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Cloudera Apache Hadoop Administration

The Cloudera Apache Hadoop Administration course provides in-depth training for administrators and IT professionals looking to deploy, manage, and maintain a Cloudera Hadoop cluster effectively. This hands-on course covers the core principles and tools necessary to configure, monitor, and troubleshoot a Hadoop Distributed File System (HDFS) and the YARN cluster manager in a Cloudera environment. By completing this course, participants will gain the skills needed to ensure a stable, scalable, and secure Hadoop ecosystem, making them proficient in managing big data clusters and supporting complex data analytics workloads.

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Schedule Learners Course Fee (Incl. of all Taxes) Register Your Interest
December 22nd - 25th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 32 Hours)
Guaranteed-to-Run
10% Off
$1,600
$1,440
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December 27th - 04th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 32 Hours)
10% Off
$1,600
$1,440
January 05th - 08th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 32 Hours)
20% Off
$1,600
$1,280
January 10th - 18th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 32 Hours)
20% Off
$1,600
$1,280
January 12th - 15th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 32 Hours)
20% Off
$1,600
$1,280
January 19th - 28th
06:00 AM - 10:00 PM (CST)
Live Virtual Classroom (Duration : 32 Hours)
20% Off
$1,600
$1,280
January 26th - 29th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 32 Hours)
Guaranteed-to-Run
20% Off
$1,600
$1,280

Course Prerequisites

  • Familiarity with Linux/Unix operating systems
  • Basic understanding of Hadoop and HDFS
  • Knowledge of SQL and database management concepts
  • Experience with cluster management tools like Cloudera Manager or Ambari is recommended, but not mandatory
  • Basic networking and security knowledge

Learning Objectives

By the end of this course, participants will be able to:

  • Understand Cloudera Hadoop architecture and components, and deploy/manage a Hadoop cluster
  • Configure and manage HDFS and YARN for optimized performance and reliability
  • Use Cloudera Manager for monitoring and managing cluster health and services
  • Implement security in Hadoop using Kerberos, Apache Ranger, and other security frameworks
  • Perform backup and disaster recovery strategies for Hadoop clusters
  • Troubleshoot and resolve common Hadoop administration issues and optimize cluster performance
  • Upgrade and maintain Cloudera Hadoop clusters efficiently
  • Integrate and optimize the Hadoop ecosystem with tools like Hive, HBase, and Spark

Target Audience

This course is ideal for Hadoop administrators, IT professionals, and big data engineers who are responsible for the deployment, configuration, and maintenance of Cloudera Hadoop clusters. The target audience includes:

  • Hadoop Administrators
  • System Administrators
  • Big Data Engineers
  • Cloudera Administrators
  • Data Engineers working with the Hadoop ecosystem
  • IT professionals responsible for Hadoop operations and infrastructure
  • Professionals interested in Cloudera and Hadoop management

Course Modules

  1. Introduction to Cloudera and Hadoop Ecosystem

    • Overview of Cloudera Hadoop and its components (HDFS, YARN, MapReduce)
    • Understanding the Hadoop architecture and Cloudera’s distribution of Hadoop
    • Exploring Cloudera Manager for cluster management
    • Core features of Hadoop and its role in big data processing

  2. Setting Up and Configuring a Cloudera Hadoop Cluster

    • Installing Cloudera Manager and setting up a Hadoop cluster
    • Configuring HDFS and YARN for optimized performance
    • Deploying Hadoop components and managing node configurations
    • Best practices for installing and configuring Hadoop components (Hive, HBase, Sqoop, etc.)

  3. Managing Hadoop Distributed File System (HDFS)

    • Understanding the architecture and functionality of HDFS
    • Configuring HDFS for high availability and fault tolerance
    • Monitoring and managing HDFS storage using Cloudera Manager
    • Troubleshooting HDFS issues like block replication and data corruption

  4. Managing and Tuning YARN Resource Management

    • Understanding YARN and its role in resource management
    • Configuring YARN Scheduler for optimal resource allocation
    • Tuning YARN settings for performance improvements
    • Monitoring and managing YARN applications and job submissions

  5. Cluster Monitoring and Maintenance with Cloudera Manager

    • Using Cloudera Manager for cluster monitoring, alerts, and health checks
    • Configuring cluster services and managing workloads
    • Setting up and maintaining Hadoop services with Cloudera Manager
    • Using the Cloudera Navigator for tracking metadata, data governance, and auditing

  6. Security in Cloudera Hadoop

    • Implementing Kerberos authentication in Hadoop clusters
    • Configuring Hadoop security for user and data access management
    • Integrating Apache Ranger and Apache Sentry for fine-grained security policies
    • Managing data encryption at rest and in transit within a Hadoop environment

  7. Backup, Recovery, and Disaster Recovery

    • Configuring and managing Hadoop backups for cluster data
    • Understanding disaster recovery strategies for Hadoop clusters
    • Performing HDFS backup and restoration
    • Implementing replication policies and disaster recovery planning

  8. Upgrading and Patching Cloudera Hadoop Clusters

    • Understanding the upgrade process for Cloudera Hadoop
    • Upgrading components and applying patches to Hadoop and other ecosystem services
    • Managing cluster versions and ensuring backward compatibility
    • Rolling upgrades and minimizing downtime during cluster upgrades

  9. Troubleshooting and Performance Tuning

    • Common issues faced during Hadoop administration and how to resolve them
    • Tuning Hadoop clusters for performance (I/O, memory, and CPU optimization)
    • Monitoring resource usage and configuring logs for troubleshooting
    • Analyzing job failures and performance bottlenecks using Cloudera Manager

  10. Optimizing Hadoop Ecosystem Integration

  • Managing integration with Apache Hive, Apache HBase, and Apache Spark
  • Tuning performance for data processing frameworks
  • Integrating Hadoop with external tools and data storage systems
  • Ensuring cross-component integration and optimal data flow across the ecosystem

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