Introduction to Hadoop Administration

Gain the Core Skills Required to Install, Maintan, Monitor, Troubleshoot, Optimize and Secure Hadoop

TTDS6503

Introductory

3 Days

Course Overview

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

Introduction to Hadoop Administration is an introductory-level, hands-on lab-intensive course geared for the administrator (new to Hadoop) who is charged with maintaining a Hadoop cluster and its related components. Attending students will learn how to install, maintain, monitor, troubleshoot, optimize, and secure Hadoop.

Course Objectives

Working within in an engaging, hands-on learning environment, guided by our expert team, attendees will learn to:

  • 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

Need different skills or topics?  If your team requires different topics or tools, additional skills or custom approach, this course may be further adjusted to accommodate.  We offer additional Big Data / Data Science, Hadoop, development, programming, analytics, Python/R, and other related topics that may be blended with this course for a track that best suits your needs.

Course Prerequisites

This is an introductory-level course designed to teach experienced systems administrators how to install, maintain, monitor, troubleshoot, optimize, and secure Hadoop. Previous Hadoop experience is not required.

We offer a wide variety of Big Data, Analytics, Data Science, Hadoop, AI / Machine Learning, Python / R / Scala / Java Programming and other related courses that can advance your skills to the next level after this course. Please see the Related Courses tab for specific Pre-Requisite courses, Related Courses or Follow On training options. Our team will be happy to help you with recommendations for next steps in your Learning Journey.

Course Agenda

Please note that this list of topics is based on our standard course offering, evolved from typical industry uses and trends. We will work with you to tune this course and level of coverage to target the skills you need most.  

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, 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, 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

Course Materials

Student Materials: Each participant will receive a Student Guide with course notes, code samples, software tutorials, step-by-step written lab instructions, diagrams and related reference materials and resource links. Students will also receive the project files (or code, if applicable) and solutions required for the hands-on work

Hands-On Setup Made Simple! Our dedicated tech team will work with you to ensure our ‘easy-access’ cloud-based course environment is accessible, fully-tested and verified as ready to go well in advance of the course start date, ensuring a smooth start to class and effective learning experience for all participants. Please inquire for details and options.

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