InfoQ Homepage Distributed Systems Content on InfoQ
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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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Pickles & Spores: Improving Distributed Prog. in Scala
Heather Miller presents attempts at better supporting distributed programming in Scala, including a new fast pickling framework, as well as Spores - composable pieces of mobile functional behaviour.
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From The Lab To The Factory: Building A Production Machine Learning Infrastructure
Josh Wills discusses using Hadoop technologies to build real-time data analysis models with a focus on strategies for data integration, large-scale machine learning, and experimentation.
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Data & Infrastructure at Airbnb
Brenden Matthews describes the infrastructure built at Airbnb using Mesos in order to support Hadoop and Storm.
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Graph Computing at Scale
Matthias Broecheler discusses graph computing, introducing the Aurelius graph cluster enabling graph computing at scale by building on distributed systems like Cassandra, HBase, and Hadoop.
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