InfoQ Homepage Architecture & Design Content on InfoQ
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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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Crafting Experience Strategy
Cathy Wang discusses experience strategy: what it is, relationship with UX, business and service design, different approaches to it, and how it can help to achieve success.
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One Weird Trick for Making Perfect Software
Pieter Hintjens teaches a trick he is using daily to create better software clients.
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Gobblin: A Framework for Solving Big Data Ingestion Problem
Lin Qiao discusses the architecture of Gobblin, LinkedIn’s framework for addressing the need of high quality and high velocity data ingestion.
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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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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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The New Features in MariaDB 10.0 and in the Upcoming MariaDB 10.1
Michael Widenius walks through the features of MariaDB 10.0 and 10.1, outlining the performance benefits resulting from switching to MariaDB.
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Designing for Human Cooperation
Attila Bujdoso presents two projects designing infrastructures for human cooperation: Format -studies cultural formats of cooperation, opp.io -designing a new technological protocol for collaboration.
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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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