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https://issues.apache.org/jira/browse/SPARK-10972?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15573364#comment-15573364
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holdenk commented on SPARK-10972:
---------------------------------

I don't think that actually solves the problem the user is looking for. You 
could do a full cross product and filter after but that's pretty expensive.

> UDFs in SQL joins
> -----------------
>
>                 Key: SPARK-10972
>                 URL: https://issues.apache.org/jira/browse/SPARK-10972
>             Project: Spark
>          Issue Type: New Feature
>          Components: SQL
>    Affects Versions: 1.5.1
>            Reporter: Michael Malak
>
> Currently expressions used to .join() in DataFrames are limited to column 
> names plus the operators exposed in org.apache.spark.sql.Column.
> It would be nice to be able to .join() based on a UDF, such as, say, 
> euclideanDistance(col1, col2) < 0.1.



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