I'm looking at setting up a Shiny app that uses the Furrr package behind the scenes for some multithreaded operations. While checking the documentation for Shiny Server I read that the Open Source version is limited to a single process.
Does this mean anything running on Shiny Server Open Source can't be used in conjunction with any of the multithreading packages, since afaik all multithreading in R requires creating multiple processes? Also would this apply as well to something like ShinyProxy?
Per Jcheng on github:
Shiny Server will launch up to one R process for each app to run Shiny, then those R processes can launch child processes if they want.
So the answer is yes shiny server open source is capable of multithreading, it simply wont automatically create new R processes to serve concurrent users' sessions (ie automatic load balancing).
Related
I am used to using R in RStudio. For a new project, I have to use R on the command line, because the data storage and analysis are only allowed to be on a specific server that I connect to using ssh. This server doesn't have rstudio-server to support remote RStudio sessions.
The project involves an extremely large dataset, and some pre-written code to load/format the data that I have been told to run using "source()" before I do anything else. This takes several minutes to run and load the data each time.
What would a good workflow be for something like this? Editing my code in a .r file, saving, then running it would require taking several minutes to load the data each time. But just running R in an interactive session would make it hard to keep track of what I am doing and repeat things if necessary.
Is there some command-line equivalent to RStudio where you can have an interactive session but be editing/saving a file of your code as you go?
Sounds like JuPyteR might be your friend here.
The R kernel works great.
You can use it on a remote server either with exposing an open port (and setting up JuPyteR login credentials)
Or via port forwarding over SSH.
It is a lot like an interactive reply, except it holds state.
And you can go back and rerun cells.
(Of course state can be dangerous for reproduceability)
For RStudio you can launch console and ssh to your remote servers even if your servers don't use expensive RStudio for servers platform. You can then execute all commands from R Studio directly into the ssh with the default shortcut key. This might allow to continue using R studio, track what you're doing in the R script, execute interactively.
We run an R shiny server (R: 3.5.1, Shiny: 1.0.3) on a virtual machine under CentOS. We are experiemcing some issues with script updates to the server.
We find that under certain conditions if we update a script to the server it may take some time (up to days occassionally) for the updated script to be actually executed.
From experience, this delay only occurs when the srcipt has multiple users. Scripts that have a sningle user (me) update instantly as soon as the updated scripts have been written to the server.
This makes sense: as long as users are running the scripts in sessions, you cannot update it. We know that resetting the Shniy server does the trick but this strikes me as a crude way of resolving this issue.
As I am not a linux expert I do not know if this is caused by Shiny or by Linux.
Does anyone know where this behaviour is documented so I can learn how to better control the process of updating?
I am working on an Shiny app in R. My goal is to put in on a server, not on my local pc.
EDIT: my goal is not to publish it on the web, but only make it run on the server locally.
I have installed R on the server, added all the libraries I need, lastly I tried to launch my app that it is quite long, the schema is more or less this:
data preprocessing (with RODBC)
some custom functions
server<- etc.
ui<- etc.
shinyapp(server,ui)
Well in my local pc everything is fine, but on the server I cannot have a result, it is impossible to reach the address.
I decided to do something like this, create the two files called server and ui, and launching them with:
runApp(".../shiny")
Having the idea to use the option of runApp.
Well it is arriving this
ERROR: Error sourcing C:\Users\...\AppData\Local\Temp\Rtmp8YeSOV\file22281c0c2f6d
First of all, this procedure is going to help me?
If so, could you tell me what that error mean?
Thanks in advance.
I'm not sure, but I think it's not possible to reach a shiny app running in a local computer (or server). For that purpose you can use the Shiny Sever, which allow you to put your Shiny apps accessible online.
It seems that your server is a Windows computer, so your options are:
Build Shiny Server from its source code, (maybe a little difficult).
Use a virtual machine like VMware Player (free for non-commercial use) and install Ubuntu or other Linux distribution to use the pre-built binary of Shiny Server. With this option you can restrict the access to only your local network and maybe faster access to your DB's.
Use a DigitalOcean virtual server (for a very reasonable price), in this case you apps will be on the cloud and accesible everywhere.
For option 2 and 3 you can follow the very useful and well written tutorial of Dean Attali about installing and setting up a Shiny Sever. It is for DigitalOcean but is pretty much the same if you decide to use a virtual machine with Linux.
The answer is quite simple, I was using IE as browser: if you use Chrome specifying it on the runApp statement, everything works fine.
I have a program that is built in R and runs on the desktop version of Shiny. I am working on moving the project to a Shiny server. Would it be possible for multiple users to use the program at the same time on the Open Source version of Shiny Server or will there be an issue with concurrent users?
Thanks
According to their support page it can have an unlimited number of users:
Yes. Shiny Server is constrained only by its features.
I am not a shiny developer but yes. The limitation is that one R process will be used. So if user1 runs some process that takes some time user2's processes will wait for user1 to finish.
RStudio server uses a headless R session and seems to pass all of the I/O operations encoded to save bandwidth. This works for everything except for packages like Rattle or Latticist, which work through their own GUI. Is there a way to use these packages through RStudio server or otherwise access the RStudio server R session to run these packages remotely?
Bonus if there's an efficient way to run these packages remotely without forwarding an X session over SSH.
I'm not sure this is possible over the RStudio interface because of the way these graphical programs work. It's easy enough for RStudio to capture textual input and output for R. Capturing normal graphical output is pretty impressive, but that's done "natively" in R. Even packages like ggplot2 and lattice use the builtin R plotting capabilities -- they do some rendering and data processing on their own, pass that onto grid and then grid renders the plots via R builtins when plot() or print is called (including implicitly in the REPL for interactive sessions). RCommander, RGL and the like use external libraries (Tcl/Tk, OpenGL), which render their interfaces directly over operating system services and not via R. R doesn't even see the output from these programs -- it only knows that the R wrapper function for these services hasn't returned yet. For local RStudio, this isn't a problem because the services are forwarded directly to the local display, but for RStudio server, there is no display!
Another consideration: assuming R could capture and forward X, that would imply having an X Server (in X, Server is the display/keyboard/etc, Client is the program that needs I/O) running in your browser. Modern JavaScript is pretty amazing at times, but X is a very complicated codebase and very sensitive to latency. Running X over the Internet is much slower than over the local network -- the protocol just wasn't designed for such things and most operations involve far too many roundtrips.
On a more practical side, you can still do most of your work via RStudio and only do the graphical commands via X forwarding:
Do everything that doesn't involve an external graphics interface.
Save your R Session (in the Environment tab or via the command line) as .RData in your project directory. (You can actually do this elsewhere, but it's generally more convenient if your workspace is saved in the working directory.)
Login in via SSH and X Forwarding and cd to the project directory.
Start R -- R will automatically load any existing workspaces saved as .RData. (You can disable this behavior with --vanilla. Depending on the size of your workspace, R may take a few seconds to a few minutes to load.
Have fun with Rattle, Latticist, RCommander, RGL, etc! Be ready for massive lag if you're doing this over the Internet and not the local network (see above).