Hadoop Boot Camp - Berlin

For Developers and Engineers

Hadoop Boot Camp - Berlin

In this two-day course participants will be given an extensive overview of the Hadoop system architecture. Once completed, you will be able to identify which problems Hadoop can solve effectively, and be proficient in developing applications for MapReduce.

When? August 27-August 28, 2009 8:00am to 4:00pm both days.

Where? Pullmann Schweizerhof, Budapester Straße 25, 
10787 Berlin, Germany Show in Google Maps

Fees? USD 1,800 (or local equivalent)

Fees: USD1,800 (or local equivalent) Any applicable taxes will be added. Go to the Eventbrite page and sign up for the class. You will be taken to the paypal page to pay your money! Discounts are available in case of groups of greater than five participants from any one organization/company/business; please contact Shirish@scaleunlimited.com for details.

Classroom materials: All materials will be in English.

Requirements: For our labs, please make sure you bring a Latop with:

  • min 1 GB RAM,
  • USB,
  • DVD R,
  • Unix compatible OS/Shell (Linux, OpenSolaris, Mac OS X) [if Win, then cygwin or preferrably a Linux VM],
  • Java IDE (Eclipse or IntelliJ are best options)

Hadoop Boot Camp Agenda (2 days)

Hadoop Conceptual and Physical Architecture
Students will learn the how and why of Hadoop through a thorough discussion of the Hadoop conceptual and physical architecture. Students will also learn to configure Hadoop for all three modes of operation.

Thinking in MapReduce with Common and Advanced Patterns
Students will learn the principles behind MapReduce and how to implement common MapReduce patterns. Advanced patterns are also introduced in depth. Lastly students are taught a way to model and design complex applications that can execute on MapReduce without having to think in MapReduce.

Hadoop API
Students will be introduced to all the core Hadoop API interfaces and classes. This will be reinforced though the development of increasingly complex Hadoop applications.

Hadoop MapReduce in Practice
Students will be able to interact with a distributed cluster in order to see how applications behave once distributed across nodes through the management interfaces.

Alternative Interfaces
Students will learn about all available high level interfaces for Hadoop and MapReduce. Some of these interfaces include PIG, HIVE, and Cascading.

Notes:

1. If you are unable to attend the class after registering, you are welcome to transfer the registration to another person. In case you cannot find another person, we will apply your fees towards the next class. Due to the expenses involved in setting up the class, we regret we cannot give refunds.

2. In case there are insufficient registrations, we reserve the right to cancel the class, and in such a case, all fees paid will be fully refunded.

 
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