Wednesday, August 21, 2013
09:00 AM - 12:00 PM
|Level: ||Technical - Introductory|
The tutorial will cover Hadoop basics and discuss best practices using Hadoop in enterprises dealing with large data sets. We will look into the current data problems you are dealing with and potential use cases of using Hadoop in your infrastructure. The presentation covers the Hadoop architecture and its main components: Hadoop Distributed File System (HDFS) and MapReduce. We will present case studies on how other enterprises are using Hadoop and look into what it takes to get Hadoop up and running in your environment.
Two case studies will be presented covering near-real time data processing scenario and Hadoop cluster implementation for large clusters (2,000 - 4,000 nodes). The near-real time case study can be used as guidance for building the infrastructure of near-real time architecture. All components used in architecture are open sourced under Apache license and will provide cost effective solution for solving big data problems
By attending this tutorial, the attendees will be able to:
- Understand Hadoop main components and Architecture
- Be comfortable working with Hadoop Distributed File System
- Understand MapReduce abstraction and how it works
- Understand components of a MapReduce job
- Know best practices of using Hadoop in the enterprise
Serge Blazhievsky is an experienced developer and architect with a rich background in C++/Java and distributed systems. His latest venture, LiveOps, Inc. uses Hadoop infrastructure for all reporting needs. LiveOps Hadoop framework was completely designed by him and satisfies very strict performance and availability requirements. Serge's prior ventures include Attributor, Inc. where he designed Hadoop infrastructure used for Internet crawling and web-page analysis. He holds a Masters Degree in Computer Engineering from Santa Clara University, CA, located in the heart of Silicon Valley. Serge is a regular attendee and contributor to various Hadoop conferences including Hadoop User Group at Yahoo, the creator of Hadoop.