Difference between revisions of "Assignment 4 - Querying with Pig and Mapreduce"
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Big Data - Spring 2014
Big Data - Spring 2014Assignment - Pig Latin and MapReduce
== Description ==
== Description ==
Revision as of 21:37, 28 April 2014
Big Data - Spring 2014: Assignment 4 - Pig Latin and MapReduce
To get some hands on experience with the pig/latin language and capabilities, you will implement a few different queries -- aggregating and combining content from two different collections. For you to have a better appreciation for the features provided by high-level languages, you will also implement a join between the two collections we provide using both MapReduce and Pig Latin.
As input you will read from two CSV files that contain descriptions about users and tweets, respectively.
Each line in the user collection contains: login, name and state from a specific user. Each line in the collection of tweets has the tweet id, content, and a reference to the user who wrote that tweet.
You can find the input files at:
Here are the problems you will solve:
1a. (5 points) Write a Pig Latin query that outputs the login of all users in NY state.
1b. (5 points) Write a Pig Latin query that returns all the tweets that include the word 'favorite', ordered by tweet id.
2a. (30 points) Write a MapReduce program that computes the natural join between the two collections, using the reduce-side join approach.
2b. (20 points) Write the equivalent join using Pig Latin.
3a. (20 points) Write a Pig Latin query that returns the number of tweets for each user name (not login). You should output one user per line, in the following format:
3b. (20 points) Write a Pig Latin query that returns the number of tweets for each user name (not login), ordered from most active to least active users. You should output one user per line, in the following format:
4a. (20 points) Write a Pig Latin query that returns the name of users that posted at least two tweets. You should output one user name per line.
4b. (20 points) Write a Pig Latin query that returns the name of users that posted no tweets. You should output one user name per line.
1. Your queries and program should run on NYU Hadoop cluster. You can use your own Pig/Hadoop installation to design your queries and code, but make sure they run on the NYU Hadoop cluster.
2. You can write your join in either Java or Python.
Java: In addition to the source code, you will submit a JAR file that can be called using the following command:
hadoop -jar join.jar Join -input1 <file_name> -input2 <file_name> -output <file_name>
Python: In addition to the source code for the mapper (join_map.py) and the reducer (join_reduce.py), you should also submit a script (join.py) that invokes Hadoop and runs your code, and can be called using the following command:
python join.py -input1 <file_name> -input2 <file_name> -output <file_name>
Note: Copy the input files to your HDFS directory. Your program should read the input files from the HDFS directory.
3. You must write the Pig Latin code as stand-alone scripts, one script per query. The name of the file should correspond to the name of the query. For example, using the first query, you should be able to run:
pix -x local 1a.pig
to get the result.
When and what to submit
Your assignment is due on May 12, 2014. The required files should be submitted to NYU Classes.
You must create and submit a ZIP file that contains:
1) If you use Java: Java source code and jar file for the hadoop code: join.java join.jar
If you use Python: Python source code: join.py, join_map.py, join_reduce.py
2) Pig Latin scripts, one for each query.
For each query, the result should be in files whose names have as prefix the query name, and extension '.result'. For instance, for the first query the result should be in 1a.result
Here's a Pig tutorial: https://cwiki.apache.org/confluence/display/PIG/PigTutorial