runTask(context: TaskContext): MapStatus
ShuffleMapTask — Task for ShuffleMapStage
ShuffleMapTask is a Task that computes a MapStatus, i.e. writes the result of computing records in a RDD partition to the shuffle system and returns information about the BlockManager and estimated size of the result shuffle blocks.
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Empty if locs was not defined. |
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Note
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Spark uses broadcast variables to send (serialized) tasks to executors. |
Creating ShuffleMapTask Instance
ShuffleMapTask takes the following when created:
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stageId— the stage of the task, -
stageAttemptId— the stage’s attempt, -
taskBinary— the broadcast variable with the serialized task (as an array of bytes), -
localProperties— task-specific local properties, -
serializedTaskMetrics— the serialized FIXME (as an array of bytes), -
jobId— optional ActiveJob id (default: undefined), -
appId— optional application id (default: undefined), -
appAttemptId— optional application attempt id (default: undefined).
ShuffleMapTask calculates preferredLocs internal attribute that is the input locs if defined. Otherwise, it is empty.
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Note
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preferredLocs and locs are transient so they are not sent over the wire with the task.
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Note
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ShuffleMapTask is created when DAGScheduler submits missing tasks for a ShuffleMapStage.
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Writing Records (After Computing RDD Partition) to Shuffle System — runTask Method
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Note
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runTask is a part of Task contract to…FIXME
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runTask computes a MapStatus (which is the BlockManager and an estimated size of the result shuffle block) after the records of the Partition were written to the shuffle system.
Internally, runTask uses the current closure Serializer to deserialize the taskBinary serialized task (into a pair of RDD and ShuffleDependency).
runTask measures the thread and CPU time for deserialization (using the System clock and JMX if supported) and stores it in _executorDeserializeTime and _executorDeserializeCpuTime attributes.
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Note
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runTask uses SparkEnv to access the current closure Serializer.
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The taskBinary serialized task is given when ShuffleMapTask is created.
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runTask requests ShuffleManager for a ShuffleWriter (given the ShuffleHandle of the deserialized ShuffleDependency, partitionId and input TaskContext).
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Note
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runTask uses SparkEnv to access the current ShuffleManager.
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The partitionId partition is given when ShuffleMapTask is created.
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runTask gets the records in the RDD partition (as an Iterator) and writes them (to the shuffle system).
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Note
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This is the moment in Task's lifecycle (and its corresponding RDD) when a RDD partition is computed and in turn becomes a sequence of records (i.e. real data) on a executor.
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runTask stops the ShuffleWriter (with success flag enabled) and returns the MapStatus.
When the record writing was not successful, runTask stops the ShuffleWriter (with success flag disabled) and the exception is re-thrown.
You may also see the following DEBUG message in the logs when the ShuffleWriter could not be stopped.
DEBUG Could not stop writer
preferredLocations Method
preferredLocations: Seq[TaskLocation]
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Note
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preferredLocations is a part of Task contract to…FIXME
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preferredLocations simply returns preferredLocs internal property.