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It’s recommended that you authenticate via the .Renviron file using DATABRICKS_HOST and DATABRICKS_TOKEN environment variables. You can also use Databricks CLI Configuration Profiles and DATABRICKS_CONFIG_FILE or DATABRICKS_CONFIG_PROFILE environment variables, but only the PAT Authentication works at the moment. If you need more authentication methods, please fork this GitHub repository and send pull request with the feature suggestion.

Example of overriding authentication profile. Look at databricks auth profiles to know which ones are working.

client <- DatabricksClient(profile="your-cli-profile")

Complete with Databricks workspace-level APIs

Databricks SDK for R comes with all public workspace-level APIs and is consistent with Databricks SDK for Python, Databricks SDK for Go, and Databricks SDK for Java. Databricks SDK for R does not expose account-level APIs and you’re recommended to use Go, Python, or Java SDK to build an account-level automation.

client <- DatabricksClient()
running <- clustersList(client) %>% filter(state == 'RUNNING')
context <- commandExecutionCreate(client, cluster_id=running$cluster_id, language='python')
res <- commandExecutionExecute(client, cluster_id=running$cluster_id, context_id=context$id, language='sql', command='show tables')


All list methods (and those, which return any list of results), do consistently return a data.frame of all entries from all pages, regardless of the underlying implementation.

> clustersList(client)[1:10,c("cluster_id", "cluster_name", "state")]
             cluster_id                                      cluster_name      state
1  1109-110110-kjfoeopq                              DEFAULT Test Cluster TERMINATED
2  0110-221212-oqqpodoa                               GO_SDK Test Cluster TERMINATED
3  1109-012301-qlwlwqpq                               BRICKS Test Cluster TERMINATED
4  1109-110012-qpwoepqq                               VSCODE Test Cluster TERMINATED
5  0110-201022-oqooqpqp                               JS_SDK Test Cluster TERMINATED

Long-running operations

All long-running operations do poll Databricks backend until the entity reaches desired state:

> clustersCreate(client, spark_version = "12.x-snapshot-scala2.12", cluster_name = "r-sdk-cluster", num_workers = 1, autotermination_minutes=20, node_type_id="i3.xlarge")
PENDING: Finding instances for new nodes, acquiring more instances if necessary

Interface stability

API clients for all services are generated from specification files that are synchronized from the main platform. Databricks may have minor documented backward-incompatible changes, such as renaming the methods or some type names to bring more consistency.

Project Support

Please note that all projects in the databrickslabs github space are provided for your exploration only, and are not formally supported by Databricks with Service Level Agreements (SLAs). They are provided AS-IS and we do not make any guarantees of any kind. Please do not submit a support ticket relating to any issues arising from the use of these projects.

Any issues discovered through the use of this project should be filed as GitHub Issues on the Repo. They will be reviewed as time permits, but there are no formal SLAs for support.