InfoQ Homepage Architecture Content on InfoQ
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The Big Data Imperative: Discovering & Protecting Sensitive Data in Hadoop
Jeremy Stieglitz discusses best practices for a data-centric security , compliance and data governance approach, with a particular focus on two customer use cases.
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Caching and Messaging Improvements in Spring Framework 4.1
Juergen Hoeller and Stéphane Nicoll present major new features in Spring Framework 4.1: the numerous improvements around the caching abstraction, and messaging-related features.
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REST Services with RabbitMQ, Spring Integration and Node.JS
The speakers provide insight into design and architectural challenges for creating REST services with Spring Integration with RabbitMQ.
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Inside spring.io: a Production Spring Reference Application
Brian Clozel talks about the newly open-sourced reference application that powers the spring.io site, built with Spring Boot, Spring Framework 4 features, cujoJS, Bower and Gulp.
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Why Spark Is the Next Top (Compute) Model
Dean Wampler argues that Spark/Scala is a better data processing engine than MapReduce/Java because tools inspired by mathematics, such as FP, are ideal tools for working with data.
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Workflows of Refactoring
Martin Fowler keynotes on the need for refactoring and different ways to approach it. You can view here part 2 of this presentation: http://www.infoq.com/presentations/healthy-social-environment.
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Customer Analytics on Hadoop
Bob Kelly presents case studies on how Platfora uses Hadoop to do analytics for several of their customers.
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Unleash the Power of HBase Shell
Jayesh Thakrar shows what can be done with irb, how to exploit JRuby-Java integration, and demonstrates how the Shell can be used in Hadoop streaming to perform complex and large volume batch jobs.
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Dashboarding: The Developers’ Role in Data Analysis
Seth Juarez shares insight on how to create applications that use dashboards to drive value, convert raw data into answers, and simplify business processes.
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Experiences Using Grails in a Microservice Architecture
Jeff Beck describes how Grails fits into a larger polyglot architecture and goes through his team's experiences building and maintaining these micro services.
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Samza in LinkedIn: How LinkedIn Processes Billions of Events Everyday in Real-time
Neha Narkhede of Kafka fame shares the experience of building LinkedIn's powerful and efficient data pipeline infrastructure around Apache Kafka and Samza to process billions of events every day.
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Mantis: Netflix's Event Stream Processing System
The authors discuss Netflix's new stream processing system that supports a reactive programming model, allows auto scaling, and is capable of processing millions of messages per second.
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