what would good spill settings be?
On Fri, Dec 12, 2014 at 2:45 PM, Sameer Farooqui
wrote:
>
> You could try re-partitioning or coalescing the RDD to partition and then
> write it to disk. Make sure you have good spill settings enabled so that
> the RDD can spill to the local temp dirs if it has
You could try re-partitioning or coalescing the RDD to partition and then
write it to disk. Make sure you have good spill settings enabled so that
the RDD can spill to the local temp dirs if it has to.
On Fri, Dec 12, 2014 at 2:39 PM, Steve Lewis wrote:
>
> The objective is to let the Spark appli
The objective is to let the Spark application generate a file in a format
which can be consumed by other programs - as I said I am willing to give up
parallelism at this stage (all the expensive steps were earlier but do want
an efficient way to pass once through an RDD without the requirement to
h
Instead of doing this on the compute side, I would just write out the file
with different blocks initially into HDFS and then use "hadoop fs
-getmerge" or HDFSConcat to get one final output file.
- SF
On Fri, Dec 12, 2014 at 11:19 AM, Steve Lewis wrote:
>
>
> I have an RDD which is potentially
I have an RDD which is potentially too large to store in memory with
collect. I want a single task to write the contents as a file to hdfs. Time
is not a large issue but memory is.
I say the following converting my RDD (scans) to a local Iterator. This
works but hasNext shows up as a separate task
