The following example uses the CRAN snapshot dated : install.packages(c("odbc", "DBI"), repos = "")īack in your R script ( View > Move Focus to Source), load the installed odbc and DBI packages: library(odbc)Ĭall the ODBC version of the dbConnect function in the DBI package, specifying the odbc driver in the odbc package as well as the ODBC DSN that you created, for example, an ODBC DSN of Databricks. Set up an ODBC Data Source Name (DSN) to your remote cluster or SQL warehouse for Windows, macOS, or Linux, based on your local machine’s operating system.įrom the RStudio console ( View > Move Focus to Console), install the odbc and DBI packages from CRAN. Install and configure the Databricks ODBC driver for Windows, macOS, or Linux, based on your local machine’s operating system. To create access tokens for service principals, see Manage access tokens for a service principal. Get an Azure Databricks personal access token.Īs a security best practice, when authenticating with automated tools, systems, scripts, and apps, Databricks recommends you use access tokens belonging to service principals instead of workspace users. For a SQL warehouse, these values are on the Connection details tab.
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 Azure Databricks cluster or SQL warehouse through ODBC for R: With the project open, click File > New File > R Script.Choose a new directory for the project, and then click Create Project.Download and install R 3.3.0 or higher.To set up RStudio Desktop on your local development machine: As an alternative to using RStudio Desktop, you can use your web browser to sign in to your Azure Databricks workspace and then connect to an Azure 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.
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