You can share HBase and MR if you run MR jobs only to process data off HBase 
and do not use HBase for real-time queries
It is not generally advisable to share live (real-time) HBase cluster and run 
MR jobs at the same time as since HDFS can get easily saturated
by MR jobs and you will have much worse HBase query latency and overall query 
throughput.

Best regards,
Vladimir Rodionov
Principal Platform Engineer
Carrier IQ, www.carrieriq.com
e-mail: [email protected]

________________________________________
From: [email protected] [[email protected]] On Behalf Of Stack 
[[email protected]]
Sent: Tuesday, June 05, 2012 9:07 PM
To: [email protected]
Cc: [email protected]
Subject: Re: Shared HDFS for HBase and MapReduce

On Tue, Jun 5, 2012 at 8:29 PM, Atif Khan <[email protected]> wrote:
> My first thoughts were to create a single HDFS cluster, and then point the
> MapReduce and HBase servers to use the common HDFS installation.  However,
> Cloudera's Dos and Don'ts page
> (http://www.cloudera.com/blog/2011/04/hbase-dos-and-donts/) insists that
> MapReduce and HBase should not share an HDFS cluster.  Rather they should
> have their own individual clusters.  I don't understand this recommendation,
> as it would result in moving data around from one HDFS cluster to another
> when running MapReduce over HBase.
>

It starts out "Be careful when running mixed workloads on an HBase
cluster."  Does your use case fit the case described: "...SLAs on
hbase access" and at the same time running heavy mapreduce jobs on
same cluster?  If so, you may want to do the suggested two clusters.

I'd suggest you start w/ all on the one cluster and see how you do.
That post is > a year old.  HBase has gotten steadily better since.

St.Ack

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