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Event Details
Introduction to Cascading
Creating complex data processing workflows with raw Hadoop is painful, tedious, and error-prone. This 1/2 day class shows you how to use the open source Cascading API to quickly create reliable, scalable, high-performance data processing workflows on top of Hadoop. We combine lab exercises and real-world examples to reinforce lecture content, so that by the end of the day you're ready to start solving Big Data problems using Cascading.
Agenda
- Overview
- Thinking in Cascading
- Log Processing Lab
- Built-in and Custom Operations
- Grouping and Joining
- Taps and Schemes (Text, Sequence files, Solr)
- Cascading Summary
Requirements:
- Reliable, fast (1.5Mbps or better) Internet connection.
- Up-to-date web browser
Scale Unlimited Classes
Classes include virtual lab environments, interactive lectures using Adobe Connect and teleconference/VoIP, personalized PDFs of lecture materials, and access to post-class support via a moderated mailing list.
Instructor
All of our classes are taught by active developers with deep, hands-on experience solving real-world problems using Hadoop, Cascading, Solr, Tika, and other powerful open source solutions. Instructor Ken Krugler has been a software developer, consultant, trainer and entrepreneur for over 20 years. Previously he started Krugle in 2005, as a pioneer in code search and an early adopter/supporter of Nutch, Hadoop, Lucene and Solr. He is a committer for the Apache Tika project, an author of one of the new Lucene In Action use cases, and an expert in web crawling and data mining.