Hadoop & Spark for Administrators Training is a comprehensive hands-on program designed to equip learners with the skills required to install, configure, manage, and optimize Hadoop and Spark ecosystems in enterprise environments. This training focuses on cluster setup, resource management, HDFS administration, YARN configuration, Spark deployment, monitoring, troubleshooting, and performance tuning. Participants will gain practical experience in managing big data infrastructure and ensuring high availability, scalability, and efficient processing of large-scale data workloads.

Participants will gain strong administrative expertise in Hadoop and Spark ecosystems, enabling them to manage distributed big data platforms, ensure system stability, and optimize performance in enterprise environments.

• Hadoop Administrators and System Administrators
• Big Data Engineers and Platform Engineers
• DevOps Engineers working on data platforms
• Cloud Infrastructure Engineers
• IT Professionals managing distributed systems

• Basic understanding of Linux/Unix operating system
• Familiarity with networking and distributed systems concepts
• Basic knowledge of Big Data concepts is helpful
• Understanding of command-line operations

• Hadoop cluster installation and configuration
• HDFS administration and file system management
• YARN resource management and scheduling
• Spark installation and cluster deployment
• Monitoring and troubleshooting Hadoop ecosystem components
• Performance tuning of Hadoop and Spark clusters
• Security and user management in big data environments

Upon completion of this training, participants will be able to install, configure, and manage Hadoop and Spark clusters in production environments. They will be capable of handling cluster administration tasks, optimizing performance, and ensuring reliable big data processing systems.

Introduction to Hadoop Ecosystem and Architecture
• Overview of Hadoop components and architecture
• HDFS concepts and storage management
• Hadoop cluster setup and configuration basics
• Namenode, Datanode, and secondary namenode roles

HDFS Administration and Management
• HDFS commands and file system operations
• Data replication and fault tolerance
• User and permission management in HDFS
• Cluster health monitoring basics
YARN and Resource Management
• YARN architecture and components
• ResourceManager and NodeManager roles
• Job scheduling and resource allocation
• Monitoring cluster performance

Hadoop Ecosystem Tools Overview
• Introduction to Hive and Pig basics
• Sqoop and data ingestion concepts
• Log management and debugging techniques
• Cluster troubleshooting methods
Apache Spark Administration
• Spark architecture and components
• Cluster modes (Standalone, YARN, Mesos overview)
• Spark deployment and configuration
• Monitoring Spark applications

Performance Tuning and Maintenance
• Hadoop and Spark performance optimization
• Memory and resource tuning techniques
• Fault tolerance and recovery strategies
• Best practices for production environments

• Hadoop architecture and cluster setup
• HDFS administration and commands
• YARN resource management
• Spark deployment and monitoring
• Cluster troubleshooting techniques
• Performance tuning and optimization

• Hands-on cluster setup and configuration exercises
• Practical Hadoop and Spark administration tasks
• Troubleshooting and performance tuning assignments
• Mini project on end-to-end cluster management

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Participants who successfully complete the training will receive an AcadNXT Certification in Hadoop & Spark for Administrators Training, validating their expertise in Hadoop cluster administration, Spark deployment, resource management, and big data platform optimization.