yes i am trying to do so. but it will try to repartition whole data.. can't
we split a large partition(data skewed partition) into multiple partitions
(any idea on this.).
On Sun, Oct 18, 2015 at 1:55 AM, Adrian Tanase wrote:
> If the dataset allows it you can try to write a custom partitioner t
If the dataset allows it you can try to write a custom partitioner to help
spark distribute the data more uniformly.
Sent from my iPhone
On 17 Oct 2015, at 16:14, shahid ashraf
mailto:sha...@trialx.com>> wrote:
yes i know about that,its in case to reduce partitions. the point here is the
data
yes i know about that,its in case to reduce partitions. the point here is
the data is skewed to few partitions..
On Sat, Oct 17, 2015 at 6:27 PM, Raghavendra Pandey <
raghavendra.pan...@gmail.com> wrote:
> You can use coalesce function, if you want to reduce the number of
> partitions. This one
You can use coalesce function, if you want to reduce the number of
partitions. This one minimizes the data shuffle.
-Raghav
On Sat, Oct 17, 2015 at 1:02 PM, shahid qadri
wrote:
> Hi folks
>
> I need to reparation large set of data around(300G) as i see some portions
> have large data(data skew)
