Now you have a solid knowledge base in HDFS, it is now time to dive into the processing module of Hadoop known as MapReduce. Once we have the data in the cluster, we need a programming model to perform advanced operations on it. This is done using Hadoop's MapReduce.
The MapReduce programming model concept has been in existence for quite some time now. This model was designed to process large volumes of data in parallel. Google implemented a version of MapReduce in house to process their data stored on GFS. Later, Google released a paper explaining their implementation. Hadoop's MapReduce implementation is based on this paper.
MapReduce in Hadoop is a Java-based distributed programming framework that leverages the features of HDFS to execute high performance batch processing of the data stored in HDFS.
The processing can be divided into major functions, which are:
Map
Reduce
Since the primary focus of this book is on the administrative aspects of Hadoop, we will...