Hadoop Projects: Apply MapReduce, Pig & Hive

Overview

By the end of this course, learners will be able to prepare raw YouTube datasets, apply MapReduce for large-scale processing, implement Pig Latin scripts for metadata analysis, and execute HiveQL queries to generate structured insights. The course blends practical scenarios with hands-on tools from the Hadoop ecosystem, empowering learners to analyze real-world data efficiently. This project-based course offers a unique opportunity to practice Big Data analytics using actual YouTube data. Unlike theoretical courses, it emphasizes end-to-end implementation — from data preparation and transformation to query execution and output interpretation. Learners will gain practical skills in Hadoop, MapReduce, Pig, and Hive, making them proficient in handling complex datasets and extracting valuable insights. By completing this course, learners will not only master essential Hadoop tools but also build a portfolio-ready project that demonstrates Big Data analysis skills applicable to industry scenarios such as video analytics, recommendation systems, and large-scale reporting. This makes the course ideal for students, professionals, and data enthusiasts aiming to strengthen their expertise in Big Data.

Syllabus

Hadoop and MapReduce Foundations

This module introduces learners to the fundamentals of Hadoop and MapReduce by exploring YouTube data analysis scenarios. It covers data preparation, Big Data basics, and the use of MapReduce to process large-scale datasets. Learners will gain hands-on insights into building analyzers that identify key patterns, high-rated videos, and structured outputs.

Pig for YouTube Data Analysis

This module explores Apache Pig as a high-level tool for simplifying data transformations in Hadoop. Learners will understand Pig Latin scripting, its commands, and how to use Pig for analyzing YouTube metadata. Practical examples will demonstrate how Pig outputs structured insights from large datasets.

Hive for YouTube Data Analysis

This module covers Apache Hive and its SQL-like language HiveQL for large-scale YouTube data analysis. Learners will practice creating tables, running Hive queries, and generating aggregated insights such as top-rated or most-viewed videos. The module concludes with a summary of integrating Hadoop, MapReduce, Pig, and Hive for scalable data analytics.