io.smartdatalake.workflow.action.sparktransformer
SQLDfsTransformer
Related Docs:
object SQLDfsTransformer
| package sparktransformer
io.smartdatalake.workflow.action.sparktransformer
name of the transformer
Optional description of the transformer
SQL code for transformation. Use tokens %{<key>} to replace with runtimeOptions in SQL code. Example: "select * from test where run = %{runId}" A special token %{inputViewName} can be used to insert the temporary view name.
Options to pass to the 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.
SQL code for transformation.
SQL code for transformation. Use tokens %{<key>} to replace with runtimeOptions in SQL code. Example: "select * from test where run = %{runId}" A special token %{inputViewName} can be used to insert the temporary view name.
Optional description of the transformer
Optional description of the transformer
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.
the factory (object) for this class.
name of the transformer
name of the transformer
Options to pass to the transformation
Options to pass to the transformation
Optional function to implement validations in prepare phase.
Optional function to implement validations in prepare phase.
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.
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)
id of the action which executes this transformation. This is mainly used to prefix error messages.
partition values to transform
Map of (dataObjectId, DataFrame) tuples available as input
Map of transformed (dataObjectId, DataFrame) tuples
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.
id of the action which executes this transformation. This is mainly used to prefix error messages.
partition values to transform
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.
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 specified in the configuration for this transformation, including evaluated runtimeOptions
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 specified in the configuration for this transformation, including evaluated runtimeOptions
Configuration of a custom Spark-DataFrame transformation between many inputs and many outputs (n:m) as SQL code. The input data is available as temporary views in SQL. As name for the temporary views the input DataObjectId is used (special characters are replaces by underscores).
name of the transformer
Optional description of the transformer
SQL code for transformation. Use tokens %{<key>} to replace with runtimeOptions in SQL code. Example: "select * from test where run = %{runId}" A special token %{inputViewName} can be used to insert the temporary view name.
Options to pass to the 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.