Apache Hadoop and MapReduce Essentials E-Learning
Order this unique E-Learning course today!
✔️ 1 year 24/7 access to rich interactive videos with voice support.
✔️ Including progress monitoring via reports and tests per chapter.
Why choose this course?
Apache Hadoop and MapReduce are essential for processing enormous amounts of data in distributed systems. This training provides a solid foundation in:
- Understanding the Hadoop architecture and how it works for data storage and processing.
Learning to use MapReduce, the powerful framework for distributed processing of large data sets.
During this course you will discover:
- How to store and process data efficiently with Hadoop HDFS.
- Building and deploying MapReduce programs.
- The application of distributed systems to analyze complex data sets.
This combination of theory and practice prepares you for real big data challenges.
Who should participate?
This course is perfect for:
- Data analysts who want to learn how to work with Hadoop and MapReduce.
- IT professionals who want to understand how distributed systems function.
- Software developers who want to build big data solutions.
- Students and beginners who want to develop a strong foundation in big data technologies.
Course content
Fundamentals of Hadoop
Course: 22 Minutes
- Course Introduction
- Basics of Hadoop
- Users of Hadoop
- The Four Vs of Big Data
- Sources of Big Data
- Clustering
- Introduction to Server Farms
Installing Hadoop
Course: 27 Minutes
- Hadoop Installation Considerations
- Testing your Hadoop Installation
- Your First Hadoop Cluster
- Hadoop Distributions
- Hadoop Ecosystem
- The Role of YARN
File Storage/Tools
Course: 28 Minutes
- Overview of Hadoop, Storage, MapReduce, Pig, and Hive4
- Understanding Data
- Types of NoSQL Databases
- Introduction to the Hadoop Distributed File System
- Interacting with the HDFS
- File Operations within the HDFS
Introduction to MapReduce
Course: 27 Minutes
- The MapReduce Principles, Mappers, and Reducers
- Using MapReduce with Pig and Hive
- Introduction to the MapReduce Life Cycle
- Understanding the MapReduce Data Flow
- Subdividing Data
Practice: Introduction to Apache Hadoop
Course: 15 Minutes
- Exercise: Apache Hadoop Basics
Writing MapReduce Programs
Course: 20 Minutes
- Course Introduction
- Creating Job Components
- Understanding MapReduce with a Conceptual Example
- Hadoop MapReduce and Java
- Executing Hadoop MapReduce Jobs
Programming Considerations and Techniques
Course: 23 Minutes
- Job Flow Progress and Monitoring
- Chaining MapReduce Jobs
- Executing Commands
- How Data is Processed, Persisted, and Read on the HDFS
- Understanding Persistence and Types of Big Data
Using Hive and Pig
Course: 35 Minutes
- Using HiveQL to Write Queries
- Understanding Hive File Formats
- Working with Custom Hive Data Types
- Using Pig Latin to Communicate with Hadoop
- Writing Pig Scripts
- Loading and Storing Data in Pig
- Comparing Performance: MapReduce, Hive, and Pig
Unit Testing with MapReduce
Course: 29 Minutes
- Understanding High-Level Processing
- Viewing Job Status and Log Files
- Killing MapReduce Jobs
- Using JUnit
- Introduction to MRUnit
- Using a Mini MapReduce and HDFS Cluster
- Using the Hadoop LocalJobRunner
Practice: Programming in MapReduce, Hive, and Pig
Course: 15 Minutes
- Exercise: Programming in MapReduce, Hive, and Pig
Get started today!
✔️ Start immediately with interactive and practice-oriented content.
✔️ Get immediate results through chapter tests and reports.
✔️ Build strong expertise in Apache Hadoop and MapReduce.
Order your course now and strengthen your skills in big data!
