ScalaCodeDfsTransformer

Instance Constructors

new ScalaCodeDfsTransformer(name: String = "scalaTransform", description: Option[String] = None, code: Option[String] = None, file: Option[String] = None, options: Map[String, String] = Map(), runtimeOptions: Map[String, String] = Map())

name
name of the transformer
description
Optional description of the transformer
code
Scala code for transformation. The scala code needs to be a function of type fnTransformType.
file
File where scala code for transformation is loaded from. The scala code in the file needs to be a function of type fnTransformType.
options
Options to pass to the transformation
runtimeOptions
optional tuples of [key, spark sql expression] to be added as additional options when executing transformation. The spark sql expressions are evaluated against an instance of DefaultExpressionData.

Value Members

final def !=(arg0: Any): Boolean

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

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

Definition Classes
AnyRef → Any
final def asInstanceOf[T0]: T0

Definition Classes
Any
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
val code: Option[String]

Scala code for transformation.
Scala code for transformation. The scala code needs to be a function of type fnTransformType.
val description: Option[String]

Optional description of the transformer
Optional description of the transformer

Definition Classes
ScalaCodeDfsTransformer → DfsTransformer
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def factory: FromConfigFactory[ParsableDfsTransformer]

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
ScalaCodeDfsTransformer → ParsableFromConfig
val file: Option[String]

File where scala code for transformation is loaded from.
File where scala code for transformation is loaded from. The scala code in the file needs to be a function of type fnTransformType.
def finalize(): Unit

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

Definition Classes
AnyRef → Any
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
val name: String

name of the transformer
name of the transformer

Definition Classes
ScalaCodeDfsTransformer → DfsTransformer
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
val options: Map[String, String]

Options to pass to the transformation
Options to pass to the transformation

Definition Classes
ScalaCodeDfsTransformer → OptionsDfsTransformer
def prepare(actionId: ActionId)(implicit session: SparkSession, context: ActionPipelineContext): Unit

Optional function to implement validations in prepare phase.
Optional function to implement validations in prepare phase.

Definition Classes
DfsTransformer
val runtimeOptions: Map[String, String]

optional tuples of [key, spark sql expression] to be added as additional options when executing transformation.
optional tuples of [key, spark sql expression] to be added as additional options when executing transformation. The spark sql expressions are evaluated against an instance of DefaultExpressionData.

Definition Classes
ScalaCodeDfsTransformer → OptionsDfsTransformer
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def transform(actionId: ActionId, partitionValues: Seq[PartitionValues], dfs: Map[String, DataFrame])(implicit session: SparkSession, context: ActionPipelineContext): Map[String, DataFrame]

Function to be implemented to define the transformation between many inputs and many outputs (n:m)
Function to be implemented to define the transformation between many inputs and many outputs (n:m)
actionId
id of the action which executes this transformation. This is mainly used to prefix error messages.
partitionValues
partition values to transform
dfs
Map of (dataObjectId, DataFrame) tuples available as input
returns
Map of transformed (dataObjectId, DataFrame) tuples

Definition Classes
OptionsDfsTransformer → DfsTransformer
def transformPartitionValues(actionId: ActionId, partitionValues: Seq[PartitionValues])(implicit session: SparkSession, context: ActionPipelineContext): Option[Map[PartitionValues, PartitionValues]]

Optional function to define the transformation of input to output partition values.
Optional function to define the transformation of input to output partition values. For example this enables to implement aggregations where multiple input partitions are combined into one output partition. Note that the default value is input = output partition values, which should be correct for most use cases.
actionId
id of the action which executes this transformation. This is mainly used to prefix error messages.
partitionValues
partition values to transform
returns
Map of input to output partition values. This allows to map partition values forward and backward, which is needed in execution modes. Return None if mapping is 1:1.

Definition Classes
OptionsDfsTransformer → PartitionValueTransformer
def transformPartitionValuesWithOptions(actionId: ActionId, partitionValues: Seq[PartitionValues], options: Map[String, String])(implicit session: SparkSession): Option[Map[PartitionValues, PartitionValues]]

Optional function to define the transformation of input to output partition values.
Optional function to define the transformation of input to output partition values. For example this enables to implement aggregations where multiple input partitions are combined into one output partition. Note that the default value is input = output partition values, which should be correct for most use cases. see also DfsTransformer.transformPartitionValues()
options
Options specified in the configuration for this transformation, including evaluated runtimeOptions

Definition Classes
OptionsDfsTransformer
def transformWithOptions(actionId: ActionId, partitionValues: Seq[PartitionValues], dfs: Map[String, DataFrame], options: Map[String, String])(implicit session: SparkSession): Map[String, DataFrame]

Function to be implemented to define the transformation between many inputs and many outputs (n:m) see also DfsTransformer.transform()
Function to be implemented to define the transformation between many inputs and many outputs (n:m) see also DfsTransformer.transform()
options
Options specified in the configuration for this transformation, including evaluated runtimeOptions

Definition Classes
ScalaCodeDfsTransformer → OptionsDfsTransformer
final def wait(): Unit

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

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

Definition Classes
AnyRef
Annotations
@throws( ... )

Related Docs: object ScalaCodeDfsTransformer | package sparktransformer

Instance Constructors

new ScalaCodeDfsTransformer(name: String = "scalaTransform", description: Option[String] = None, code: Option[String] = None, file: Option[String] = None, options: Map[String, String] = Map(), runtimeOptions: Map[String, String] = Map())

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def clone(): AnyRef

val code: Option[String]

val description: Option[String]

final def eq(arg0: AnyRef): Boolean

def factory: FromConfigFactory[ParsableDfsTransformer]

val file: Option[String]

def finalize(): Unit

final def getClass(): Class[_]

final def isInstanceOf[T0]: Boolean

val name: String

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

val options: Map[String, String]

def prepare(actionId: ActionId)(implicit session: SparkSession, context: ActionPipelineContext): Unit

val runtimeOptions: Map[String, String]

final def synchronized[T0](arg0: ⇒ T0): T0

def transform(actionId: ActionId, partitionValues: Seq[PartitionValues], dfs: Map[String, DataFrame])(implicit session: SparkSession, context: ActionPipelineContext): Map[String, DataFrame]

def transformPartitionValues(actionId: ActionId, partitionValues: Seq[PartitionValues])(implicit session: SparkSession, context: ActionPipelineContext): Option[Map[PartitionValues, PartitionValues]]

def transformPartitionValuesWithOptions(actionId: ActionId, partitionValues: Seq[PartitionValues], options: Map[String, String])(implicit session: SparkSession): Option[Map[PartitionValues, PartitionValues]]

def transformWithOptions(actionId: ActionId, partitionValues: Seq[PartitionValues], dfs: Map[String, DataFrame], options: Map[String, String])(implicit session: SparkSession): Map[String, DataFrame]

final def wait(): Unit

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

final def wait(arg0: Long): Unit

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from OptionsDfsTransformer

Inherited from ParsableDfsTransformer

Inherited from ParsableFromConfig[ParsableDfsTransformer]

Inherited from DfsTransformer

Inherited from PartitionValueTransformer

Inherited from AnyRef

Inherited from Any

Ungrouped