Databricks Runtime ML includes an unmodified version of the RStudio Server Open Source Edition package for which the source code can be found in GitHub.
If you want to use RStudio Workbench / RStudio Server Pro, you must transfer your existing RStudio Workbench / RStudio Server Pro license to Databricks (see Get started: RStudio Workbench).ĭatabricks recommends that you use Databricks Runtime for Machine Learning (Databricks Runtime ML) on Databricks clusters with RStudio Server, to reduce cluster start times. You cannot use packages such as SparkR or sparklyr in the RStudio Desktop scenario, unless you also use Databricks Connect.įor RStudio Server, you can use either the Open Source Edition or RStudio Workbench (previously RStudio Server Pro) edition on Databricks. For a SQL warehouse, these values are on the Connection details tab.Īs an alternative to RStudio Server, you can use RStudio Desktop to connect to a Databricks cluster or SQL warehouse from your local development machine through an ODBC connection, and call ODBC package functions for R. For a cluster, these values are on the JDBC/ODBC tab of Advanced options. Get the Server hostname, Port, and HTTP path values for your remote cluster or SQL warehouse. To connect to the remote Databricks cluster or SQL warehouse through ODBC for R:
With the project open, click File > New File > R Script. To set up RStudio Desktop on your local development machine:Ĭhoose a new directory for the project, and then click Create Project.
As an alternative to using RStudio Desktop, you can use your web browser to sign in to your Databricks workspace and then connect to a Databricks cluster that has RStudio Server installed in that workspace. You cannot use packages such as SparkR or sparklyr in this RStudio Desktop scenario, unless you also use Databricks Connect.
0 kommentar(er)
