Apache Pig allows users to write custom scripts on top of the MapReduce framework. Pig was founded to offer flexibility in terms of data programming over large data sets and non-Java programmers. Pig can apply multiple transformations on input data in order to produce output on top of a Java virtual machine or an Apache Hadoop multi-node cluster. Pig can be used as a part of ETL (Extract Transform Load) implementations for any big data project.
Setting up Apache Pig in your Hadoop environment is relatively easy compared to other software; all you need to do is download the Pig source and build it to a pig.jar file, which can be used for your programs. Pig-generated compiled artifacts can be deployed on a standalone JVM, Apache Spark, Apache Tez, and MapReduce, and Pig supports six different execution environments (both local and distributed). The respective...