[pdal] Memory management with PDAL/Docker

[Andrew Bell]

This isn't surprising.  150 million points at even 30 bytes per point (and
it's more than 30 bytes per point) is 4.5 gig.  Until the EPT reader
supports stream mode, you're not going to be able to get around this
limitation with PDAL.  There are no EPT options you can set that will
change this.

On Mon, Apr 1, 2019 at 9:26 AM Matt Beckley <beckley at unavco.org> wrote:

> Is there a way to optimize docker or PDAL to be able to run larger queries
> on ept files?  Or Is there some info about memory management, or some
> settings I should be using to facilitate larger queries?  I have been
> trying to run a test on the JSON pipeline below, and I am only able to get
> it to run successfully if I set my docker memory to over 6GB....anything
> less than 6GB will fail.  When successfully run, the resulting LAZ file is
> only about 150 million points - so, not huge by lidar standards.    I've
> tried increasing the "threads" keyword to the ept reader, but that didn't
> seem to help.
>
> {
>     "pipeline": [{
>         "type": "readers.ept",
>         "filename": "
> https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_HI_Oahu_2012_LAS_2015
> ",
>         "bounds": "([-17606581.532235783,
> -17598784.955350697],[2441398.6834285296,2448889.512200477])"
>     },
>     {
>         "type" : "writers.las",
>         "filename": "HI_LargeOutput_Local.laz"
>     }]}
>
> Any ideas would be appreciated.
>
> Thanks!
>
> matt.
> ---------------------------
> Matthew Beckley
> Data Engineer
> UNAVCO/OpenTopography
> beckley at unavco.org
> 303-381-7487
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-- 
Andrew Bell
andrew.bell.ia at gmail.com
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