In this chapter, we have explored two wrappers of MapReduce programming–Pig and Hive.

MapReduce is very powerful but a very complex high learning curve. The difficult part is to manage the MapReduce programs and the time taken for the development and optimizations. For easier and faster development in MapReduce, we have abstraction layers such as Pig, which is a wrapper of the Pig Latin procedural language on top of MapReduce, and Hive which is a SQL-like HiveQL wrapper.

Pig is used in the data flow model, as it uses the DAG model to transform the Pig Latin language to the MapReduce job. Pig does the transformation in three plans, namely Logical to Physical to MapReduce, where each plan translates the statements and produces an optimized plan of execution. Pig also has the grunt mode for analyzing data interactively. Pig has very useful commands to filter, group, aggregate, cogroup, and so on, and it also supports user-defined functions.

Hive is used by users who are more comfortable...