InfoQ Homepage Distributed Systems Content on InfoQ
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Distributed Systems in Production
Jeff Hodges discusses tactics and strategy for creating distributed systems today and a little about what the future holds.
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The Game of Big Data: Scalable, Reliable Analytics Infrastructure at KIXEYE
Randy Shoup describes KIXEYE's analytics infrastructure from Kafka queues through Hadoop 2 to Hive and Redshift, built for flexibility, experimentation, iteration, testability, and reliability.
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The Next Wave of SQL-on-Hadoop: The Hadoop Data Warehouse
Marcel Kornacker presents a case study of an EDW built on Impala running on 45 nodes, reducing processing time from hours to seconds and consolidating multiple data sets into one single view.
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Finding the Needle in a Big Data Haystack
In this solutions track talk, sponsored by Cloudera, Eva Andreasson discusses how search and Hadoop can help with some of the industry's biggest challenges. She introduces the data hub concept.
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A Big Data Arsenal for the 21st Century
In this solutions track talk, sponsored by MongoDB, Matt Asay discusses the differences between some of the NoSQL and SQL databases and when Hadoop makes sense to be used with a NoSQL solution.
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Principles of Reliable Communication & Shared State
Andy Piper describes some fundamentals of communicating reliably in an unreliable world and communication techniques used to build distributed data structures that can tolerate failures.
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Cloud, Distributed, Embedded: Erlang in the Heterogeneous Computing World
Omer Kilic provides an overview of heterogeneous computing discussing how Erlang can help with the orchestration of different processing platforms, introduces Erlang/ALE + updates on Erlang Embedded.
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Real World Akka Recipes
Jamie Allen describes three patterns using Akka actors: handling a lack of guaranteed delivery, distributing tasks to worker actors and implementing distributed workers in an Akka cluster.
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Next Gen Hadoop
Akmal B. Chaudhri introduces Apache™ Hadoop® 2.0 and Yet Another Resource Negotiator (YARN).
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What Can Hadoop Do for You?
Eva Andreasson presents typical categories of problems that are commonly solved using Hadoop and also some concrete examples in each category.
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Design Patterns for Large-Scale Real-Time Learning
Sean Owen provides examples of operational analytics projects, presenting a reference architecture and algorithm design choices for a successful implementation based on his experience Oryx/Cloudera.
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Going Reactive: New and Old Ideas for Your 21st Century Architectures
Jonas Bonér, Francesco Cesarini discuss the evolution of distributed concurrent thinking along with the problems it has to solve and the toolchains created along the way.
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