MapReduce Training

7 Lesson

30 Hours

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igmGuru provides the best MapReduce Training Online worldwide and course content is designed by certified professionals who have more than 15 years of experience in distributed computing and big data technologies. In this MapReduce course, you will learn all the key topics such as Hadoop architecture, data flow, job execution, input/output formats, custom mappers and reducers, and performance tuning. After completing this course, person can clear the latest MapReduce Certification Exams to become certified

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MapReduce Course Overview

Prerequisites

Any Degree or Basic Educational Qualification required
Basic knowledge of Java programming
Familiarity with Linux/Unix commands
Understanding of Big Data concepts

What Will You Learn

Overview of MapReduce and Hadoop Ecosystem
Overview of Distributed Data Processing
Understanding MapReduce Architecture
Writing Mapper and Reducer Programs
InputFormat and OutputFormat
Job Configuration and Execution
Combiner and Partitioner Usage
Shuffle and Sort Mechanism
Counters and Distributed Cache
Performance Tuning Techniques
Real-world MapReduce Examples
Debugging and Job Monitoring
Advanced MapReduce Features
Integration with Other Hadoop Tools

Who Should Enroll

Big Data professionals
Data engineers
Software developers
Data analysts
IT professionals
Students and graduates

Key Features

100% Money-Back Guarantee
Flexible Schedule
Experienced & Professional Trainers
24 X 7 Lifetime Support & Access
1 On 1 Training Option Available
Small Batches Upto 10 Participants

Course Curriculum

Lesson 1 - Introduction to MapReduce

1. Purpose and architecture of MapReduce

2. Overview of distributed data processing

3. Key components: Mapper, Reducer, Driver

4. Hadoop Ecosystem Overview (HDFS, YARN, Pig, Hive, HBase)

5. Hadoop vs Traditional RDBMS

6. Setting Up Hadoop Environment (Local & Cloud)

Lesson 2 - MapReduce Programming Model

1. Input and Output formats

2. Writing custom Mapper and Reducer classes

3. WordCount example walkthrough

4. Data Flow in MapReduce: Input → Map → Shuffle & Sort → Reduce → Output

5. Data Serialization (Writable, WritableComparable)

Lesson 3 - Job Configuration and Execution

1. Job setup and submission

2. InputSplit and RecordReader

3. OutputCommitter and RecordWriter

4. Job Execution Flow (Submission, Execution, Monitoring)

5. Error Handling and Debugging

6. Counters and DistributedCache

Lesson 4 - Advanced MapReduce Concepts

1. Combiner Functions (Optimizing Data Transfer)

2. Partitioning and Sorting (Custom Partitioners, Comparators)

3. MapReduce Optimization Techniques (Performance Tuning, Best Practices)

4. Memory Management

5. Shuffle and Sort Tuning

6. Skipping Bad Records

7. Data Compression Techniques

Lesson 5 - Integrating MapReduce with Hadoop Components

1. Using MapReduce with HDFS (Read/Write Operations)

2. Integration with Hive (Complex Queries) and Pig (Data Transformations)

3. Data Import/Export with Sqoop

4. Streaming Data with Flume

Lesson 6 - MapReduce Libraries and Tools

1. Distributing Libraries with Jobs

2. Using Tool and ToolRunner

3. Profiling and JVM Reuse

4. Task Logs and Debugging

5. Job Control and Monitoring

Lesson 7 - Practical Examples and Projects

1. WordCount v1 & v2.0

2. Log File Analysis

3. Data Aggregation

4. Join Operations (Reduce-side Join, Replicated Join)

5. Sample Runs and Output Analysis

6. Custom MapReduce Job Implementation

7. Performance Tuning & Optimization

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Course Fees

Online Class Room Program

US $ 799.00

100% Money Back Guarantee

Duration : 30 Hrs
Plus Self Paced

Classes Starting From

Fast Track Batch 29 May 2026
Weekday Batch 01 Jun 2026
Weekend Batch 30 May 2026

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MapReduce Certification

igmGuru provides recognized course completion certificates for MapReduce training. These certificates are valid for a lifetime. To earn this certification, you need to enroll in the MapReduce Training Course and fulfill the minimum requirements.

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MapReduce Training