[allg12]

So far, I've only generated the graph for Europe(using Graphhopper). Even just Europe required 128GB of RAM and around 10 hours of computation time (the entire planet would likely need 384GB of RAM). I plan to add North America on a separate Docker container soon though. I started with Europe because I’m familiar with some of the bike trails here, which makes it easier for me to check if the routing makes sense.

[karussell]

> the entire planet would likely need 384GB of RAM

Unlikely. Even with turn costs enabled 256GB (or less) are sufficient. You could also try to disable CH as for bike often no long routes are required (you could disable them). Here we have written down a few more details: https://www.graphhopper.com/blog/2022/06/27/host-your-own-wo...

[allg12]

Hey karussell, I really appreciate all the hard work you’ve put into Graphhopper. I wouldn't be able to create this project without GH. I have a question about memory usage during the import stage (specifically in the OSM Reader's preprocessRelations function). I'm using a HashMap<Long, List<Long>> to map way IDs to OSM bike route relation IDs, which means allocating lots of arrays. Could this be causing me to run out of heap memory faster or am I off base here?

I thought I would be able to compute the graph with 64GB of ram but it kept crushing before CH and LM stage. After switching to a 128GB instance, it finally worked, hitting around 90GB at peak memory usage. For context, I was using 3 profiles - one with CH and two with LM, plus elevation data and used all of the tips from deploy.md

[mvdtnz]

You should at least add some kind of error handling so I'm not sitting there like a dope clicking over and over with no result.

[allg12]

Apologies, just added a popup with region availability info

[cfcfcf]

Cool project, best of luck! Agree with the other commenter that some kind of error handling or warning re: outside-of-EU availability.