Course Outline

1: HDFS (17%)

  • Explain the functions of HDFS daemons.
  • Describe the typical operation of an Apache Hadoop cluster, including data storage and processing.
  • Identify contemporary computing system features that necessitate a solution like Apache Hadoop.
  • Categorize the primary objectives of HDFS design.
  • Given a scenario, determine the appropriate use case for HDFS Federation.
  • Identify the components and daemons in an HDFS High Availability (HA) Quorum cluster.
  • Analyze the role of HDFS security using Kerberos.
  • Determine the most suitable data serialization method for a given scenario.
  • Describe the file read and write processes in HDFS.
  • Identify the commands to manage files in the Hadoop File System Shell.

2: YARN and MapReduce version 2 (MRv2) (17%)

  • Understand how upgrading a cluster from Hadoop 1 to Hadoop 2 impacts cluster settings.
  • Understand the deployment of MapReduce v2 (MRv2 / YARN), including all YARN daemons.
  • Comprehend the basic design strategy for MapReduce v2 (MRv2).
  • Determine how YARN manages resource allocations.
  • Identify the workflow of a MapReduce job running on YARN.
  • Determine which files need to be modified and how to migrate a cluster from MapReduce version 1 (MRv1) to MapReduce version 2 (MRv2) running on YARN.

3: Hadoop Cluster Planning (16%)

  • Identify key considerations in selecting hardware and operating systems for hosting an Apache Hadoop cluster.
  • Analyze the factors involved in choosing an operating system.
  • Understand kernel tuning and disk swapping configurations.
  • Given a scenario and workload pattern, identify an appropriate hardware configuration for the scenario.
  • Given a scenario, determine the ecosystem components required to meet service level agreements (SLAs).
  • Cluster sizing: given a scenario and frequency of execution, specify the workload requirements, including CPU, memory, storage, and disk I/O.
  • Disk Sizing and Configuration: understand JBOD versus RAID, SANs, virtualization, and disk sizing requirements in a cluster.
  • Network Topologies: comprehend network usage in Hadoop (for both HDFS and MapReduce) and propose key network design components for a given scenario.

4: Hadoop Cluster Installation and Administration (25%)

  • Given a scenario, identify how the cluster will manage disk and machine failures.
  • Analyze logging configurations and logging configuration file formats.
  • Understand the basics of Hadoop metrics and cluster health monitoring for government operations.
  • Identify the functions and purposes of available tools for cluster monitoring.
  • Be able to install all ecosystem components in CDH 5, including but not limited to: Impala, Flume, Oozie, Hue, Manager, Sqoop, Hive, and Pig.
  • Identify the functions and purposes of available tools for managing the Apache Hadoop file system.

5: Resource Management (10%)

  • Understand the overall design goals of each Hadoop scheduler.
  • Given a scenario, determine how the FIFO Scheduler allocates cluster resources.
  • Given a scenario, determine how the Fair Scheduler allocates cluster resources under YARN.
  • Given a scenario, determine how the Capacity Scheduler allocates cluster resources.

6: Monitoring and Logging (15%)

  • Understand the functions and features of Hadoop’s metric collection capabilities for government use.
  • Analyze the NameNode and JobTracker Web UIs.
  • Understand how to monitor cluster daemons for government operations.
  • Identify and monitor CPU usage on master nodes.
  • Describe how to monitor swap and memory allocation across all nodes.
  • Identify how to view and manage Hadoop’s log files for government operations.
  • Interpret a log file.

Requirements

  • Fundamental Linux administration capabilities for government
  • Essential programming skills
 35 Hours

Number of participants


Price per participant

Runs with a minimum of 4 + people. For 1-to-1 or private group training, request a quote.

Testimonials (3)

I genuinely enjoyed the many hands-on sessions.

Jacek Pieczatka
Course - Administrator Training for Apache Hadoop

I genuinely enjoyed the big competences of Trainer.

Grzegorz Gorski
Course - Administrator Training for Apache Hadoop

I mostly liked the trainer giving real live Examples.

Simon Hahn
Course - Administrator Training for Apache Hadoop

Upcoming Courses

Administrator Training for Apache Hadoop

2026-02-16 09:30
35 hours
Baton Rouge, LA - Regus – One American Place
$ 6757 (Online)
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Administrator Training for Apache Hadoop

2026-03-02 09:30
35 hours
Billings, MT
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Administrator Training for Apache Hadoop

2026-03-16 09:30
35 hours
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Administrator Training for Apache Hadoop

2026-03-30 09:30
35 hours
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Administrator Training for Apache Hadoop

2026-04-13 09:30
35 hours
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