Master MapReduce with ENCODE-IT’s Comprehensive Online Course

Take your big data expertise to the next level with ENCODE-IT’s Comprehensive MapReduce course.
MapReduce is a core component of the Hadoop ecosystem, enabling the processing of massive
datasets across distributed systems. Whether you're just starting in big data or looking to enhance
your skills, this course is designed to provide you with the essential knowledge and hands-on
experience to write, optimize, and deploy efficient MapReduce jobs. You will learn how to handle
large-scale data processing tasks, implement advanced features, and understand how MapReduce
fits within the larger Hadoop ecosystem. With this course, you’ll gain the skills needed to harness the
full power of MapReduce for processing and analyzing data at scale.

Course Overview
MapReduce is a powerful programming model for processing large data sets with a parallel,
distributed algorithm on a Hadoop cluster. It enables the efficient processing of vast amounts of
data by breaking tasks into smaller, independent chunks and processing them simultaneously across
multiple machines. In ENCODE-IT’s Comprehensive MapReduce course, you will delve into the
essential concepts of MapReduce, from writing your first MapReduce program to optimizing
performance for complex tasks.
Throughout the course, you will build a solid foundation in the key principles of the MapReduce
framework, including the Map and Reduce functions, input/output formats, partitioners, and
combiners. You’ll also learn how to integrate MapReduce with other Hadoop components like HDFS,
YARN, and HBase. By the end of this course, you'll be able to develop, troubleshoot, and optimize
MapReduce jobs to handle real-world data processing challenges.

Salary Scale in India
As MapReduce is a vital skill in big data and Hadoop, professionals specializing in this area are in high
demand. The salary for professionals with MapReduce and Hadoop expertise ranges from ₹6 lakhs to
₹15 lakhs per year for entry-level positions, depending on experience and job location. With
increasing experience, roles like Big Data Engineers, Hadoop Developers, and Data Engineers can
earn anywhere from ₹12 lakhs to ₹25 lakhs annually. Mastery of MapReduce can significantly boost
your career prospects in fields like data engineering, machine learning, and business analytics, where
big data processing plays a critical role.

Placement Assistance & Certification in India
ENCODE-IT is committed to helping you kickstart your career with its placement assistance services.
We partner with top-tier organizations to ensure that our students are well-connected with leading
employers in the industry. Upon completing the MapReduce course, you will receive a Certificate of
Completion from ENCODE-IT, certifying your proficiency in data processing with MapReduce. This
certification, combined with our placement support, will give you a competitive edge when seeking
roles in big data and analytics.

Course Curriculum

1. Introduction to Big Data and Hadoop
o Understanding Big Data and Its Importance
o Overview of the Hadoop Ecosystem and Key Components
o Introduction to MapReduce and Its Role in Data Processing
o Setting Up a Hadoop Cluster for MapReduce Jobs

2. MapReduce Basics
o The MapReduce Programming Model: Map and Reduce Phases
o Writing Your First MapReduce Program in Java
o Understanding Input and Output Formats in MapReduce
o The Hadoop Distributed File System (HDFS) and Its Integration with MapReduce

3. MapReduce Architecture and Components
o Detailed Overview of the MapReduce Framework
o Map and Reduce Functions: Logic and Execution Flow
o Key Concepts: Mapper, Reducer, and Combiner
o Handling Input/Output Data and Custom Data Formats

4. MapReduce Advanced Features
o Using Partitioner to Control Data Distribution
o Integrating Combiners to Optimize MapReduce Jobs
o Secondary Sorting and Custom Sorting in MapReduce
o Working with MapReduce Join and Aggregation Techniques

5. Optimizing MapReduce Jobs
o Improving Job Performance and Reducing Latency
o Strategies for Data Locality and Efficient Data Processing
o Memory Management and Tuning in MapReduce
o Debugging and Monitoring MapReduce Jobs Using Hadoop Logs

6. Working with Data Formats and Storage
o Using Text, Sequence, and Avro Data Formats with MapReduce
o Integration of MapReduce with HDFS for Large Dataset Storage
o Writing Custom Input and Output Formats for Complex Data Processing
o Managing Data Compression and Efficient Data Storage

7. Integrating MapReduce with Other Hadoop Components

o Integrating MapReduce with HBase for NoSQL Data Processing
o Running MapReduce Jobs on YARN (Yet Another Resource Negotiator)
o Combining MapReduce with Hive for SQL-Like Data Queries
o Integrating with Pig for Scripting-based Data Processing

8. Real-Time Data Processing with MapReduce
o Using MapReduce for Batch vs. Real-Time Processing
o Handling Streaming Data with MapReduce and Kafka
o Integrating MapReduce with Apache Storm for Real-Time Analytics

9. Best Practices for MapReduce Development
o Code Optimization: Reducing Complexity and Enhancing Efficiency
o Writing Scalable and Fault-Tolerant MapReduce Programs
o Error Handling and Exception Management in MapReduce Jobs
o Best Practices for Writing Readable and Maintainable MapReduce Code

10. Advanced Data Processing with MapReduce
o Using Custom Partitioner and Combiner to Optimize Data Flow
o Complex Joins and Data Merging Techniques
o Scaling MapReduce Jobs for Large Datasets Using Hadoop Clusters
o Running Multiple MapReduce Jobs in a Hadoop Pipeline

11. Real-World Projects and Case Studies
o Building a Data Processing Pipeline Using MapReduce
o Optimizing Large-Scale Data Analytics Jobs with Hadoop MapReduce
o Real-World Use Case: Data Transformation for Business Intelligence
o Implementing Complex Data Aggregation and Join Operations

12. Final Project and Certification Exam
o Final Project: Designing and Deploying a Large-Scale MapReduce Solution
o Implementing Best Practices in Job Performance, Optimization, and Debugging
o Final Exam: Comprehensive Assessment of MapReduce Skills
o Certification of Completion from ENCODE-IT and Job Placement Assistance

Why Choose ENCODE-IT for MapReduce Training?

ENCODE-IT offers an in-depth, practical learning experience, ensuring that students master
MapReduce for large-scale data processing. With hands-on projects, real-world case studies, and
expert instructors, ENCODE-IT provides the perfect platform for gaining expertise in MapReduce.
You’ll gain the necessary skills to develop, deploy, and optimize MapReduce jobs in real-world
scenarios, while receiving placement assistance and a Certificate of Completion to boost your
career. Whether you’re aspiring to work in big data, machine learning, or data engineering, ENCODE-
IT’s Comprehensive MapReduce course will prepare you to excel in the dynamic field of data
processing.