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Detailed Introduction Towards Understanding Apache Hadoop Pig

Introduction to Pig-

Apache Pig can be interpreted as an advanced high-level programming language which is specially designed for analyzing large data sets. As a matter of fact, the effort behind the development of Pig is of Yahoo.

If you are having knowledge of MapReduce framework, then you must have known that all the programs in it must be translated into a series of Map and Reduce stages. But however, most of the data analysts aren’t comfortable with coding in programming & so this would be turning into a major setback for them. This is where Pig comes into the play.

Apache Pig helps data analysts to set their focus on analyzing massive data sets & limited time writing Map-Reduce programs. Just like Pigs can eat or consume almost anything, Pig programming has been designed to work upon any kind of data. So now you must have got a clear idea on why the name, Pig.

Understanding The Pig Architecture-

Let’s have a clear look at the architecture of Pig

Pig consists of two components:

  • Pig Latin, which is a language
  • A runtime environment, for running PigLatin programs

In a Pig Latin program, input data is applied with a series of transformations so as to produce the desired output. The data flow can be described by these set of operations which can be translated into an executable representation, by Pig execution environment.

One thing which you need to know here is that there will be a series of MapReduce jobs underneath the results of these transformations which most of the programmers are unaware. This simply means that analysts can set their focus on data management rather than program execution.

Advantages Of Apache Pig-

The major advantages of Apache Pig are mentioned here below

  • It consumes less development time
  • Pig is quite easy to learn
  • It is a procedural language
  • Dataflow
  • The control execution here is a lot easier
  • UDFs
  • Lazy evaluation
  • Usage of Hadoop features
  • Effective for unstructured
  • Base Pipeline

Looking at these benefits, there’s no wonder why Pig is one among the most popular tools in the Hadoop Big Data framework.

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