Introduction to Hadoop Cluster Administration Course

Course Summary

The Introduction to Administering Hadoop Clusters training course is designed to demonstrate the key aspects of installing and maintaining a Hadoop cluster in various forms.

The course begins by examining how to operate the Hadoop Distributed File System (HDFS) file system and MapReduce I/O framework as complementary technologies. Next, it explores how to configure and monitor processes to manage storage and job tasks. The course concludes with an analysis of supplementing clusters with enhanced storage features and client tools.

Purpose

Learn how to set, configure, and administer Hadoop.

Audience

System administrators, developers, and DevOps engineers creating Big Data solutions using Hadoop.

Role

Software Developer - System Administrator

Skill Level

Intermediate

Style

Hack-a-thon - Learning Spikes - Workshops

Duration

4 Days

Related Technologies

Download

Productivity Objectives:

Describe the HDFS file system and MapReduce I/O frameworks
Configure and monitor storage management processes and tasks
Add network topology awareness to a cluster
Configure a highly-available storage system
Supplement clusters with enhanced storage features and client tools

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about our training

Real-World Content

Project-focused demos and labs using your tool stack and environment, not some canned "training room" lab.
Expert Practitioners

Industry experts with 15+ years of industry experience that bring their battle scars into the classroom.
Experiential Learning

More coding than lecture, coupled with architectural and design discussions.
Fully Customized

One-size-fits-all doesn't apply to training teams. That's where we come in!

What You'll Learn

In the Introduction to Administering Hadoop Clusters training course, you'll learn:

Hadoop Concepts
- Operate on large data sets
- Parallelize to improve performance
- Use large block sizes
- Distribute and replicate data
- Assign code to data
- Compensate for Node failures and recoveries
- Add Nodes for better performance
- Utilize virtualization for rapid deployment
Installing a Hadoop Cluster
- Understand the NameNode
- Understand the secondary NameNode
- Understand the Data Node
- Understand the JobTracker
- Understand the TaskTracker
Understanding the MapReduce Flow
- Map data
- Shuffle and sorting
- Reduce data
- Utilize the “Write Once, Read Many” approach
Reviewing Job Performance
- Interpret console output
- Navigate the JobTracker UI
- Use TaskTracker logs
Configuring Nodes
- Understand Hadoop property management
- Manage core properties
- Manage HDFS properties
- Manage MapReduce properties
- Manage worker properties
- Restrict job property changes
Supporting Federated & HA File Systems
- Restore NameNode services
- Protect NameNode metadata
- Use Federated NameNodes
- Understand the NameNode HA model
  - Configure a Federated HDFS system
  - Create defensive copies of NameNode metadata
Controlling Jobs and Resources
- Schedule jobs
- Understand the FairScheduler
- Orchestrate Workflows
Importing Legacy and Continuous Data
- Utilize Sqoop
- Use Flume
- Understand Hive, Impala, and HBase
Maintaining HDFS
- Check block integrity
- Balance data across nodes
- Use HDFS Safe Mode
- Address other HDFS systems
- Restrict Node additions
Installing Ecosystem Packages
- Install Pig
- Install Hive
- Review HBase requirements
Improving Hadoop Security
- Review authentication & authorization
- Analyze Hadoop’s authorization model
- Understand kerberos architecture
- Review Kerberos implementation options