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Introduction to Hadoop Administration (TTDS6503)

Learn how to install, maintain, monitor, troubleshoot, optimize, and secure Hadoop.

Apache Hadoop is an open source framework for creating reliable and distributable compute clusters. Hadoop provides an excellent platform to process large unstructured or semi-structured data sets from multiple sources to dissect, classify, learn, and make suggestions for business analytics, decision support, and other advanced forms of machine intelligence.

This course will teach you how to install, maintain, monitor, troubleshoot, optimize, and secure Hadoop. Previous Hadoop experience is not required.

GK# 5122
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Who Should Attend?

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

What You'll Learn

Join an engaging hands-on learning environment, where you’ll:

  • 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.

Course Outline

Introduction

  • Hadoop history and concepts
  • Ecosystem
  • Distributions
  • High level architecture
  • Hadoop myths
  • Hadoop challenges (hardware/software)

Planning and installation

  • 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

HDFS operations

  • 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

MapReduce operations

  • 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

Advanced topics

  • 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