Thinking at Scale: Introduction to Hadoop
You know your data is big – you found Hadoop. What implications must you consider when working at this scale? This lecture addresses common challenges and general best practices for scaling with your data.
MapReduce and HDFS
These tools provide the core functionality to allow you to store, process, and analyze big data. This lecture “lifts the curtain” and explains how the technology works. You’ll understand how these components fit together and build on one another to provide a scalable and powerful system.
The Hadoop Ecosystem
An introduction to other projects surrounding Hadoop, which complete the greater ecosystem of available large- data processing tools.
Augmenting Existing Systems with Hadoop
Hadoop rarely replaces existing infrastructure, but rather enables you to do more with your data by providing a scalable batch processing system. This lecture helps you understand how it all fits together.
Aaron Kimball is a software engineer at Cloudera, Inc., the Commercial Hadoop company. Aaron is the principle developer of Sqoop, the SQL-to-Hadoop database import/export tool. Aaron has been working with Hadoop since early 2007, and contributes actively to its development. Through Cloudera, he additionally provides training to developers and system administrators working with Hadoop. Aaron holds a B.S. in Computer Science from Cornell University, and an M.S. in Computer Science and Engineering from the University of Washington.
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