Learn to deploy, configure, and manage Cloudera’s Apache Hadoop implementation and HDFS.

In this interactive, hands-on Apache Hadoop course, you will gain a comprehensive understanding of all the steps necessary to operate and maintain a Hadoop cluster. Covering topics from installation and configuration through load balancing and tuning, this course is the best preparation for the real-world challenges faced by Hadoop administrators.

This course covers concepts addressed on the Cloudera Certified Administrator for Apache Hadoop (CCAH) exam.

Course Duration

3 day

What You’ll Learn

  • The internals of MapReduce and HDFS and how to build Hadoop architecture
  • Proper cluster configuration and deployment to integrate with systems and hardware in the data center
  • How to load data into the cluster from dynamically generated files using Flume and from RDBMS using Sqoop
  • Configuring the FairScheduler to provide service-level agreements for multiple users of a cluster
  • Installing and implementing Kerberos-based security for your cluster
  • Best practices for preparing and maintaining Apache Hadoop in production
  • Troubleshooting, diagnosing, tuning, and solving Hadoop issues

Who Needs to Attend

System administrators and others responsible for managing Apache Hadoop clusters in production or development environments


This course is designed for system administrators and IT managers who have basic Linux systems administration experience. Prior knowledge of Hadoop is not required.

Follow-On Courses

There are no follow-ons for this course.

Certification Programs and Certificate Tracks

This course is part of the following programs or tracks:

  • CCAH: Cloudera Certified Administrator for Apache Hadoop (CDH4)

Course Outline

1. The Case for Apache Hadoop

  • Why Hadoop?
  • A Brief History of Hadoop
  • Core Hadoop Components
  • Fundamental Concepts


  • HDFS Features
  • Writing and Reading Files
  • NameNode Considerations
  • HDFS Security
  • Using the NameNode Web UI
  • Using the Hadoop File Shell

3. Getting Data into HDFS

  • Ingesting Data from External Sources with Flume
  • Ingesting Data from Relational Databases with Sqoop
  • REST Interfaces
  • Best Practices for Importing Data

4. MapReduce

  • Features of MapReduce
  • Basic Concepts
  • Architectural Overview
  • MapReduce Version 2
  • Failure Recovery
  • Using the JobTracker Web UI

5. Planning Your Hadoop Cluster

  • General Planning Considerations
  • Choosing the Right Hardware
  • Network Considerations
  • Configuring Nodes
  • Planning for Cluster Management

6. Hadoop Installation and Initial Configuration

  • Deployment Types
  • Installing Hadoop
  • Specifying the Hadoop Configuration
  • Performing Initial HDFS Configuration
  • Performing Initial MapReduce Configuration
  • Log File Locations

7. Installing and Configuring Hive, Impala, and Pig

  • Hive
  • Impala
  • Pig

8. Hadoop Clients

  • Installing and Configuring Hadoop Clients
  • Installing and Configuring Hue
  • Hue Authentication and Configuration

9. Cloudera Manager

  • The Motivation for Cloudera Manager
  • Cloudera Manager Features
  • Standard and Enterprise Versions
  • Cloudera Manager Topology
  • Installing Cloudera Manager
  • Installing Hadoop Using Cloudera Manager
  • Performing Basic Administration Tasks
  • Using Cloudera Manager

10. Advanced Cluster Configuration

  • Advanced Configuration Parameters
  • Configuring Hadoop Ports
  • Explicitly Including and Excluding Hosts
  • Configuring HDFS for Rack Awareness
  • Configuring HDFS High Availability

11. Hadoop Security

  • Why Hadoop Security Is Important
  • Hadoop’s Security System Concepts
  • What Kerberos Is and How it Works
  • Securing a Hadoop Cluster with Kerberos

12. Managing and Scheduling Jobs

  • Managing Running Jobs
  • Scheduling Hadoop Jobs
  • Configuring the FairScheduler

13. Cluster Maintenance

  • Checking HDFS Status
  • Copying Data Between Clusters
  • Adding and Removing Cluster Nodes
  • Rebalancing the Cluster
  • NameNode Metadata Backup
  • Cluster Upgrading

14. Cluster Monitoring and Troubleshooting

  • General System Monitoring
  • Managing Hadoop’s Log Files
  • Monitoring Hadoop Clusters
  • Common Troubleshooting Issues

15. Conclusion


Throughout the course, you’ll participate in hands-on labs to help build your knowledge and apply the concepts discussed.