Optimizing Large-Scale OpenStreetMap Data with SQLite
The article discusses optimizing large-scale OpenStreetMap data with SQLite. Converting OSMPBF to SQLite enhanced search functionalities. Indexing, full-text search, and compression improved query performance, despite some false positives.
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The article discusses the optimization of large-scale OpenStreetMap (OSM) data using SQLite. The author converted a massive dataset from OSMPBF format to an SQLite database to enhance search functionalities. OSM data comprises nodes, ways, and relations, each with associated metadata. Initially, the SQLite database was large, prompting the need for optimization to improve query performance. The author explored indexing and full-text search techniques in SQLite to speed up searches. By compressing the SQLite file using Zstandard, the database size was significantly reduced, improving read performance. Despite some false positives in search results, the compressed database allowed for faster queries. Further optimization included reducing false positives in queries and enhancing search efficiency. The project showcases the iterative refinement process and the effectiveness of combining different technologies to address complex data optimization challenges.
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13 commentsFor example, it's simple to count the cafes in North America in under 30s:
SELECT COUNT(*) FROM st_readOSM('/home/wcedmisten/Downloads/north-america-latest.osm.pbf') WHERE tags['amenity'] = ['cafe'];
┌──────────────┐
│ count_star() │
│ int64 │
├──────────────┤
│ 57150 │
└──────────────┘
Run Time (s): real 24.643 user 379.067204 sys 3.696217
[1]: https://duckdb.org/docs/extensions/spatial.html#st_readosm--...
SELECT id
FROM entries e
JOIN search s ON s.rowid = e.id
WHERE
-- use FTS index to find subset of possible results
search MATCH 'amenity cafe'
-- use the subset to find exact matches
AND tags->>'amenity' = 'cafe';What's DuckDB bringing to the table relative to sqlite, which seems like the boring-and-therefore-best choice?
This uninformative non-sentence sounds an awful lot like ChatGPT.
That's not how indexes work at all. This will be fine.
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