Introduction to Hadoop Administration Training

Introduction to Hadoop Administration Training is designed to help professionals develop a conceptual understanding of all the important steps to maintain and operate a Hadoop cluster.

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Course Overview

Introduction to Hadoop Administration Training is designed to help professionals develop a conceptual understanding of all the important steps to maintain and operate a Hadoop cluster.

This technical course educates about the Big Data landscape and provides comprehensive information about the system administration working aspect of running Hadoop.

Throughout the program, students get to learn about the most challenging situations that Hadoop administrators face in the real world.

It also familiarizes them with the latest updates and details of the platform.

This course is suitable for Administrators who are responsible for managing the Hadoop cluster and other related elements in Linux environments.

In this course, trainees will learn the leading methodologies to test Hadoop programs and tune and optimize the Hadoop performance.

It also teaches them to install Hadoop for HBase and helps in explore Mahout, MLib, and other frameworks.

Mode of Training

🏫 Classroom 💻 Live Online 🧪 Blended 👨‍👩‍👧‍👦 Private Group

What you will learn

  • Understand the benefits of distributed computing
  • Understand the Hadoop architecture (including HDFS and MapReduce)
  • Define administrator participation in Big Data projects
  • Plan, implement, and maintain Hadoop clusters
  • Deploy and maintain additional Big Data tools (Pig, Hive, Flume, etc.)
  • Plan, deploy and maintain HBase on a Hadoop cluster
  • Monitor and maintain hundreds of servers
  • Pinpoint performance bottlenecks and fix them
  • *This course has a 50% hands-on labs to 50% lecture ratio with engaging instruction, demos, group discussions, labs, and project work.

Who Should Attend This Course?

  • Experienced System Administrators who are responsible for maintaining a Hadoop cluster and its related components.

 

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📘 Introduction to Hadoop Administration Outline

  • Hadoop history and concepts
  • Ecosystem
  • Distributions
  • High level architecture
  • Hadoop myths
  • Hadoop challenges (hardware/software)
  • Selecting software and Hadoop distributions
  • Sizing the cluster and planning for growth
  • Selecting hardware and network
  • Rack topology
  • Installation
  • Multi-tenancy
  • Directory structure and logs
  • Benchmarking
  • Concepts (horizontal scaling, replication, data locality, rack awareness)
  • Nodes and daemons (NameNode, Secondary NameNode, HA Standby NameNode, and DataNode)
  • Health monitoring
  • Command-line and browser-based administration
  • Adding storage and replacing defective drives
  • Parallel computing before MapReduce: compare HPC versus Hadoop administration
  • MapReduce cluster loads
  • Nodes and Daemons (JobTracker and TaskTracker)
  • MapReduce UI walk through
  • MapReduce configuration
  • Job config
  • Job schedulers
  • Administrator view of MapReduce best practices
  • Optimizing MapReduce
  • Fool proofing MR: what to tell your programmers
  • YARN: architecture and use
  • Hardware monitoring
  • System software monitoring
  • 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

Still have questions?

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