Posted by Maarten Winkels in the early morning: July 2nd, 2009
Apache Hadoop promises “a software platform that lets one easily write and run applications that process vast amounts of data”. Sure enough, when reading the documentation, descriptions like:
(input) <k1, v1> -> map -> <k2, v2> -> combine -> <k2, v2> -> reduce -> <k3, v3> (output)
Are simple enough to read and understand, but how do you apply MapReduce to a problem you face in a real-life project?
This blog tries to give some insight into how to apply MapReduce with Hadoop.
