Administrator Training for Apache Hadoop Training Course

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Course Language

This course is delivered in English.

Course Code

apacheh

Duration Duration

35 hours (usually 5 days including breaks)

Requirements Requirements

  • Basic Linux administration skills
  • Basic programming skills

Overview Overview

Audience:

The course is intended for IT specialists looking for a solution to store and process large data sets in a distributed system environment

Goal:

Deep knowledge on Hadoop cluster administration.

Course Outline Course Outline

1: HDFS (17%)

  • Describe the function of HDFS Daemons
  • Describe the normal operation of an Apache Hadoop cluster, both in data storage and in data processing.
  • Identify current features of computing systems that motivate a system like Apache Hadoop.
  • Classify major goals of HDFS Design
  • Given a scenario, identify appropriate use case for HDFS Federation
  • Identify components and daemon of an HDFS HA-Quorum cluster
  • Analyze the role of HDFS security (Kerberos)
  • Determine the best data serialization choice for a given scenario
  • Describe file read and write paths
  • Identify the commands to manipulate 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 affects cluster settings
  • Understand how to deploy MapReduce v2 (MRv2 / YARN), including all YARN daemons
  • Understand basic design strategy for MapReduce v2 (MRv2)
  • Determine how YARN handles resource allocations
  • Identify the workflow of MapReduce job running on YARN
  • Determine which files you must change and how in order to migrate a cluster from MapReduce version 1 (MRv1) to MapReduce version 2 (MRv2) running on YARN.

3: Hadoop Cluster Planning (16%)

  • Principal points to consider in choosing the hardware and operating systems to host an Apache Hadoop cluster.
  • Analyze the choices in selecting an OS
  • Understand kernel tuning and disk swapping
  • Given a scenario and workload pattern, identify a hardware configuration appropriate to the scenario
  • Given a scenario, determine the ecosystem components your cluster needs to run in order to fulfill the SLA
  • Cluster sizing: given a scenario and frequency of execution, identify the specifics for the workload, including CPU, memory, storage, disk I/O
  • Disk Sizing and Configuration, including JBOD versus RAID, SANs, virtualization, and disk sizing requirements in a cluster
  • 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%)

  • Given a scenario, identify how the cluster will handle disk and machine failures
  • Analyze a logging configuration and logging configuration file format
  • Understand the basics of Hadoop metrics and cluster health monitoring
  • Identify the function and purpose of available tools for cluster monitoring
  • Be able to install all the 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 overall design goals of each of Hadoop schedulers
  • 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 abilities
  • Analyze the NameNode and JobTracker Web UIs
  • Understand how to monitor cluster Daemons
  • Identify and monitor CPU usage on master nodes
  • Describe how to monitor swap and memory allocation on all nodes
  • Identify how to view and manage Hadoop’s log files
  • Interpret a log file

Guaranteed to run even with a single delegate!
Public Classroom Public Classroom
Participants from multiple organisations. Topics usually cannot be customised
From 10000EUR
(46)
Private Classroom Private Classroom
Participants are from one organisation only. No external participants are allowed. Usually customised to a specific group, course topics are agreed between the client and the trainer.
From 10000EUR
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Private Remote Private Remote
The instructor and the participants are in two different physical locations and communicate via the Internet
From 9050EUR
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SelfStudy SelfStudy
Self-study courses allow you to learn at your own pace on your own time. There is no live instructor involved. The participants use recorded video, quizzes and reading at their own convenience.
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The more delegates, the greater the savings per delegate. Table reflects price per delegate and is used for illustration purposes only, actual prices may differ.

Number of Delegates Public Classroom Private Classroom Private Remote
1 10000EUR 10000EUR 9050EUR
2 5750EUR 5700EUR 5225EUR
3 4333EUR 4267EUR 3950EUR
4 3625EUR 3550EUR 3313EUR
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