By the end of this course, learners will be able to design Hive databases, manage complex tables, process XML data with Pig, execute MapReduce jobs, and analyze large-scale social media datasets to extract meaningful insights. The course begins with foundational concepts of Hive, including databases, partitions, and bucketing, then advances into table optimization and constraints for schema design. Learners will gain practical experience in ingesting data with Sqoop, processing it using MapReduce, and applying location- and author-based analytics to real-world datasets. Finally, the course explores Pig scripting for XML processing and Hive complex data types for advanced bookmarking dataset analysis.
Big Data Analytics with Hive, Pig & MapReduce
Big Data Analytics with Hive, Pig & MapReduce
This course is part of Hadoop Big Data Analytics & Projects Mastery Specialization
Instructor: EDUCBA
Included with 
Gain insight into a topic and learn the fundamentals.
9 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Design and optimize Hive databases for large datasets.
Process XML data and execute MapReduce and Pig scripts.
Apply analytics to real-world telecom and social data.
Skills you'll gain
Details to know
Shareable certificate
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Recently updated!
November 2025
Assessments
15 assignments
Taught in English
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This course is part of the Hadoop Big Data Analytics & Projects Mastery Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
This module introduces Apache Hive and its role in the Hadoop ecosystem. Learners will explore Hive’s basic features, database commands, table operations, and foundational concepts like external tables, partitions, and bucketing. By the end, they will have a strong foundation to query and manage data effectively in Hadoop using Hive.
What's included
10 videos4 assignments
This module dives deeper into advanced Hive functionality, including table constraints and complex table creation. Learners will understand how to design optimized tables and implement constraints to improve schema structure and maintainability in Hive.
What's included
4 videos3 assignments
This module focuses on importing social media data into Hadoop, processing it with MapReduce, and analyzing it for insights. Learners will practice using Sqoop for RDBMS to HDFS transfers, run MapReduce programs, and analyze datasets by location, authors, and reader preferences.
What's included
11 videos4 assignments
This module explores Pig and Hive for advanced social media analytics. Learners will process XML data with Pig, store and explore outputs, and utilize Hive complex data types with MapReduce for deep insights into bookmarking datasets and user interactions.
What's included
12 videos4 assignments
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