Video Description
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 howto architect and implement a complete solution with Hadoop.
Table of Contents
- Introduction to Clickstream Case Study 00:11:19
- Requirements 00:08:04
- Data Modeling 00:14:55
- Data Ingest 00:16:16
- Data Processing Engines - Part 1 00:16:23
- Data Processing Engines - Part 2 00:10:59
- Data Processing Patterns 00:09:32
- Orchestration 00:14:34
- Putting It All Together 00:03:08
- Demo 00:21:47
- Q&A 00:24:35
Product Information
- Title: Architectural Considerations for Hadoop Applications
- Author(s):
- Release date: March 2015
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491923313