[gdal-dev] Filesize too large when writing compressed float's to a Geotiff from Python

[Even Rouault]

> It makes sense that the order in which the data is written/stored affects
> the performance of the compression, but i don't get why it would be
> different for integers as compared to floats?

Floats are larger than Int8 and Int16, so for the same amount of 
GDAL_CACHEMAX, you can cache less blocks, causing more temporary flushes of 
partial tiles/strips to disk (partial = that have data only for one or two 
bands, but not the 3), than need to be refetched when data for the remaining 
bands is available and then recompressed and rewritten.

> 
> 
> Regards,
> Rutger
> 
> 
> 
> 
> Even Rouault-2 wrote
> 
> > Le mercredi 03 juin 2015 15:21:07, Rutger a écrit :
> > 
> > Rutger,
> > 
> > the issue is that you write data band after band, whereas by default the
> > GTiff
> > driver create pixel-interleaved datasets. So some blocks in the GTiff
> > might be
> > reread and rewritten several times as the data coming from the various
> > bands
> > come.
> > 
> > Several fixes/workarounds :
> > - if you've sufficient RAM to hold another copy of the uncompressed
> > dataset,
> > increase GDAL_CACHEMAX
> > - or add options = [ 'INTERLEAVE=BAND' ] in the Create() call to create a
> > band
> > interleaved dataset
> > - more involved fix: since there's no dataset WriteArray() in GDAL Python
> > for
> > now, you would have to iterate block by block and for each block write
> > the corresponding region of each band.
> > - you could also use Dataset.WriteRaster() if you can get a buffer from
> > the
> > numpy array
> > 
> > Even
> 
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