Difference between revisions of "Course: Massive Data Analysis 2014/Hadoop Exercise"
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== Exercise 1: Fixed-Length WordCount == | == Exercise 1: Fixed-Length WordCount == | ||
* For this exercise, you will only count words with 5 characters | |||
== Exercise 2: InitialCount == | == Exercise 2: InitialCount == | ||
== Exercise 3 Top-K WordCount == | == Exercise 3 Top-K WordCount == | ||
Revision as of 19:48, 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://vgc.poly.edu/~fchirigati/mda-class/RunHadoopAWS.pdf
- 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
- For this exercise, you will only count words with 5 characters