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From devansh kumar <devansh_ku...@yahoo.com>
Subject Re: Basic queries regarding Apache Drill working
Date Fri, 05 Apr 2013 04:48:59 GMT
Hi,

As Andrew asked, how will average work without an operation of Reduce present. 
Can you explain more on how will the data be aggregated?




________________________________
 From: Andrew Brust <andrew.brust@bluebadgeinsights.com>
To: "drill-user@incubator.apache.org" <drill-user@incubator.apache.org>; devansh kumar
<devansh_kumar@yahoo.com> 
Sent: Thursday, April 4, 2013 8:00 PM
Subject: RE: Basic queries regarding Apache Drill working
 
Still not sure I follow (and pardon what must be a very rudimentary misunderstanding on my
part) how you get an average across a data set if the data is split across nodes.  With MapReduce,
the reducer can get it because all data for a given key is kept to one node.  How would this
work with Drill?

-----Original Message-----
From: Ted Dunning [mailto:ted.dunning@gmail.com] 
Sent: Thursday, April 4, 2013 9:27 AM
To: drill-user@incubator.apache.org; devansh kumar
Subject: Re: Basic queries regarding Apache Drill working

On Thu, Apr 4, 2013 at 12:27 PM, devansh kumar <devansh_kumar@yahoo.com>wrote:

> Hi,
>
> I am new and am trying to understand how Apache Drill  works but i 
> have a few queries.
> Can anyone help me understand these things?
>
> 1.
> I am trying to understand if the execution engine is going to break up 
> the data.
>

Normally the data will already have been broken up across a cluster.


> What will happen if i am trying to an aggregation operation like (AVERAGE).
> How will that work??
>

Yes.


> I have seen operations as SUM and COUNT.
> How will the Query execution tree look like in case of an AVERAGE
>

It will look exactly like a SUM or COUNT except that two numbers will be accumulated instead
of one.


> 2.
> Does the Resource model is optimized when compared to MapReduce.
>

Yes.  This will happen because multiple levels of aggregation can be done in one tree without
the barrier between map and reduce imposed by the MapReduce structure.
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