This topic explains how to get workspace, cluster, notebook, and job details in Databricks.
An instance name is assigned to each Databricks deployment. To segregate the workload and grant access to only relevant users, usually Databricks customers create separate instances for development, staging, and production. The instance name is the first part of the URL when you log into your Databricks deployment.
For example, if you log into
https://cust-success.cloud.databricks.com/, the instance name is
Databricks clusters provide a unified platform for various use cases such as running production ETL pipelines, streaming analytics, ad-hoc analytics, and machine learning. Each cluster in Databricks has a unique ID called the cluster ID. This is applicable for both interactive and job clusters. To get the details of a cluster using the REST API, the cluster ID is essential. To get the cluster ID, click the Clusters tab in left pane and then select a cluster name. The URL of this page
http://<databricks-instance>/#/settings/clusters/<cluster-id> has the cluster ID.
In the following screenshot, the cluster ID is
A notebook is a web-based interface to a document that contains runnable code, visualizations, and narrative text. Notebooks are one interface for interacting with Databricks. Each notebook has a unique ID. The notebook URL has the notebook ID, hence the notebook URL is unique to a notebook. It can be shared with anyone on Databricks platform with permission to view and edit the notebook. In addition, each notebook cell has a different URL.
In the following notebook, the notebook URL is
https://cust-success.cloud.databricks.com/#notebook/333096 and the cell URL is
A job is a way of running a notebook or JAR either immediately or on a scheduled basis. To get to a job URL, click the Jobs tab in left pane and click a job name. This job URL is very critical piece of information needed to troubleshoot job runs that have failed and investigate the root cause.
In the following screenshot, the job URL is