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HBase >> mail # user >> Re: Adding a new region server or splitting an old region in a Hash-partitioned HBase Data Store


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Shahab Yunus 2013-06-27, 13:24
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Re: Adding a new region server or splitting an old region in a Hash-partitioned HBase Data Store
I don't have a particular document or source stating this but I think it is
actually kind of self-explanatory if your think about the algorithm.

Anyway, you can read this
http://blog.sematext.com/2012/04/09/hbasewd-avoid-regionserver-hotspotting-despite-writing-records-with-sequential-keys/

And some older discussions by experts on this topic:
http://search-hadoop.com/?q=prefix+salt+key+hotspot&fc_project=HBase

Regards,
Shahab
On Thu, Jun 27, 2013 at 9:44 AM, Joarder KAMAL <[EMAIL PROTECTED]> wrote:

> Thanks Shahab for the reply. I was also thinking in the same way.
> Could you able to guide me through any reference which can confirm this
> understanding?
>
>
> Regards,
> Joarder Kamal
>
>
>
> On 27 June 2013 23:24, Shahab Yunus <[EMAIL PROTECTED]> wrote:
>
> > I think you will need to update your hash function and redistribute data.
> > As far as I know this has been on of the drawbacks of this approach (and
> > the SemaText library)
> >
> > Regards,
> > Shahab
> >
> >
> > On Wed, Jun 26, 2013 at 7:24 PM, Joarder KAMAL <[EMAIL PROTECTED]>
> wrote:
> >
> > > May be a simple question to answer for the experienced HBase users and
> > > developers:
> > >
> > > If I use hash partitioning to evenly distribute write workloads into my
> > > region servers and later add a new region server to scale or split an
> > > existing region, then do I need to change my hash function and
> re-shuffle
> > > all the existing data in between all the region servers (old and new)?
> > Or,
> > > is there any better solution for this? Any guidance would be very much
> > > helpful.
> > >
> > > Thanks in advance.
> > >
> > >
> > > Regards,
> > > Joarder Kamal
> > >
> >
>
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ramkrishna vasudevan 2013-06-28, 03:39
NEW: Monitor These Apps!
elasticsearch, apache solr, apache hbase, hadoop, redis, casssandra, amazon cloudwatch, mysql, memcached, apache kafka, apache zookeeper, apache storm, ubuntu, centOS, red hat, debian, puppet labs, java, senseiDB