【flink状态管理（四）】MemoryStateBackend的实现

文章目录

• 1.基于MemoryStateBackend创建KeyedStateBackend
• 2. 基于MemoryStateBackend创建OperatorStateBackend
• 3.基于MemoryStateBackend创建CheckpointStorage

在Flink中，默认的StateBackend实现为MemoryStateBackend，本文以MemoryStateBackend为例说明StateBackend的设计与实现。

 
本文介绍MemoryStateBackend中如下三个主要组件的创建过程：

FsStateBackend和RocksDBStateBackend这两种状态后端存储的实现，功能和MemoryStateBackend类似，区别在于内部创建的KeyedStateBackend和CheckpointStorage。

 

1.基于MemoryStateBackend创建KeyedStateBackend

1.1. 状态初始化

AbstractStreamOperator.keyedStatedBackend()方法定义了创建和初始化KeyedStatedBackend的逻辑，具体如下。

protected <K> AbstractKeyedStateBackend<K> keyedStateBackend(
   TypeSerializer<K> keySerializer,
   String operatorIdentifierText,
   PrioritizedOperatorSubtaskState prioritizedOperatorSubtaskStates,
   CloseableRegistry backendCloseableRegistry,
   MetricGroup metricGroup) throws Exception {
   if (keySerializer == null) {
      return null;
   }
   String logDescription = "keyed state backend for " + operatorIdentifierText;
   //1. 
   TaskInfo taskInfo = environment.getTaskInfo();
   final KeyGroupRange keyGroupRange = 
       KeyGroupRangeAssignment.computeKeyGroupRangeForOperatorIndex(
      taskInfo.getMaxNumberOfParallelSubtasks(),
      taskInfo.getNumberOfParallelSubtasks(),
      taskInfo.getIndexOfThisSubtask());
   // 确保恢复状态过程中构建的数据流被关闭
   CloseableRegistry cancelStreamRegistryForRestore = new CloseableRegistry();
   backendCloseableRegistry.registerCloseable(cancelStreamRegistryForRestore);
   // 创建BackendRestorerProcedure
   BackendRestorerProcedure<AbstractKeyedStateBackend<K>, KeyedStateHandle> 
      backendRestorer =
      new BackendRestorerProcedure<>(
         (stateHandles) -> stateBackend.createKeyedStateBackend(
            environment,
            environment.getJobID(),
            operatorIdentifierText,
            keySerializer,
            taskInfo.getMaxNumberOfParallelSubtasks(),
            keyGroupRange,
            environment.getTaskKvStateRegistry(),
            TtlTimeProvider.DEFAULT,
            metricGroup,
            stateHandles,
            cancelStreamRegistryForRestore),
         backendCloseableRegistry,
         logDescription);
   try {
      return backendRestorer.createAndRestore(
         prioritizedOperatorSubtaskStates.getPrioritizedManagedKeyedState());
   } finally {
      if (backendCloseableRegistry.unregisterCloseable(cancelStreamRegistryFor
         Restore)) {
         IOUtils.closeQuietly(cancelStreamRegistryForRestore);
      }
   }
}

 

1.2. 创建状态

接下来我们看MemoryStateBackend.createKeyedStateBackend()方法的具体实现。

public <K> AbstractKeyedStateBackend<K> createKeyedStateBackend(
   Environment env,
   JobID jobID,
   String operatorIdentifier,
   TypeSerializer<K> keySerializer,
   int numberOfKeyGroups,
   KeyGroupRange keyGroupRange,
   TaskKvStateRegistry kvStateRegistry,
   TtlTimeProvider ttlTimeProvider,
   MetricGroup metricGroup,
   @Nonnull Collection<KeyedStateHandle> stateHandles,
   CloseableRegistry cancelStreamRegistry) throws BackendBuildingException {
   // 获取TaskStateManager实例
   TaskStateManager taskStateManager = env.getTaskStateManager();
   // 创建HeapPriorityQueueSetFactory实例
   HeapPriorityQueueSetFactory priorityQueueSetFactory =
      new HeapPriorityQueueSetFactory(keyGroupRange, numberOfKeyGroups, 128);
   // 创建HeapKeyedStateBackendBuilder实例HeapKeyedStateBackend
   return new HeapKeyedStateBackendBuilder<>(
      kvStateRegistry,
      keySerializer,
      env.getUserClassLoader(),
      numberOfKeyGroups,
      keyGroupRange,
      env.getExecutionConfig(),
      ttlTimeProvider,
      stateHandles,
      AbstractStateBackend.getCompressionDecorator(env.getExecutionConfig()),
      taskStateManager.createLocalRecoveryConfig(),
      priorityQueueSetFactory,
      isUsingAsynchronousSnapshots(),
      cancelStreamRegistry).build();
}

 

2. 基于MemoryStateBackend创建OperatorStateBackend

和创建KeyedStateBackend的过程相似，AbstractStreamOperator.operatorStateBackend()方法实现了创建OperatorStateBackend的方法。

protected OperatorStateBackend operatorStateBackend(
   String operatorIdentifierText,
   PrioritizedOperatorSubtaskState prioritizedOperatorSubtaskStates,
   CloseableRegistry backendCloseableRegistry) throws Exception {
   String logDescription = "operator state backend for " + operatorIdentifierText;
   CloseableRegistry cancelStreamRegistryForRestore = new CloseableRegistry();
   backendCloseableRegistry.registerCloseable(cancelStreamRegistryForRestore);
   BackendRestorerProcedure<OperatorStateBackend, OperatorStateHandle> 
      backendRestorer =
      new BackendRestorerProcedure<>(
         (stateHandles) -> stateBackend.createOperatorStateBackend(
            environment,
            operatorIdentifierText,
            stateHandles,
            cancelStreamRegistryForRestore),
         backendCloseableRegistry,
         logDescription);
   try {
      return backendRestorer.createAndRestore(
         prioritizedOperatorSubtaskStates.getPrioritizedManagedOperatorState());
   } finally {
      if (backendCloseableRegistry.unregisterCloseable(cancelStreamRegistryFor
         Restore)) {
         IOUtils.closeQuietly(cancelStreamRegistryForRestore);
      }
   }
}

其中prioritizedOperatorSubtaskStates是从TaskStateManager中根据OperatorID获取的算子专有历史状态，可以通过prioritizedOperatorSubtaskStates获取当前算子中的PrioritizedManagedOperatorState，并基于这些状态数据恢复OperatorStateBackend中算子的状态。

 

3.基于MemoryStateBackend创建CheckpointStorage

在createCheckpointStorage()方法中，直接创建MemoryBackendCheckpointStorage实例并返回，没有涉及太多的流程

public CheckpointStorage createCheckpointStorage(JobID jobId) throws IOException {
   return new MemoryBackendCheckpointStorage(jobId, getCheckpointPath(), 
      getSavepointPath(), maxStateSize);
}

 

参考：《Flink设计与实现：核心原理与源码解析》–张利兵