How replacing a 3 GB SQLite database with a 10 MB FST binary achieved a 300x memory reduction for a Finnish-English dictionary
By
hiAndrewQuinn
The bagel they save for the regulars. Don't skim, savour.
Summary
A developer describes replacing a 3 GB SQLite database for a Finnish-English dictionary with a 10 MB finite state transducer (FST) binary, achieving a ~300x memory reduction. The article details the technical journey of moving from a hacked-together database solution to a specialized, static data structure optimized for incremental search. Key insights include using FSTs for efficient string lookup, the trade-offs between dynamic databases and static specialized structures, and the importance of choosing the right tool for specific use cases rather than defaulting to familiar solutions.
Key quotes
· 3 pulledIt's much more valuable to walk away with the heuristic 'some dude got a 300x memory reduction by swapping out a database he hacked together for a tiny, static, specialized data structure that does exactly what he needs it to and no more.'
I found myself with an increasingly rare opportunity to work this weekend on Taskusanakirja, also often called tsk, a Finnish-English dictionary with incremental search
All numbers have been rounded to their first significant digit, because I'm a fan of Rob Eastaway's 'zequals' method of getting to the point when it comes to estimation.
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