This course is best suited to systems administrators and IT managers who have basic Linux experience. Prior knowledge of Apache Hadoop is not required.

There are no prerequisites for this course.

Through instructor-led discussion and interactive, hands-on exercises, participants will navigate the Hadoop ecosystem, learning topics such as:

• Cloudera Manager features that make managing your clusters easier, such as aggregated logging, configuration management, resource management, reports, alerts, and service management
• Configuring and deploying production-scale clusters that provide key Hadoop-related services, including YARN, HDFS, Impala, Hive, Spark, Kudu, and Kafka
• Determining the correct hardware and infrastructure for your cluster
• Proper cluster configuration and deployment to integrate with the data center
• Ingesting, storing, and accessing data in HDFS, Kudu, and cloud object stores such as Amazon S3
• How to load file-based and streaming data into the cluster using Kafka and Flume
• Configuring automatic resource management to ensure service-level agreements are met for multiple users of a cluster
• Best practices for preparing, tuning, and maintaining a production cluster
• Troubleshooting, diagnosing, and solving cluster issues

The Cloudera Enterprise Data Hub

• Cloudera Enterprise Data Hub
• CDH Overview
• Cloudera Manager Overview
• Hadoop Administrator Responsibilities

Installing Cloudera Manager and CDH

• Cluster Installation Overview
• Cloudera Manager Installation
• CDH Installation
• CDH Cluster Services

Configuring a Cloudera Cluster

• Overview
• Configuration Settings
• Modifying Service Configurations
• Configuration Files
• Managing Role Instances
• Adding New Services
• Adding and Removing Hosts

Hadoop Distributed File System

• Overview
• HDFS Topology and Roles
• Edit Logs and Checkpointing
• HDFS Performance and Fault Tolerance
• HDFS and Hadoop Security Overview
• Web User Interfaces for HDFS
• Using the HDFS Command Line Interface
• Other Command Line Utilities

HDFS Data Ingest

• Data Ingest Overview
• File Formats
• Ingesting Data using File Transfer or REST Interfaces
• Importing Data from Relational Databases with Apache Sqoop
• Ingesting Data From External Sources with Apache Flume
• Best Practices for Importing Data

Hive and Impala

• Apache Hive
• Apache Impala

YARN and MapReduce

• YARN Overview
• Running Applications on YARN
• Viewing YARN Applications
• YARN Application Logs
• MapReduce Applications
• YARN Memory and CPU Settings

Apache Spark

• Spark Overview
• Spark Applications
• How Spark Applications Run on YARN
• Monitoring Spark Applications

Planning Your Cluster

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

Advanced Cluster Configuration

• Configuring Service Ports
• Tuning HDFS and MapReduce
• Enabling HDFS High Availability

Managing Resources

• Configuring cgroups with Static Service Pools
• The Fair Scheduler
• Configuring Dynamic Resource Pools
• Impala Query Scheduling

Cluster Maintenance

• Checking HDFS Status
• Copying Data Between Clusters
• Rebalancing Data in HDFS
• HDFS Directory Snapshots
• Upgrading a Cluster

Monitoring Clusters

• Cloudera Manager Monitoring Features
• Health Tests
• Events and Alerts
• Charts and Reports
• Monitoring Recommendations

Cluster Troubleshooting

• Overview
• Troubleshooting Tools
• Misconfiguration Examples
• Essential Points

Installing and Managing Hue

• Overview
• Managing and Configuring Hue
• Hue Authentication and Authorization

Security

• Hadoop Security Concepts
• Hadoop Authentication Using Kerberos
• Hadoop Authorization
• Hadoop Encryption
• Securing a Hadoop Cluster

Apache Kudu

• Kudu Overview
• Architecture
• Installation and Configuration
• Monitoring and Management Tools

Apache Kafka

• What Is Apache Kafka?
• Apache Kafka Overview
• Apache Kafka Cluster Architecture
• Apache Kafka Command Line Tools
• Using Kafka with Flume

Object Storage in the Cloud

• Object Storage
• Connecting Hadoop to Object Storage