Contents
What should I do if my KML is too big?
Consider it an upgrade to KML without having to drastically modify the front-end. You can break down your KML in to multiple KML’s with a Parent KML referencing the smaller kmls. At least this will bring your file sizes down to a respectable level and allow you to reference much larger datasets as KML’s.
How to make KML files smaller by reducing precision?
Simply discarding unnecessary decimal places reduces the file size by almost half. We also show the effects of using the KMZ format. We thought that other people with large KML files might find the idea useful. So, below is a JavaScript tool that will take a KML file and reduce the precision of the latitudes and longitudes.
How are KML files used in Google Earth?
KML is a file format used to display geographic data in a tool such as Google Earth or Google Maps. For shapefile versions of these files, please see our Cartographic Boundary Files – Shapefile page. For more details about these files, please see our Cartographic Boundary File Description page.
How many decimal places in a KML file?
For our KML file five decimal places should be more than enough. As you can see below, the results were quite impressive. Simply discarding unnecessary decimal places reduces the file size by almost half.
Can a KML be referenced to multiple KML’s?
You can break down your KML in to multiple KML’s with a Parent KML referencing the smaller kmls. At least this will bring your file sizes down to a respectable level and allow you to reference much larger datasets as KML’s. Honestly KML is really only good for small datasets with few features and associated attributes.
What to do if your KML is too big for the Google Maps API?
If you haven’t invested too much time in your Google Maps API you could switch to OpenLayers which has a client side KML parser that can read your own KML files – see example below: However for a 15MB file this would likely grind the browser to a halt.
What are some examples of microservices performance problems?
Examples include adding timeout and retry functions. While theoretically a good idea, if the service being called is very slow and always triggers a timeout, the retry puts extra stress on an already overloaded system, exacerbating latency issues.