Introduction to Hadoop Administration (TTDS6503)

3 Days

18 CPD hours

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.

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

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.
This 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. You will learn how to install, maintain, monitor, troubleshoot, optimize, and secure Hadoop.

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