Hi Yogesh
Pretty much all the requirements fit well into hive, pig etc. The HivQL and pig
latin are parsed by its respective parsers to map reduce jobs. This MR code
thus generated is generic and is totally based on some rules defined in the
parser.
But say your requirement has something more to be done in your job. Like
updating some stats in hbase or so in between your hdfs data processing. When
you combine hdfs data processing along with some hbase inserts/updates Hive /
Pig may do it in two sets of MR jobs. But if you write a custom code you may be
able to integrate this hbase updates along with the Map/Reduce job that does
hdfs data processing. Summarizing my thought the custom MR code can limit the
no of MR jobs in this case.
There can be n number of complex scenarios like this where your custom code
turns more efficient and performant.
Regards
Bejoy KS
Sent from handheld, please excuse typos.
-----Original Message-----
From: yogesh dhari <yogeshdh...@live.com>
Date: Thu, 8 Nov 2012 00:37:44
To: hadoop helpforoum<user@hadoop.apache.org>
Reply-To: user@hadoop.apache.org
Subject: RE: Map-Reduce V/S Hadoop Ecosystem
Thanks Bejoy Sir,
I am always grateful to u for your help.
Please explain these word into simple language with some case (if possible)
" If your requirement is that complex and you need very low level control
of your code mapreduce is better. If you are an expert in mapreduce your
code can be efficient as yours would very specific to your app but the
MR in hive and pig may be more generic.
"
If my requirement is complex. I will prefer Ecosystem(bcoz it provide simple
interface to run Map-Reduce).
What is low level control of code. belongs here?? plz provide an example..
please do explain it into simple way so that I can understand your point of
view.
Regards
Yogesh Kumar
> Subject: Re: Map-Reduce V/S Hadoop Ecosystem
> To: user@hadoop.apache.org
> From: bejoy.had...@gmail.com
> Date: Wed, 7 Nov 2012 18:24:52 +0000
>
> Hi Yogesh,
>
> The development time in Pig and hive are pretty less compared to its
> equivalent mapreduce code and for generic cases it is very efficient.
> If your requirement is that complex and you need very low level control of
> your code mapreduce is better. If you are an expert in mapreduce your code
> can be efficient as yours would very specific to your app but the MR in hive
> and pig may be more generic.
>
> To just write your custom mapreduce functions, just basic knowledge on java
> is good. As you are better with java you can understand the internals better.
>
>
> Regards
> Bejoy KS
>
> Sent from handheld, please excuse typos.
>
> -----Original Message-----
> From: <yogesh.kuma...@wipro.com>
> Date: Wed, 7 Nov 2012 15:33:07
> To: <user@hadoop.apache.org>
> Reply-To: user@hadoop.apache.org
> Subject: Map-Reduce V/S Hadoop Ecosystem
>
> Hello Hadoop Champs,
>
> Please give some suggestion..
>
> As Hadoop Ecosystem(Hive, Pig...) internally do Map-Reduce to process.
>
> My Question is
>
> 1). where Map-Reduce program(written in Java, python etc) are overtaking
> Hadoop Ecosystem.
>
> 2). Limitations of Hadoop Ecosystem comparing with Writing Map-Reduce program.
>
> 3) for writing Map-Reduce jobs in java how much we need to have skills in
> java out of 10 (?/10)
>
>
> Please put some light over it.
>
>
> Thanks & Regards
> Yogesh Kumar
>
>
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