com.alpine.plugin.core.spark.templates
Override this method to define an output schema in some way other than by defining an array of the fixed column definitions.
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
Since Alpine 6.
Since Alpine 6.3, SDK 1.9.
This is called to get the current status of the operator, i.e. whether it is valid, information about the expected runtime output, and error messages to display in the properties window.
This is intended to replace onInputOrParameterChange, as we want to be able to pass more general metadata between operators instead of only TabularSchema.
The default implementation calls onInputOrParameterChange, to maintain compatibility with old operators.
contains information about the input operators, the current parameters, and the available data-sources.
the current status of the operator.
Calls 'updateOutputSchema' when the parameters are changed
Calls 'updateOutputSchema' when the parameters are changed
If the connected inputs contain tabular schemas, this is where they can be accessed, each with unique Ids.
The current parameter values of the operator.
This should be used to change the input/output schema, etc.
A status object about whether the inputs and/or parameters are valid. The default implementation assumes that the connected inputs and/or parameters are valid.
This is kept only for old operators.
This is kept only for old operators. New ones should implement OperatorRuntime#createVisualResults, which has more things available. If neither are implemented, Alpine will generate default a visualization.
This is invoked for GUI to customize the operator output visualization after the operator finishes running. Each output should have associated default visualization, but the developer can customize it here.
The parameter values to the operator.
This is the output from running the operator.
For creating visual models.
The visual model to be sent to the GUI for visualization.
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.
The operator dialog where the operator could add input text boxes, etc. to define UI for parameter inputs.
This contains that available data-sources (filtered for hadoop or database depending on the operator runtime class) that could be used by the operator at runtime.
This can be used to provide information about the nature of the output/input schemas. E.g., provide the output schema.
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.