Geospatial Query Optimization
Definition
Geospatial query optimization is the art of making spatial SQL and API queries efficient. It blends indexing, tiling, predicate ordering, simplification, and careful schema design to minimize CPU, IO, and network transfer. Well‑optimized queries turn sluggish dashboards into responsive tools and keep cloud bills predictable.
Application
Analysts speed up spatial joins, map servers deliver tiles faster, and event pipelines filter massive streams in real time. Optimized queries are crucial when millions of features meet complex geometries.
FAQ
Which predicates should run first?
Cheap, coarse filters like bounding boxes and attribute predicates should prune data before exact intersection or within tests.
How do we avoid exploding joins?
Pre‑aggregate, partition by region, or use spatial bucketing to only compare local candidates. Streaming joins with windows also help.
Does geometry complexity matter?
Yes. Simplify shapes for visualization and pre‑compute centroids or envelopes for frequent checks. Keep authoritative geometries for final analysis.
How can we see if the DB does the right thing?
Explain plans, index usage stats, and query runtimes across representative workloads reveal whether changes help or harm.
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