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Hadoop Projects: Apply MapReduce, Pig & Hive

EDUCBA via Coursera

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

3 weeks, 2 hours a week
Sessions

Self-Paced
Level

Intermediate
Subtitles

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

Found in

Part of

Hadoop Big Data Analytics & Projects Mastery

Overview

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Build practical Big Data analytics skills by analyzing real-world YouTube metadata with Hadoop, MapReduce, Apache Pig, and Apache Hive. You’ll begin by preparing and structuring raw YouTube datasets, exploring Big Data fundamentals, and applying MapReduce jobs to identify patterns and high-rated videos. Next, you’ll use Pig Latin commands and scripts to design scalable data transformation workflows. You’ll process YouTube metadata, store results in HDFS, and interpret structured outputs. You’ll then create Hive tables and execute HiveQL queries to generate aggregated insights, including top-rated and most-viewed videos. Designed for students, professionals, and data enthusiasts, this project-based course emphasizes end-to-end implementation rather than theory alone. You’ll connect data preparation, large-scale processing, transformation, querying, and output interpretation in one structured workflow. By completing the course, you’ll be able to apply key Hadoop ecosystem tools efficiently and build a portfolio-ready YouTube data analysis project that demonstrates practical Big Data skills.

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.