[R-sig-Geo] rgdal: problem reading a bigger raster dataset (R 4.0.0/3.6.3, Ubuntu 20.04)

Roger Bivand Roger@B|v@nd @end|ng |rom nhh@no
Tue Apr 28 12:10:48 CEST 2020


On Tue, 28 Apr 2020, Thorsten Behrens wrote:

> Michael,
>
> Thanks for the hint, it seems to work! Real-world tests will follow in
> the next few days...
>
> So it definitely seems to be a problem of rgdal. It would be great if it
> could still be solved.

Not rgdal, but your use of it. Try looking at a sequence of

file <- system.file("pictures/SP27GTIF.TIF", package="rgdal")
obj <- GDAL.open(file)
(dims <- dim(obj))
band <- 1
data_vector <- getRasterData(obj, band)
GDAL.close(obj)
str(data_vector)

This does not create any more complicated objects, just a matrix. In some 
cases, the rows in the matrix are ordered S -> N, so it may appear the 
wrong way up.

rgdal::getRasterData() is lightweight, and has many arguments which may be 
helpful. rgdal::readGDAL() is heavyweight, creating a SpatialGridDataFrame 
object. This involves much copying of data, but the output object can be 
used for example in mapping or analysis without further conversion. My 
guess is that rgdal::getRasterData() gives you your matrix directly. Look 
at the R code to see how as.is= etc. work (files may include scale and 
offset values - recently a user was confused that scale and offset were 
"magically" applied to convert Uint16 values to degrees Kelvin on 
reading). For example, if as.is == TRUE or scale == 1 and offset == 0, no 
copying of the input matrix occurs because it is not converted. If you 
could check this route, others following this thread could also benefit; 
if I'm wrong, that would also be good to know.

Roger


>
> Best,
>
> Thorsten
>
>
>
> Am 27.04.2020 um 15:58 schrieb Michael Sumner:
>> Try stars it worked for me on a test
>>
>> On Mon., 27 Apr. 2020, 23:54 Thorsten Behrens,
>> <thorsten.m.behrens using gmail.com <mailto:thorsten.m.behrens using gmail.com>>
>> wrote:
>>
>>     Roger,
>>
>>     thanks a lot for your reply!
>>
>>     I have 256GB RAM installed (mentioned it somewhere). And there,
>>     all is
>>     fine when I run:
>>
>>     rDemTest = raster(nrow = 48000, ncol = 72000, ext = extent(c(0, 72000,
>>
>>     values(rDemTest) = 1
>>
>>     When limiting the memory to about 8GB with
>>     ulimit::memory_limit(8000),
>>     the max size which can be allocated seems to be around 10000 x
>>     10000px.
>>     In this case all tests run fine. Unfortunately it seems to be
>>     related to
>>     the size of the grid (48000 x 72000) and therefore the problem
>>     can't be
>>     reproduced on machines with 8GB RAM. For some processing steps I need
>>     grids of that size in the memory, which is why I have 256 GB
>>     installed.
>>
>>     Normally, I use the raster package and not rgdal::readGDAL(). This
>>     was
>>     just a desperate attempt to find the source of the problem.
>>
>>     This is what I use in my code:
>>
>>     rDem = raster(sFileNameTiff)
>>     mDem = raster::as.matrix(rDem)
>>
>>     But maybe this is the same...
>>
>>     Any further suggestions are much appreciated!
>>
>>     Thanks again!
>>
>>     Best,
>>
>>     Thorsten
>>
>>
>>
>>
>>     Am 27.04.2020 um 14:50 schrieb Roger Bivand:
>>    > On Mon, 27 Apr 2020, Thorsten Behrens wrote:
>>    >
>>    >> Dear all,
>>    >>
>>    >> my problem is that I want to read a big geotiff raster dataset
>>     into R
>>    >> and convert it to a matrix, which does not work.
>>    >> The file is big but there is sufficient memory. I need all the
>>     data
>>    >> in the memory at the same time.
>>    >>
>>    >> The error occurs under R 3.6.3 as well as 4.0.0 using Ubuntu 20.04
>>    >> LTS with the latest version of the packages (see session info
>>     below)
>>    >> and 256GB RAM installed.
>>    >>
>>    >> When loading the raster dataset using rgdal (via readGDAL or
>>    >> raster::readAll) I get the follwoing error in R 4.0.0:
>>    >>
>>    >> ```
>>    >> Error in rgdal::getRasterData(con, offset = offs, region.dim =
>>     reg,
>>    >> band = object using data@band) :
>>    >>   long vectors not supported yet: memory.c:3782
>>    >> ```
>>    >
>>    > On a 16GB Fedora platform:
>>    >
>>    >> library(raster) # 3.1-5
>>    >> rDemTest = raster(nrow = 48000, ncol = 72000, ext = extent(c(0,
>>     72000,
>>    > 0,
>>    > + 48000))) # all fine
>>    >> rDemTest
>>    > class      : RasterLayer
>>    > dimensions : 48000, 72000, 3.456e+09  (nrow, ncol, ncell)
>>    > resolution : 1, 1  (x, y)
>>    > extent     : 0, 72000, 0, 48000  (xmin, xmax, ymin, ymax)
>>    > crs        : NA
>>    >
>>    >> values(rDemTest) = 1
>>    > Error: cannot allocate vector of size 25.7 Gb
>>    >
>>    > So you are deceiving yourself into thinking that all is fine at
>>     this
>>    > point. Please try to instantiate an example that can be
>>     reproduced on
>>    > a machine with 8GB RAM.
>>    >
>>    > Further note that rgdal::readGDAL() is not how you handle very
>>     large
>>    > objects in files, and never has been. raster can handle blocks
>>     of data
>>    > from bands in file; stars and gdalcubes can use proxy=TRUE for the
>>    > same purpose. Why did you choose rgdal::readGDAL() when this is not
>>    > its purpose?
>>    >
>>    > You did not say how much RAM is on your platform.
>>    >
>>    > Roger
>>    >
>>    >>
>>    >> In R 3.6.3 is is "... memory.c:3717"
>>    >>
>>    >> However, I can load the same file with the tiff package and a
>>     file of
>>    >> the same size in the native raster package format (*.grd) with the
>>    >> raster package but again not with the rgdal package.
>>    >>
>>    >> gdalinfo (gdalUtils) does not complain (see below). Hence, Even
>>    >> Rouault assumes the problem is related to rgdal and not gdal
>>    >> (https://github.com/OSGeo/gdal/issues/2442).
>>    >>
>>    >> Below you find reproducible code, which generates a raster file,
>>    >> saves the two formats (.tiff and .grd) and tries to read them with
>>    >> the different packages.
>>    >>
>>    >> Is this a known limitation? Any help is greatly appreciated!
>>    >>
>>    >> Thanks a lot in advance!
>>    >>
>>    >> Best wishes and stay healthy,
>>    >> Thorsten
>>    >>
>>    >>
>>    >>
>>    >> ### Steps to reproduce the problem.
>>    >>
>>    >> R code:
>>    >>
>>    >> ```
>>    >> library(rgdal) # 1.4-8
>>    >> library(raster) # 3.1-5
>>    >> library(tiff) # 0.1-5
>>    >>
>>    >> ## generate and manipulate a big raster dataset
>>    >> # - generate
>>    >> rDemTest = raster(nrow = 48000, ncol = 72000, ext = extent(c(0,
>>    >> 72000, 0, 48000))) # all fine
>>    >>
>>    >> # - manipulate
>>    >> values(rDemTest) = 1 # all fine
>>    >>
>>    >> # - convert
>>    >> mDemTest = raster::as.matrix(rDemTest) # all fine
>>    >> str(mDemTest)
>>    >>
>>    >> ## save a big dataset
>>    >>
>>    >> # - as raster/gdal
>>    >> sFileNameTiff = "BigData.tif"
>>    >> writeRaster(rDemTest, sFileNameTiff, "GTiff", overwrite = TRUE,
>>    >> NAflag = -9999) # all fine
>>    >>
>>    >> # - as raster native
>>    >> sFileNameNative = "BigData.grd"
>>    >> writeRaster(rDemTest, sFileNameNative, "raster", overwrite = TRUE,
>>    >> NAflag = -9999) # all fine
>>    >>
>>    >>
>>    >> ## load the big raster datasets with different packages and options
>>    >> # - load the tiff data with the gdal package via the raster package
>>    >> rDem = raster(sFileNameTiff) # all fine
>>    >> extent(rDem) # all fine
>>    >> mDem = raster::as.matrix(rDem) # error
>>    >> rDem = readAll(rDem) # error
>>    >>
>>    >> # - load the native raster data with the raster package
>>    >> rDem = raster(sFileNameNative) # all fine
>>    >> extent(rDem) # all fine
>>    >> mDem = raster::as.matrix(rDem) # all fine
>>    >> str(mDem)
>>    >>
>>    >> # - load the tiff data with the tiff package
>>    >> mDem = readTIFF(sFileNameTiff) # all fine
>>    >> str(mDem)
>>    >>
>>    >> # - load the tiff data with the gdal package
>>    >> sfDem = readGDAL(sFileNameTiff) # error
>>    >>
>>    >> # - load the native raster data with the gdal package
>>    >> sfDem = readGDAL(sFileNameNative) # error
>>    >>
>>    >> ```
>>    >>
>>    >>
>>    >> ### Startup messages when rgdal is attached (requested by Roger
>>     Bivand)
>>    >>>  library(rgdal)
>>    >> rgdal: version: 1.4-8, (SVN revision 845)
>>    >>  Geospatial Data Abstraction Library extensions to R
>>     successfully loaded
>>    >>  Loaded GDAL runtime: GDAL 3.0.4, released 2020/01/28
>>    >>  Path to GDAL shared files:
>>    >>  GDAL binary built with GEOS: TRUE
>>    >>  Loaded PROJ.4 runtime: Rel. 6.3.1, February 10th, 2020,
>>     [PJ_VERSION:
>>    >> 631]
>>    >>  Path to PROJ.4 shared files: (autodetected)
>>    >>  Linking to sp version: 1.4-1
>>    >>
>>    >>
>>    >> ### Session info
>>    >>>  sessionInfo()
>>    >> R version 4.0.0 (2020-04-24)
>>    >> Platform: x86_64-pc-linux-gnu (64-bit)
>>    >> Running under: Ubuntu 20.04 LTS
>>    >>
>>    >> Matrix products: default
>>    >> BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
>>    >> LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/liblapack.so.3
>>    >>
>>    >> locale:
>>    >>  [1] LC_CTYPE=de_DE.UTF-8       LC_NUMERIC=C LC_TIME=de_DE.UTF-8
>>    >>  [4] LC_COLLATE=de_DE.UTF-8 LC_MONETARY=de_DE.UTF-8
>>    >> LC_MESSAGES=de_DE.UTF-8
>>    >>  [7] LC_PAPER=de_DE.UTF-8       LC_NAME=C LC_ADDRESS=C
>>    >> [10] LC_TELEPHONE=C LC_MEASUREMENT=de_DE.UTF-8
>>    >> LC_IDENTIFICATION=C
>>    >>
>>    >> attached base packages:
>>    >> [1] stats     graphics  grDevices utils     datasets methods base
>>    >>
>>    >> other attached packages:
>>    >> [1] gdalUtils_2.0.3.2 rgdal_1.4-8       tiff_0.1-5 raster_3.1-5
>>    >> sp_1.4-1
>>    >>
>>    >> loaded via a namespace (and not attached):
>>    >>  [1] compiler_4.0.0    tools_4.0.0       Rcpp_1.0.4.6
>>    >> R.methodsS3_1.8.0 codetools_0.2-16
>>    >>  [6] grid_4.0.0        iterators_1.0.12 foreach_1.5.0
>>    >> R.utils_2.9.2     R.oo_1.23.0
>>    >> [11] lattice_0.20-41
>>    >>
>>    >>
>>    >> ### gdalInfo
>>    >>>  gdalinfo(sFileNameTiff)
>>    >>  [1] "Driver: GTiff/GeoTIFF"
>>    >>  [2] "Files: BigData.tif"
>>    >>  [3] "Size is 72000, 48000"
>>    >>  [4] "Origin = (0.000000000000000,48000.000000000000000)"
>>    >>  [5] "Pixel Size = (1.000000000000000,-1.000000000000000)"
>>    >>  [6] "Image Structure Metadata:"
>>    >>  [7] "  COMPRESSION=LZW"
>>    >>  [8] "  INTERLEAVE=BAND"
>>    >>  [9] "Corner Coordinates:"
>>    >> [10] "Upper Left  (       0.000,   48000.000) "
>>    >> [11] "Lower Left  (   0.0000000,   0.0000000) "
>>    >> [12] "Upper Right (   72000.000,   48000.000) "
>>    >> [13] "Lower Right (   72000.000,       0.000) "
>>    >> [14] "Center      (   36000.000,   24000.000) "
>>    >> [15] "Band 1 Block=72000x1 Type=Float32, ColorInterp=Gray"
>>    >> [16] "  Min=1.000 Max=1.000 "
>>    >> [17] "  Minimum=1.000, Maximum=1.000, Mean=nan, StdDev=nan"
>>    >> [18] "  NoData Value=-9999"
>>    >> [19] "  Metadata:"
>>    >> [20] "    STATISTICS_MAXIMUM=1"
>>    >> [21] "    STATISTICS_MEAN=nan"
>>    >> [22] "    STATISTICS_MINIMUM=1"
>>    >> [23] "    STATISTICS_STDDEV=nan"
>>    >>
>>    >> _______________________________________________
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>>    >>
>>    >>
>>    >
>>
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-- 
Roger Bivand
Department of Economics, Norwegian School of Economics,
Helleveien 30, N-5045 Bergen, Norway.
voice: +47 55 95 93 55; e-mail: Roger.Bivand using nhh.no
https://orcid.org/0000-0003-2392-6140
https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en


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