Override this method to define an output schema instead of using automatic inference.
Override this method to define an output schema instead of using automatic inference.
Override this method to define the output schema by assigning fixed column definitions.
Override this method to define the output schema by assigning fixed column definitions. If you want to have a variable number of output columns, simply override the defineEntireOutputSchema method The default implementation of this method returns the same columns as the input data.
- the Alpine 'TabularSchema' for the input DataFrame
The parameters of the operator, including values set by the user.
A list of Column definitions used to create the output schema
Calls 'updateOutputSchema' when the parameters are changed
Calls 'updateOutputSchema' when the parameters are changed
Defines the params the user will be able to select.
Defines the params the user will be able to select. The default asks for desired output format & output location.
Control the GUI of your Spark job, through this you can specify any visualization for the output of your job, and what params the user will need to specify. Uses the provided operator to generate an updated schema, this should work for most operators but if not (e.g. your operator doesn't handle empty data or output schema depends on input data) then you will have to perform your own schema update.