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https://issues.apache.org/jira/browse/SPARK-53779?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Wenchen Fan reassigned SPARK-53779:
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Assignee: Yicong Huang
> Implement transform in column API
> ---------------------------------
>
> Key: SPARK-53779
> URL: https://issues.apache.org/jira/browse/SPARK-53779
> Project: Spark
> Issue Type: New Feature
> Components: Spark Core
> Affects Versions: 4.1.0
> Reporter: Yicong Huang
> Assignee: Yicong Huang
> Priority: Major
> Labels: pull-request-available
>
> Proposal to introduce a transform API for Column in Spark, inspired by
> Scala’s pipe operator and SQL pipeline syntax. This would allow chaining
> transformations in a pipeline style, improving readability compared to nested
> function calls.
>
> *Motivation*
> * Scala’s pipe API and SQL pipeline syntax provide a cleaner,
> pipeline-oriented style.
> * Current nested function invocations (e.g., f2(f1(col))) are less readable
> than a chained style (col.transform(f1).transform(f2)).
> * AI code generators also tend to produce pipeline style code more cleanly.
> * This aligns with the existing DataFrame API pipeline style
> (df.transform(f) → DataFrame).
>
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