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Apache Pig: Analyze, Transform & Optimize Data

EDUCBA via Coursera

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Details

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

3 weeks, 3 hours a week
Sessions

Self-Paced
Level

Beginner
Subtitles

English, Arabic, German, Korean, Portuguese, Japanese, Italian, French, Hungarian, Spanish

Found in

Part of

Hadoop & Big Data Foundations Mastery Course

Overview

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Master Apache Pig and learn to analyze, transform, and optimize large-scale datasets using Pig Latin. You’ll begin by exploring Apache Pig’s role in the Hadoop ecosystem, comparing it with Hive, and working with Local and MapReduce execution modes, Pig data types, and essential commands such as LOAD, DUMP, and STORE. As you progress, you’ll use GROUP, COGROUP, JOIN, UNION, SPLIT, FILTER, DISTINCT, and COUNT to integrate, partition, refine, and prepare data for analytics. You’ll then develop Pig Latin scripts, integrate them with HDFS for batch processing, interact with the Grunt Shell, examine execution plans with EXPLAIN, debug programs, and extend Pig through custom UDFs and Piggy Bank libraries. Designed for learners who want practical skills in big data processing, data transformation, and ETL workflows, this course offers a structured path from Apache Pig fundamentals to advanced programming. Its blend of scripting exercises and data transformation scenarios shows how Pig can simplify workflows compared with traditional MapReduce coding. By the end, you’ll be able to build, troubleshoot, and extend Apache Pig workflows that process and prepare large datasets efficiently.

Syllabus

Foundations of Apache Pig
- This module introduces learners to the fundamentals of Apache Pig. It covers its role in the Hadoop ecosystem, explores execution modes, explains essential data types, and demonstrates core commands for data storage, loading, and visualization. By the end of this module, learners will understand the basic building blocks needed to work effectively with Pig.
Mastering Pig Operators and Functions
- This module focuses on data transformation and manipulation in Pig. Learners will explore grouping, joining, and combining datasets; practice filtering, splitting, and deduplication; and apply built-in Pig functions to handle real-world data challenges. Emphasis is placed on using operators to transform and prepare data efficiently.
Advanced Pig Programming
- This module advances learners’ skills in Pig programming by focusing on scripting, debugging, and extending Pig’s functionality. It introduces Pig Latin scripting, HDFS integration, execution plans, and Grunt Shell interaction. Learners will also explore UDFs and Piggy Bank to enhance Pig’s capabilities for enterprise-level data workflows.