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recipe #15
Tightly bounded Populated Places

2011 January 28

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The problem

Yet another problem based on the populated_places dataset. This time the question is:
  • Identify any possible couple of Populated Places laying at very close distance: < 1 Km
Please note: this problem hides an unpleasant complication.
  • the Populated Places dataset is in the 4236 SRID (Geographic, WGS84, long-lat)
  • accordingly to this, distances are naturally measured in decimal degrees
  • but the imposed range limit is expressed in meters/Km

PopulatedPlace #1 Distance (meters) PopulatedPlace #2
Vallarsa 49.444299 Raossi
Raossi 49.444299 Vallarsa
Seveso 220.780551 Meda
Meda 220.780551 Seveso
... ... ...

SELECT AS "PopulatedPlace #1",
    MakeLine(pp1.geometry, pp2.geometry))
      AS "Distance (meters)", AS "PopulatedPlace #2"
FROM populated_places AS pp1,
  populated_places AS pp2
WHERE GeodesicLength(
    MakeLine(pp1.geometry, pp2.geometry)) < 1000.0
  AND <>
  AND pp2.ROWID IN (
    SELECT pkid
    FROM idx_populated_places_geometry
    WHERE pkid MATCH RTreeDistWithin(
      ST_Y(pp1.geometry), 0.02))
This time we'll go straight forward to final solution.
I suppose that's now very clear to everyone that using a Spatial Index is absolutely required to get a decently well-performing query.
And that a JOIN between two different instances of the same table is required to perform this kind of Spatial Analysis, and so on ...

So we'll simply focus our attention on the most notable highlights:
Performing a Spatial query like this one in the most naive way requires an extremely long time, even if you'll use the most recent and powerful CPU.
But carefully applying a little bit of optimization is not too much difficult.
And a properly defined an well optimized SQL query surely runs in the smoothest and fastest way.

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CC-BY-SA logo Author: Alessandro Furieri
This work is licensed under the Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0) license.

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