Difference between revisions of "Hadoop/MapReduce Tutorials"

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These tutorials target the Hadoop/MapReduce Cluster in the CS Dept. at Smith College, as well as Amazon's EC2 and S3.
 
These tutorials target the Hadoop/MapReduce Cluster in the CS Dept. at Smith College, as well as Amazon's EC2 and S3.
  
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! Tutorial
 
! Tutorial
! Comments
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! Description
 
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[[Hadoop_Tutorial_3.2_--_Using_Your_Own_WordCount_program | Tutorial #3.2]]
 
[[Hadoop_Tutorial_3.2_--_Using_Your_Own_WordCount_program | Tutorial #3.2]]
 
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Compiling our own version of the Java WordCount program and uploading it to AWS.
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Uploading and Running your own streaming version of the WordCount program on AWS.
 
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[[Hadoop Tutorial 3.3 -- How Much? | Tutorial #3.3]]
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Computing the cost of maintaining a cluster of 6 MapReduce instances on Amazon's AWS
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[[Hadoop Tutorial 4: Start an EC2 Instance | Tutorial #4]]
 
[[Hadoop Tutorial 4: Start an EC2 Instance | Tutorial #4]]

Latest revision as of 15:54, 18 April 2010

--D. Thiebaut 16:01, 18 April 2010 (UTC)


AmazonAWS.jpg


HadoopCartoon.png


These tutorials target the Hadoop/MapReduce Cluster in the CS Dept. at Smith College, as well as Amazon's EC2 and S3.






Tutorial Description

Tutorial #1

Running WordCount written in Java on the Smith College Hadoop/MapReduce Cluster

Tutorial #1.1

Creating timelines of the execution of tasks during the execution of a MapReduce program.

Tutorial #2

Running WordCount in Python on the Smith College Hadoop/MapReduce Cluster

Tutorial #2.1

Running a streaming Python MapReduce program on XML files

Tutorial #2.2

Running C++ programs under Hadoop Pipes

Tutorial #3

Running Hadoop jobs on Amazon AWS

Tutorial #3.1

Uploading text to S3 and running Amazon's WordCount Java program on our own data.

Tutorial #3.2

Uploading and Running your own streaming version of the WordCount program on AWS.

Tutorial #3.3

Computing the cost of maintaining a cluster of 6 MapReduce instances on Amazon's AWS

Tutorial #4

Start a server on Amazon's EC2 infrastructure