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https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17132743#comment-17132743
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Everett Rush commented on SPARK-27249:
--------------------------------------
I checked out the code and the design. Thanks for the great effort, but this
doesn't quite meet the need. The transformer contract can still be met with a
transform function that returns a Dataframe.
I would like something more like this.
{{@DeveloperApi}}
{{abstract class MultiColumnTransformer[T<: MultiColumnTransformer[T]]}}
{{ extends Transformer with HasOutputCol with Logging {}}
{{ def setOutputCol(value: String): T = set(outputCol, value).asInstanceOf[T]}}
{{ /** Returns the data type of the output column. */}}
{{ protected def outputDataType: DataType}}
{{ protected def *transformFunc*: Iterator[Row] => Iterator[Row]}}
{{ override def *transformSchema*(schema: StructType): StructType = {}}
{{ }}}
{{ def *transform*(dataset: DataFrame, targetSchema: StructType): DataFrame =
{}}
{{ val targetEncoder = RowEncoder(targetSchema)}}
{{ dataset.mapPartitions(transformFunc)(targetEncoder)}}
{{ }}}
{{ override def *transform*(dataset: Dataset[_]): DataFrame = {}}
{{ val dataframe = dataset.toDF()}}
{{ val targetSchema = transformSchema(dataframe.schema, logging = true)}}
{{ transform(dataframe, targetSchema)}}
{{ }}}
{{ override def copy(extra: ParamMap): T = defaultCopy(extra)}}
{{}}}
> Developers API for Transformers beyond UnaryTransformer
> -------------------------------------------------------
>
> Key: SPARK-27249
> URL: https://issues.apache.org/jira/browse/SPARK-27249
> Project: Spark
> Issue Type: New Feature
> Components: ML
> Affects Versions: 3.1.0
> Reporter: Everett Rush
> Priority: Minor
> Labels: starter
> Attachments: Screen Shot 2020-01-17 at 4.20.57 PM.png
>
> Original Estimate: 96h
> Remaining Estimate: 96h
>
> It would be nice to have a developers' API for dataset transformations that
> need more than one column from a row (ie UnaryTransformer inputs one column
> and outputs one column) or that contain objects too expensive to initialize
> repeatedly in a UDF such as a database connection.
>
> Design:
> Abstract class PartitionTransformer extends Transformer and defines the
> partition transformation function as Iterator[Row] => Iterator[Row]
> NB: This parallels the UnaryTransformer createTransformFunc method
>
> When developers subclass this transformer, they can provide their own schema
> for the output Row in which case the PartitionTransformer creates a row
> encoder and executes the transformation. Alternatively the developer can set
> output Datatype and output col name. Then the PartitionTransformer class will
> create a new schema, a row encoder, and execute the transformation.
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