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Using machine learning to rank search results (part 2)
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Running A/B tests on our hosting infrastructure
19 Sep 2016
Running A/B tests on our hosting infrastructure
19 Jan
Optimising Redis storage, part two
19 Jan 2017
Optimising Redis storage, part two
27 Mar
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27 Mar 2017
Every service is an island

25 Oct 2012

0 min read

Fuzzily, a Ruby gem for blazing-fast fuzzy text search

I just released fuzzily, a small piece of software that gives you a way to very quickly perform fuzzy searches against tables in exchange for a little data and write overhead.

It’s a trigram-based, database-backed fuzzy string search/match engine for Rails.

Loosely inspired from this old blog post.

Anecdotical benchmark: against our whole Geonames-derived table of locations (3.2M records, about 1GB of data), on my development machine (a 2011 MacBook Pro)

  • searching for the top 10 matching records takes 6ms ±1
  • preparing the index for all records takes about 10min
  • the DB query overhead when changing a record is at 3ms ±2
  • the memory overhead (footprint of the trigrams table index) is about 300MB

This looks like it scales very well, since the total number of possible trigrams is low (about 19k).

Pretty fast if you ask me!

This website is graciously hosted by Github Pages.

It's built using jekyll, markdown, bootstrap, bootstrap-sass, sass, haml plus a hefty dose of love and the benevolent tolerance of my significant other.

Unless otherwise stated, all content is © 2012-2014 Julien Letessier, all rights reserved. All code snippets are reusable free of charge under the terms of the MIT Licence.