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Pulsar: Real-time Analytics at Scale
Sharad Murthy & Tony Ng present Pulsar, a real-time streaming system which can scale to millions of events per second with high availability and 4GL language support.
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Machine Learning and IoT
Ajit Jaokar discusses data science and IoT: sensor data, real-time processing, cognitive computing, integration of IoT analytics with hardware, IoT’s impact on healthcare, automotive, wearables, etc.
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How 30 Years of Ticket Transaction Data Helps you Discover New Shows!
Vaclav Petricek discusses how to train models, architect and build a scalable system powered by Storm, Hadoop, Spark, Spring Boot and Vowpal Wabbit that meets SLAs measured in tens of milliseconds.
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Taking the Pain out of Real-time Mobile Back-end Development
Mandy Waite shows how to get started with Firebase before walking through a live demo of building a multi-user, collaborative mobile app that provides real-time updates to its users.
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Java 8 in Anger
Trisha Gee uses Java 8 streams and lambdas to build an app consuming a real-time feed of high velocity data, using services to make sense of the data, and presenting it in a JavaFX dashboard.
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Mini-talks: Deterministic Testing, Typesafe Config, Spreads v Probe, & Real-Time Event-Driven
Small sessions on: Deterministic testing in a non-deterministic world. Hash Spreads and Probe Functions. Typesafe Config on Steroids. Real-Time Distributed Event-Driven Computing at Credit Suisse.
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Scaling Uber's Real-time Market Platform
Matt Ranney explains the Uber architecture overall, with a focus on the dispatch systems, the geospatial index, handling failure, and dealing with the distributed traveling salesman problem.
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IoT Realized - The Connected Car
This session explores the power of Spring XD in the context of the Internet of Things (IoT).
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Better Together - Using Spark and Redshift to Combine Your Data with Public Datasets
Eugene Mandel discusses challenges of conforming data sources and compares processing stacks: Hadoop+Redshift vs Spark, showing how the technology drives the way the problem is modeled.
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Scalability Lessons from eBay, Google, and Real-time Games
Randy Shoup tells war stories from Google and eBay focusing on how to scale code, infrastructure, performance, and operations, along with hard-won lessons learned in scaling them.
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Scalable Big Data Stream Processing with Storm and Groovy
Eugene Dvorkin provides an introduction to Storm framework, explains how to build real-time applications on top of Storm with Groovy, how to process data from Twitter in real-time, etc.
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Applications of Enterprise Integration Patterns to Near Real-Time Radar Data Processing
Garrett Wampole describes an experimental methodology of applying Enterprise Integration Patterns to the near real-time processing of surveillance radar data, developed by MITRE.
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