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MapReduce >> mail # user >> Low latency data access Vs High throughput of data


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Re: Low latency data access Vs High throughput of data
Hi Chris,

Thanks for the explaination.

Regards,
Raj
________________________________
 From: Chris Embree <[EMAIL PROTECTED]>
To: [EMAIL PROTECTED]; Raj Hadoop <[EMAIL PROTECTED]>
Sent: Monday, May 20, 2013 1:51 PM
Subject: Re: Low latency data access Vs High throughput of data
 
I'll take a swing at this one.

Low latency data access:  I hit the enter key (or submit button) and I expect results within seconds at most.  My database query time should be sub-second.
High throughput of data:  I want to scan millions of rows of data and count or sum some subset.  I expect this will take a few minutes (or much longer depending on complexity) to complete.  Think of more batch style jobs.

Caveats: This is really a map/reduce issue also.  The Set up and processing of M/R jobs takes a bit of overhead.  There are a couple of projects working now to move toward lower latency data access.

Also, HDFS stores data in blocks and distributes them across many nodes.  This means that there will (almost) always be some network data transfer required to get the final answer, and that "slows" things down a bit, depending on throughput and various other factors.

Hope that helps. :)

On Mon, May 20, 2013 at 10:48 AM, Raj Hadoop <[EMAIL PROTECTED]> wrote:

Hi,
>
>
>I have a basic question on HDFS. I was reading that HDFS doesnt work well with
low latency data access. Rather it is designed for the high throughput
of data. Can you please explain in simple words the difference between
"Low latency data access Vs High throughput of data".
>
>
>
>Thanks,
>Raj