Architectural Considerations for Hadoop Applications: Using Clickstream Analytics As an End-to-End Example

Implementing solutions with Apache Hadoop requires understanding notjust Hadoop, but a broad range of related projects in the Hadoopecosystem such as Hive, Pig, Oozie, Sqoop, and Flume. The good news isthat there’s an abundance of materials – books, web sites,conferences, etc. – for gaining a deep understanding of Hadoop andthese related projects. The bad news is there’s still a scarcity ofinformation on how to integrate these components to implement completesolutions. In this video we’ll walk through an end-to-end case studyof a clickstream analytics engine to provide a concrete example of howto architect and implement a complete solution with Hadoop.

Tables of Contents:
– Introduction to Clickstream Case Study 11m 19s
– Requirements 08m 04s
– Data Modeling 14m 55s
– Data Ingest 16m 16s
– Data Processing Engines – Part 1 16m 23s
– Data Processing Engines – Part 2 10m 59s
– Data Processing Patterns 09m 31s
– Orchestration 14m 34s
– Putting It All Together 03m 07s
– Demo 21m 46s
– Q&A 24m 35s

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