[jira] [Resolved] (SPARK-27582) Add Dataset DSL for left_anti and left_semi joins

["Hyukjin Kwon (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-27582?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-27582.
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    Resolution: Won't Fix

I don't think we should add a set of aliases. The way of them looks already super easy.

> Add Dataset DSL for left_anti and left_semi joins
> -------------------------------------------------
>
>                 Key: SPARK-27582
>                 URL: https://issues.apache.org/jira/browse/SPARK-27582
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 2.4.2
>            Reporter: Stanislav Bytsko
>            Priority: Major
>
> Currently we have
> {code:java}
> org.apache.spark.sql.Dataset[T]#joinWith[U](other: Dataset[U], condition: Column, joinType: String): Dataset[(T, U)]
> {code}
> which explicitly excludes left_anti and left_semi joins, which is understandable, because result would have different signature.
> I think it's easily fixed drawback, which accepts 2 solutions I can think of:
> - Extend current joinWith to return null for second (_2) item in the tuple. Not ideal as no-one likes nulls, but workable, as client should be able to handle that by doing {code}.map(_._1){code} immediately afterwards
> - Add 2 new methods {code}org.apache.spark.sql.Dataset[T]#joinSemiWith[U](other: Dataset[U], condition: Column): Dataset[T]{code} and {code}org.apache.spark.sql.Dataset[T]#joinAntiWith[U](other: Dataset[U], condition: Column): Dataset[T]{code} which is much nicer, but adds 2 methods to the API. Method names could be semiJoinWith and antiJoinWith, which is more logical, but not sorted properly in the list of org.apache.spark.sql.Dataset methods



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