Class

io.smartdatalake.workflow.action

SparkSubFeedsAction

Related Doc: package action

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abstract class SparkSubFeedsAction extends Action

Linear Supertypes
Action, SmartDataLakeLogger, DAGNode, ParsableFromConfig[Action], SdlConfigObject, AnyRef, Any
Known Subclasses
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Inherited
  1. SparkSubFeedsAction
  2. Action
  3. SmartDataLakeLogger
  4. DAGNode
  5. ParsableFromConfig
  6. SdlConfigObject
  7. AnyRef
  8. Any
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Visibility
  1. Public
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Instance Constructors

  1. new SparkSubFeedsAction()

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Abstract Value Members

  1. abstract def factory: FromConfigFactory[Action]

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    Returns the factory that can parse this type (that is, type CO).

    Returns the factory that can parse this type (that is, type CO).

    Typically, implementations of this method should return the companion object of the implementing class. The companion object in turn should implement FromConfigFactory.

    returns

    the factory (object) for this class.

    Definition Classes
    ParsableFromConfig
  2. abstract val id: ActionObjectId

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    A unique identifier for this instance.

    A unique identifier for this instance.

    Definition Classes
    Action → SdlConfigObject
  3. abstract def initExecutionMode: Option[ExecutionMode]

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    Execution mode if this Action is a start node of a DAG run

  4. abstract def inputs: Seq[DataObject with CanCreateDataFrame]

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    Input DataObjects To be implemented by subclasses

    Input DataObjects To be implemented by subclasses

    Definition Classes
    SparkSubFeedsAction → Action
  5. abstract def metadata: Option[ActionMetadata]

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    Additional metadata for the Action

    Additional metadata for the Action

    Definition Classes
    Action
  6. abstract def outputs: Seq[DataObject with CanWriteDataFrame]

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    Output DataObjects To be implemented by subclasses

    Output DataObjects To be implemented by subclasses

    Definition Classes
    SparkSubFeedsAction → Action
  7. abstract def transform(subFeeds: Seq[SparkSubFeed])(implicit session: SparkSession, context: ActionPipelineContext): Seq[SparkSubFeed]

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    Transform SparkSubFeed's.

    Transform SparkSubFeed's. To be implemented by subclasses.

    subFeeds

    SparkSubFeed's to be transformed

    returns

    transformed SparkSubFeed's

Concrete Value Members

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

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    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  4. def addRuntimeEvent(phase: String, state: RuntimeEventState, msg: String): Unit

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    Adds an action event

    Adds an action event

    Definition Classes
    Action
  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  6. def breakDataFrameLineage: Boolean

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    Stop propagating input DataFrame through action and instead get a new DataFrame from DataObject This is needed if the input DataFrame includes many transformations from previous Actions.

  7. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  8. def enableRuntimeMetrics(): Unit

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    Runtime metrics

    Runtime metrics

    Note: runtime metrics are disabled by default, because they are only collected when running Actions from an ActionDAG. This is not the case for Tests other use cases. If enabled exceptions are thrown if metrics are not found.

    Definition Classes
    Action
  9. def enrichSubFeedsDataFrame(inputs: Seq[DataObject with CanCreateDataFrame], subFeeds: Seq[SparkSubFeed])(implicit session: SparkSession): Seq[SparkSubFeed]

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    Enriches SparkSubFeeds with DataFrame if not existing

    Enriches SparkSubFeeds with DataFrame if not existing

    inputs

    input data objects.

    subFeeds

    input SubFeeds.

    Attributes
    protected
  10. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  11. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  12. final def exec(subFeeds: Seq[SubFeed])(implicit session: SparkSession, context: ActionPipelineContext): Seq[SubFeed]

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    Action.exec implementation

    Action.exec implementation

    subFeeds

    SparkSubFeed's to be processed

    returns

    processed SparkSubFeed's

    Definition Classes
    SparkSubFeedsAction → Action
  13. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  14. final def getClass(): Class[_]

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    Definition Classes
    AnyRef → Any
  15. def getFinalMetrics(dataObjectId: DataObjectId): Option[ActionMetrics]

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    Definition Classes
    Action
  16. def getInputDataObject[T <: DataObject](id: DataObjectId)(implicit arg0: ClassTag[T], arg1: scala.reflect.api.JavaUniverse.TypeTag[T], registry: InstanceRegistry): T

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    Attributes
    protected
    Definition Classes
    Action
  17. def getOutputDataObject[T <: DataObject](id: DataObjectId)(implicit arg0: ClassTag[T], arg1: scala.reflect.api.JavaUniverse.TypeTag[T], registry: InstanceRegistry): T

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    Attributes
    protected
    Definition Classes
    Action
  18. def getRuntimeState: (Option[RuntimeEventState], Option[Duration])

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    get latest runtime state and duration if successfully finished.

    get latest runtime state and duration if successfully finished.

    Definition Classes
    Action
  19. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  20. final def init(subFeeds: Seq[SubFeed])(implicit session: SparkSession, context: ActionPipelineContext): Seq[SubFeed]

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    Generic init implementation for Action.init

    Generic init implementation for Action.init

    subFeeds

    SparkSubFeed's to be processed

    returns

    processed SparkSubFeed's

    Definition Classes
    SparkSubFeedsAction → Action
  21. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any
  22. lazy val logger: Logger

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    Attributes
    protected
    Definition Classes
    SmartDataLakeLogger
  23. lazy val mainInput: Option[DataObject with CanCreateDataFrame]

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    Attributes
    protected
  24. lazy val mainOutput: Option[DataObject with CanWriteDataFrame]

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    Attributes
    protected
  25. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  26. def nodeId: String

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    provide an implementation of the DAG node id

    provide an implementation of the DAG node id

    Definition Classes
    Action → DAGNode
  27. final def notify(): Unit

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    Definition Classes
    AnyRef
  28. final def notifyAll(): Unit

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    Definition Classes
    AnyRef
  29. def onRuntimeMetrics(dataObjectId: Option[DataObjectId], metrics: ActionMetrics): Unit

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    Definition Classes
    Action
  30. def persist: Boolean

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    Force persisting DataFrame on Disk.

    Force persisting DataFrame on Disk. This helps to reduce memory needed for caching the DataFrame content and can serve as a recovery point in case an task get's lost.

  31. def postExec(inputSubFeed: Seq[SubFeed], outputSubFeed: Seq[SubFeed])(implicit session: SparkSession, context: ActionPipelineContext): Unit

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    Executes operations needed after executing an action.

    Executes operations needed after executing an action. In this step any operation on Input- or Output-DataObjects needed after the main task is executed, e.g. JdbcTableDataObjects postSql or CopyActions deleteInputData.

    Definition Classes
    Action
  32. def preExec(implicit session: SparkSession, context: ActionPipelineContext): Unit

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    Executes operations needed before executing an action.

    Executes operations needed before executing an action. In this step any operation on Input- or Output-DataObjects needed before the main task is executed, e.g. JdbcTableDataObjects preSql

    Definition Classes
    Action
  33. def prepare(implicit session: SparkSession, context: ActionPipelineContext): Unit

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    Prepare DataObjects prerequisites.

    Prepare DataObjects prerequisites. In this step preconditions are prepared & tested: - directories exists or can be created - connections can be created

    This runs during the "prepare" operation of the DAG.

    Definition Classes
    Action
  34. def setSparkJobMetadata(operation: Option[String] = None)(implicit session: SparkSession): Unit

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    Sets the util job description for better traceability in the Spark UI

    Sets the util job description for better traceability in the Spark UI

    Note: This sets Spark local properties, which are propagated to the respective executor tasks. We rely on this to match metrics back to Actions and DataObjects. As writing to a DataObject on the Driver happens uninterrupted in the same exclusive thread, this is suitable.

    operation

    operation description (be short...)

    Definition Classes
    Action
  35. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  36. final def toString(): String

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    This is displayed in ascii graph visualization

    This is displayed in ascii graph visualization

    Definition Classes
    Action → AnyRef → Any
  37. def toStringMedium: String

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    Definition Classes
    Action
  38. def toStringShort: String

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    Definition Classes
    Action
  39. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  40. final def wait(arg0: Long, arg1: Int): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  41. final def wait(arg0: Long): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Action

Inherited from SmartDataLakeLogger

Inherited from DAGNode

Inherited from ParsableFromConfig[Action]

Inherited from SdlConfigObject

Inherited from AnyRef

Inherited from Any

Ungrouped