Hi,

You may be hitting this bug: 
SPARK-9879<https://issues.apache.org/jira/browse/SPARK-9879>

In other words: did you try without the LIMIT clause?

Regards,
Christophe.

On 02/05/16 20:02, Gourav Sengupta wrote:
Hi,

I have worked on 300GB data by querying it  from CSV (using SPARK CSV)  and 
writing it to Parquet format and then querying parquet format to query it and 
partition the data and write out individual csv files without any issues on a 
single node SPARK cluster installation.

Are you trying to cache in the entire data? What is that you are trying to 
achieve in your used case?

Regards,
Gourav

On Mon, May 2, 2016 at 5:59 PM, Ted Yu 
<yuzhih...@gmail.com<mailto:yuzhih...@gmail.com>> wrote:
That's my interpretation.

On Mon, May 2, 2016 at 9:45 AM, Buntu Dev 
<<mailto:buntu...@gmail.com>buntu...@gmail.com<mailto:buntu...@gmail.com>> 
wrote:
Thanks Ted, I thought the avg. block size was already low and less than the 
usual 128mb. If I need to reduce it further via parquet.block.size, it would 
mean an increase in the number of blocks and that should increase the number of 
tasks/executors. Is that the correct way to interpret this?

On Mon, May 2, 2016 at 6:21 AM, Ted Yu 
<<mailto:yuzhih...@gmail.com>yuzhih...@gmail.com<mailto:yuzhih...@gmail.com>> 
wrote:
Please consider decreasing block size.

Thanks

> On May 1, 2016, at 9:19 PM, Buntu Dev 
> <<mailto:buntu...@gmail.com>buntu...@gmail.com<mailto:buntu...@gmail.com>> 
> wrote:
>
> I got a 10g limitation on the executors and operating on parquet dataset with 
> block size 70M with 200 blocks. I keep hitting the memory limits when doing a 
> 'select * from t1 order by c1 limit 1000000' (ie, 1M). It works if I limit to 
> say 100k. What are the options to save a large dataset without running into 
> memory issues?
>
> Thanks!





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