Computation complexity in relation to the number of *.laz files vs total size of *.laz files

[Mboga]

Thank you for your response to question I raised before.

I had a look at your Foss4G presentation in 2016, and at minute 15:08 and 15:25, list the point cloud characteristics and infrastructure, respectively used to create the entwine database using AHN of the Netherlands.

I wanted to seek a clarification on computation complexity and how much time it takes to build an entwine database. I understand that I can use the subsetoption in the entwine build command.

I will use an example to make my point. Consider that I have a dataset that has 41000 .laz files organized in regular grids, and say 1.5TB How would the processing time and computation complexity increase if- A) The same dataset was instead available as 410000 laz files?

B) If I had second dataset that was 3 TB, would it be advisable to reduce the number of *.laz files before building the entwine database?

In other words, I would like to understand how the processing time and computation complexity increase based on the number of .laz files and the total size of the input .laz files.

Thank you

[Mboga]

Here is the link to the Foss4G presentation 2016 https://ftp.gwdg.de/pub/misc/openstreetmap/FOSS4G-2016/foss4g-2016-1204-500_billion_points_organizing_point_clouds_as_infrastructure-hd.mp4

[connormanning]

I'd expect this to have very little or no impact on performance but you would be best off trying a representative subset from your own dataset.