Introduction to Pig

  • APACHE PIG is one of the major components of hadoop which is an abstract layer (high level) on the top of MAPREDUCE.
  • Apache pig is meant for processing huge amount of data that gets stored on top of HDFS.
  • The processing will be carried out in apache pig by making use of different transform actions like load, Generate, filter etc.
  • So, we can call apache pig as transformation language (or) Data flow language.
  • So the data has to go through this transformation to archive the dizer functionality.

Note: Apache Pig is a abstract layer or high level language on top of HDFS as every statement of the pig is internally getting converted into MR.

Related Page:: Introduction to HDFS (Distributed File System) - Hadoop

Map Reduce Vs Apache Pig

Subscribe to our youtube channel to get new updates..!

1. In MapReduce, for processing data we have to write the driver code, Mapper code and Reduces code (if required) irrespective of business logic that we are applying Where as in Apache pig, we can archive some functionality by making use of scripting language with less number of lines of coding.
2. MapReduce is expecting Java programming language skills where as in apache pig even a non java programming member  can write the code using simple scripting.
3. 200 lines of MR code is equal to 10 lines of a pig code.
4. In Map reduce, we have to follow scripting process something like compilation of MR code, Executing code, packaging code and deploy in cluster where as in apache pig, it is very easy to run the code without involving many steps

Interested To Learn Map Reduce Certification Training?  Enroll now for FREE Demo On Map Reduce Training !

Installing and Running Pig

  • Pig runs as a client – side application
  • If you want to run pig on a hadoop cluster, there is nothing extra to install on the cluster i.e. pig launches jobs and interacts with HDFS or other Hadoop file systems from your work station.
  • Installation is straight forward and Java 6 is a prerequisite.
  • Download a stable release from and un place the tar ball in a suitable place on your work station i.e % tar xzf pig – x.y.z tar.  Gz.
  • It’s convenient to add pig’s bin directory to your command line path.
  • For Example:  % export PIG-INSTALL=/home/tom/pig-x.y.z export PATH = $ PIG-INSTALL/bin

    You also need to set the JAVA-HOME environment variable to point to a suitable Java Installation.
  • Provide the command pig-help to get usage instructions.
Explore MapReduce Sample Resumes! Download & Edit, Get Noticed by Top Employers!Download Now!

List of Other Big Data Courses: