Difference between revisions of "Course: Massive Data Analysis 2014/Hadoop Exercise"
Jump to navigation
Jump to search
Line 16: | Line 16: | ||
* Exercise 1: Fixed-Length WordCount | * Exercise 1: Fixed-Length WordCount | ||
** For this exercise, you will only count words with 5 characters | ** For this exercise, you will only count words with 5 characters | ||
** Output: Key is the word, and value is the number of times the word appear in the input. | |||
* Exercise 2: InitialCount | * Exercise 2: InitialCount | ||
** Count the number of words based on theirs initial (first character), i.e., count the number of words per initial | |||
** The letter case should not be taken into account. For example, '''Apple''' and '''apple''' will be both counted for initial '''A''' | |||
** Output: Key is the initial (A to Z in UPPERCASE), and value is the number of words having that initial (in either uppercase or lowercase). | |||
* Exercise 3 Top-K WordCount | * Exercise 3: Top-K WordCount | ||
** Output the top 100 most frequent 7-character words, in descending order of frequency |
Revision as of 20:05, 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)
Hands-on exercises
- 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
- Output: Key is the word, and value is the number of times the word appear in the input.
- Exercise 2: InitialCount
- Count the number of words based on theirs initial (first character), i.e., count the number of words per initial
- The letter case should not be taken into account. For example, Apple and apple will be both counted for initial A
- Output: Key is the initial (A to Z in UPPERCASE), and value is the number of words having that initial (in either uppercase or lowercase).
- Exercise 3: Top-K WordCount
- Output the top 100 most frequent 7-character words, in descending order of frequency