im  using CDH 4.5:
Hadoop:  2.0.0-cdh4.5.0
HBase:   0.94.6-cdh4.5.0

Regards


On Sun, Jan 5, 2014 at 1:24 AM, Ted Yu <yuzhih...@gmail.com> wrote:

> What version of HBase / hdfs are you running with ?
>
> Cheers
>
>
>
> On Sat, Jan 4, 2014 at 12:17 PM, Akhtar Muhammad Din
> <akhtar.m...@gmail.com>wrote:
>
> > Hi,
> > I have been running a map reduce job that joins 2 datasets of 1.3 and 4
> GB
> > in size. Joining is done at reduce side. Output is written to either
> Hbase
> > or HDFS depending upon configuration. The problem I am having is that
> Hbase
> > takes about 60-80 minutes to write the processed data, on the other hand
> > HDFS takes only 3-5 mins to write the same data. I really want to improve
> > the Hbase speed and bring it down to 1-2 min.
> >
> > I am using amazon EC2 instances, launched a cluster of size 3 and later
> 10,
> > have tried both c3.4xlarge and c3.8xlarge instances.
> >
> > I can see significant increase in performance while writing to HDFS as i
> > use cluster with more nodes, having high specifications, but in the case
> of
> > Hbase there was no significant change in performance.
> >
> > I have been going through different posts, articles and have read Hbase
> > book to solve the Hbase performance issue but have not been able to
> succeed
> > so far.
> > Here are the few things i have tried out so far:
> >
> > *Client Side*
> > - Turned off writing to WAL
> > - Experimented with write buffer size
> > - Turned off auto flush on table
> > - Used cache, experimented with different sizes
> >
> >
> > *Hbase Server Side*
> > - Increased region servers heap size to 8 GB
> > - Experimented with handlers count
> > - Increased Memstore flush size to 512 MB
> > - Experimented with hbase.hregion.max.filesize, tried different sizes
> >
> > There are many other parameters i have tried out following the
> suggestions
> > from  different sources, but nothing worked so far.
> >
> > Your help will be really appreciated.
> >
> > --
> > Regards
> > Akhtar Muhammad Din
> >
>



-- 
Regards
Akhtar Muhammad Din

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