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

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

English | March 2015 | mp4 | H264 1280x720 | AAC 2 ch | 2 hrs 31 min | 676 MB

eLearning

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.

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

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

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

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