Hadoop Administration Training in pune




1 on 1 sessions


Free cloud access


24*7 call support


Course Features


  VM for practice.


Free cloud storage


CCDH preparation





Video Lectures


Complete modules


Multiple batches

Syllabus for Hadoop Administrator

Hadoop History And Conceptual Understanding

  • Intriduction to Hadoop Ecosystem
  • Hadoop Distributions
  • Available architectures1.0 and 2.0 (YARN)
  • True nature of Hadoop and common Hadoop myths
  • Hadoop challenges with respect to OLTP and real time processing


Planning a Hadoop Cluster and installation

  • Making a choice of Hadoop distribution

  • Cluster capacity planning

  • Choice of Hardware and Platforms.

  • Configuring Rack Topology

  • Installation with Single Node and Multi node system

  • Configuring Multi-tenancy

  • Directory structure of Hadoop and edit logs

  • Benchmarking



Insight on HDFS

  • Hadoop Select Topics (Horizontal scaling, replication, data locality, rack awareness)

  • Daemons with respect to 1.X and 2.X architecture

  • Cluster monitoring and controlling

  • Web-based GUI for Namenode administration

  • Configuring external storage for Hadoop rack



Optimizing Map-Reduce

  • 6-phase operations with Hadoop Map-Reduce

  • Load balancing with respect to bigdata loads.

  • Resource Manager and Application Master

  • MapReduce UI walk through

  • MapReduce configuration

  • Configuration of Job with respect to 1.0 architecture

  • Capacity scheduler, Fair scheduler and FIFO scheduler

  • Some usage tips and tricks

  • Configuring mapreduce to optimize cluster performance


Advanced administration concepts

  • Whereabouts on hardware monitoring and failures

  • Whereabouts on software monitoring and failures

  • Hadoop cluster monitoring

  • Adding and removing servers and upgrading Hadoop

  • Backup, recovery, and business continuity planning

  • Cluster configuration tweaks

  • Hardware maintenance schedule

  • Oozie scheduling for administrators

  • Securing your cluster with Kerberos

  • The future of Hadoop





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