Next Meetup

Finding Cost Efficiencies with Spark & AWS
**** PRE-REGISTER HERE: Please complete this simple form to expedite the sign-in process. We will be on the 5th Floor. Please join us, HatchIT and Gravy Analytics for this FREE event to hear how a Spark and AWS architecture offers great opportunities for cost savings. *** ABSTRACT ===================== Gravy Analytics is a venture-backed location intelligence company. In support of our data product and service offerings, we process billions of signals against millions of place and event-related data objects that are created and maintained by Gravy. The data is handled by several sequential Spark jobs that are coordinated by an orchestration layer. To do this processing in a cost-effective manner, we use AWS EMR Spot instances. AWS Spot instances provide significant cost savings but present their own unique challenges. We’ll explore these challenges in detail, and review how we’ve addressed these and other technical obstacles that arise with sudden changes to our incoming data supply. *** SPEAKERS ===================== Guy DeCorte - Bio Guy is Founder and Chief Technology Officer at Gravy Analytics. As CTO, Guy leads a talented team of professionals developing innovative data products and related services. This includes processing billions of signals a day, acquiring, improving and managing millions of high value data assets, and delivering real-time and batch data products. He has spent much of his career working with engineering teams to develop new software and data products at leading companies, including CSC and AT&T. Guy splits his time between Central Oregon and Northern Virginia. His interests range from anthropology & history to research on machine learning techniques that emulate the way humans learn from 0-5 years old. Nathan Case – Bio Nathan is the lead engineer for Gravy Analytics’ Core Platform team. In this role, Nathan is responsible for processing the billions of signal and device-related information received each day in support of Gravy’s data products and real-time services. To do so, Nathan and his team rely on large Spark jobs, Java, Scala, S3, DynamoDB, Snowflake, MySQL, data mining, and geospatial and heuristic algorithms. A key member of the Gravy team since 2014, Nathan has helped to architect, expand and optimize Gravy's core platform. He also works closely with the team charged with creating strategies underpinning Gravy's continued growth in data and product offerings. Outside of the office, Nathan’s many interests include 3D printing, amphibians and fish, cooking, and woodworking. ====================== Parking Options: WeWork Directions: ====================== SPARK + AI SUMMIT EUROPE DISCOUNT CODE As you know Spark + AI Summit Europe 2018 will be at the ExCeL Exhibition Centre, London, from Oct 2-4th. We are providing members of your meetup organization a special 20% discount code DCMU ===================== "WeWork is the platform for creators. We provide the space, community and services you need to create your life’s work. To learn more send an email to [masked].”

WeWork Tysons

1775 Tysons Blvd · tysons, VA

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    Past Meetups (44)

    What we're about

    This is an interactive meetup for Washington DC, Virginia and Maryland users, enthusiasts, and explorers of Apache Spark ( Spark is the powerful open source Data processing framework that extends and accelerates Hadoop; built around speed, ease of use, and sophisticated analytics. This is a very interactive meetup where we will exchange ideas, inspire and learn from each other, and bring the top minds and innovators around big data and real-time solutions to the table. This meetup is meant for both the business and technical community (both the curious and the experts) interested in the "how" and the "why" of Spark's capabilities. The meetup will include introductions to the various Spark features and functions, case studies from current users, best practices for deployment, and speakers from the top technology leaders and vendors who are helping craft Spark's roadmap for the future. Let's build this exciting Spark community together!

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