case class CustomSparkAction(id: ActionId, inputIds: Seq[DataObjectId], outputIds: Seq[DataObjectId], transformer: Option[CustomDfsTransformerConfig] = None, transformers: Seq[ParsableDfsTransformer] = Seq(), breakDataFrameLineage: Boolean = false, persist: Boolean = false, mainInputId: Option[DataObjectId] = None, mainOutputId: Option[DataObjectId] = None, executionMode: Option[ExecutionMode] = None, executionCondition: Option[Condition] = None, metricsFailCondition: Option[String] = None, metadata: Option[ActionMetadata] = None, recursiveInputIds: Seq[DataObjectId] = Seq(), inputIdsToIgnoreFilter: Seq[DataObjectId] = Seq())(implicit instanceRegistry: InstanceRegistry) extends SparkActionImpl with Product with Serializable

Action to transform data according to a custom transformer. Allows to transform multiple input and output dataframes.

inputIds

input DataObject's

outputIds

output DataObject's

transformer

custom transformation for multiple dataframes to apply

mainInputId

optional selection of main inputId used for execution mode and partition values propagation. Only needed if there are multiple input DataObject's.

mainOutputId

optional selection of main outputId used for execution mode and partition values propagation. Only needed if there are multiple output DataObject's.

executionMode

optional execution mode for this Action

executionCondition

optional spark sql expression evaluated against SubFeedsExpressionData. If true Action is executed, otherwise skipped. Details see Condition.

metricsFailCondition

optional spark sql expression evaluated as where-clause against dataframe of metrics. Available columns are dataObjectId, key, value. If there are any rows passing the where clause, a MetricCheckFailed exception is thrown.

recursiveInputIds

output of action that are used as input in the same action

inputIdsToIgnoreFilter

optional list of input ids to ignore filter (partition values & filter clause)

Annotations
@Scaladoc()
Linear Supertypes
Serializable, Serializable, Product, Equals, SparkActionImpl, ActionSubFeedsImpl[SparkSubFeed], Action, AtlasExportable, SmartDataLakeLogger, DAGNode, ParsableFromConfig[Action], SdlConfigObject, AnyRef, Any
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  1. CustomSparkAction
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. SparkActionImpl
  7. ActionSubFeedsImpl
  8. Action
  9. AtlasExportable
  10. SmartDataLakeLogger
  11. DAGNode
  12. ParsableFromConfig
  13. SdlConfigObject
  14. AnyRef
  15. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new CustomSparkAction(id: ActionId, inputIds: Seq[DataObjectId], outputIds: Seq[DataObjectId], transformer: Option[CustomDfsTransformerConfig] = None, transformers: Seq[ParsableDfsTransformer] = Seq(), breakDataFrameLineage: Boolean = false, persist: Boolean = false, mainInputId: Option[DataObjectId] = None, mainOutputId: Option[DataObjectId] = None, executionMode: Option[ExecutionMode] = None, executionCondition: Option[Condition] = None, metricsFailCondition: Option[String] = None, metadata: Option[ActionMetadata] = None, recursiveInputIds: Seq[DataObjectId] = Seq(), inputIdsToIgnoreFilter: Seq[DataObjectId] = Seq())(implicit instanceRegistry: InstanceRegistry)

    inputIds

    input DataObject's

    outputIds

    output DataObject's

    transformer

    custom transformation for multiple dataframes to apply

    mainInputId

    optional selection of main inputId used for execution mode and partition values propagation. Only needed if there are multiple input DataObject's.

    mainOutputId

    optional selection of main outputId used for execution mode and partition values propagation. Only needed if there are multiple output DataObject's.

    executionMode

    optional execution mode for this Action

    executionCondition

    optional spark sql expression evaluated against SubFeedsExpressionData. If true Action is executed, otherwise skipped. Details see Condition.

    metricsFailCondition

    optional spark sql expression evaluated as where-clause against dataframe of metrics. Available columns are dataObjectId, key, value. If there are any rows passing the where clause, a MetricCheckFailed exception is thrown.

    recursiveInputIds

    output of action that are used as input in the same action

    inputIdsToIgnoreFilter

    optional list of input ids to ignore filter (partition values & filter clause)

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. def addRuntimeEvent(executionId: ExecutionId, phase: ExecutionPhase, state: RuntimeEventState, msg: Option[String] = None, results: Seq[SubFeed] = Seq(), tstmp: LocalDateTime = LocalDateTime.now): Unit

    Adds a runtime event for this Action

    Adds a runtime event for this Action

    Definition Classes
    Action
    Annotations
    @Scaladoc()
  5. def addRuntimeMetrics(executionId: Option[ExecutionId], dataObjectId: Option[DataObjectId], metric: ActionMetrics): Unit

    Adds a runtime metric for this Action

    Adds a runtime metric for this Action

    Definition Classes
    Action
    Annotations
    @Scaladoc()
  6. def applyExecutionMode(mainInput: DataObject, mainOutput: DataObject, subFeed: SubFeed, partitionValuesTransform: (Seq[PartitionValues]) ⇒ Map[PartitionValues, PartitionValues])(implicit context: ActionPipelineContext): Unit

    Applies the executionMode and stores result in executionModeResult variable

    Applies the executionMode and stores result in executionModeResult variable

    Attributes
    protected
    Definition Classes
    Action
    Annotations
    @Scaladoc()
  7. def applyTransformers(transformers: Seq[PartitionValueTransformer], partitionValues: Seq[PartitionValues])(implicit context: ActionPipelineContext): Map[PartitionValues, PartitionValues]

    apply transformer to partition values

    apply transformer to partition values

    Attributes
    protected
    Definition Classes
    SparkActionImpl
    Annotations
    @Scaladoc()
  8. def applyTransformers(transformers: Seq[DfsTransformer], inputPartitionValues: Seq[PartitionValues], inputSubFeeds: Seq[SparkSubFeed], outputSubFeeds: Seq[SparkSubFeed])(implicit context: ActionPipelineContext): Seq[SparkSubFeed]

    apply transformer to SubFeeds

    apply transformer to SubFeeds

    Attributes
    protected
    Definition Classes
    SparkActionImpl
    Annotations
    @Scaladoc()
  9. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  10. def atlasName: String
    Definition Classes
    Action → AtlasExportable
  11. def atlasQualifiedName(prefix: String): String
    Definition Classes
    AtlasExportable
  12. val breakDataFrameLineage: Boolean

    Stop propagating input DataFrame through action and instead get a new DataFrame from DataObject.

    Stop propagating input DataFrame through action and instead get a new DataFrame from DataObject. This can help to save memory and performance if the input DataFrame includes many transformations from previous Actions. The new DataFrame will be initialized according to the SubFeed's partitionValues.

    Definition Classes
    CustomSparkAction → SparkActionImpl
  13. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native() @HotSpotIntrinsicCandidate()
  14. def createEmptyDataFrame(dataObject: DataObject with CanCreateDataFrame, subFeed: SparkSubFeed)(implicit context: ActionPipelineContext): DataFrame
    Definition Classes
    SparkActionImpl
  15. def enrichSubFeedDataFrame(input: DataObject with CanCreateDataFrame, subFeed: SparkSubFeed, phase: ExecutionPhase, isRecursive: Boolean = false)(implicit context: ActionPipelineContext): SparkSubFeed

    Enriches SparkSubFeed with DataFrame if not existing

    Enriches SparkSubFeed with DataFrame if not existing

    input

    input data object.

    subFeed

    input SubFeed.

    phase

    current execution phase

    isRecursive

    true if this input is a recursive input

    Definition Classes
    SparkActionImpl
    Annotations
    @Scaladoc()
  16. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  17. final def exec(subFeeds: Seq[SubFeed])(implicit context: ActionPipelineContext): Seq[SubFeed]

    Executes the main task of an action.

    Executes the main task of an action. In this step the data of the SubFeed's is moved from Input- to Output-DataObjects.

    subFeeds

    SparkSubFeed's to be processed

    returns

    processed SparkSubFeed's

    Definition Classes
    ActionSubFeedsImpl → Action
  18. val executionCondition: Option[Condition]

    execution condition for this action.

    execution condition for this action.

    Definition Classes
    CustomSparkAction → Action
  19. val executionConditionResult: Option[(Boolean, Option[String])]
    Attributes
    protected
    Definition Classes
    Action
  20. val executionMode: Option[ExecutionMode]

    execution mode for this action.

    execution mode for this action.

    Definition Classes
    CustomSparkAction → Action
  21. val executionModeResult: Option[Try[Option[ExecutionModeResult]]]
    Attributes
    protected
    Definition Classes
    Action
  22. def factory: FromConfigFactory[Action]

    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
    CustomSparkAction → ParsableFromConfig
  23. def filterDataFrame(df: DataFrame, partitionValues: Seq[PartitionValues], genericFilter: Option[Column]): DataFrame

    Filter DataFrame with given partition values

    Filter DataFrame with given partition values

    df

    DataFrame to filter

    partitionValues

    partition values to use as filter condition

    genericFilter

    filter expression to apply

    returns

    filtered DataFrame

    Definition Classes
    SparkActionImpl
    Annotations
    @Scaladoc()
  24. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  25. def getDataObjectsState: Seq[DataObjectState]

    Get potential state of input DataObjects when executionMode is DataObjectStateIncrementalMode.

    Get potential state of input DataObjects when executionMode is DataObjectStateIncrementalMode.

    Definition Classes
    Action
    Annotations
    @Scaladoc()
  26. def getInputDataObject[T <: DataObject](id: DataObjectId)(implicit arg0: ClassTag[T], arg1: scala.reflect.api.JavaUniverse.TypeTag[T], registry: InstanceRegistry): T
    Attributes
    protected
    Definition Classes
    Action
  27. def getLatestRuntimeEventState: Option[RuntimeEventState]

    Get latest runtime state

    Get latest runtime state

    Definition Classes
    Action
    Annotations
    @Scaladoc()
  28. def getMainInput(inputSubFeeds: Seq[SubFeed])(implicit context: ActionPipelineContext): DataObject
    Attributes
    protected
    Definition Classes
    ActionSubFeedsImpl
  29. def getMainPartitionValues(inputSubFeeds: Seq[SubFeed])(implicit context: ActionPipelineContext): Seq[PartitionValues]
    Attributes
    protected
    Definition Classes
    ActionSubFeedsImpl
  30. def getOutputDataObject[T <: DataObject](id: DataObjectId)(implicit arg0: ClassTag[T], arg1: scala.reflect.api.JavaUniverse.TypeTag[T], registry: InstanceRegistry): T
    Attributes
    protected
    Definition Classes
    Action
  31. def getRuntimeDataImpl: RuntimeData
    Definition Classes
    SparkActionImpl → Action
  32. def getRuntimeInfo(executionId: Option[ExecutionId] = None): Option[RuntimeInfo]

    Get summarized runtime information for a given ExecutionId.

    Get summarized runtime information for a given ExecutionId.

    executionId

    ExecutionId to get runtime information for. If empty runtime information for last ExecutionId are returned.

    Definition Classes
    Action
    Annotations
    @Scaladoc()
  33. def getRuntimeMetrics(executionId: Option[ExecutionId] = None): Map[DataObjectId, Option[ActionMetrics]]

    Get the latest metrics for all DataObjects and a given SDLExecutionId.

    Get the latest metrics for all DataObjects and a given SDLExecutionId.

    executionId

    ExecutionId to get metrics for. If empty metrics for last ExecutionId are returned.

    Definition Classes
    Action
    Annotations
    @Scaladoc()
  34. val id: ActionId

    A unique identifier for this instance.

    A unique identifier for this instance.

    Definition Classes
    CustomSparkAction → Action → SdlConfigObject
  35. final def init(subFeeds: Seq[SubFeed])(implicit context: ActionPipelineContext): Seq[SubFeed]

    Initialize Action with SubFeed's to be processed.

    Initialize Action with SubFeed's to be processed. In this step the execution mode is evaluated and the result stored for the exec phase. If successful - the DAG can be built - Spark DataFrame lineage can be built

    subFeeds

    SparkSubFeed's to be processed

    returns

    processed SparkSubFeed's

    Definition Classes
    ActionSubFeedsImpl → Action
  36. val inputIds: Seq[DataObjectId]
  37. val inputIdsToIgnoreFilter: Seq[DataObjectId]
    Definition Classes
    CustomSparkAction → ActionSubFeedsImpl
  38. val inputs: Seq[DataObject with CanCreateDataFrame]

    Input DataObjects To be implemented by subclasses

    Input DataObjects To be implemented by subclasses

    Definition Classes
    CustomSparkAction → SparkActionImpl → Action
  39. def isAsynchronous: Boolean

    If this Action should be run as asynchronous streaming process

    If this Action should be run as asynchronous streaming process

    Definition Classes
    SparkActionImpl → Action
  40. def isAsynchronousProcessStarted: Boolean
    Definition Classes
    SparkActionImpl → Action
  41. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  42. def logWritingFinished(subFeed: SparkSubFeed, noData: Option[Boolean], duration: Duration)(implicit context: ActionPipelineContext): Unit
    Attributes
    protected
    Definition Classes
    ActionSubFeedsImpl
  43. def logWritingStarted(subFeed: SparkSubFeed)(implicit context: ActionPipelineContext): Unit
    Attributes
    protected
    Definition Classes
    ActionSubFeedsImpl
  44. lazy val logger: Logger
    Attributes
    protected
    Definition Classes
    SmartDataLakeLogger
    Annotations
    @transient()
  45. val mainInputId: Option[DataObjectId]
    Definition Classes
    CustomSparkAction → ActionSubFeedsImpl
  46. lazy val mainOutput: DataObject
    Attributes
    protected
    Definition Classes
    ActionSubFeedsImpl
  47. val mainOutputId: Option[DataObjectId]
    Definition Classes
    CustomSparkAction → ActionSubFeedsImpl
  48. val metadata: Option[ActionMetadata]

    Additional metadata for the Action

    Additional metadata for the Action

    Definition Classes
    CustomSparkAction → Action
  49. val metricsFailCondition: Option[String]

    Spark SQL condition evaluated as where-clause against dataframe of metrics.

    Spark SQL condition evaluated as where-clause against dataframe of metrics. Available columns are dataObjectId, key, value. If there are any rows passing the where clause, a MetricCheckFailed exception is thrown.

    Definition Classes
    CustomSparkAction → Action
  50. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  51. def nodeId: String

    provide an implementation of the DAG node id

    provide an implementation of the DAG node id

    Definition Classes
    Action → DAGNode
    Annotations
    @Scaladoc()
  52. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  53. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  54. val outputIds: Seq[DataObjectId]
  55. val outputs: Seq[DataObject with CanWriteDataFrame]

    Output DataObjects To be implemented by subclasses

    Output DataObjects To be implemented by subclasses

    Definition Classes
    CustomSparkAction → SparkActionImpl → Action
  56. val persist: Boolean

    Force persisting input DataFrame's on Disk.

    Force persisting input DataFrame's on Disk. This improves performance if dataFrame is used multiple times in the transformation and can serve as a recovery point in case a task get's lost. Note that DataFrames are persisted automatically by the previous Action if later Actions need the same data. To avoid this behaviour set breakDataFrameLineage=false.

    Definition Classes
    CustomSparkAction → SparkActionImpl
  57. def postExec(inputSubFeeds: Seq[SubFeed], outputSubFeeds: Seq[SubFeed])(implicit context: ActionPipelineContext): Unit

    Executes operations needed after executing an action.

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

    Definition Classes
    SparkActionImpl → ActionSubFeedsImpl → Action
  58. def postExecFailed(implicit context: ActionPipelineContext): Unit

    Executes operations needed to cleanup after executing an action failed.

    Executes operations needed to cleanup after executing an action failed.

    Definition Classes
    SparkActionImpl → Action
  59. def postprocessOutputSubFeedCustomized(subFeed: SparkSubFeed)(implicit context: ActionPipelineContext): SparkSubFeed

    Implement additional processing logic for SubFeeds after transformation.

    Implement additional processing logic for SubFeeds after transformation. Can be implemented by subclass.

    Definition Classes
    SparkActionImpl → ActionSubFeedsImpl
  60. def postprocessOutputSubFeeds(subFeeds: Seq[SparkSubFeed])(implicit context: ActionPipelineContext): Seq[SparkSubFeed]
    Definition Classes
    ActionSubFeedsImpl
  61. def preExec(subFeeds: Seq[SubFeed])(implicit context: ActionPipelineContext): Unit

    Executes operations needed before executing an action.

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

    Definition Classes
    SparkActionImpl → Action
  62. def preInit(subFeeds: Seq[SubFeed], dataObjectsState: Seq[DataObjectState])(implicit context: ActionPipelineContext): Unit

    Checks before initalization of Action In this step execution condition is evaluated and Action init is skipped if result is false.

    Checks before initalization of Action In this step execution condition is evaluated and Action init is skipped if result is false.

    Definition Classes
    Action
    Annotations
    @Scaladoc()
  63. def prepare(implicit context: ActionPipelineContext): Unit

    Prepare DataObjects prerequisites.

    Prepare DataObjects prerequisites. In this step preconditions are prepared & tested: - connections can be created - needed structures exist, e.g Kafka topic or Jdbc table

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

    Definition Classes
    ActionSubFeedsImpl → Action
  64. def prepareInputSubFeed(input: DataObject with CanCreateDataFrame, subFeed: SparkSubFeed, ignoreFilters: Boolean = false)(implicit context: ActionPipelineContext): SparkSubFeed

    Applies changes to a SubFeed from a previous action in order to be used as input for this actions transformation.

    Applies changes to a SubFeed from a previous action in order to be used as input for this actions transformation.

    Definition Classes
    SparkActionImpl
    Annotations
    @Scaladoc()
  65. def prepareInputSubFeeds(subFeeds: Seq[SubFeed])(implicit context: ActionPipelineContext): (Seq[SparkSubFeed], Seq[SparkSubFeed])
    Definition Classes
    ActionSubFeedsImpl
  66. def preprocessInputSubFeedCustomized(subFeed: SparkSubFeed, ignoreFilters: Boolean, isRecursive: Boolean)(implicit context: ActionPipelineContext): SparkSubFeed

    Implement additional preprocess logic for SubFeeds before transformation Can be implemented by subclass.

    Implement additional preprocess logic for SubFeeds before transformation Can be implemented by subclass.

    isRecursive

    If subfeed is recursive (input & output)

    Attributes
    protected
    Definition Classes
    SparkActionImpl → ActionSubFeedsImpl
  67. lazy val prioritizedMainInputCandidates: Seq[DataObject]
    Attributes
    protected
    Definition Classes
    ActionSubFeedsImpl
  68. val recursiveInputIds: Seq[DataObjectId]
  69. val recursiveInputs: Seq[DataObject with CanCreateDataFrame]

    Recursive Inputs are DataObjects that are used as Output and Input in the same action.

    Recursive Inputs are DataObjects that are used as Output and Input in the same action. This is usually prohibited as it creates loops in the DAG. In special cases this makes sense, i.e. when building a complex comparision/update logic.

    Usage: add DataObjects used as Output and Input as outputIds and recursiveInputIds, but not as inputIds.

    Definition Classes
    CustomSparkAction → SparkActionImpl → Action
  70. def saveModeOptions: Option[SaveModeOptions]

    Override and parametrize saveMode in output DataObject configurations when writing to DataObjects.

    Override and parametrize saveMode in output DataObject configurations when writing to DataObjects.

    Definition Classes
    SparkActionImpl
    Annotations
    @Scaladoc()
  71. def setSparkJobMetadata(operation: Option[String] = None)(implicit context: ActionPipelineContext): Unit

    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

    phase description (be short...)

    Definition Classes
    Action
    Annotations
    @Scaladoc()
  72. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  73. final def toString(executionId: Option[ExecutionId]): String
    Definition Classes
    Action
  74. final def toString(): String

    This is displayed in ascii graph visualization

    This is displayed in ascii graph visualization

    Definition Classes
    Action → AnyRef → Any
    Annotations
    @Scaladoc()
  75. def toStringMedium: String
    Definition Classes
    Action
  76. def toStringShort: String
    Definition Classes
    Action
  77. def transform(inputSubFeeds: Seq[SparkSubFeed], outputSubFeeds: Seq[SparkSubFeed])(implicit context: ActionPipelineContext): Seq[SparkSubFeed]

    Transform subfeed content To be implemented by subclass.

    Transform subfeed content To be implemented by subclass.

    Definition Classes
    CustomSparkAction → ActionSubFeedsImpl
  78. def transformPartitionValues(partitionValues: Seq[PartitionValues])(implicit context: ActionPipelineContext): Map[PartitionValues, PartitionValues]

    Transform partition values.

    Transform partition values. Can be implemented by subclass.

    Definition Classes
    CustomSparkAction → ActionSubFeedsImpl
  79. val transformer: Option[CustomDfsTransformerConfig]
  80. val transformers: Seq[ParsableDfsTransformer]
  81. def validateAndUpdateSubFeedCustomized(output: DataObject, subFeed: SparkSubFeed)(implicit context: ActionPipelineContext): SparkSubFeed

    The transformed DataFrame is validated to have the output's partition columns included, partition columns are moved to the end and SubFeeds partition values updated.

    The transformed DataFrame is validated to have the output's partition columns included, partition columns are moved to the end and SubFeeds partition values updated.

    output

    output DataObject

    subFeed

    SubFeed with transformed DataFrame

    returns

    validated and updated SubFeed

    Definition Classes
    SparkActionImpl
    Annotations
    @Scaladoc()
  82. def validateConfig(): Unit

    put configuration validation checks here

    put configuration validation checks here

    Definition Classes
    ActionSubFeedsImpl → Action
    Annotations
    @Scaladoc()
  83. def validateDataFrameContainsCols(df: DataFrame, columns: Seq[String], debugName: String): Unit

    Validate that DataFrame contains a given list of columns, throwing an exception otherwise.

    Validate that DataFrame contains a given list of columns, throwing an exception otherwise.

    df

    DataFrame to validate

    columns

    Columns that must exist in DataFrame

    debugName

    name to mention in exception

    Definition Classes
    SparkActionImpl
    Annotations
    @Scaladoc()
  84. def validatePartitionValuesExisting(dataObject: DataObject with CanHandlePartitions, subFeed: SubFeed)(implicit context: ActionPipelineContext): Unit
    Attributes
    protected
    Definition Classes
    ActionSubFeedsImpl
  85. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  86. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  87. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  88. def writeOutputSubFeeds(subFeeds: Seq[SparkSubFeed])(implicit context: ActionPipelineContext): Unit
    Definition Classes
    ActionSubFeedsImpl
  89. def writeSubFeed(subFeed: SparkSubFeed, output: DataObject with CanWriteDataFrame, isRecursiveInput: Boolean = false)(implicit context: ActionPipelineContext): Option[Boolean]

    writes subfeed to output respecting given execution mode

    writes subfeed to output respecting given execution mode

    returns

    true if no data was transferred, otherwise false. None if unknown.

    Definition Classes
    SparkActionImpl
    Annotations
    @Scaladoc()
  90. def writeSubFeed(subFeed: SparkSubFeed, isRecursive: Boolean)(implicit context: ActionPipelineContext): WriteSubFeedResult

    Write subfeed data to output.

    Write subfeed data to output. To be implemented by subclass.

    isRecursive

    If subfeed is recursive (input & output)

    returns

    false if there was no data to process, otherwise true.

    Attributes
    protected
    Definition Classes
    SparkActionImpl → ActionSubFeedsImpl

Deprecated Value Members

  1. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] ) @Deprecated
    Deprecated

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from SparkActionImpl

Inherited from ActionSubFeedsImpl[SparkSubFeed]

Inherited from Action

Inherited from AtlasExportable

Inherited from SmartDataLakeLogger

Inherited from DAGNode

Inherited from ParsableFromConfig[Action]

Inherited from SdlConfigObject

Inherited from AnyRef

Inherited from Any

Ungrouped