Hi Diego,

The phoenix-spark RDD partition count is equal to the number of splits that
the query planner returns. Adjusting the HBase region splits, table salting
[1], as well as the guidepost width [2] should help with the
parallelization here.

Using 'EXPLAIN' for the generated query in sqlline might be helpful for
debugging here as well.

It would be great if you could update this thread with any lessons learned
as well.

Good luck,

Josh

[1] https://phoenix.apache.org/salted.html
[2] https://phoenix.apache.org/update_statistics.html

On Mon, Apr 18, 2016 at 4:37 AM, Fustes, Diego <diego.fus...@ndt-global.com>
wrote:

> Hi all,
>
>
>
> I'm working with the Phoenix spark plugin to process a HUGE table. The
> table is salted in 100 buckets and is split in 400 regions. When I read it
> with phoenixTableAsRDD, I get a RDD with 150 parititions. These partitions
> are too big, such
>
> that I am getting OutOfMemory problems. Therefore, I would like to get
> smaller partitions. To do this, I could just call repartition, but it would
> shuffle the whole dataset... So, my question is, is there a way to modify
> PhoenixInputFormat
>
> to get more partitions in the resulting RDD?
>
>
>
> Thanks and regards,
>
>
>
> Diego
>
>
>
>
>
>
>
>
>
>
>
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