InfoQ Homepage Programming Content on InfoQ
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0 – 100 MPH - Launching a New Product at Scale
Dan Macklin explains why bet365 has adopted Erlang as a core development platform and goes through the highs and lows of managing change in one of the world's biggest on-line bookmakers.
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Groovy Browser Automation
Colin Harrington introduces GEB, a browser automation solution, combining the power of WebDriver, jQuery content selection, the robustness of Page Object modelling and the expressiveness of Groovy.
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Groovy for Java Developers
Peter Ledbrook attempts to answer the question "Java is a good all-purpose programming language, but does that mean it's the best tool for all jobs?"
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Big Data in Memory
John Davies shows a Spring work-flow consuming 7.4kB XML messages, binding them to 25kB Java but storing them in just 450 bytes each, 10 million derivative contracts in-memory on a laptop.
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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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Cloud-scale Event Processing using Rx
Bart De Smet explains what it took to bring the concepts of Reactive Extensions (Rx) to the cloud to deal with latency, scale, reliability, and other concerns.
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Remote Access Made Easy and Fast with Haskell
Simon Marlow explains how to use Haxl to automatically batch and overlap requests for data from multiple data sources.
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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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Asychronous Design with Spring and RTI: 1M Events per Second
Stuart Williams takes a walk through the RTI architecture and explains how Spring performs at hundreds (and millions) of events/operations per second.
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Building a Recommendation Engine with Spring and Hadoop
Michael Minella uses Spring XD and Spring Batch to orchestrate the full lifecycle of Hadoop processing and uses Apache Mahout to provide the audience with the recommendation processing.
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Become a Data-driven Organization with Machine Learning
Peter Harrington explains what you do with machine learning, and what are the building blocks for an application that uses machine learning from collected data to creating predictions for customers.
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Apps + Data + Cloud: What Does It All Mean?
Matt Stine presents how combine Spring Boot, Spring Data, Spring Reactor, Spring XD, Hadoop and run them in the cloud.
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