When will I have access to the lectures and assignments?

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

MapReduce with Hadoop: Analyze, Design & Deploy

Ends tomorrow! Save on skills that make you shine with 40% off 3 months of Coursera Plus. Save now

MapReduce with Hadoop: Analyze, Design & Deploy

This course is part of Hadoop & Big Data Foundations Mastery Course Specialization

Instructor: EDUCBA

Included with

Learn more

5 modules

Gain insight into a topic and learn the fundamentals.

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

5 modules

Gain insight into a topic and learn the fundamentals.

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Develop and optimize custom MapReduce programs in Hadoop.
Build and analyze data workflows using Pig and Java APIs.
Deploy and manage real-world projects on Cloudera clusters.

Skills you'll gain

Tools you'll learn

Apache Hadoop

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

20 assignments

Taught in English

91%

of learners achieved a positive career outcome

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Build your subject-matter expertise

This course is part of the Hadoop & Big Data Foundations Mastery Course Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 5 modules in this course

By the end of this course, learners will be able to analyze Hadoop’s data processing model, design custom MapReduce jobs, implement combiners and partitioners, build advanced applications with Pig and Java, parse weblogs, create inverted indexes, and deploy projects on Cloudera Local Host. Through a structured progression from foundational concepts to advanced analytics and real-world projects, learners will gain both theoretical knowledge and hands-on expertise.

This course stands out by combining step-by-step demonstrations, real-world datasets, and final capstone projects that mirror industry use cases. Learners won’t just memorize commands—they will apply MapReduce for rating analysis, log processing, indexing, and social graph computation, building skills that scale from testing in local mode to deploying on production clusters. The integration of practice programs and examples ensures continuous reinforcement of concepts, making the learning process engaging and practical. Whether you are a beginner seeking a solid foundation or an intermediate learner aiming to expand into advanced MapReduce programming, this course equips you to confidently design, execute, and optimize distributed data processing solutions in the Hadoop ecosystem.

Module details

This module introduces learners to the essential building blocks of Hadoop and MapReduce. It covers sorting mechanisms, the importance of composite keys, partitioning, core Hadoop commands, and the use of combiners. Learners will also see how real-world datasets are integrated into MapReduce projects.

What's included

15 videos4 assignments

15 videosTotal 115 minutes

Secondary Sort Hadoop9 minutes
Creating Composite Key8 minutes
Continue on Composite Key9 minutes
Word Count Group7 minutes
Importance of Partition11 minutes
Hadoop FS - LS5 minutes
Joins in Hadoop7 minutes
Creating Configuration Object6 minutes
Setup Method7 minutes
Map Side Join Mapper8 minutes
Hadoop Commands7 minutes
Combiner in Hadoop6 minutes
Continue on Combiner in Hadoop9 minutes
Uploading Combiner Jar4 minutes
Introduction to Real World10 minutes

4 assignmentsTotal 60 minutes

Sorting, Keys, and Word Count Basics10 minutes
Hadoop Commands and Setup10 minutes
Combiners and Real-World Introduction10 minutes
Foundations of Hadoop and MapReduce30 minutes

This module focuses on real-world applications of MapReduce with emphasis on movie rating analysis and user-based aggregations. It also introduces YARN resource management and NodeManager functionality, followed by practical demonstrations of running MapReduce jobs.

What's included

11 videos4 assignments

11 videosTotal 97 minutes

Ratings Mapper7 minutes
Movie and Ratings Runner9 minutes
Movie and Rating Calc Jar4 minutes
Total Ratings By A User8 minutes
User Rating Reducer11 minutes
User Rating Class5 minutes
Yarn Basic Tutorial10 minutes
Node Manager10 minutes
Running a MapReduce Program11 minutes
Running a MapReduce Program Continues11 minutes
HDFS File System10 minutes

4 assignmentsTotal 60 minutes

Movie Ratings and User Analysis10 minutes
Yarn and Node Management10 minutes
Running MapReduce Programs10 minutes
Practical MapReduce Applications30 minutes

This module deepens understanding of advanced MapReduce operations. Learners explore extended Word Count applications, log processors, and integration with Pig for high-level scripting. The module also introduces Java class customization and inverted indexing for search applications.

What's included

11 videos4 assignments

11 videosTotal 116 minutes

Combination of Word Count Functionality9 minutes
Word Count With Tools10 minutes
Log Processor11 minutes
Advanced MapReduce and PIG10 minutes
More on Advanced MapReduce9 minutes
Executing Similar Program8 minutes
HDI Data and Export Data13 minutes
Creating New Java Class12 minutes
Text Out Inverted Indexer13 minutes
Introduction to MapReduce on Hadoop10 minutes
Java Build Path10 minutes

4 assignmentsTotal 60 minutes

Word Count and Processing Extensions10 minutes
Advanced MapReduce with Pig and Similar Programs10 minutes
Java Integration and Inverted Indexing10 minutes
Advanced MapReduce Concepts30 minutes

This module introduces learners to different Hadoop data formats and their importance. It covers SequenceFiles for key-value storage, weblog parsing, analytics programs, and indexing methods. Learners will also understand social graph analysis using MapReduce.

What's included

9 videos4 assignments

9 videosTotal 85 minutes

Local MapReduce4 minutes
Using MapReduce9 minutes
Sequence file Format11 minutes
Parse Weblogs11 minutes
Page View Mapper9 minutes
Analytics Program9 minutes
Analytics Program Continue12 minutes
Inverted Index Map Reduce11 minutes
Friend Sofa Friend8 minutes

4 assignmentsTotal 60 minutes

Local MapReduce and Sequence Files10 minutes
Weblog Parsing and Analytics10 minutes
Indexing and Social Graph Programs10 minutes
Data Formats, Analytics, and Indexing30 minutes

This module brings together all concepts through deployment and project execution. Learners will practice on Cloudera local host, run final projects, and strengthen skills through examples and practice programs that mirror real-world scenarios.