![]() Load an arbitrary environment module, if using Environment Modules (see environment modules).Execute an arbitrary script when the version is loaded, perhaps to dynamically alter any important environment variables (such as LD_LIBRARY_PATH).This makes it easy to differentiate between similar versions for different environments, such as when running parallel versions of Microsoft R and Vanilla R. Label each version so users can have a friendly name associated with each version.We’ve improved management of various versions of R within your environments, allowing you to: For more information on using the Job Launcher with RStudio Server Pro, see the documentation. We plan to develop more plugins in the future, and would love to hear from you about what we should tackle next! At present, we plan to add support for LSF.įor more information on launching ad-hoc jobs, see our upcoming blog post on background jobs. However, the Job Launcher is an extensible system that makes it fairly simple to develop plugins to target different cluster types. We determined that most RSP users were already using Slurm and Kubernetes, so integration with them was added first. When starting RSP sessions via the Launcher, users will still use the same home page that they are familiar with, but will have additional options for controlling the creation of their sessions within your distributed environment of choice. The following diagram shows an example of how you can use the Job Launcher with Kubernetes to painlessly scale RStudio Server Pro across potentially hundreds of nodes. At release, we will support the following clusters: This allows you to run RStudio sessions and ad-hoc R scripts within your already existing cluster workload managers, such as Kubernetes, allowing you to leverage your existing infrastructure instead of provisioning load balancer nodes manually. Perhaps the biggest new change in v1.2 is the Job Launcher. Let’s get started! RStudio Server Pro The Job Launcher We’ve added some great new features to RStudio Pro for v1.2, which includes not only Server Pro, but also the new and improved Pro Desktop. If you’d like to try these features out for yourself, you can download a preview release of RStudio Pro 1.2. If you have any questions or comments, please get in touch with us on the community forums.Today, we’re continuing our blog series on new features in RStudio 1.2. You can download the RStudio 1.2 Preview Release at. There are lots of great resources available, including: If you are new to C++ or Rcpp, you might be surprised at how easy it is to get started. (Currently, Ubuntu 18.04 provides libclang 6.0.0) Try it Out On Linux, we now default to the version of libclang provided by your package manager, so that RStudio can make use of new and improved C++ tooling as it becomes available on your system. With this, RStudio gains improved support for modern C++: all standards from C++ 11, C++ 14 and C++ 17 are now supported. On Windows and macOS, we’ve updated the bundled version of libclang from 3.5.0 to 5.0.2. RStudio also provides code diagnostics, alerting you to any issues that might exist in your code. We also now provide autocompletion results for the headers you’d like to use in your program. RStudio provides autocompletion support in C++ source files, and can autocomplete symbols used from R’s C API, Rcpp, and any other libraries you may have imported. Thanks to the abstractions provided by Rcpp, the code implementing gibbs() in C++ is nearly identical to the code you’d write in R, but runs 20 times faster. In each case, we use Rcpp::sourceCpp() to compile and link the code – after this, any exported functions can be called like any other R function in your session. Such C++ code can be used both in standalone files (e.g. when used as part of an R package, or when prototyping locally) or within an R Markdown document (within an Rcpp chunk). For example, the following chunk defines a simple Gibbs sampler: #include RStudio integrates closely with Rcpp, which allows you to easily write performant C++ code and use that code in your R session. The update improves performance as well as adds compatibility with modern C++ 17 language features. The major new C/C++ feature in RStudio v1.2 is an upgrade to libclang (our underlying completion and diagnostics engine). Tight integration with the Rcpp package.The IDE has had excellent support for C/C++ since RStudio v0.99, including: Today, we’ll talk about IDE support for C/C++ and Rcpp. We’ve now discussed the improved support in RStudio v1.2 for SQL, D3, and Python.
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