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Course Outline
1: HDFS (17%)
- Explain the roles of HDFS Daemons
- Describe the standard operation of an Apache Hadoop cluster, covering both data storage and processing.
- Identify the computing system features that drive the need for a system like Apache Hadoop.
- Outline the primary objectives of HDFS design.
- In specific scenarios, determine the appropriate use cases for HDFS Federation.
- Identify the components and daemons within an HDFS HA-Quorum cluster.
- Analyze the role of HDFS security, specifically Kerberos.
- Select the optimal data serialization method for a given scenario.
- Describe the pathways for file reading and writing.
- Recognize the commands used to manipulate files in the Hadoop File System Shell.
2: YARN and MapReduce version 2 (MRv2) (17%)
- Comprehend how upgrading a cluster from Hadoop 1 to Hadoop 2 impacts cluster configurations.
- Learn how to deploy MapReduce v2 (MRv2 / YARN), including all associated YARN daemons.
- Understand the fundamental design strategy of MapReduce v2 (MRv2).
- Determine how YARN manages resource allocation.
- Trace the workflow of a MapReduce job running on YARN.
- Identify which files require modification and the necessary changes to migrate a cluster from MapReduce version 1 (MRv1) to MapReduce version 2 (MRv2) on YARN.
3: Hadoop Cluster Planning (16%)
- Key considerations when selecting hardware and operating systems to host an Apache Hadoop cluster.
- Evaluate options for selecting an operating system.
- Grasp kernel tuning and disk swapping mechanisms.
- Given a scenario and workload pattern, identify the hardware configuration suitable for that situation.
- For a given scenario, determine the ecosystem components required for your cluster to meet SLAs.
- Cluster sizing: Based on a scenario and execution frequency, identify workload specifics, including CPU, memory, storage, and disk I/O.
- Disk Sizing and Configuration, covering JBOD versus RAID, SANs, virtualization, and cluster disk sizing requirements.
- Network Topologies: Understand network usage in Hadoop (for both HDFS and MapReduce) and propose or identify key network design components for a given scenario.
4: Hadoop Cluster Installation and Administration (25%)
- In a given scenario, identify how the cluster manages disk and machine failures.
- Analyze logging configurations and the format of logging configuration files.
- Understand the fundamentals of Hadoop metrics and cluster health monitoring.
- Identify the function and purpose of available cluster monitoring tools.
- Install all ecosystem components in CDH 5, including (but not limited to): Impala, Flume, Oozie, Hue, Manager, Sqoop, Hive, and Pig.
- Identify the function and purpose of available tools for managing the Apache Hadoop file system.
5: Resource Management (10%)
- Understand the overarching design goals of each Hadoop scheduler.
- In a given scenario, determine how the FIFO Scheduler allocates cluster resources.
- In a given scenario, determine how the Fair Scheduler allocates cluster resources under YARN.
- In a given 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.
- Analyze the NameNode and JobTracker Web UIs.
- Learn how to monitor cluster Daemons.
- Identify and monitor CPU usage on master nodes.
- Describe methods for monitoring swap and memory allocation across all nodes.
- Identify how to view and manage Hadoop’s log files.
- Interpret log files.
Requirements
- Foundational skills in Linux administration
- Basic programming proficiency
35 Hours
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 6500 € + VAT*
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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.
