Is there an option in R Studio to autosave the global environment at specified intervals? I use it for work and although yes, and there are a lot of auto updates that get pushed through to my machine and force a restart.
Yes, I can just save it myself periodically, but call me crazy, I forget to do it now and then when I leave at the end of the workday.
I looked around R options but don't see it listed, and don't see an answer to the question online, other than someone asks and others warn the person why they think it's a bad idea (memory, size of file, etc).
Is there no option to autosave, say, every 60 minutes, at 13:00 everyday, etc?
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I use R, Rstudio and Rcpp and I spent over a week debugging some code, that was just giving errors and warnings in unexpected places, in some cases with direct sample code from online or package documentation.
I often restart the R session or Rstudio if there are obvious problems and they usually go away.
But this morning it was really bad to the point were basic R commands would fail and restarting R did nothing. I closed all the Rstudio sessions and restarted the machine for good measure, (which was unnecessary).
When it came back and I re-loaded the sessions everything seems to be working.
Even the some rcpp code I was working on for weeks with outside packages will now compile and run where it gave gibberish errors before.
I have known for a while that R needs to be restarted once in a while, but I know it when basic functions don't run, how can I know earlier.
I am looking for a good general resource or function that can tell me I need to restart because something is not running right. I would be nice if I can also know what to restart.
Whether the R session, the GUI such as Rstudio, all sessions and GUIs or a full machine restart.
For as long as I have been dabbling with or actually using R (ie more than two decades), it has always been recommended to start a clean and fresh session.
Which is why I prefer to work on command-line for tests. When you invoke R, or Rscript, or, in my case, r (from littler) you know you get a fresh session free of possible side-effects. By keeping these tests to the command-line, my main sessions (often multiple instances inside Emacs via ESS, possibly multiple RStudio sessions too) are less affected.
Even RStudio defaults to 'install and restart' when you rebuild a package.
(I will note that a certain development package implies you could cleanly unload a package. That has been debated at length, and I think by now even its authors qualify that claim. I don't really know or case as I don't use it, having had established workflows before it appeared.)
And to add: You almost never need to restart the computer. But a fresh clean process is a something to use often. Your computer can create millions of those for you.
I made a little app and deployed it into a Ubuntu server using Meteor Up.
There are very few users each day (<10), but after few days a lot of the memory of the server is used.
So I think that there is a memory leak somewhere in my code.
How to find it ?
Thanks a lot !
We actually had a memory leak the last days and it was relatively easy to find using a package called heapdump, you can find it here: https://www.npmjs.com/package/heapdump
It is not made for meteor in specific, but for nodejs. Just read through the README carefully to install it. Afterwards find a good moment to get the first heapdump by running kill -USR2 <pid_of_meteor_app> on the server. A good moment is when there is not much going on on the server but enough so that the memory is leaking.
Afer a while, when you recognized a good amount of memory growth without a logical explanation: go make another heapdump and download both.
Hit F12 to open up you webdev console on your browser (Chrome, Firefox, Edge,...) and got to Memory there. Import both heapdumps after.
Now you need to find what changed between those two heapdumps, what actually helped me there was this article to understand how to do that: https://www.useanvil.com/blog/engineering/isolating-memory-leak-in-node/
Remember that you are most probably looking for memory reservations of the same size, sometimes just tiny amounts of kb as in our case, but hundreds of thousands of them. So sorting by space is a good idea.
In our case it was an outdated package called tslib which reserverd all the memory after a day or so. We were on 2.3.1, so we went to https://github.com/microsoft/tslib/releases/tag/2.4.0 and read there:
This release includes the __classPrivateFieldIn helper as well as an
update to __createBinding to reduce indirection between multiple
re-exports.
We updated the package, which was a dependency of another package and that fixed it.
Kadira, Monti APM and whatever is often absolutely useless in such cases, you cannot really track down the source more often than not.
There is a kadira package to check your app. have a look https://kadira.io/
I would like to know how to restore my previous RStudio session after RStudio and the R session crashed.
Background:
I find that my R session crashes very often, at random times for random reasons. I am fine with that I guess.
Most of the time RStudio restarts the R session and I can continue.
But sometimes it just freezes at which time I noticed power cycling the entire machine allows RStudio to recover and even reload my old session.
Stupid me, I don't think power cycling is a good idea so I manually killed the R session, but then RStudio responded but was not really working so I restarted it and it came back with an empty work-space.
I have been backing up with Session->Save Workspace As, but it seems to do nothing as recovering leaves me with the blank empty environment.
I am looking to restore the RStudio display, including the command history , which for a novice like me is precious, and my list of open scripts, some of which were unsaved at the time of the crash.
I am assuming since RStudio can recover itself, there is a file somewhere I can use to recover it.
And if there is no way to recover, how can I completely save my workspace so this cannot happen again?
Also, is there a proper way to recover from an RStudio freeze without a hard reset?
It has been a while since I asked this question. I was never able to fully recover, but I switched to Rprojects which is the recommended way to use Rstudio.
Rprojects are stored in a folder and they remember all files and data from that project in that folder.
This did not help me with my initial problem, but projects prevent it from happening again. The hard part is moving a work-space to a project if it was not in a project to start.
Hi the first step of this article helped me entirely.
https://datacornering.com/how-to-restore-closed-unsaved-script-in-rstudio/
Basically, if on windows, go to C:\Users\xx\AppData\Local\RStudio\sources\s-xx and find a file with "-contents" at the end. This is your unsaved file.
I'm trying to learn about the guts of Unix right now, mostly through experimentation. When I was first starting, I found myself looking through forum posts, copying and pasting bash code. When I broke something, I often had to do a fresh install because I couldn't remember what exactly I had changed where. Now, the simple solution is to record a log of all the system files I've changed and keep original copies of all the default files so I can revert if necessary. It would be great if there was a cl tool which did this for me automatically. It would be even greater if I could step back through changes. Basically, I'm looking to version control my entire OS.
Does anything like this exist? I would also accept alternative strategies for spelunking through Unix without causing permanent damage if you think I'm going about this wrong.
Using debian if it matters.
In RStudio there's a Tools menu which allows you to select an installed version/architecture of R under Global Options.
That's great, but my issue with that is that, as the name implies, it is a Global option, so once you select a different architecture (or version number) you then have to restart RStudio and it applies to all of your RStudio instances and projects.
This is a problem for me because:
I have some scripts within a given project that strictly require 32-bit R due to the fact that they're interfacing with 32-bit databases, such as Hortonworks' Hadoop
I have other scripts within the same project which strictly require 64-bit R, due to (a) availability of certain packages and (b) memory limits being prohibitively small in 32-bit R on my OS
which we can call "Issue #1" and it's also a problem because I have certain projects which require a specific architecture, though all the scripts within the project use the same architecture (which should theoretically be an easier to solve problem that we can call "Issue #2").
If we can solve Issue #1 then Issue #2 is solved as well. If we can solve Issue #2 I'll still be better off, even if Issue #1 is unsolved.
I'm basically asking if anyone has a hack, work-around, or better workflow to address this need for frequently switching architectures and/or needing to run different architectures in different R/RStudio sessions simultaneously for different projects on a regular basis.
I know that this functionality would probably represent a feature request for RStudio and if this question is not appropriate for StackOverflow for that reason then let me know and I'll delete it. I just figured that a lot of other people probably have this issue, so maybe someone has found a work-around/hack?
There's no simple way to do this, but there are some workarounds. One you might consider is launching the correct bit-flavor of R from the current bit-flavor of R via system2 invoking Rscript.exe, e.g. (untested code):
source32 <- function(file) {
system2("C:\\Program Files\\R\\R-3.1.0\\bin\\i386\\Rscript.exe", normalizePath(file))
}
...
# Run a 64 bit script
source("my64.R")
# Run a 32 bit script
source32("my32.R")
Of course that doesn't really give you a 32 bit interactive session so much as the ability to run code as 32 bit.
One other tip: If you hold down CTRL while launching RStudio, you can pick the R flavor and bitness to launch on startup. This will save you some time if you're switching a lot.