This training focuses on HDFS operations, MapReduce programming, data processing workflows, Hadoop ecosystem tools integration, and building efficient data pipelines.
Overview
Hadoop for Developers Training is a practical, hands-on program designed to equip learners with the skills required to develop scalable big data applications using the Hadoop ecosystem. This training focuses on HDFS operations, MapReduce programming, data processing workflows, Hadoop ecosystem tools integration, and building efficient data pipelines. Participants will gain real-world experience in developing distributed applications that process large-scale datasets in batch processing environments.
Learning Outcomes
Participants will gain strong development skills in Hadoop ecosystem, enabling them to build scalable data processing applications, implement MapReduce jobs, and handle large-scale datasets efficiently.
Duration & Delivery Mode
17 hours
Target Audience
• Java Developers and Software Engineers
• Big Data Developers and Data Engineers
• Backend Developers working with large datasets
• IT Professionals transitioning into Big Data development
• Students and professionals entering Hadoop ecosystem
Pre-requisites
• Basic knowledge of Java programming
• Understanding of data structures and algorithms fundamentals
• Familiarity with Linux/Unix command line
• Basic understanding of databases and data concepts
Skillset Achieved
• Hadoop architecture and ecosystem understanding
• HDFS file system operations and data handling
• MapReduce programming and job development
• Data processing and batch computation techniques
• Integration with Hadoop ecosystem tools
• Debugging and optimizing Hadoop jobs
• Building scalable distributed data processing applications
Course Outcome
Upon completion of this training, participants will be able to develop distributed data processing applications using Hadoop. They will be capable of writing MapReduce programs, managing large datasets in HDFS, and building scalable batch processing solutions for big data environments.
Course Outline
Introduction to Hadoop Development Environment
• Overview of Hadoop architecture and components
• Setting up Hadoop development environment
• HDFS commands and file system operations
• Data storage and retrieval concepts
HDFS Programming and Data Handling
• Reading and writing data in HDFS
• File formats and data ingestion basics
• Data replication and fault tolerance concepts
• Working with large datasets
MapReduce Programming Fundamentals
• Introduction to MapReduce programming model
• Mapper and Reducer implementation
• Job configuration and execution
• Input and output formats
Advanced Hadoop Development Concepts
• Job optimization techniques
• Debugging MapReduce applications
• Introduction to Hive and Pig integration
• Real-world batch processing use cases
Assessment Topics
• Hadoop architecture and HDFS operations
• MapReduce programming model
• Mapper and Reducer implementation
• Job execution and optimization
• Data ingestion and file handling
• Batch processing workflows
Evaluation
• Hands-on MapReduce coding exercises
• HDFS data handling assignments
• Practical job execution tasks
• Mini project on batch data processing pipeline
Course Materials
Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.
Certification
Participants who successfully complete the training will receive an AcadNXT Certification in Hadoop for Developers Training, validating their expertise in Hadoop development, MapReduce programming, HDFS data processing, and distributed application development.
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What Our Students Say
“The training gave me a strong understanding of Hadoop development and MapReduce programming.”
“Excellent hands-on sessions that made distributed processing concepts very clear.”
“The course helped me build real Hadoop applications with confidence.”
“Very practical training with good focus on HDFS and MapReduce workflows.”
“This course is perfect for anyone starting with Hadoop development.”