You can use Apache Spark inside Shiny applications with either SparkR or sparklyr. Shiny on hosted RStudio Server Requirements To ensure a stable URL, you can set the shiny.port option, or, when restarting the app on the same cluster, you can specify the port argument. Also, if you restart the app on the same cluster, Shiny might pick a different random port. If you attach and run the notebook hosting the Shiny app on a different cluster, the Shiny URL changes. You can disable automatic termination in the cluster settings. If the cluster that the app is running on terminates, the app is no longer accessible. Any Azure Databricks user with Can Attach To permission on the cluster can view and interact with the app as long as both the app and the cluster are running. The Shiny app URL generated when you start an app is shareable with other users. RunApp("/databricks/driver/shiny-examples/007-widgets/") To run the application, enter code similar to the following in another cell: library(shiny) You must use the absolute path or set the working directory with setwd().Ĭheck out the code from a repository using code similar to: %sh git clone To share this app with other users, see Share Shiny app URL. When the app is ready, the output includes the Shiny app URL as a clickable link which opens a new tab. Import the Shiny package and run the example app 01_hello as follows: library(shiny) You can interactively develop and test Shiny applications inside Azure Databricks R notebooks similarly to hosted RStudio. The Shiny package is included with Databricks Runtime. Get started with Shiny inside R notebooks This article describes how to run Shiny applications on Azure Databricks and use Apache Spark inside Shiny applications. You can run these tutorials on Azure Databricks notebooks. To get started with Shiny, see the Shiny tutorials. You can also develop, host, and share Shiny applications directly from an Azure Databricks notebook. You can use Shiny inside RStudio Server hosted on Azure Databricks clusters. Shiny is an R package, available on CRAN, used to build interactive R applications and dashboards.
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