Class/Object

org.apache.spark

TaskContext

Related Docs: object TaskContext | package spark

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abstract class TaskContext extends Serializable

Contextual information about a task which can be read or mutated during execution. To access the TaskContext for a running task, use:

org.apache.spark.TaskContext.get()
Source
TaskContext.scala
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Instance Constructors

  1. new TaskContext()

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Abstract Value Members

  1. abstract def addTaskCompletionListener(listener: TaskCompletionListener): TaskContext

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    Adds a (Java friendly) listener to be executed on task completion.

    Adds a (Java friendly) listener to be executed on task completion. This will be called in all situation - success, failure, or cancellation. An example use is for HadoopRDD to register a callback to close the input stream.

    Exceptions thrown by the listener will result in failure of the task.

  2. abstract def addTaskFailureListener(listener: TaskFailureListener): TaskContext

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    Adds a listener to be executed on task failure.

    Adds a listener to be executed on task failure. Operations defined here must be idempotent, as onTaskFailure can be called multiple times.

  3. abstract def attemptNumber(): Int

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    How many times this task has been attempted.

    How many times this task has been attempted. The first task attempt will be assigned attemptNumber = 0, and subsequent attempts will have increasing attempt numbers.

  4. abstract def getLocalProperty(key: String): String

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    Get a local property set upstream in the driver, or null if it is missing.

    Get a local property set upstream in the driver, or null if it is missing. See also org.apache.spark.SparkContext.setLocalProperty.

  5. abstract def getMetricsSources(sourceName: String): Seq[Source]

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    ::DeveloperApi:: Returns all metrics sources with the given name which are associated with the instance which runs the task.

    ::DeveloperApi:: Returns all metrics sources with the given name which are associated with the instance which runs the task. For more information see org.apache.spark.metrics.MetricsSystem.

    Annotations
    @DeveloperApi()
  6. abstract def isCompleted(): Boolean

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    Returns true if the task has completed.

  7. abstract def isInterrupted(): Boolean

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    Returns true if the task has been killed.

  8. abstract def partitionId(): Int

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    The ID of the RDD partition that is computed by this task.

  9. abstract def stageAttemptNumber(): Int

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    How many times the stage that this task belongs to has been attempted.

    How many times the stage that this task belongs to has been attempted. The first stage attempt will be assigned stageAttemptNumber = 0, and subsequent attempts will have increasing attempt numbers.

  10. abstract def stageId(): Int

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    The ID of the stage that this task belong to.

  11. abstract def taskAttemptId(): Long

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    An ID that is unique to this task attempt (within the same SparkContext, no two task attempts will share the same attempt ID).

    An ID that is unique to this task attempt (within the same SparkContext, no two task attempts will share the same attempt ID). This is roughly equivalent to Hadoop's TaskAttemptID.

  12. abstract def taskMetrics(): TaskMetrics

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    Annotations
    @DeveloperApi()
  13. abstract def isRunningLocally(): Boolean

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    Returns true if the task is running locally in the driver program.

    Returns true if the task is running locally in the driver program.

    returns

    false

    Annotations
    @deprecated
    Deprecated

    (Since version 2.0.0) Local execution was removed, so this always returns false

Concrete Value Members

  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. def addTaskCompletionListener(f: (TaskContext) ⇒ Unit): TaskContext

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    Adds a listener in the form of a Scala closure to be executed on task completion.

    Adds a listener in the form of a Scala closure to be executed on task completion. This will be called in all situations - success, failure, or cancellation. An example use is for HadoopRDD to register a callback to close the input stream.

    Exceptions thrown by the listener will result in failure of the task.

  5. def addTaskFailureListener(f: (TaskContext, Throwable) ⇒ Unit): TaskContext

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    Adds a listener to be executed on task failure.

    Adds a listener to be executed on task failure. Operations defined here must be idempotent, as onTaskFailure can be called multiple times.

  6. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

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  11. final def getClass(): Class[_]

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  15. final def notify(): Unit

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  19. final def wait(): Unit

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  20. final def wait(arg0: Long, arg1: Int): Unit

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  21. final def wait(arg0: Long): Unit

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