Difference between revisions of "Hadoop/MapReduce Tutorials"
Line 64: | Line 64: | ||
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. | ||
|- style="background:#eeeeff" valign="top" | |- style="background:#eeeeff" valign="top" | ||
+ | | | ||
+ | [[Hadoop Tutorial 3.3 -- How Much? | Tutorial #3.3]] | ||
+ | | | ||
+ | Computing the cost of maintaining a cluster of 6 MapReduce instances on Amazon's AWS | ||
+ | |- style="background:#ffffff" valign="top" | ||
| | | | ||
[[Hadoop Tutorial 4: Start an EC2 Instance | Tutorial #4]] | [[Hadoop Tutorial 4: Start an EC2 Instance | Tutorial #4]] |
Revision as of 14:59, 18 April 2010
--D. Thiebaut 16:01, 18 April 2010 (UTC)
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 a streaming Python MapReduce program on XML files
Running C++ programs under Hadoop Pipes
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.
Computing the cost of maintaining a cluster of 6 MapReduce instances on Amazon's AWS
Start a server on Amazon's EC2 infrastructure