2015
O'Reilly Media
Gwen Shapira, Mark Grover, Ted Malaska, Jonathan Seid
2:30
English

Implementing solutions with Apache Hadoop requires understanding not just Hadoop, but a broad range of related projects in the Hadoop ecosystem such as Hive, Pig, Oozie, Sqoop, and Flume. The good news is that there's an abundance of materials - books, web sites, conferences, etc. - for gaining a deep understanding of Hadoop and these related projects. The bad news is there's still a scarcity of information on how to integrate these components to implement complete solutions. In this video we'll walk through an end-to-end case study of a clickstream analytics engine to provide a concrete example of how to architect and implement a complete solution with Hadoop.

01. Architectural Considerations For Hadoop Applications
0101 Introduction To Clickstream Case Study
0102 Requirements
0103 Data Modeling
0104 Data Ingest
0105 Data Processing Engines - Part 1
0106 Data Processing Engines - Part 2
0107 Data Processing Patterns
0108 Orchestration
0109 Putting It All Together
0110 Demo
0111 Q And A

Download File Size:657.28 MB

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