Cloudera Administrator Training for Apache Hadoop

• System Administrators
• IT Managers
• Application Support Professionals

• Basic Linux experience
• Prior knowledge of Apache Hadoop is not required

By the end of this course, you will learn:

• Cloudera Manager features that make managing your clusters easier, such as aggregated logging, configuration management, resource management, reports, alerts and service management
• The internals of YARN, MapReduce, Spark, and HDFS
• Determining the correct hardware and infrastructure for your cluster
• Proper cluster configuration and deployment to integrate with 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
• Best practices for preparing and maintaining Apache Hadoop in production
• Troubleshooting, diagnosing, tuning, and solving Hadoop issues

Cloudera University’s four-day administrator training course for Apache Hadoop provides you with a comprehensive understanding of all the steps necessary to operate and maintain a Hadoop cluster. From installation and configuration through load balancing and tuning, Cloudera’s training course is the best preparation for the real-world challenges faced by Hadoop administrators.

Module 1: The Case for Apache Hadoop

• Why Hadoop?
• Fundamental Concepts
• Core Hadoop Components

Module 2: Hadoop Cluster Installation

• Rationale for a Cluster Management Solution
• Cloudera Manager Features
• Cloudera Manager Installation
• Hadoop (CDH) Installation

Module 3: The Hadoop Distributed File System (HDFS)

• HDFS Features
• Writing and Reading Files
• NameNode Memory Considerations
• Overview of HDFS Security
• Web UIs for HDFS
• Using the Hadoop File Shell

Module 4: MapReduce and Spark on YARN

• The Role of Computational Frameworks
• YARN: The Cluster Resource Manager
• MapReduce Concepts
• Apache Spark Concepts
• Running Computational Frameworks on YARN
• Exploring YARN Applications Through the Web UIs, and the Shell
• YARN Application Logs

Module 5: Hadoop Configuration and Daemon Logs

• Cloudera Manager Constructs for Managing Configurations
• Locating Configurations and Applying Configuration Changes
• Managing Role Instances and Adding Services
• Configuring the HDFS Service
• Configuring Hadoop Daemon Logs
• Configuring the YARN Service

Module 6: 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

Module 7: Planning Your Hadoop Cluster

• General Planning Considerations
• Choosing the Right Hardware
• Virtualization Options
• Network Considerations
• Configuring Nodes

Module 8: Installing and Configuring Hive, Impala and Pig

• Hive
• Impala
• Pig

Module 9: Hadoop Clients Including Hue

• What Are Hadoop Clients?
• Installing and Configuring Hadoop Clients
• Installing and Configuring Hue
• Hue Authentication and Authorization

Module 10: Advanced Cluster Configuration

• Advanced Configuration Parameters
• Configuring Hadoop Ports
• Configuring HDFS for Rack Awareness
• Configuring HDFS High Availability

Module 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
• Other Security Concepts

Module 12: Managing Resources

• Configuring cgroups with Static Service Pools
• The Fair Scheduler
• Configuring Dynamic Resource Pools
• YARN Memory and CPU Settings
• Impala Query Scheduling

Module 13: Cluster Maintenance

• Checking HDFS Status
• Copying Data Between Clusters
• Adding and Removing Cluster Nodes
• Rebalancing the Cluster
• Directory Snapshots
• Cluster Upgrading

Module 14: Cluster Monitoring and Troubleshooting

• Cloudera Manager Monitoring Features
• Monitoring Hadoop Clusters
• Troubleshooting Hadoop Clusters
• Common Misconfigurations