Using In-Memory, Data-Parallel Computing for Operational Intelligence
This talk will describe the use of in-memory, data-parallel computing to obtain operational intelligence in several scenarios, including financial services, ecommerce, and cable-based media. It will show both how an in-memory model is constructed and how data-parallel analysis can be implemented to provide immediate feedback.
Performance results from a simulation of 10M live cable-TV set-top boxes will illustrate how this technique was used to correlate and enrich 25K events per second and complete a parallel analysis every 10 seconds on a cluster of commodity servers.
The talk also will compare the use of in-memory computing to the more traditional 'big data' model popularized by Hadoop MapReduce. It also will examine simplifications offered by this approach over directly analyzing incoming event streams from an operational system using complex event processing or Storm. Lastly, it will explain key requirements of the in-memory computing platform, in particular real-time updating of individual objects and high availability, and compare these requirements to the design goals for stream processing in Spark.
Dr. William L. Bain is Founder and CEO of ScaleOut Software, Inc. Bill has a Ph.D. in electrical engineering/parallel computing from Rice University, and he has worked at Bell Labs research, Intel, and Microsoft.
Bill founded and ran three start-up companies prior to joining Microsoft. In the most recent company (Valence Research), he developed a distributed Web load-balancing software solution that was acquired by Microsoft and is now called Network Load Balancing within the Windows Server operating system.
Bill holds several patents in computer architecture and distributed computing. As a member of the Seattle-based Alliance of Angels, Bill is actively involved in entrepreneurship and the angel community