did you try this -
DataFrame joinedDf_intersect =
leftDf.select("x", "y", "z")
.join(rightDf,leftDf.col("x").equalTo(rightDf.col("x"))
.and(leftDf.col("y").equalTo(rightDf.col("y"))), "left_outer") ;
Hope that helps.
On Mon, Feb 22, 2016 at 12:22 PM, praneshvyas [via Apache Spark User List] <
ml-node+s1001560n26293...@n3.nabble.com> wrote:
> Hi Spark Users,
>
> I am using spark 1.5+.
>
> I am trying to do left/right outer join on multiple columns. But looks
> like there is no way to do that.
>
> I can do a inner join on multiple columns, but not left/right outer join.
>
> THIS WORKS:
> val joinedDf_intersect = leftDf.join(rightDf, Seq("device_id",
> "normalized_subscriber_id"))
>
> THIS DOESN'T WORK
> val joinedDf = leftDf.join(rightDf, Seq("device_id",
> "normalized_subscriber_id"), left_outer)
>
>
> Please let me know if there is a way to do.
>
> Thanks in advance
>
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--
*Regards , Shobhit Gupta.*
*"If you salute your job, you have to salute nobody. But if you pollute
your job, you have to salute everybody..!!"*
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