Apache Pig Tutorial

Introduction to Apache Pig

Pig tutorial provides basic and advanced Pig concepts. Our Pig tutorial is designed for beginners and professionals.

Pig is a high-level programming language used for executing Map-Reduce programs of Hadoop. A pig was developed by Yahoo!

Our Pig tutorial involves all topics of Apache Pig with Pig usage, Pig runs Modes, Pig Installation, Pig Data Types, Pig Example, Pig Latin concepts, pig user-defined functions, etc.

What is Pig?

Pig is an open-source high-level data flow platform for creating programs that run on Hadoop. Pig provides a simple language called pig Latin, used for data manipulation and queries. The Hadoop jobs in Map Reduce can be executed by the Pig.

The pig can handle any data type, i.e., structured, semi-structured, or unstructured, and store the results in the Hadoop Data File System.

Properties

The properties of pig are listed below:

  • Easy Programming

The programming is easy to write, understand, and maintain because all the complex activities, which involve multiple interrelated data transformations, are correctly represented as data flow sequences.

  • Optimization opportunities

It allows users to focus on sequencing rather than performance, which increases the execution automatically. It helps in the encryption of tasks of the program.

  • Extensibility

For special-purpose processing, users can create their own functions.

Features of Apache Pig

The Features of Apache pig are as follows:

  • Rich set of operator
  • Easy of programming
  • Optimization opportunities
  • User-Defined Functions (UDF’s)
  • Handles all types of data
  • Extensibility
  • ETL (Extract Transform Load)
  • Multi Query Approach
  • Optimal Schema

Rich set of the operator

Apache pig has a rich collection of operators to perform operations such as joining, filing, and sorting.

Easy Programming

Pig Latin is similar to SQL (Structured Query Language). The developers can write a Pig script very easily. The basic knowledge of SQL eases the learning process of Pig.

Optimization opportunities

In Apache, pig has automatically optimized the execution of the task by itself, so programmers only need to focus on the language's semantics.

User-Defined Function (UDF’s):-

Apache Pig allows you to create user-defined functions in other languages such as java and can invoke them in PigLatin Scripts.

Handles all types of data

One of the reasons for easy programming is the handling of all types of data, which means all kinds of data are analyzed, either structured or unstructured. It also stores HDFS data.

Extensibility

The users can create their individual data reading, encoding, and writing functions by using the Apache pig's existing operators.

ETL (Extract Transform Load)

Apache Pig extracts the large data set, performs large data operations, and dumps data in HDFS in the required format.

Multi Query Approach

Apache Pig uses the multi-query method. It reduces the length of the codes.

Optimal Schema

In Apache Pig, the schema is optional. Therefore, we can store data without designing a scheme. Thus, values of $01, $02, etc. are stored.

Application of Apache Pig

The Applications of Apache Pig are-

  • Pig is used to process large data sources like streaming online data, weblogs, etc.
  • It is used for search platform data processing.
  • It Support Ad Hoc queries across large data set.

Advantages of Apache Pig

The advantages of the Apache Pig are listed below:

  • Pig Latin can be programmed easily.
  • The development time is reduced.
  • It can manage more complex flows of data.
  • Apache pig is used to operate on a cluster's server-side.
  • It supports the recovery of the code.
  • Pig is one of the best tools for creating structured and the large unstructured data.
  • Pig is an open-source platform.
  • If you are familiar with SQL, Pig is easy to learn, read and write.

Disadvantages of Apache Pig

The disadvantages of the Apache Pig are listed below:

  • It has a slow start-up and clean-up of MapReduce jobs.
  • It is not suitable for interactive OLAP analysis.                                                   

Prerequisite

The requirement of Apache Pig is basic knowledge of Hadoop.

Audience

Our Pig Tutorial is designed for professionals and beginners.

Problem

You will not find any problem in this Pig tutorial. However, if there is any mistake, please post the problem in the contact form.



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