Arrow Electronics, Inc.

Apache Hadoop Fundamentals on Power Systems

CÓDIGO: QZD10G

DURACIÓN: 16 Hours (2 días)

Precio: €1.200,00

Descripción

This course describes the concepts and implementation details to install, configure, and implement Hadoop on IBM Power Systems. The course covers planning for a Hadoop installation, customizing the environment, management, and using Hadoop. Hands-on exercises reinforce the lecture and give the students the experience of installing and configuring Hadoop on a Power Systems-based environment.

 

Objetivos

After completing this course, you should be able to:

• Distinguish between Big Data and Data Analytics
• Summarize the architectural components, resources, terminology and capabilities of Hadoop
• Apply both planning and requirement processes for installation of Hadoop
• Carry out the steps to configure, startup and shutdown a Hadoop cluster with the appropriate web user interfaces and administration tasks
• Implement the proper administration commands, use of safe mode and steps to add and remove DataNodes from a Hadoop Cluster

 

Público

Anyone responsible for implementing and managing Hadoop on IBM Power Systems. The audience for this training includes the following:

• Hadoop administrators
• POWER technical support individuals
• POWER system administrators
• POWER system engineers
• POWER system architects

Requisitos Previos

Students must already know the basics of configuring and managing a Virtual I/O server, virtual devices and use of the HMC to manage partitions. This prerequisite can be met by attending the following courses:
• (LX21G) - PowerLinux Administration (LX21G)

Additional course information and roadmaps can be found at:

www.ibm.com/training

Programa

Lecture:

• Unit 1 - Introduction to Data Analytics
• Unit 2 - Introduction to Hadoop
• Unit 3 - Hadoop planning and implementation
• Unit 4 - Hadoop configuration management
• Unit 5 - Hadoop administration


Labs:

• Exercise 1 - Introduction to the lab environment
• Exercise 2 - Hadoop planning and implementation
• Exercise 3 - Hadoop configuration management
• Exercise 4 - Hadoop administration

Fechas Programadas