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Published by Alex Slotnick on Mar 23, 2017 12:15:00 PM

Common Pitfalls When Using database/sql in Go

Updated 3/23/2017

Here at VividCortex, we’re huge fans of the Go language and its database access library, database/sql. As you’ve probably seen firsthand, the surface area of database/sql is pretty small, but there’s a lot you can do with it. That includes plenty of risk for error and deceptive mistakes. This blog post is dedicated to some of the past mistakes we’ve made ourselves, in hopes that you won’t also make them when the time comes.

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Published by Alex Slotnick on Sep 12, 2016 5:11:24 PM

Queueing Theory in the News: NYT Asks "How do You Pick the Fastest Line?"

Just in time for the release of the newest edition of our popular, free ebook -- "The Essential Guide to Queueing Theory" -- the New York Times has published an article that delves straight into the heart of one of the most common daily-life instances of queueing-theory-in-action: titled "How to Pick the Fastest Line at the Supermarket," it investigates the grocery store line, that most common and well-known of quotidian queues.

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Published by Alex Slotnick on Mar 16, 2016 2:49:34 PM

New Ebook: Sampling a Stream of Events With a Probabilistic Sketch

Stream processing is a hot topic today. As modern Big Data processing systems have evolved, stream processing has become recognized as a first-class citizen in the toolbox. That’s because when you take away the how of Big Data and look at the underlying goals and end results, deriving real-time insights from huge, high-velocity, high-variety streams of data is a fundamental, core use case.

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Published by Alex Slotnick on Jan 19, 2016 1:19:36 PM

Queueing Theory in the News: London Underground Escalator Policy Challenges Social Norms

Back in October, we published our ebook Everything You Need to Know About Queueing Theory, and as part of its launch, we blogged about one way (of the many) that queueing theory has recently shown up in the real world and the news. In that post, we shared a report showing that the London Underground behaves in ways that at first seem unintuitive, but are comprehendible if you have a handle on how queueing works. Specifically, studies suggested that when the Underground’s individual trains travelled at higher velocities, travel time for passengers actually got worse. Why? The higher individual speeds were not optimal for the particular parameters of the Underground system, and they caused bottlenecks to form at key hubs, hindering the circulation of the entire system. 

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