> Another set of tests with a brand new and quite powerful laptop. > Specs for the > computer: > Intel i7-2760QM @2.4 GHz processor (8 threads) > Hitachi Travelstar Z7K320 7200 rpm SATA disk > 8 GB of memory > Windows 7, 64-bit > > GDAL-version r24717, Win64 build from gisinternals.com > > Timings for germany.osm.pbf (1.3 GB) > ==================================== > > A) Default settings with command > ogr2ogr -f sqlite -dsco spatialite=yes germany.sqlite > germany.osm.pbf -gt 20000 -progress --config OGR_SQLITE_SYNCHRONOUS OFF > > - reading the data 67 minutes > - creating spatial indexes 38 minutes > - total 105 minutes > > B) Using in-memory Spatialite db for the first step by giving > SET OSM_MAX_TMPFILE_SIZE=7000 > > - reading the data 16 minutes > - creating spatial indexes 38 minutes > - total 54 minutes > > Peak memory usage during this conversion was 4.4 GB. > > Conclusions > =========== > * The initial reading of data is heavily i/o bound. This phase > is really fast if there is enough memory for keeping the OSM > tempfile in memory but SSD disk seems to offer equally good > performance. > * Creating spatial indexes for the Spatialite tables is also > i/o bound. The hardware sets the speed limit and there are > no other tricks for improving the performance. Multi-core > CPU is quite idle during this phase with 10-15% load. > * If user does not plan to do spatial queries then then it > may be handy to save some time and create the Spatialite db > without spatial indexes by using -lco SPATIAL_INDEX=NO option. > * Windows disk i/o may be a limiting factor. > > I consider that for small OSM datasets the speed starts to be > good enough. For me it is about the same if converting the > Finnish OSM data (137 MB in .pbf format) takes 160 or 140 > seconds when using the default settings or in-memory temporary > database, respectively.
Interesting findings. A SSD is of course the ideal hardware to get efficient random access to the nodes. I've just introduced inr 24719 a new config. option OSM_COMPRESS_NODES that can be set to YES. The effect is to use a compression algorithm while storing the temporary node DB. This can compress to a factor of 3 or 4, and help keeping the node DB to a size where it is below the RAM size and that the OS can dramatically cache it (at least on Linux). This can be efficient for OSM extracts of the size of the country, but probably not for a planet file. In the case of Germany and France, here's the effect on my PC (SATA disk) : $ time ogr2ogr -f null null /home/even/gdal/data/osm/france_new.osm.pbf - progress --config OSM_COMPRESS_NODES YES [...] real 25m34.029s user 15m11.530s sys 0m36.470s $ time ogr2ogr -f null null /home/even/gdal/data/osm/france_new.osm.pbf - progress --config OSM_COMPRESS_NODES NO [...] real 74m33.077s user 15m38.570s sys 1m31.720s $ time ogr2ogr -f null null /home/even/gdal/data/osm/germany.osm.pbf -progress --config OSM_COMPRESS_NODES YES [...] real 7m46.594s user 7m24.990s sys 0m11.880s $ time ogr2ogr -f null null /home/even/gdal/data/osm/germany.osm.pbf -progress --config OSM_COMPRESS_NODES NO [...] real 108m48.967s user 7m47.970s sys 2m9.310s I didn't turn it to YES by default, because I'm unsure of the performance impact on SSD. Perhaps you have a chance to test. _______________________________________________ gdal-dev mailing list [email protected] http://lists.osgeo.org/mailman/listinfo/gdal-dev
