Cascading is an open source workflow abstraction atop Hadoop and other Big Data frameworks, with a 5+ year history of large-scale Enterprise deployments. For example, half of Twitter's total compute uses this API, along with other large use cases at eBay, Etsy, Airbnb, LinkedIn, Apple, Climate, Nokia, Factual, Telefonica, etc. Cascading leverages some aspects of functional programming so that developers can create large-scale data pipelines which are robust and easier to operationalize. There are popular DSLs in Scala (Scalding) and Clojure (Cascalog), plus Jython, JRuby, etc. Recent support also implements DSLs for ANSI SQL (Lingual) and PMML (Pattern).

This talk will describe the technology and some of the large use cases for Cascading, plus show sample apps in Scalding, Cascalog, and go into examples of ANSI SQL with Lingual and PMML with Pattern. We'll also cover material about Mesos, a cluster scheduler akin to Google's "Borg" which is used at scale by Twitter, Airbnb, Box, etc.

Doors are open at 6:15, Talk starts at 7pm. Light snacks, beverages and brews will be available and will have a social hour following the talk.

Please RSVP via Eventbrite if you plan to attend: http://pdx-hadoop.eventbrite.com/

Talk will be led by Paco Nathan.

Paco Nathan is Chief Scientist at Mesosphere, a committer on Cascading, and an O'Reilly author for "Enterprise Data Workflows with Cascading". He is a recognized expert in Hadoop, R, cloud computing, distributed systems, machine learning, and predictive analytics, with 25+ years experience in the tech industry ranging from Bell Labs to early-stage start-ups. For the past 10+ years, Paco has led innovative Data teams building large-scale apps.

http://liber118.com/pxn/ @pacoid

Organized/Sponsored By: Aaron Betik, NIKE, Inc Global Technology Director, Consumer and Digital Analytics & BI