Administration of Hadoop Cluster Training

The training sessions are usually held in German. Please contact us if you are interested in training sessions in English.

Setting up and operating Apache Hadoop Clusters is a complex process. This training course teaches this knowledge in a very practical way.

Hadoop Training at inovex

Target audience: Linux administrators, software developers (with basic Linux Skills)
Length: 3 days 
Dates: Available upon request
Times: 9 am – 5 pm 
Number of participants: min. 3, max. 12 
Price: 1,800 euros plus VAT

Over the past few years, Hadoop has become the standard for big data systems. Setting up and operating Hadoop clusters is, however, a fundamentally more complex task than, for example, setting up and operating web server farms or even traditional database clusters. The high level of integration of the Hadoop nodes and the “eventual consistency” paradigm require in-depth knowledge of the architecture and the essential processes involved in Hadoop clusters in order to ensure highly available, high-performance, secure operation. 

This training covers this content in a very practical way. During the course, the participants set up their own Hadoop cluster on which they then practice typical scenarios, such as integrating third-party systems, creating a backup, or handling a malfunctioning node. 

 

Agenda: 

  • Hadoop basics, infrastructure and architecture
  • Setup and configuration of a Hadoop cluster
  • Hadoop security basics
  • High availability for Hadoop clusters
  • Backup and recovery strategies for Hadoop clusters
  • Introduction to the ecosystem and integration of frequently used components
  • Monitoring and ongoing optimisation of a Hadoop cluster
  • Hadoop logfile analysis

 

Note:

  • The course fees include training materials, lunches, drinks and snacks.
  • Participants must bring their own laptops to the training sessions.

 

Instructor:

Hans-Peter Zorn is a big data scientist at inovex. He specialises in big data architectures, Hadoop security, machine learning and data-driven products. Previously, he worked at the UKP Lab at the Technical University of Darmstadt, where he used Hadoop to analyse large text volumes.