InfoQ Homepage Infrastructure Content on InfoQ
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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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Develop Powerful Big Data Applications Easily with Spring XD
The speakers show how to provide a scalable runtime environment, that is easily configured and assembled via a simple DSL.
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TSAR: How to Count Tens of Billions of Daily Events in Real Time Using Open Source Technologies
Gabriel Gonzalez introduces TSAR (TimeSeries AggregatoR), a service for real-time event aggregation designed to deal with tens of billions of events per day at Twitter.
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Building a Data Pipeline with the Tools You Have - An Orbitz Case Study
Steve Hoffman, Ken Dallmeyer share their experience integrating Hadoop into the existing environment at Orbitz, creating a reusable data pipeline, ingesting, transporting, consuming and storing data.
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Weathering the Data Storm
Claudia Perlich discusses privacy-preserving representations, robust high-dimensional modeling, large-scale automated learning systems, transfer learning, and fraud detection.
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Vagrant, Packer, Consul, Serf: Maximum Potency DevOps
Mitchell Hashimoto introduces Vagrant, Packer, Consul, Serf, explaining how they can help DevOps streamline the entire process from development through to production.
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Running Your Spring Apps in the Cloud
Cornelia Davis takes the Spring Trader application and makes (a few) modifications (mostly to config) to get it running on the same components in the cloud, specifically on the Cloud Foundry PaaS.
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Apache Spark Plus Many Other Frameworks: How Spark Fits into the Big Data Landscape
Paco Nathan keynotes on how Spark fits into the big data landscape, describing what other systems work with Spark, and explaining why Spark is needed in the future.
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