Difference between revisions of "Hadoop/MapReduce Tutorials"
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[[Hadoop Tutorial 1 -- Running WordCount | Tutorial #1]] | [[Hadoop Tutorial 1 -- Running WordCount | Tutorial #1]] | ||
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Running WordCount written in Java on the Smith College Hadoop/MapReduce Cluster | Running WordCount written in Java on the Smith College Hadoop/MapReduce Cluster | ||
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[[Hadoop Tutorial 1.1 -- Generating Task Timelines | Tutorial #1.1]] | [[Hadoop Tutorial 1.1 -- Generating Task Timelines | Tutorial #1.1]] | ||
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Creating timelines of the execution of tasks during the execution of a MapReduce program. | Creating timelines of the execution of tasks during the execution of a MapReduce program. | ||
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[[Hadoop Tutorial 2 -- Running WordCount in Python | Tutorial #2]] | [[Hadoop Tutorial 2 -- Running WordCount in Python | Tutorial #2]] | ||
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Running WordCount in Python on the Smith College Hadoop/MapReduce Cluster | Running WordCount in Python on the Smith College Hadoop/MapReduce Cluster | ||
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[[Hadoop Tutorial 3 -- Hadoop on Amazon AWS | Tutorial #3]] | [[Hadoop Tutorial 3 -- Hadoop on Amazon AWS | Tutorial #3]] | ||
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Running Hadoop jobs on Amazon AWS | Running Hadoop jobs on Amazon AWS | ||
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[[Hadoop_Tutorial_3.1_--_Using_Amazon's_WordCount_program | Tutorial #3.1]] | [[Hadoop_Tutorial_3.1_--_Using_Amazon's_WordCount_program | Tutorial #3.1]] | ||
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Uploading text to S3 and running Amazon's WordCount Java program on our own data. | Uploading text to S3 and running Amazon's WordCount Java program on our own data. | ||
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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. | Compiling our own version of the Java WordCount program and uploading it to AWS. | ||
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[[Hadoop Tutorial 4: Start an EC2 Instance | Tutorial #4]] | [[Hadoop Tutorial 4: Start an EC2 Instance | Tutorial #4]] | ||
Revision as of 14:55, 4 April 2010
These tutorials target the Hadoop/MapReduce Cluster in the CS Dept. at Smith College, as well as Amazon's EC2 and S3.
Tutorial Comments Running WordCount written in Java on the Smith College Hadoop/MapReduce Cluster
Creating timelines of the execution of tasks during the execution of a MapReduce program.
Running WordCount in Python on the Smith College Hadoop/MapReduce Cluster
Running Hadoop jobs on Amazon AWS
Uploading text to S3 and running Amazon's WordCount Java program on our own data.
Compiling our own version of the Java WordCount program and uploading it to AWS.
Start a server on Amazon's EC2 infrastructure
