Diskussion:HSR Texas Geo Database Benchmark
Aus Geoinformation HSR
Feel free to discusss 'HSR Texas Spatial Database Benchmark' issues here! Stefan 18:39, 22. Dez. 2009 (CET)
- Standardise data and input process (circumvent or minimize floating point problem)
- Define the variables (@bbox and @point)
- MS SQL Server representatives report that geography types are 20-30% slower than geometry types.
- About PostGIS 1.5 there was said, that geography types are somewhat faster (see http://blog.cleverelephant.ca/)
- Secondary index optimization makes performance about 50% faster (from: MS SQL Server discussion)
- The number of points of a query window is important for a secondary filter overhead.
Data and queries per se:
- These queries return quite large percent of the data overall (50%-100% for points and polygons)
- The Number of points for a query windows is very small.
- The query windows are "aligned bounding boxes" which may put in favor RTree (e.g. Postgres) or spatial grid (SQL Server) index, depending on a position of the window. If the window is aligned with the grid, performance can be much faster than when it's slightly off.
- Volker Mische reported that boundingbox queries with different boundingboxes (selecting 5%, 10%, 15%, 20%, 25% of all features) show the same performance in spatialite.
- Should we take an average of multiple runs with different values (@point, @bbox)?
- Should we vary the queries' result sizes? (see observations)
- Should we vary the shape and alignment of the query window? (see observations)
- Should we run the benchmark with parallelized queries?
- Query 1 actually shouldn't be included in the benchmark, data copying and preparation isn't really done often in a spatial database.