Thursday, June 11, 2009 from 9:00 AM - 6:00 PM (PT)
This year, we are excited to offer training as part of the 2009 Hadoop Summit. On June 11th, the day after the Hadoop Summit, attendees may choose to attend either basic or advanced training.
The basic session is appropriate for users who are new to Hadoop, while the advanced training is designed to help existing users get the most out of Hadoop and related tools.
Cloudera training staff will lead a majority of the sessions, while Yahoo! will lead sessions on Apache Pig.
2009 Hadoop Summit Training Agenda
| Basic Training |
Advanced Training |
| Instructors: Alex Loddengaard (Cloudera) | Instructors: Aaron Kimball (Cloudera), Alan Gates (Y!) |
| Thinking at Scale: Introduction to Hadoop and Big Data | Overview: Augmenting existing systems with Hadoop |
| MapReduce and HDFS | Importing Data into Hadoop |
| Exercise: Getting Started with Hadoop | Exercise: Importing existing databases with Sqoop |
| The Hadoop Ecosystem | Introduction to Pig |
| Programming with Hadoop | Exercise: Working with Pig |
| Exercise: Writing MapReduce Programs | Introduction to Hive - A Data Warehouse for Hadoop |
| Hadoop Deployment and Management | Exercise: Working with Hive |
| Walkthrough: Deployment on Local Servers and Amazon EC2 | Best Practices for Data Processing Pipelines |
If you have not already registered for the 2009 Hadoop Summit, please register now.
Cloudera brings Hadoop to enterprise users. We provide a certified distribution based on the most recent stable release from Apache, online and live training, as well as commercial support.
Yahoo's support of Hadoop extends back to 2004. Yahoo! started with a 20-node cluster in March 2006, increased the size to 200 nodes a month later, and has since continued to invest in grid computing. In Sept. 2008, Yahoo! constructed the largest Hadoop cluster to date with 4000 nodes.
Yahoo! has a history of supporting open source software including Apache, PHP, MySQL, Zimbra, and most recently, YUI. In contributing to the Hadoop project, Yahoo! hopes to make Hadoop's "scalable, economical, efficient, and reliable" feature-set available to an ever-expanding community of users
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