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  • darothen · 2 ✖

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  • Chunked processing across multiple raster (geoTIF) files · 2 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
666422864 https://github.com/pydata/xarray/issues/2314#issuecomment-666422864 https://api.github.com/repos/pydata/xarray/issues/2314 MDEyOklzc3VlQ29tbWVudDY2NjQyMjg2NA== darothen 4992424 2020-07-30T14:52:50Z 2020-07-30T14:52:50Z NONE

Hi @shaprann, I haven't re-visited this exact workflow recently, but one really good option (if you can manage the intermediate storage cost) would be to try to use new tools like http://github.com/pangeo-data/rechunker to pre-process and prepare your data archive prior to analysis. 

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   Chunked processing across multiple raster (geoTIF) files 344621749
417175383 https://github.com/pydata/xarray/issues/2314#issuecomment-417175383 https://api.github.com/repos/pydata/xarray/issues/2314 MDEyOklzc3VlQ29tbWVudDQxNzE3NTM4Mw== darothen 4992424 2018-08-30T03:09:41Z 2018-08-30T03:09:41Z NONE

Can you provide a gdalinfo of one of the GeoTiffs? I'm still working on some documentation for use-cases with cloud-optimized GeoTiffs to supplement @scottyhq's fantastic example notebook. One of the wrinkles I'm tracking down and trying to document is when exactly the GDAL->rasterio->dask->xarray pipeline eagerly load the entire file versus when it defers reading or reads subsets of files. So far, it seems that if the GeoTiff is appropriately chunked ahead of time (when it's written to disk), things basically work "automagically."

 
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   Chunked processing across multiple raster (geoTIF) files 344621749

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