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We are not yet at the End of History for database theory as Peter Bailis and the Database Group at UC Berkeley continue to prove with a great companion blog post to their new paper: Scalable Atomic Visibility with RAMP Transactions. I like the approach of pairing a blog post
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Famous computer scientist Leslie Lamport is definitely not a worse is better kind of guy. In Computation and State Machines he wants to make the case that to get better programs we need to teach programmers to think better. And programmers will think better when they learn to think in
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Most every programmer who gets sucked into deep performance analysis for long running processes eventually realizes memory allocation is the heart of evil at the center of many of their problems. So you replace malloc with something less worse. Or you tune your garbage collector like a fine ukulele. But
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Counting at scale in a distributed environment is surprisingly hard. And it's a subject we've covered before in various ways: Big Data Counting: How to count a billion distinct objects using only 1.5KB of Memory, How to update video views count effectively?, Numbers Everyone Should
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Algorithms are moving out of the Platonic realm and are becoming dynamic first class players in real life. We've seen corporations become people. Algorithms will likely also follow that path to agency. Kevin Slavin in his intriguing TED talk: How Algorithms Shape Our World, gives many and varied
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In the scalability is specialization department here is an interesting paper presented at HotNets '13 on high performance networking: Network Stack Specialization for Performance. The idea is generalizing a service so it fits in the kernel comes at a high performance cost. So move TCP into user space. The
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How do you turn Big Data into fast, useful, and interesting visualizations? Using R and technology called Nanocubes. The visualizations are stunning and amazingly reactive. Almost as interesting as the technologies behind them. David Smith wrote a great article explaining the technology and showing a demo by Simon Urbanek of
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An interesting and different implementation approach: Tempest: Scalable Time-Critical Web Services Platform: Tempest is a new framework for developing time-critical web services. Tempest enables developers to build scalable, fault-tolerant services that can then be automatically replicated and deployed across clusters of computing nodes. The platform automatically adapts to load fluctuations,
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Awesome paper on how particular synchronization mechanisms scale on multi-core architectures: Everything You Always Wanted to Know About Synchronization but Were Afraid to Ask. The goal is to pick a locking approach that doesn't degrade as the number of cores increase. Like everything else in life, that doesn&
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Ever wonder what powers Google's world spirit sensing Zeitgeist service? No, it's not a homunculus of Georg Wilhelm Friedrich Hegel sitting in each browser. It's actually a stream processing (think streaming MapReduce on steroids) system called MillWheel, described in this very well written paper:
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Google has released an epic second edition of their ground breaking The Datacenter as a Computer book. It's called an introduction, but at 156 pages I would love to see what the Advanced version would look like! John Fries in a G+ comment has what I think is
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If like many humans you've found even Paxos Made Simple a bit difficult to understand, you might enjoy RAFT as described in In Search of an Understandable Consensus Algorithm by Stanford's Diego Ongaro and John Ousterhout. The video presentation of the paper is given by John