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https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17079337#comment-17079337
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Everett Rush commented on SPARK-27249:
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Hi Nick,
I think the solution could make use of the mapPartitions method, but still
there should be a multicolumn transformer class. The unary transformer is very
limiting.
> 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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