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https://issues.apache.org/jira/browse/SPARK-30983?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17054692#comment-17054692
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L. C. Hsieh commented on SPARK-30983:
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For option 2, adding more overloading typed select APIs, one issue is that it
can be a breaking change to existing user code that calls untyped select API.
> Support more than 5 typed column in typed Dataset.select API
> ------------------------------------------------------------
>
> Key: SPARK-30983
> URL: https://issues.apache.org/jira/browse/SPARK-30983
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 3.0.0
> Reporter: L. C. Hsieh
> Priority: Major
>
> Because Dataset only provides overloading typed select API to at most 5 typed
> columns, once more than 5 typed columns given, the select API call will go
> for untyped one.
> Currently users cannot call typed select with more than 5 typed columns.
> There are few options:
> 1. Expose Dataset.selectUntyped (could rename it) to accept any number (due
> to the limit of ExpressionEncoder.tuple, at most 22 actually) of typed
> columns. Pros: not need to add too much code in Dataset. Cons: The returned
> type is generally Dataset[_], not a specified one like Dataset[(U1, U2)] for
> the overloading method.
> 2. Add more overloading typed select APIs up to 22 typed column inputs. Pros:
> Clear returned type. Cons: A lot of code to be added to Dataset for just
> corner cases.
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