This new part of the series focuses on the use of fast compressors such as
Snappy to improve access speed to image data:
https://medium.com/@p.rozas.larraondo/divide-compress-and-conquer-building-an-earth-data-server-in-go-part-2-88670cafc167
IMO fast compressors will play a very important role i
To consider for your series, at some point down the line:
There are standards for serving geo-located tiles, and if you match one of
them, your little Go program can serve tiles to already existing map
browsers, from Javascript based slippy-maps, to Android or iOS street-map
viewers, to full G
Certainly as you say, individual user patterns are not generally
predictable. Sometimes aggregate patterns can be. The "sea of tiles" is the
natural design and works great in normal cases. It seems the way to teach
it in any case.
Where the filesystem issue comes in would be, for example, the nomi
Hi Michael,
Thanks for your comments, I totally agree with them. File systems will
struggle with the explosion of files resulting from the tile operation. As
you point out, other formats, such as geoTIFF, HDF5 or NetCDF define the
tiling or chunking process internally at the file level.
The
Thank you, Pablo. Very helpful to have this kind of step by step example
for Go developers.
I have some familiarity in this area and I'd say the practical issues in
large-scale, high-throughput operation tend to relate to the native
filesystem. Too many small files overwhelm them and can make dire
Thank you Thomas for the link to the vips library. I didn't know about it
and now I want to read more about its design and internals.
The objective of the article was to set a baseline using the Go image
library and play with several factors to see how it affects performance. In
this first arti
Interesting and nice pieces of code. I wonder if the performances can be
compared to something like `vips` (https://jcupitt.github.io/libvips).
Le lundi 18 décembre 2017 22:51:49 UTC+1, Pablo Rozas Larraondo a écrit :
>
> Hi,
>
> For those interested on serving or using satellite imagery, I've ju
