{"id": "spatialite:making-use-of-a-spatial-index", "page": "spatialite", "ref": "making-use-of-a-spatial-index", "title": "Making use of a spatial index", "content": "SpatiaLite spatial indexes are R*Trees. They allow you to run efficient bounding box queries using a sub-select, with a similar pattern to that used for  Searches using custom SQL . \n             In the above example, the resulting index will be called  idx_museums_point_geom . This takes the form of a SQLite virtual table. You can inspect its contents using the following query: \n             select * from idx_museums_point_geom limit 10; \n             Here's a live example:  timezones-api.datasette.io/timezones/idx_timezones_Geometry \n             \n                 \n                     \n                     \n                     \n                     \n                     \n                     \n                         \n                             \n                                 pkid \n                             \n                             \n                                 xmin \n                             \n                             \n                                 xmax \n                             \n                             \n                                 ymin \n                             \n                             \n                                 ymax \n                             \n                         \n                     \n                     \n                         \n                             \n                                 1 \n                             \n                             \n                                 -8.601725578308105 \n                             \n                             \n                                 -2.4930307865142822 \n                             \n                             \n                                 4.162120819091797 \n                             \n                             \n                                 10.74019718170166 \n                             \n                         \n                         \n                             \n                                 2 \n                             \n                             \n                                 -3.2607860565185547 \n                             \n                             \n                                 1.27329421043396 \n                             \n                             \n                                 4.539252281188965 \n                             \n                             \n                                 11.174856185913086 \n                             \n                         \n                         \n                             \n                                 3 \n                             \n                             \n                                 32.997581481933594 \n                             \n                             \n                                 47.98238754272461 \n                             \n                             \n                                 3.3974475860595703 \n                             \n                             \n                                 14.894054412841797 \n                             \n                         \n                         \n                             \n                                 4 \n                             \n                             \n                                 -8.66890811920166 \n                             \n                             \n                                 11.997337341308594 \n                             \n                             \n                                 18.9681453704834 \n                             \n                             \n                                 37.296207427978516 \n                             \n                         \n                         \n                             \n                                 5 \n                             \n                             \n                                 36.43336486816406 \n                             \n                             \n                                 43.300174713134766 \n                             \n                             \n                                 12.354820251464844 \n                             \n                             \n                                 18.070993423461914 \n                             \n                         \n                     \n                 \n             \n             You can now construct efficient bounding box queries that will make use of the index like this: \n             select * from museums where museums.rowid in (\n    SELECT pkid FROM idx_museums_point_geom\n    -- left-hand-edge of point > left-hand-edge of bbox (minx)\n    where xmin > :bbox_minx\n    -- right-hand-edge of point < right-hand-edge of bbox (maxx)\n    and xmax < :bbox_maxx\n    -- bottom-edge of point > bottom-edge of bbox (miny)\n    and ymin > :bbox_miny\n    -- top-edge of point < top-edge of bbox (maxy)\n    and ymax < :bbox_maxy\n); \n             Spatial indexes can be created against polygon columns as well as point columns, in which case they will represent the minimum bounding rectangle of that polygon. This is useful for accelerating  within  queries, as seen in the Timezones API example.", "breadcrumbs": "[\"SpatiaLite\"]", "references": "[{\"href\": \"https://timezones-api.datasette.io/timezones/idx_timezones_Geometry\", \"label\": \"timezones-api.datasette.io/timezones/idx_timezones_Geometry\"}]"}