Map-side join sample in Java using reference data (MapFile) from distributed cache - Part 2

This post covers, map-side join in Java map-reduce, has links to Apache documentation, my notes on the topic and my sample program demonstrating the functionality. Feel free to share any insights or constructive criticism. Cheers!!

What's in this blog?

A sample map-reduce program in Java that joins two datasets, on the map-side - an employee dataset and a department dataset, with the department number as join key.  The department dataset is a very small dataset in MapFile format, is in HDFS, and is added to the distributed cache.  The MapFile is referenced in the map method of the mapper to look up the department name, and emit the employee dataset with department name included.

Apache documentation on DistributedCache:

http://hadoop.apache.org/docs/current/api/org/apache/hadoop/filecache/DistributedCache.html

Related blogs:
1. Map-side join sample in Java using reference data (text file) from distributed cache - Part 1
2. Map-side join sample in Java using reference data (MapFile) from distributed cache - Part 2

Data used in this blog:
http://dev.mysql.com/doc/employee/en.index.html

Pig and Hive for joins:
Pig and Hive have join capabilities built-in, and are optimized for the same.  Programs with joins written in java are more performant, but time-consuming to code, test and support - and in some companies considered an anti-pattern for joins.

Sample program