Difference between revisions of "Course: Massive Data Analysis 2014/Hadoop Exercise"

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* Follow the instruction here to create your Amazon Elastic MapReduce (EMR): http://example.com
* Follow the instruction here to create your Amazon Elastic MapReduce (EMR): http://example.com
* Instructions to run WordCount on your local machine and EMR cluster will be given in class
* Instructions to run WordCount on your local machine and EMR cluster will be given in class
* '''Note: You don't have to submit code and results for this exercise.'''


== Exercise 1: Fixed-Length WordCount ==
== Exercise 1: Fixed-Length WordCount ==

Revision as of 19:32, 3 October 2014

Before you start

  • You must have Hadoop installed and working on your local machine. You also need to setup your Amazon AWS account. Refer to the instruction in the course page.
  • Download the following package: http://vgc.poly.edu/~fchirigati/mda-class/hadoop-exercise.zip. This package contains the basic WordCount example to help you get started.
  • What to submit
    • Code: place your code in a public GitHub repository
    • Results: put the results in your S3 bucket (don't forget to make it public)
    • Complete this form to add the links to your GitHub repository and S3 bucket. Deadline: 11:59 PM on the same day of class (Oct 6, 2014)

Exercise 0: WordCount

  • Run the basic WordCount example on your local machine and AWS
  • Follow the instruction here to create your Amazon Elastic MapReduce (EMR): http://example.com
  • Instructions to run WordCount on your local machine and EMR cluster will be given in class
  • Note: You don't have to submit code and results for this exercise.

Exercise 1: Fixed-Length WordCount

Exercise 2: InitialCount

Exercise 3 Top-K WordCount