Thanks - because of the origin of the data the Geotiffs are not adjacent, there's a little group for each of about 500 cities, but strictly one of them at a time is shown, so I'm not sure how much that's going to help. If there's something computationally intensive going on at the server's end, that's going to be a drag in any case.
Going through the Geoserver on Steroids presentation now, thanks! Max On 17 March 2016 at 11:16, Ian Turton <ijtur...@gmail.com> wrote: > Those sound like small tiffs so you would be better combining them together > to avoid opening too many files at a time. Have a look at gdalbuildvrt to > make a virtual raster catalogue that you can then convert into a tiled > compressed geotiff that is in your main output projection. > > Have a read through the annual "GeoServer on Steroids" presentation > (http://www.slideshare.net/geosolutions/geoserver-on-steroids-foss4g-2015 ) > for more ideas.# > > Ian > > On 17 March 2016 at 09:51, Max <basili...@gmail.com> wrote: >> >> I have a large number - more than 60 thousand - of relatively small >> Geotiffs, usually from 2 to 12 Mb. I have a web client that uses >> Leaflet to view them, but things are quite slow even inside our own >> network. I have a hunch that both Geoserver and these Geotiffs are not >> configured in the best way possible. >> >> The tiffs were generated from a bunch of EPSG:3035 Ascii grid files >> using this command: >> >> for f in *.rsl; do gdal_translate -a_srs EPSG:3035 -co "TILED=YES" >> -co "BLOCKXSIZE=512" -co "BLOCKYSIZE=512" -co "COMPRESS=DEFLATE" -co >> "ZLEVEL=9" -co "BIGTIFF=YES" $f $f.tif; done >> >> Then I wrote a Python script that created a store and a layer for each >> of the tiffs. >> >> Here is the output from gdalinfo for a typical one: >> >> Driver: GTiff/GeoTIFF >> Files: se502c_R9_C1_3_T_2531_sec.rsl.tif >> Size is 3396, 2271 >> Coordinate System is: >> PROJCS["ETRS89 / LAEA Europe", >> GEOGCS["ETRS89", >> DATUM["European_Terrestrial_Reference_System_1989", >> SPHEROID["GRS 1980",6378137,298.2572221010002, >> AUTHORITY["EPSG","7019"]], >> TOWGS84[0,0,0,0,0,0,0], >> AUTHORITY["EPSG","6258"]], >> PRIMEM["Greenwich",0], >> UNIT["degree",0.0174532925199433], >> AUTHORITY["EPSG","4258"]], >> PROJECTION["Lambert_Azimuthal_Equal_Area"], >> PARAMETER["latitude_of_center",52], >> PARAMETER["longitude_of_center",10], >> PARAMETER["false_easting",4321000], >> PARAMETER["false_northing",3210000], >> >> As you can see they are EPSG:3035. They should be internally tiled. In >> the Coordinate Reference Systems for Geoserver, it says that both >> Native SRS and Declared SRS are EPSG:3035, and that the handling >> should be to reproject native to declared. >> >> My web client overlays these Geotiffs on a standard OpenStreetMap >> layer in Web Mercator. All the geotiffs we have tried appear >> correctly, so I guess reprojection is still happening at some stage. >> >> My gut feeling is that I might gain some speed by reprojecting the >> original Geotiffs to Web Mercator, or at least changing the declared >> SRS to Web Mercator in Geoserver. Not keen on it, it's going to take >> days. What other properties of the Geotiffs could I tinker with? >> >> Would caching with GeoWebCache help, given the file size? >> >> Bonus question - if a Geotiff is changed, by reprojecting or retiling >> or what have you, does the Geoserver layer associated with it get >> invalidated? It took days to create them all. >> >> I'd really appreciate your feeback. >> >> Thanks in advance, >> Max >> >> >> ------------------------------------------------------------------------------ >> Transform Data into Opportunity. >> Accelerate data analysis in your applications with >> Intel Data Analytics Acceleration Library. >> Click to learn more. >> http://pubads.g.doubleclick.net/gampad/clk?id=278785231&iu=/4140 >> _______________________________________________ >> Geoserver-users mailing list >> Geoserver-users@lists.sourceforge.net >> https://lists.sourceforge.net/lists/listinfo/geoserver-users > > > > > -- > Ian Turton ------------------------------------------------------------------------------ Transform Data into Opportunity. Accelerate data analysis in your applications with Intel Data Analytics Acceleration Library. Click to learn more. http://pubads.g.doubleclick.net/gampad/clk?id=278785231&iu=/4140 _______________________________________________ Geoserver-users mailing list Geoserver-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/geoserver-users
