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.

This message was sent by Atlassian JIRA

To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org

Reply via email to