To complement what Eric said, here’s the ‘getfield’ function (This code was taken from ArchGDAL so we are talking of the same thing)
https://github.com/GenericMappingTools/GMT.jl/blob/master/src/gdal.jl#L2161 From: gdal-dev <gdal-dev-boun...@lists.osgeo.org> On Behalf Of Erik Schnetter via gdal-dev Sent: Tuesday, June 24, 2025 5:21 PM To: gdal-dev@lists.osgeo.org Subject: Re: [gdal-dev] Read a /vsigzip/ csv.gz all at once The Julia wrapper (ArchGDAL.jl) for `getfield` calls `OGR_FD_GetFieldDefn` and several related function (to get the type of the field etc.). Are these possibly expensive operations in GDAL? Any C function in GDAL can easily be called from Julia. Which C function would get all fields at once? I assume that e.g. `OGR_F_GetFieldAsDoubleList` would not work; this would be for values that are themselves lists? The Julia code for `getfield` spends quite a bit of work to find out the type of the field. This includes a bit of reference counting, allocating small structures on the heap, registering finalizers for them etc. This could be avoided by adding a Julia wrapper that calls `getfield` repeatedly (even from Julia, calling C has no overhead by itself) for a range of integers. This would avoid the additional overhead having to do with handling types, and the Julia/GDAL reference counting. Even, is that what you had in mind? -erik On Jun 24, 2025, at 11:01, Even Rouault via gdal-dev <gdal-dev@lists.osgeo.org<mailto:gdal-dev@lists.osgeo.org>> wrote: Hi, I don't know anything about Julia but I'd suspect that there must be something particularly slow in the way it interacts with C. For comparison, "time python3 swig/python/gdal-utils/osgeo_utils/samples/ogrinfo.py /vsigzip//vsicurl/https://bulk.meteostat.net/v2/hourly/2022/08554.csv.gz -al > /dev/null" that does essentially your loop, and also prints on stdout, runs in 1.5 seconds (compared to native ogrinfo that runs in 0.7 s). Perhaps you could write a Julia wrapper to get all fields of feature at once and return whatever dictionary or equivalent data structure is idiomatic (and efficient )in Julia ? Also are you sure your Julia wrapper is built with optimization enabled? Even Le 24/06/2025 à 16:33, Joaquim Manuel Freire Luís via gdal-dev a écrit : Hi, Im trying to read files like https://bulk.meteostat.net/v2/hourly/2022/08554.csv.gz in my Julia wrapper. The point is that, although I’m kind off succeeding, the hole operation is very slow. What I’m doing (code not committed yet so can’t post a link) is to read like this layer = getlayer(dataset, 0) for f in layer for k = 1: Gdal.nfield(f) Gdal.getfield(f, k-1) … This works but it’s extremely slow because each “getfield” takes about 1e-4 seconds and the file has ~8 k rows, each with 13 fields. That amounts to > 10 sec. I’ve searched but couldn’t find a way to read the entire file at once (which takes 1e-2 seconds if I read it, locally, with a gzip wrapper) and return it as a single string array that I could parse later. Is that possible? Thanks Joaquim _______________________________________________ gdal-dev mailing list gdal-dev@lists.osgeo.org<mailto:gdal-dev@lists.osgeo.org> https://lists.osgeo.org/mailman/listinfo/gdal-dev -- http://www.spatialys.com<http://www.spatialys.com/> My software is free, but my time generally not. _______________________________________________ gdal-dev mailing list gdal-dev@lists.osgeo.org<mailto:gdal-dev@lists.osgeo.org> https://lists.osgeo.org/mailman/listinfo/gdal-dev
_______________________________________________ gdal-dev mailing list gdal-dev@lists.osgeo.org https://lists.osgeo.org/mailman/listinfo/gdal-dev
