Phil Booth

Blog

• Automating MySQL EXPLAIN checks

  a month ago

  About a month ago, we had an outage caused by a slow-running query in MySQL. This particular slow query wasn't spotted when it was deployed because it depended on data inserted by client browsers and the related preference in Firefox was not enabled at that point. A few weeks after it shipped, the client pref was flipped on and as the table grew, it slowed down MySQL increasingly until the whole of Firefox Accounts became unresponsive. And of course, because Sod's Law is one of the fundamental forces of nature, this happened late on a Friday night. There were some complicating factors that slowed down diagnosis, but it's also fair to say we could have caught it at source with an EXPLAIN of the offending query during code review. Because of that, I decided to try and automate EXPLAIN checks for our MySQL queries.
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• Refactoring with Rust macros

  a couple of months ago

  Refactoring boilerplate code is always easy in dynamically-typed languages, but sometimes takes a bit more effort when constrained by strong typing. This is something I was puzzling over recently, when the penny dropped for me about how Rust's macros can be used to bridge the gap.
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• Bye Dad

  4 months ago

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• The elegance of Rust

  5 months ago

  Here's three little Rust tricks that I learned in the last week or so. Each struck me as being an elegant approach to working cleanly within the confines of a strongly-typed language.
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• Parsing individual data items from huge JSON streams in Node.js

  7 months ago

  Let's say you have a huge amount of JSON data and you want to parse values from it in Node.js. Perhaps it's stored in a file on disk or, more trickily, it's on a remote machine and you don't want to download the entire thing just to get some data from it. And even if it is on the local file system, the thing is so huge that reading it in to memory and calling JSON.parse will crash the process with an out-of-memory exception. Today I implemented a new method for my async JSON-parsing lib, BFJ, which has exactly this type of scenario in mind.
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• Showing how poor performance affects user behaviour

  a year ago

  "Bad performance hurts user engagement" is a sentiment that feels intuitively true but can be hard to sell in product conversations. The best way to persuade a non-believer is to point them at hard evidence and for that you need to do a few things with your performance data.
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