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From seth <s...@untethered.org>
Subject Re: HDFS using SAN
Date Thu, 18 Oct 2012 15:15:43 GMT
I wonder if large NAS equipment manufacturers have ever considered modifying their firmware
to directly talk the DFS protocol that hadoop uses.  This way your compute nodes could be
'pure' compute nodes with only tasktracker processes.

Might be a way to extend their market a bit.  Not sure it would actually perform well until
it was tried.

On Oct 18, 2012, at 10:08 AM, "Pamecha, Abhishek" <apamecha@x.com> wrote:

> Yes, I had similar views from  the netapp paper.  My usecase is io heavy and that's why
( atleast IMO), when data set grows, a shared SAN begins to make less sense as opposed to
DAS for MR type of jobs. 
> 
> As Lucas pointed out, sharing the same data with other apps is a great adv. w SAN. 
> 
> Thanks
> Abhishek
> 
> 
> i Sent from my iPad with iMstakes 
> 
> On Oct 18, 2012, at 6:59, "Michael Segel" <michael_segel@hotmail.com> wrote:
> 
> I haven't played with a NetApp box, but the way it has been explained to me is that your
SAN appears as if its direct attached storage. 
> Its possible, based on drives and other hardware, plus it looks like they are focusing
on read times only. 
> 
> I'd contact a NetApp rep for a better answer. 
> 
> Actually if you are looking at a higher density in terms of storage, going with a storage
/ compute cluster  makes sense. 
> 
> On Oct 18, 2012, at 8:48 AM, Jitendra Kumar Singh <jksingh26jun@gmail.com> wrote:
> 
>> Hi,
>> 
>> In the NetApp whitepaper on SAN solution (link given by Kevin) it makes following
statement. Can someone please elaborate (or give a link that explains) how 12-disk in SAN
can give 2000 IOPS while if used as JBOD would give 600 IOPS? 
>> 
>> "The E2660 can deliver up to 2,000 IOPS 
>> from a 12-disk stripe (the bottleneck being the 12 disks). This headroom translates
into better read times 
>> for those 64KB blocks. Twelve copies of 12 MapReduce jobs reading from 12 SATA disks
can at best 
>> never exceed 12 x 50 IOPS, or 600 IOPS. The E2660 volume has five times the IOPS
headroom, which 
>> translates into faster read times and high MapReduce throughput " 
>> 
>> Thanks and Regards,
>> --
>> Jitendra Kumar Singh
>> 
>> 
>> 
>> On Thu, Oct 18, 2012 at 6:02 PM, Luca Pireddu <pireddu@crs4.it> wrote:
>> On 10/18/2012 02:21 AM, Pamecha, Abhishek wrote:
>> Tom
>> 
>> Do you mean you are using GPFS instead of HDFS? Also, if you can share,
>> are you deploying it as DAS set up or a SAN?
>> 
>> Thanks,
>> 
>> Abhishek
>> 
>> 
>> 
>> Though I don't think I'd buy a SAN for a new Hadoop cluster, we have a SAN and are
using it *instead of HDFS* with a small/medium Hadoop MapReduce cluster (up to 100 nodes or
so, depending on our need).  We still use the local node disks for intermediate data (mapred
local storage).  Although this set-up does limit our possibility to scale to a large number
of nodes, that's not a concern for us.  On the plus, we gain the flexibility to be able to
share our cluster with non-Hadoop users at our centre.
>> 
>> 
>> -- 
>> Luca Pireddu
>> CRS4 - Distributed Computing Group
>> Loc. Pixina Manna Edificio 1
>> 09010 Pula (CA), Italy
>> Tel: +39 0709250452
>> 
> 


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