Register you dataframes as temp tables and then try the join on the temp table.
This should resolve your issue.


On Mon, Aug 8, 2016 at 11:47 PM, Ashic Mahtab <> wrote:
We have two parquet inputs of the following form:

a: id:String, Name:String  (1.5TB)
b: id:String, Number:Int  (1.3GB)

We need to join these two to get (id, Number, Name). We've tried two approaches:

a.join(b, Seq("id"), "right_outer")

where a and b are dataframes. We also tried taking the rdds, mapping them to pair rdds with id as the key, and then joining. What we're seeing is that temp file usage is increasing on the join stage, and filling up our disks, causing the job to crash. Is there a way to join these two data sets without well...crashing?

Note, the ids are unique, and there's a one to one mapping between the two datasets. 

Any help would be appreciated.