Hi,
You send new mails faster than I can read and understand the previous ones but
here comes some quick comments.
* The gdalbuildvrt command looks good but it would be kind to tell which
file is international and which one is UK. It is not obvious to me by the paths
/5/ and /3/. You want to write the international file first into the VRT and UK
after that to suit your workflow.
* This does not make sense: gdal_translate /data/coastal-2020.vrt
/data/3/coastal-2020.tif /data/5/coastal-2020.tif. gdal_translate needs one
input and one output, so: gdal_translate /data/coastal-2020.vrt output.tif
* I think that gdal_translate does not have option -n
* NUM_THREADS=ALL_CPUS is not a creation option -co, but an open option
-oo, or it can be used as a configuration option
* It may be that -co BLOCKXSIZE=128 -co BLOCKYSIZE=128 can really be used
without -co TILED=YES. I have never tried. It is still essential that the
output is tiled.
* Without testing I am not sure if the issues above make the input rubbish
but it is possible.
* Your second and third trials are doomed to do something else than what
you want very soon: gdalwarp -r near -overwrite. Overwrite switch means that
the existing outputfile will be deleted and a new one with the same name will
be created. You wanted just update the target file so don't use -overwrite. And
when you use an existing file as a target the creation options have no effect;
the target file is already created with some options.
* Now you understand why The output is: 18376, 17086 not 450000, 225000.
(if not I can give a hint: what file did the -overwrite delete?)
I suppose that you start getting frustrated because testing all kind of random
commands with huge images takes a long time ("The AWS Instance with over 60
VCPU ran for over 8 hours"). However, you could have made all your mistakes
much faster with much smaller files (1000 by 1000 pixels for example). Make the
commands work with small images and when you are satisfied test them with
bigger images. That said, I cannot promise that you will have good performance
with updating 450000, 225000 sized LZW compressed GeoTIFF. I have never tried
anything like that with such a big image myself.
-Jukka Rahkonen-
Lähettäjä: gdal-dev <gdal-dev-boun...@lists.osgeo.org> Puolesta Clive Swan
Lähetetty: keskiviikko 14. joulukuuta 2022 18.34
Vastaanottaja: gdal-dev@lists.osgeo.org
Aihe: Re: [gdal-dev] gdalwarp running very slow
I want to APPEND the UK data into the international.tif
The updated international size should also be: 450000, 225000
I first tried
gdalbuildvrt -o /data/coastal-2020.vrt /vsis3/summer/3/coastal-2020.tif
/vsis3/summer/5/coastal-2020.tif
gdal_translate /data/coastal-2020.vrt /data/3/coastal-2020.tif
/data/5/coastal-2020.tif -n -9999 -co BIGTIFF=YES -co COMPRESS=LZW -co
BLOCKXSIZE=128 -co BLOCKYSIZE=128 -co NUM_THREADS=ALL_CPUS --config
CPL_VSIL_USE_TEMP_FILE_FOR_RANDOM_WRITE YES --config
The output was rubbish
The UK image size is: 18376, 17086
The international size is: 450000, 225000
I tried
/data/3/coastal-2020-test.tif = 7GB
/data/5/coastal-2020.tif = 700MB
gdalwarp -r near -overwrite /data/3/coastal-2020.tif
/data/3/coastal-2020-test1.tif -co BIGTIFF=YES -co COMPRESS=LZW -co
BLOCKXSIZE=128 -co BLOCKYSIZE=128 -co NUM_THREADS=ALL_CPUS -co PREDICTOR=3
--config CPL_VSIL_USE_TEMP_FILE_FOR_RANDOM_WRITE YES & disown -h
The AWS Instance with over 60 VCPU ran for over 8 hours
I tried:
/data/5/coastal-2020.tif = 700MB
/data/3/coastal-2020-test.tif = 7GB
gdalwarp -r near -overwrite /data/5/coastal-2020.tif
/data/3/coastal-2020-test.tif -co BIGTIFF=YES -co COMPRESS=LZW -co
BLOCKXSIZE=128 -co BLOCKYSIZE=128 -co NUM_THREADS=ALL_CPUS -co PREDICTOR=3
--config CPL_VSIL_USE_TEMP_FILE_FOR_RANDOM_WRITE YES
The output is: 18376, 17086 not 450000, 225000
Any assistance appreciated
Thanks
Clive
On Wed, 14 Dec 2022 at 09:23, Rahkonen Jukka
<jukka.rahko...@maanmittauslaitos.fi<mailto:jukka.rahko...@maanmittauslaitos.fi>>
wrote:
Hi,
I don't mean that you should try this and that blindly but to describe what
data you have in your hands and what you are planning to do with it so that the
other GDAL users could consider what reasonable alternatives you could have. I
have never done anything that is even close to your use case but due to other
experience I can see potential issues in a few places:
* You try to update image A that has a size 450000 by 225000 pixels with
image B that has the same size. The result would be A updated into a full copy
of B if all pixels in B are valid.
* However, image B probably has very much NoData (we do not know because
you have not told that) and if GDAL deals with NoData correctly the result
would be A updated with valid pixels from B and that is probably what is
desired.
* However, we do not know how effectively GDAL skips the nodata pixels of
B. It may be fast or not. If we know that most part of the world is NoData it
might be good to crop image B to include just the area where there is data.
That's maybe UK in your case. If skipping the NoData is fast then cropping
won't give speedup but it is cheap to test.
* You have compressed images. LZW algorithm is compressing some data more
effectively than some other. If you expect that you can replace a chunk of LZW
compressed data inside a TIFF file with another chunk of LZW compressed data in
place you are wrong. The new chunk of data may be larger and it just cannot fit
into the same space. Assumption that updating a 6 GB image with 600 MB new data
would yield a 6 GB image is not correct with compressed data.
* I can imagine that there could be other technical reasons to write the
replacing data at the end of the existing TIFF and update the image
directories. If the image size is critical it may require re-writing the
updated TIFF into a new TIFF file. The complete re-write can be done in most
optimal way. See this wiki page
https://trac.osgeo.org/gdal/wiki/UserDocs/GdalWarp#GeoTIFFoutput-coCOMPRESSisbroken<https://eur06.safelinks.protection.outlook.com/?url=https%3A%2F%2Ftrac.osgeo.org%2Fgdal%2Fwiki%2FUserDocs%2FGdalWarp%23GeoTIFFoutput-coCOMPRESSisbroken&data=05%7C01%7Cjukka.rahkonen%40maanmittauslaitos.fi%7C5b67ce172b5b4c48990108daddf10a33%7Cc4f8a63255804a1c92371d5a571b71fa%7C0%7C0%7C638066324581688598%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=JyLbYpMyvjON3BsPZ9INgBNAy8DUGMwrJ2TVv6%2BhGHY%3D&reserved=0>
* If the images are in AWS it is possible that the process should be
somehow different than with local images. I have no experience about AWS yet.
* A 450000 by 225000 image is rather big. It is possible that it would be
faster to split the image into smaller parts, update the parts that need
updating, and combine the parts back into a big image. Or keep the parts and
combine them virtually with gdalbuildvrt into VRT.
Your use case is not so usual and it is rather heavy but there are certainly
several ways to do what you want. What should be avoided it to select an
inefficient method and try to optimize it.
Good luck with your experiments,
-Jukka-
Lähettäjä: Clive Swan <clives...@gmail.com<mailto:clives...@gmail.com>>
Lähetetty: keskiviikko 14. joulukuuta 2022 10.29
Vastaanottaja: Rahkonen Jukka
<jukka.rahko...@maanmittauslaitos.fi<mailto:jukka.rahko...@maanmittauslaitos.fi>>
Aihe: Re: [gdal-dev] gdalwarp running very slow
Hi Jukka,
Thanks for that, was really stressed.
I will export the UK extent, and rerun the script.
Thanks
Clive
Sent from Outlook for
Android<https://eur06.safelinks.protection.outlook.com/?url=https%3A%2F%2Faka.ms%2FAAb9ysg&data=05%7C01%7Cjukka.rahkonen%40maanmittauslaitos.fi%7C5b67ce172b5b4c48990108daddf10a33%7Cc4f8a63255804a1c92371d5a571b71fa%7C0%7C0%7C638066324581688598%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=VrXwCU6Hs%2FdjSHmxQBVIXJI30tUikSCe36HZaTNpiYA%3D&reserved=0>
________________________________
From: Rahkonen Jukka
<jukka.rahko...@maanmittauslaitos.fi<mailto:jukka.rahko...@maanmittauslaitos.fi>>
Sent: Wednesday, December 14, 2022 7:18:50 AM
To: Clive Swan <clives...@gmail.com<mailto:clives...@gmail.com>>;
gdal-dev@lists.osgeo.org<mailto:gdal-dev@lists.osgeo.org>
<gdal-dev@lists.osgeo.org<mailto:gdal-dev@lists.osgeo.org>>
Subject: Re: [gdal-dev] gdalwarp running very slow
Hi,
Thank you for the information about the source files. I do not yet understand
what you are trying to do and why. The both images have the same size 450000
and 225000 and they cover the same area. Is the "image 5_UK_coastal-2020.tif"
just NoData with pixel value -9999 everywhere outside the UK? The name of the
image makes me think so.
-Jukka Rahkonen-
Lähettäjä: Clive Swan <clives...@gmail.com<mailto:clives...@gmail.com>>
Lähetetty: tiistai 13. joulukuuta 2022 19.22
Vastaanottaja: gdal-dev@lists.osgeo.org<mailto:gdal-dev@lists.osgeo.org>
Kopio: Rahkonen Jukka
<jukka.rahko...@maanmittauslaitos.fi<mailto:jukka.rahko...@maanmittauslaitos.fi>>
Aihe: [gdal-dev] gdalwarp running very slow
Greetings,
I am using the same files, I copied them from an AWS Bucket to a local AWS
Instance.
I tried gdal_merge << tries to create 300GB file
I tried gdal_translate ran but created 2.5 GB not 6.9 GB file
Now trying gdalwarp.
the gdalinfo is the same in both datasets:
coastal-2020.tif (6.9GB)
Driver: GTiff/GeoTIFF
Size is 450000, 225000
Coordinate System is:
GEOGCRS["WGS 84",
DATUM["World Geodetic System 1984",
ELLIPSOID["WGS 84",6378137,298.257223563,
LENGTHUNIT["metre",1]]],
PRIMEM["Greenwich",0,
ANGLEUNIT["degree",0.0174532925199433]],
CS[ellipsoidal,2],
AXIS["geodetic latitude (Lat)",north,
ORDER[1],
ANGLEUNIT["degree",0.0174532925199433]],
AXIS["geodetic longitude (Lon)",east,
ORDER[2],
ANGLEUNIT["degree",0.0174532925199433]],
ID["EPSG",4326]]
Data axis to CRS axis mapping: 2,1
Origin = (-180.000000000000000,90.000000000000000)
Pixel Size = (0.000800000000000,-0.000800000000000)
Metadata:
AREA_OR_POINT=Area
datetime_created=2022-11-14 18:05:14.053301
Image Structure Metadata:
COMPRESSION=LZW
INTERLEAVE=BAND
PREDICTOR=3
Corner Coordinates:
Upper Left (-180.0000000, 90.0000000) (180d 0' 0.00"W, 90d 0' 0.00"N)
Lower Left (-180.0000000, -90.0000000) (180d 0' 0.00"W, 90d 0' 0.00"S)
Upper Right ( 180.0000000, 90.0000000) (180d 0' 0.00"E, 90d 0' 0.00"N)
Lower Right ( 180.0000000, -90.0000000) (180d 0' 0.00"E, 90d 0' 0.00"S)
Center ( 0.0000000, 0.0000000) ( 0d 0' 0.01"E, 0d 0' 0.01"N)
Band 1 Block=128x128 Type=Float32, ColorInterp=Gray
Description = score
NoData Value=-9999
Band 2 Block=128x128 Type=Float32, ColorInterp=Undefined
Description = severity_value
NoData Value=-9999
Band 3 Block=128x128 Type=Float32, ColorInterp=Undefined
Description = severity_min
NoData Value=-9999
Band 4 Block=128x128 Type=Float32, ColorInterp=Undefined
Description = severity_max
NoData Value=-9999
Band 5 Block=128x128 Type=Float32, ColorInterp=Undefined
Description = likelihood
NoData Value=-9999
Band 6 Block=128x128 Type=Float32, ColorInterp=Undefined
Description = return_time
NoData Value=-9999
Band 7 Block=128x128 Type=Float32, ColorInterp=Undefined
Description = likelihood_confidence
NoData Value=-9999
Band 8 Block=128x128 Type=Float32, ColorInterp=Undefined
Description = climate_reliability
NoData Value=-9999
Band 9 Block=128x128 Type=Float32, ColorInterp=Undefined
Description = hazard_reliability
NoData Value=-9999
5_UK_coastal-2020.tif (600MB)
Driver: GTiff/GeoTIFF
Size is 450000, 225000
Coordinate System is:
GEOGCRS["WGS 84",
DATUM["World Geodetic System 1984",
ELLIPSOID["WGS 84",6378137,298.257223563,
LENGTHUNIT["metre",1]]],
PRIMEM["Greenwich",0,
ANGLEUNIT["degree",0.0174532925199433]],
CS[ellipsoidal,2],
AXIS["geodetic latitude (Lat)",north,
ORDER[1],
ANGLEUNIT["degree",0.0174532925199433]],
AXIS["geodetic longitude (Lon)",east,
ORDER[2],
ANGLEUNIT["degree",0.0174532925199433]],
ID["EPSG",4326]]
Data axis to CRS axis mapping: 2,1
Origin = (-180.000000000000000,90.000000000000000)
Pixel Size = (0.000800000000000,-0.000800000000000)
Metadata:
AREA_OR_POINT=Area
datetime_created=2022-11-14 18:05:14.053301
hostname=posix.uname_result(sysname='Linux', nodename='ip-172-31-12-125',
release='5.15.0-1022-aws', version='#26~20.04.1-Ubuntu SMP Sat Oct 15 03:22:07
UTC 2022', machine='x86_64')
Image Structure Metadata:
COMPRESSION=LZW
INTERLEAVE=BAND
PREDICTOR=3
Corner Coordinates:
Upper Left (-180.0000000, 90.0000000) (180d 0' 0.00"W, 90d 0' 0.00"N)
Lower Left (-180.0000000, -90.0000000) (180d 0' 0.00"W, 90d 0' 0.00"S)
Upper Right ( 180.0000000, 90.0000000) (180d 0' 0.00"E, 90d 0' 0.00"N)
Lower Right ( 180.0000000, -90.0000000) (180d 0' 0.00"E, 90d 0' 0.00"S)
Center ( 0.0000000, 0.0000000) ( 0d 0' 0.01"E, 0d 0' 0.01"N)
Band 1 Block=128x128 Type=Float32, ColorInterp=Gray
Description = score
NoData Value=-9999
Band 2 Block=128x128 Type=Float32, ColorInterp=Undefined
Description = severity_value
NoData Value=-9999
Band 3 Block=128x128 Type=Float32, ColorInterp=Undefined
Description = severity_min
NoData Value=-9999
Band 4 Block=128x128 Type=Float32, ColorInterp=Undefined
Description = severity_max
NoData Value=-9999
Band 5 Block=128x128 Type=Float32, ColorInterp=Undefined
Description = likelihood
NoData Value=-9999
Band 6 Block=128x128 Type=Float32, ColorInterp=Undefined
Description = return_time
NoData Value=-9999
Band 7 Block=128x128 Type=Float32, ColorInterp=Undefined
Description = likelihood_confidence
NoData Value=-9999
Band 8 Block=128x128 Type=Float32, ColorInterp=Undefined
Description = climate_reliability
NoData Value=-9999
Band 9 Block=128x128 Type=Float32, ColorInterp=Undefined
Description = hazard_reliability
NoData Value=-9999
--
Regards,
Clive Swan
--
Hi,
If you are still struggling with the same old problem could you please finally
send the gdalinfo reports of your two input files which are this time:
coastal-2020.tif
5_UK_coastal-2020.tif
-Jukka Rahkonen-
Lähettäjä: gdal-dev <gdal-dev-bounces at
lists.osgeo.org<https://eur06.safelinks.protection.outlook.com/?url=https%3A%2F%2Flists.osgeo.org%2Fmailman%2Flistinfo%2Fgdal-dev&data=05%7C01%7Cjukka.rahkonen%40maanmittauslaitos.fi%7C5b67ce172b5b4c48990108daddf10a33%7Cc4f8a63255804a1c92371d5a571b71fa%7C0%7C0%7C638066324581688598%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=ksdZuGTu2MsFwMcQTQT1XXt4v8JHhDTDgbVbna0zfoA%3D&reserved=0>>
Puolesta Clive Swan
Lähetetty: tiistai 13. joulukuuta 2022 17.23
Vastaanottaja: gdal-dev at
lists.osgeo.org<https://eur06.safelinks.protection.outlook.com/?url=https%3A%2F%2Flists.osgeo.org%2Fmailman%2Flistinfo%2Fgdal-dev&data=05%7C01%7Cjukka.rahkonen%40maanmittauslaitos.fi%7C5b67ce172b5b4c48990108daddf10a33%7Cc4f8a63255804a1c92371d5a571b71fa%7C0%7C0%7C638066324581688598%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=ksdZuGTu2MsFwMcQTQT1XXt4v8JHhDTDgbVbna0zfoA%3D&reserved=0>
Aihe: [gdal-dev] gdalwarp running very slow
Greetings,
I am running gdalwarp on a 6GB (output) and 600MB (input) tif image, the AWS
Instance has approx 60 VCPU
It has taken over 6 hours so far - still running, is it possible to optimise
this and speed it up??
gdalwarp -r near -overwrite coastal-2020.tif 5_UK_coastal-2020.tif -co
BIGTIFF=YES -co COMPRESS=LZW -co BLOCKXSIZE=128 -co BLOCKYSIZE=128 -co
NUM_THREADS=ALL_CPUS --config CPL_VSIL_USE_TEMP_FILE_FOR_RANDOM_WRITE YES
--
Regards,
Clive Swan
--
M: +44 7766 452665
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