Hi Josh,

Thanks for the information. For the moment, I was able to control the 
partitions by switching to JdbcRDD, such that I create 6000 partitions based on 
a numeric column. I think that such approach is slower, but at least scales 
well.

Raising the number of HBase regions that much would be counterproductive, as it 
affects HBase performance... It would be nice if you can provide an alternative 
to the PhoenixInputFormat that creates more splits... In any case, thanks for 
the help.

Diego

From: Josh Mahonin [mailto:jmaho...@gmail.com]
Sent: 18 April 2016 20:25
To: user@phoenix.apache.org
Subject: Re: Phoenix-Spark: Number of partitions in PhoenixRDD

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<mailto: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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