Buck Hx

A must-read followup that explores other data structures for geofencing: https://medium.com/@buckhx/unwinding-uber-s-most-efficient-service-406…

An excellent response that I remember from the last time this article made the rounds: https://medium.com/@buckhx/unwinding-uber-s-most-efficient-service-406…

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That post you linked is the one that got heavily criticised by a Bing Maps engineer for being under-engineered[1]. 1. https://medium.com/@buckhx/unwinding-uber-s-most-efficient-service-406…

There's a famous 'rebuttal' post to this here https://medium.com/@buckhx/unwinding-uber-s-most-efficient-service-406…

This is a very inefficient implementation. Really, just poor quality work overall, as anyone with even a basic understanding of spatial indexing would know that an R-tree would be many times faster, as illustrated here: https://medium.com/@buckhx/unwinding-uber-s-most-efficient-service-406…

> They delivered value to the business. That's the only thing that matters. Except this is an engineering blog post, so the engineering part actually matters. And, as demonstrated in the article [1] linked around this discussion, there were better engineering approaches that would have been even "better for business", as being more efficient means lower costs per transaction and/or higher throughput. [1] https://medium.com/@buckhx/unwinding-uber-s-most-efficient-service-406…

Sometimes it feels like Groundhog Day, behold: https://medium.com/@buckhx/unwinding-uber-s-most-efficient-service-406… tl;dr - S2 is a good library. There's also a joke in here somewhere about bikeshedding and yak shaving.