InfoQ Homepage Distributed Systems Content on InfoQ
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Distributed Data Analysis with Hadoop and R
Jonathan Seidman and Ramesh Venkataramaiah present how they run R on Hadoop in order to perform distributed analysis on large data sets, including some alternatives to their solution.
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Panel: Hadoop for the Enterprise Architect
Peter Sirota, Amr Awadallah, Eric Baldeschwieler, Ted Dunning, Guy Bayes, and moderator Ron Bodkin discuss various existing Hadoop use cases, ecosystems, and disaster recovery.
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On Distributed Failures (and handling them with Doozer)
Blake Mizerany presents various ways that can lead to system failure in distributed systems and how to recover using Doozer, a highly available, consistent data store.
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Distributed Systems: What Nobody Told You
Shaneal Manek tells the story of how things can go wrong with a distributed system which turned into a success after incorporating appropriate tools for monitoring, analytics, logging, security.
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Storm: Distributed and Fault-tolerant Real-time Computation
Nathan Marz explain Storm, a distributed fault-tolerant and real-time computational system currently used by Twitter to keep statistics on user clicks for every URL and domain.
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Things Break, Riak Bends
Justin Sheehy talks about failure and the need to prepare for it, giving some real life examples along with techniques implemented in Riak to make it resilient to faults.
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Building Solid Distributed Applications with Haskell and Riak
Bryan O'Sullivan discusses the design considerations and types usage when building distributed systems with Haskell and Riak, starting from a case study of a system using vector clocks.
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Concurrent and Distributed Applications with Spring
David Syer and Mark Fisher on using Spring to develop concurrent and distributed apps, covering topics such as: asynchronous execution, intra-process, inter-process and inter-JVM communication.
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Riak Core: Dynamo Building Blocks
Andy Gross discusses the design philosophy behind Riak based on Amazon Dynamo - Gossip Protocol, Consistent Hashing, Vector clocks, Read Repair, etc. -, overviewing its main features and architecture.
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Being Elastic - Evolving Programming for the Cloud
Randy Shoup discusses the cloud programming model, covering topics such as state/statelessness, distribution, workload partitioning, cost and resource metering, automation, and deployment strategies.
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NoSQL at Twitter
Ryan King presents how Twitter uses NoSQL technologies - Gizzard, Cassandra, Hadoop, Redis - to deal with increasing data amounts forcing them to scale out beyond what the traditional SQL has to offer
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NoSQL at Twitter
Kevin Weil presents how Twitter does data analysis using Scribe for logging, base analysis with Pig/Hadoop, and specialized data analysis with HBase, Cassandra, and FlockDB.
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