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From Sudhir Vallamkondu <Sudhir.Vallamko...@icrossing.com>
Subject Re: Hadoop/Elastic MR on AWS
Date Mon, 27 Dec 2010 18:17:38 GMT
We recently crossed this bridge and here are some insights. We did an
extensive study comparing costs and benchmarking local vs EMR for our
current needs and future trend.

- Scalability you get with EMR is unmatched although you need to look at
your requirement and decide this is something you need.

- When using EMR its cheaper to use reserved instances vs nodes on the fly.
You can always add more nodes when required. I suggest looking at your
current computing needs and reserve instances for a year or two and use
these to run EMR and add nodes at peak needs. In your cost estimation you
will need to factor in the data transfer time/costs unless you are dealing
with public datasets on S3

- EMR fared similar to local cluster on CPU benchmarks (we used MRBench to
benchmark map/reduce) however IO benchmarks were slow on EMR (used DFSIO
benchmark). For IO intensive jobs you will need to add more nodes to
compensate this.

- When compared to local cluster, you will need to factor the time it takes
for the EMR cluster to setup when starting a job. This like data transfer
time, cluster replication time etc

- EMR API is very flexible however you will need to build a custom interface
on top of it to suit your job management and monitoring needs

- EMR bootstrap actions can satisfy most of your native lib needs so no
drawbacks there.


-- Sudhir


On 12/26/10 5:26 AM, "common-user-digest-help@hadoop.apache.org"
<common-user-digest-help@hadoop.apache.org> wrote:

> From: Otis Gospodnetic <otis_gospodnetic@yahoo.com>
> Date: Fri, 24 Dec 2010 04:41:46 -0800 (PST)
> To: <common-user@hadoop.apache.org>
> Subject: Re: Hadoop/Elastic MR on AWS
> 
> Hello Amandeep,
> 
> 
> 
> ----- Original Message ----
>> From: Amandeep Khurana <amansk@gmail.com>
>> To: common-user@hadoop.apache.org
>> Sent: Fri, December 10, 2010 1:14:45 AM
>> Subject: Re: Hadoop/Elastic MR on AWS
>> 
>> Mark,
>> 
>> Using EMR makes it very easy to start a cluster and add/reduce  capacity as
>> and when required. There are certain optimizations that make EMR  an
>> attractive choice as compared to building your own cluster out. Using  EMR
> 
> 
> Could you please point out what optimizations you are referring to?
> 
> Thanks,
> Otis
> ----
> Sematext :: http://sematext.com/ :: Solr - Lucene - Nutch - Hadoop - HBase
> Hadoop ecosystem search :: http://search-hadoop.com/
> 
>> also ensures you are using a production quality, stable system backed by  the
>> EMR engineers. You can always use bootstrap actions to put your own  tweaked
>> version of Hadoop in there if you want to do that.
>> 
>> Also, you  don't have to tear down your cluster after every job. You can set
>> the alive  option when you start your cluster and it will stay there even
>> after your  Hadoop job completes.
>> 
>> If you face any issues with EMR, send me a mail  offline and I'll be happy to
>> help.
>> 
>> -Amandeep
>> 
>> 
>> On Thu, Dec 9,  2010 at 9:47 PM, Mark <static.void.dev@gmail.com>  wrote:
>> 
>>> Does anyone have any thoughts/experiences on running Hadoop  in AWS? What
>>> are some pros/cons?
>>> 
>>> Are there any good  AMI's out there for this?
>>> 
>>> Thanks for any advice.
>>> 
>> 


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