There’s an old distributed systems adage, “You can have a second computer when you learn how to use the first one.” When it comes to data-access patterns, most of our favorite patterns are unsafe on a single computer. Most of our applications assume a concurrency model where all access is serialized. What happens when that mental model meets distributed data?
Sean Allen reviews data race and corruption problems that exist on single-machine systems and shows how we’ve transferred many of those patterns over to distributed systems and distributed state. You’ll learn the basics of data races, deadlocks, and problems in even the simplest of concurrent data access patterns and how existing scaling patterns replicate the same issues across multiple machines, increasing the potential problems, as well as designs that can alleviate them.
Sean T. Allen is vice president of engineering at Wallaroo Labs and a member of the Pony core team. His turn-ons include programming languages, distributed computing, Hiwatt amplifiers, and Fender Telecasters. His turn-offs include mayonnaise, stirring yogurt, and sloppy code. He’s one of the authors of Storm Applied.
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