Administrator Training

Hadoop Administrator Training  – Hadoop Training Chennai

          Hadoop Administrator training  is for System Administrators and others responsible for managing Apache Hadoop clusters in production or development environments.

Hadoop Training Chennai

You Will Learn

  • How the Hadoop Distributed File System and MapReduce work
  • What hardware configurations are optimal for Hadoop clusters
  • What network considerations to take into account when building out your cluster
  • How to configure Hadoop’s options for best cluster performance
  • How to configure NameNode High Availability
  • How to maintain and monitor your cluster
  • How to load data into the cluster from dynamically-generated files using Flume and from relational database management systems using Sqoop
  • What system administration issues exist with other Hadoop projects such as Hive, Pig and HBase

Hadoop Administrator Training – Prerequisites

          This course is appropriate for system administrators who will be setting up or maintaining a Hadoop cluster. Basic Linux system administration experience is a prerequisite for this training session. Prior knowledge of Hadoop is not required.

Hands-On Exercises

Throughout the course, hands-on labs help students build their knowledge and apply the concepts being discussed.

Hands-On Hadoop Training Chennai

Through instructor-led discussion and interactive, hands-on exercises, participants will navigate the Hadoop ecosystem, learning topics such as:

  • The internals of MapReduce and HDFS and how to build Hadoop architecture
  • Proper cluster configuration and deployment to integrate with systems and hardware in the data center
  • How to load data into the cluster from dynamically-generated files using Flume and from RDBMS using Sqoop
  • Configuring the FairScheduler to provide service-level agreements for multiple users of a cluster
  • Installing and implementing Kerberos-based security for your cluster
  • Best practices for preparing and maintaining Apache Hadoop in production
  • Troubleshooting, diagnosing, tuning, and solving Hadoop issues
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