
紧接着释放Task相关的网络、内存、文件系统资源。最后通过Task->TaskManager->JobMaster的传递链路将Task的终止状态通知给Leader JobMaster线程。
Task.notifyFinalState() -> TaskManagerActions.updateTaskExecutionState(TaskExecutionState) -> JobMasterGateway.updateTaskExecutionState(TaskExecutionState)
- TaskExecutionState携带的关键信息：
TaskExecutionState {
JobID // 任务ID
ExecutionAttemptID // Task执行的唯一ID，标示每次执行
ExecutionState // 枚举值，Task执行状态
SerializedThrowable // 若Task抛出异常，该字段记录异常堆栈信息
...
}
- Task 执行状态转换：
CREATED -> SCHEDULED -> DEPLOYING -> RUNNING -> FINISHED
| | | |
| | | +------+
| | V V
| | CANCELLING -----+----> CANCELED
| | |
| +-------------------------+
|
| ... -> FAILED
V
RECONCILING -> RUNNING | FINISHED | CANCELED | FAILED
2 JobMaster端failover流程
2.1 Task Execute State Handle
JobMaster收到TaskManager通过rpc发送的task执行状态变更信息，将通知当前Flink作业的调度器（SchedulerNG）处理，因为都是通过同个线程调用，后续对ExecutionGraph（运行时执行计划）、failover计数等有状态实例的read/write操作都不会出现线程安全问题。
JobMaster的核心处理逻辑在SchedulerBase.updateTaskExecutionState(TaskExecutionStateTransition) 中（TaskExecutionStateTransition主要是TaskExecutionState的可读性封装）。
处理逻辑：尝试将收到的Task执行状态信息更新到ExecutionGraph中。若更新成功且target状态为FINISHED，根据具体的SchedulingStrategy实现策略，选择可消费的结果分区并调度相应的消费者Task；若更新成功且target状态为FAILED，进入具体的failover流程。
- SchedulerBase.updateTaskExecutionState(TaskExecutionStateTransition) ：
public final boolean updateTaskExecutionState(
final TaskExecutionStateTransition taskExecutionState) {
final Optional<ExecutionVertexID> executionVertexId =
getExecutionVertexId(taskExecutionState.getID());
boolean updateSuccess = executionGraph.updateState(taskExecutionState);
if (updateSuccess) {
checkState(executionVertexId.isPresent());
if (isNotifiable(executionVertexId.get(), taskExecutionState)) {
updateTaskExecutionStateInternal(executionVertexId.get(), taskExecutionState);
}
return true;
} else {
return false;
}
}
- ExecutionGraph.updateState(TaskExecutionStateTransition): 在当前的物理执行拓扑中找不到目标ExecutionAttemptID 时，将更新失败。需要注意的是这个ID用于唯一标示一个Execution，而Execution则代表ExecutionVertex（代表拓扑顶点的一个subTask计划）的一次执行实例，ExecutionVertex可以重复多次执行。这意味着当有subTask重新运行，currentExecutions将不再持有上一次执行的ID信息。
/**
* Updates the state of one of the ExecutionVertex's Execution attempts. If the new status if
* "FINISHED", this also updates the accumulators.
*
* @param state The state update.
* @return True, if the task update was properly applied, false, if the execution attempt was
* not found.
*/
public boolean updateState(TaskExecutionStateTransition state) {
assertRunningInJobMasterMainThread();
final Execution attempt = currentExecutions.get(state.getID());
if (attempt != null) {
try {
final boolean stateUpdated = updateStateInternal(state, attempt);
maybeReleasePartitions(attempt);
return stateUpdated;
} catch (Throwable t) {
......
return false;
}
} else {
return false;
}
}
-
JobMaster: 负责一个任务拓扑的中心操作类，涉及作业调度，资源管理，对外通讯等…
-
SchedulerNG：负责调度作业拓扑。所有对该类对象方法的调用都会通过ComponentMainThreadExecutor触发，将不会出现并发调用的情况。
-
ExecutionGraph: 当前执行拓扑的中心数据结构，协调分布在各个节点上的Execution。描述了整个任务的各个SubTask及其分区数据，并与其保持通讯。
2.2 Job Failover
2.2.1 Task Failure Handle
- Task异常的主要流程在 DefaultScheduler.handleTaskFailure(ExecutionVertexID, Throwable), 根据RestartBackoffTimeStrategy判断是重启还是failed-job；根据FailoverStrategy选择需要重启的SubTask；最后根据任务当前的SchedulingStrategy执行相应的调度策略重启相应的Subtask。
private void handleTaskFailure(
final ExecutionVertexID executionVertexId, @Nullable final Throwable error) {
// 更新当前任务异常信息
setGlobalFailureCause(error);
// 如果相关的算子（source、sink）存在coordinator，同知其进一步操作
notifyCoordinatorsAboutTaskFailure(executionVertexId, error);
// 应用当前的restart-stratege并获取FailureHandlingResult
final FailureHandlingResult failureHandlingResult =
executionFailureHandler.getFailureHandlingResult(executionVertexId, error);
// 根据结果重启Task或将任务失败
maybeRestartTasks(failureHandlingResult);
}
public class FailureHandlingResult {
//恢复所需要重启的所有SubTask
Set<ExecutionVertexID> verticesToRestart;
//重启延迟
long restartDelayMS;
//万恶之源
Throwable error;
//是否全局失败
boolean globalFailure;
}
- ExecutionFailureHandler：处理异常信息，根据当前应用策略返回异常处理结果。
public FailureHandlingResult getFailureHandlingResult(
ExecutionVertexID failedTask, Throwable cause) {
return handleFailure(
cause,
failoverStrategy.getTasksNeedingRestart(failedTask, cause), // 选择出需要重启的SubTask
false);
}
private FailureHandlingResult handleFailure(
final Throwable cause,
final Set<ExecutionVertexID> verticesToRestart,
final boolean globalFailure) {
if (isUnrecoverableError(cause)) {
return FailureHandlingResult.unrecoverable(
new JobException("The failure is not recoverable", cause), globalFailure);
}
restartBackoffTimeStrategy.notifyFailure(cause);
if (restartBackoffTimeStrategy.canRestart()) {
numberOfRestarts++;
return FailureHandlingResult.restartable(
verticesToRestart, restartBackoffTimeStrategy.getBackoffTime(), globalFailure);
} else {
return FailureHandlingResult.unrecoverable(
new JobException(
"Recovery is suppressed by " + restartBackoffTimeStrategy, cause),
globalFailure);
}
}
-
FailoverStrategy: 故障转移策略。
- RestartAllFailoverStrategy： 使用该策略，当出现故障，将重启整个作业，即重启所有Subtask。
- RestartPipelinedRegionFailoverStrategy：当出现故障，重启故障出现Subtask所在的的Region。
- RestartBackoffTimeStrategy: 当Task发生故障时，决定是否重启以及重启的延迟时间。
-
FixedDelayRestartBackoffTimeStrategy：允许任务以指定延迟重启固定次数。
- FailureRateRestartBackoffTimeStrategy：允许在固定失败频率内，以固定延迟重启。
- NoRestartBackoffTimeStrategy：不重启。
-
SchedulingStrategy： Task执行实例的调度策略
- EagerSchedulingStrategy： 饥饿调度，同时调度所有Task。
- LazyFromSourcesSchedulingStrategy：当消费的分区数据都准备好后才开始调度其后续Task，用于批处理任务。
- PipelinedRegionSchedulingStrategy：以pipline链接的Task为一个Region，作为其调度粒度。
2.2.2 Restart Task
private void maybeRestartTasks(final FailureHandlingResult failureHandlingResult) {
if (failureHandlingResult.canRestart()) {
restartTasksWithDelay(failureHandlingResult);
} else {
failJob(failureHandlingResult.getError());
}
}
private void restartTasksWithDelay(final FailureHandlingResult failureHandlingResult) {
final Set<ExecutionVertexID> verticesToRestart =
failureHandlingResult.getVerticesToRestart();
final Set<ExecutionVertexVersion> executionVertexVersions =
new HashSet<>(
executionVertexVersioner
.recordVertexModifications(verticesToRestart)
.values());
final boolean globalRecovery = failureHandlingResult.isGlobalFailure();
addVerticesToRestartPending(verticesToRestart);
// 取消所有需要重启的SubTask
final CompletableFuture<?> cancelFuture = cancelTasksAsync(verticesToRestart);
delayExecutor.schedule(
() ->
FutureUtils.assertNoException(
cancelFuture.thenRunAsync( // 停止后才能重新启动
restartTasks(executionVertexVersions, globalRecovery),
getMainThreadExecutor())),
failureHandlingResult.getRestartDelayMS(),
TimeUnit.MILLISECONDS);
}
2.2.3 Cancel Task：
- 取消正在等待Slot分配的SubTask，若已经处于部署/运行状态，则需要通知TaskExecutor执行停止操作并等待操作完成。
private CompletableFuture<?> cancelTasksAsync(final Set<ExecutionVertexID> verticesToRestart) {
// clean up all the related pending requests to avoid that immediately returned slot
// is used to fulfill the pending requests of these tasks
verticesToRestart.stream().forEach(executionSlotAllocator::cancel); // 取消可能正处于等待分配Slot的SubTask
final List<CompletableFuture<?>> cancelFutures =
verticesToRestart.stream()
.map(this::cancelExecutionVertex) // 开始停止SubTask
.collect(Collectors.toList());
return FutureUtils.combineAll(cancelFutures);
}
public void cancel() {
while (true) { // 状态变更失败则重试
ExecutionState current = this.state;
if (current == CANCELING || current == CANCELED) {
// already taken care of, no need to cancel again
return;
}
else if (current == RUNNING || current == DEPLOYING) {
// 当前状态设为CANCELING，并向TaskExecutor发送RPC请求停止SubTask
if (startCancelling(NUM_CANCEL_CALL_TRIES)) {
return;
}
} else if (current == FINISHED) {
// 即使完成运行，后续也无法消费，释放分区结果
sendReleaseIntermediateResultPartitionsRpcCall();
return;
} else if (current == FAILED) {
return;
} else if (current == CREATED || current == SCHEDULED) {
// from here, we can directly switch to cancelled, because no task has been deployed
if (cancelAtomically()) {
return;
}
} else {
throw new IllegalStateException(current.name());
}
}
}
- 操作完毕后又会执行Task退出流程通知ExecutionGraph执行相应数据更新： ExecutionGraph.updateState(TaskExecutionStateTransition)->ExecutionGraph.updateStateInternal(TaskExecutionStateTransition, Execution) -> Execution.completeCancelling(…) -> Execution.finishCancellation(boolean) -> ExecutionGraph.deregisterExecution(Execution) 。在deregisterExecution操作会在currentExecutions中移除已停止的执行ExecutionTask。
2.2.4 Start Task
private Runnable restartTasks(
final Set<ExecutionVertexVersion> executionVertexVersions,
final boolean isGlobalRecovery) {
return () -> {
final Set<ExecutionVertexID> verticesToRestart =
executionVertexVersioner.getUnmodifiedExecutionVertices(
executionVertexVersions);
removeVerticesFromRestartPending(verticesToRestart);
// 实例化新的SubTask执行实例（Execution）
resetForNewExecutions(verticesToRestart);
try {
// 恢复状态
restoreState(verticesToRestart, isGlobalRecovery);
} catch (Throwable t) {
handleGlobalFailure(t);
return;
}
// 开始调度，申请Slot并部署
schedulingStrategy.restartTasks(verticesToRestart);
};
}
3 Task失败的自动重启策略
Task 级别的故障重启，是系统自动进行的；文章来源：https://www.toymoban.com/news/detail-836434.html
文章来源地址https://www.toymoban.com/news/detail-836434.html
到了这里，关于Flink Task退出流程与Failover机制的文章就介绍完了。如果您还想了解更多内容，请在右上角搜索TOY模板网以前的文章或继续浏览下面的相关文章，希望大家以后多多支持TOY模板网！
