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From "Ladda, Anand" <lan...@microstrategy.com>
Subject RE: [Marketing Mail] Doubts related to Amazon EMR
Date Mon, 23 Apr 2012 14:40:22 GMT
Once you have a Hive Job flow running on Amazon EMR, you'll have access to the file system
on the underlying EC2 machines (you'll get the machine name, etc once the cluster is running).
You can then move your data files on the EC2 machine file system and load it into HDFS/Hive.
I am not sure about the Sqoop part

From: Bhavesh Shah [mailto:bhavesh25shah@gmail.com]
Sent: Monday, April 23, 2012 8:42 AM
To: user@hive.apache.org; dev@hive.apache.org
Subject: [Marketing Mail] Doubts related to Amazon EMR


Hello all,
I want to deploy my task on Amazon EMR. But as I am new to Amazon Web Services I am confused
in understanding the concepts.

My Use Case:

I want to import the large data from EC2 through SQOOP into the Hive. Imported data in Hive
will get processed in Hive by applying some algorithm and will generate some result (in table
form, in Hive only). And generated result will be exported back to Ec2 again through SQOOP
only.

I am new to Amazon Web Services and want to implement this use case with the help of AWS EMR.
I have implemented it on local machine.

I have read some links related to AWS EMR for launching the instance and about what is EMR,
How it works and etc...

I have some doubts about EMR like:

1) EMR uses S3 Buckets, which holds Input and Output data Hadoop Processing (in the form of
Objects). ---> I didn't get How to store the data in the form of Objects on S3 (My data
will be files)

2) As already said I have implemented a task for my use case in Java. So If I create the JAR
of my program and create the Job Flow with Custom JAR. Will it be possible to implement like
this or do need to do some thing extra for that?

3) As I said in my Use Case that I want to export my result back to Ec2 with the help of SQOOP.
Does EMR have support of SQOOP?



If you have any kind of idea related to AWS, please reply me with your answer as soon as possible.
I want to do this as early as possible.

many Thanks.




--
Regards,
Bhavesh Shah


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