This tells me that there's not a simple way of launching like localhost:54321, which is what I need for. say, web interface to h2o cluster I managed to launch in space. I understand that you guys need to write custom wrapper for every application (port?) to re-expose it in Rstudio.cloud and there's no way I can just launch arbitrary web app from the cloud instance in browser session. I did not test tensorflow, but there you have tensorboard which is also a localhost web app. Do you guys have to explicitly map ports to folders to enable web access? How about mapping 54321 for H2O Flow, please?
Note however that for security reasons, this feature is being deprecated, so we wouldn't recommend building infrastructure on it. In a future RStudio release, you will need to use the rstudioapi::translateLocalUrl() method to create these URLs.
Pretty cool, thanks. There's something going on with H2O web interface not being able to talk to the java cluster, but I guess it is a java security issue, rather than anything related to R.
Error calling GET /3/Models
HTTP connection failure: status=error, code=404, error=Not Found
I will file a ticket with them, but eventually you guys may want to talk to each other and/or establish some rules for making "Rstudio.cloud compatible" web fronts for processes running in the background. I understand that Rstudio.cloud is not VM service and may have some limitations. Other than web interface, everything is running flawlessly and I couldn't be happier! Thanks for making this awesome product!
Reprex is actually very easy:
library(h2o)
h2o.init()
After this cluster should be available at localhost:54321, and it is. But none of the commands are working. Trying Admin > ClusterStatus fails with error above.
What is the output of h2o.clusterStatus(), right after calling h2o.init()?
You may need to explicitly limit the memory that h2o consumes, as I don't believe that it properly detects the cgroup limit and instead looks at the host machines total memory and attempts to start a JVM with too high a maximum memory.
That said, I still can't get the Flow interface to properly launch, fiddling with it...
Okay, I was able to launch Flow and got the same error you did.
I tested on a regular RStudio Server Pro instance and saw the same behavior, so this is not an issue with rstudio.cloud itself. h2o Flow appears to make its REST calls with an absolute path such that only the protocol and server are prepended. Which obviously won't work if it is actually being served with leading path elements.
If you do open a ticket, please link it here, I would be interested in following it.
H2O R package doesn't have a default value for the amount of Java memory to allocate. The H2O backend thus starts with JVM's default.
You guys are using openjdk 8 and in that case it will take 1/4 of available memory which might be too little for H2O. Anything less than 1GB will be probably too little. 1 GB is probably fine for experimenting.
I am trying to reproduce the issue and access Flow. The example URL in this discussion looks like this:
This will display Flow but it won't let you do anything because Flow doesn't expect to work behind a proxy like that. I think we can fix that and make it work on RStudio Cloud.
Thank you for prompt turnaround, Michal. This is very useful.
Flow doesn't expect to work behind a proxy
This reminded me of another issue PUBDEV-5602 I figured out recently. Clearing all proxy settings in R session allowed me to connect to Flow on my corporate machine. That issue is, I am sure, unrelated, but generally speaking some clarification with regards to use of H2O behind proxy would be useful.