|Date:||Tuesday, November 15, 2016|
6 Executive Park Dr., Atlanta, GA
ABOUT THE EVENT
This presentation will showcase a processing engine for ingesting real time streams of trades, bids and asks into streams at a high rate. The example application encompasses a multi-threaded Consumer microservice that indexes the trades by receiver and sender, example Spark code for querying the indexed streams at interactive speeds, enabling Spark SQL queries, and example code for persisting the streaming data to HBase tables.
IF YOU WILL JOIN IN PERSON - Please arrive at 6:30pm. We'll have soft drinks, water, and light snacks on-hand, so plan to eat dinner before you get there!
Emory has asked us to wrap up by 8:30pm since their building closes at 9:00. Directions to the location are here: http://www.ece.emory.edu/new_location/directions.html
IF YOU WILL JOIN IN REMOTELY - Please register now for the webcast at this link: http://bit.ly/ATLsparkWebcast There's a very short registration form, plus an opportunity to test your browser to make sure you can join when the event starts.
Paul Curtis is a Senior Field Enablement Engineer at MapR, where he provides pre- and post-sales technical support to MapR’s Worldwide Systems Engineering team. Prior to joining MapR, Paul served as Senior Operations Engineer for Unami, a startup founded to deliver on the promise of interactive TV for consumers, networks and advertisers. Previously, Paul was Systems Manager for Spiral Universe, a company providing school administration software as a service. He has also held senior sustaining engineer positions at Sun Microsystems, as well as enterprise account technical management positions for both Netscape and FileNet. Earlier in his career, Paul worked in application development for Applix, IBM Service Bureau, and Ticketron. His background extends back to the ancient personal computing days, having started his first full time programming job on the day the IBM PC was introduced.
On apache spark
- Free Hadoop Training: Spark Essentials - Apache Spark Essentials
- Getting Started with Apache Spark - ebook
- Apache Spark Use Case for Better Drug Discovery - Whiteboard Walkthrough - YouTube
- Apache Spark vs. Apache Flink - Whiteboard Walkthrough - YouTube
- Live Demo: Apache Spark on MapR with MLlib - YouTube
- Free Code Friday - Machine Learning with Apache Spark - YouTube
- MapR Sandbox VM download page: MapR Sandbox for Hadoop | MapR