OptionsDfTransformer

Abstract Value Members

abstract def description: Option[String]

Definition Classes
DfTransformer
abstract def factory: FromConfigFactory[ParsableDfTransformer]

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
abstract def name: String

Definition Classes
DfTransformer
abstract def options: Map[String, String]
abstract def runtimeOptions: Map[String, String]
abstract def transformWithOptions(actionId: ActionId, partitionValues: Seq[PartitionValues], df: DataFrame, dataObjectId: DataObjectId, options: Map[String, String])(implicit session: SparkSession): DataFrame

Function to be implemented to define the transformation between an input and output DataFrame (1:1)
Function to be implemented to define the transformation between an input and output DataFrame (1:1)
options
Options specified in the configuration for this transformation, including evaluated runtimeOptions

Concrete 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( ... )
final def eq(arg0: AnyRef): Boolean

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

Definition Classes
AnyRef → Any
def finalize(): Unit

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

Definition Classes
AnyRef → Any
def hashCode(): Int

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

Definition Classes
Any
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
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
DfTransformer
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
AnyRef → Any
def transform(actionId: ActionId, partitionValues: Seq[PartitionValues], df: DataFrame, dataObjectId: DataObjectId)(implicit session: SparkSession, context: ActionPipelineContext): DataFrame

Function to be implemented to define the transformation between an input and output DataFrame (1:1)
Function to be implemented to define the transformation between an input and output DataFrame (1:1)

Definition Classes
OptionsDfTransformer → DfTransformer
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
OptionsDfTransformer → 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.
options
Options specified in the configuration for this transformation, including evaluated runtimeOptions
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 Doc: package sparktransformer

trait OptionsDfTransformer extends ParsableDfTransformer

Abstract Value Members

abstract def description: Option[String]

abstract def factory: FromConfigFactory[ParsableDfTransformer]

abstract def name: String

abstract def options: Map[String, String]

abstract def runtimeOptions: Map[String, String]

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

Concrete Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

final def getClass(): Class[_]

def hashCode(): Int

final def isInstanceOf[T0]: Boolean

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

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

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

def toString(): String

def transform(actionId: ActionId, partitionValues: Seq[PartitionValues], df: DataFrame, dataObjectId: DataObjectId)(implicit session: SparkSession, context: ActionPipelineContext): 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]]

final def wait(): Unit

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

final def wait(arg0: Long): Unit

Inherited from ParsableDfTransformer

Inherited from ParsableFromConfig[ParsableDfTransformer]

Inherited from DfTransformer

Inherited from PartitionValueTransformer

Inherited from AnyRef

Inherited from Any

Ungrouped