Hadoop Administration
Format
Hands-on Labs
Price
£199
About the course
Develop practical big data administration skills through a series of self-paced, hands-on labs focused on Apache Hadoop and its distributed computing environment.
The course introduces learners to Hadoop versions 1.2.1 and 2.7.3, exploring core components, cluster architecture, and the principles of storing and processing large datasets across distributed systems.
Learners will explore MapReduce for distributed data processing, configure and manage Hadoop clusters, and examine the administration of Hadoop 1.2.1 and Hadoop 2.7.3 environments.
Additional labs cover NameNode failover, introducing high availability concepts and techniques for maintaining access to distributed data and supporting cluster reliability.
The labs connect Hadoop concepts with practical administration tasks, helping learners understand cluster configuration, distributed processing, system availability, and the management of big data infrastructure.
Activities reinforce the relationship between Hadoop components and the operational considerations involved in maintaining reliable distributed computing environments.
By completing the labs, learners will develop foundational skills in Hadoop administration, MapReduce, cluster management, NameNode failover, and working with different Hadoop versions.
The course provides a practical foundation for further study in big data technologies, distributed systems, and data infrastructure administration.
The course introduces learners to Hadoop versions 1.2.1 and 2.7.3, exploring core components, cluster architecture, and the principles of storing and processing large datasets across distributed systems.
Learners will explore MapReduce for distributed data processing, configure and manage Hadoop clusters, and examine the administration of Hadoop 1.2.1 and Hadoop 2.7.3 environments.
Additional labs cover NameNode failover, introducing high availability concepts and techniques for maintaining access to distributed data and supporting cluster reliability.
The labs connect Hadoop concepts with practical administration tasks, helping learners understand cluster configuration, distributed processing, system availability, and the management of big data infrastructure.
Activities reinforce the relationship between Hadoop components and the operational considerations involved in maintaining reliable distributed computing environments.
By completing the labs, learners will develop foundational skills in Hadoop administration, MapReduce, cluster management, NameNode failover, and working with different Hadoop versions.
The course provides a practical foundation for further study in big data technologies, distributed systems, and data infrastructure administration.
Course Lessons
