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https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17086029#comment-17086029
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Nick Afshartous commented on SPARK-27249:
-----------------------------------------
[~enrush] Hi Everett,
Using the {{Iterator}} approach would seem to deviate from the existing
{{Transformer}} contract. More specifically, the {{transform}} function should
output a new {{DataFrame}} object. What I would propose is adding a new
function {{Transformer.compose}} to allow the composition of {{Transformers}}.
{code}
def compose(other: Transformer): Transformer = {
new Transformer {
override def transform(dataset: Dataset[_]): DataFrame = {
other.transform(this.transform(dataset));
}
...
{code}
Then one could {{compose}} {{Transformers}} which effectively would enable
multi-column transformations.
{code}
val dataFrame = ...
val transformers = List(transformer1, transformer2, transformer3)
val multiColumnTransformer = transformers.reduce((x, y) => x.compose(y))
multiColumnTransformer.transform(dataFrame)
{code}
I'd be happy to submit a PR if this meets your requirments.
> 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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