InfoQ Homepage Infrastructure Content on InfoQ
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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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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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Unified Big Data Processing with Apache Spark
Matei Zaharia talks about the latest developments in Spark and shows examples of how it can combine processing algorithms to build rich data pipelines in just a few lines of code.
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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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My Three Ex’s: A Data Science Approach for Applied Machine Learning
Daniel Tunkelang focuses on the data science mindset for successfully applying machine learning to solve problems: express, explain, experiment.
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Painless Build and Deploy for YARN Applications with Spring
Janne Valkealahti shows how Spring provides a simple programming model to develop applications that can easily be tested and deployed as either a YARN application or a traditional application.
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Implementing the Lambda Architecture with Spring XD
Carlos Queiroz introduces the lambda architecture and showcases how it can be implemented with SpringXD, GemFireXD and Hadoop in a CDR(Call Detail Record) mining application.
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Spring XD for Real-time Hadoop Workload Analysis
The authors explain how the Pivotal team leveraged familiar SQL-based queries to analyze fine-grained cluster utilization using Spring XD.
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Leading a Healthcare Company to the Big Data Promised Land: A Case Study of Hadoop in Healthcare
Mohammad Quraishi presents implementing a Big Data initiative, detailing preparation, goal evaluation, convincing executives, and post implementation evaluation.
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