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Integrating DBeaver with Lakehouse SQL

Overview​

DBeaver is an open-source database tool for developers, analysts, and database administrators. It supports Databricks as well as other popular databases. You can use the Skypoint AI Lakehouse SQL tool to run SQL commands and browse database objects in Databricks. Also, you can perform CRUD (Create, Read, Update, and Delete) operations using an SQL server.
Follow the below steps to integrate DBeaver with Lakehouse SQL:

Step 1: Install DBeaver and Download Databricks JDBC Driver​

Follow the below steps to install DBeaver and Download Databricks JDBC Driver:

  • Download DBeaver from https://dbeaver.io/download/. Choose Dbeaver Community 22.2.0, run the process, and set up the tool. You download the latest version. This article is tested with version 22.2.0.

  • Download the Databricks JDBC Driver onto your local development machine. Extract the databricksJDBC42.jar file from the downloaded DatabricksJDBC42.zip file.

Once DBeaver is installed, follow the below steps to configure and work with databases in Lakehouse SQL.

Step 2: Configure the Databricks JDBC Driver for DBeaver​

Set up DBeaver with information about the Databricks JDBC Driver that you downloaded earlier.

  1. Start DBeaver.
  2. If you are prompted to create a new database, click No.
  3. If you are prompted to connect to or select a database, click Cancel.
  4. Click Database > Driver Manager.
  5. In the Driver Manager dialog box, click New.
  6. In the Create new driver dialog box, click the Libraries tab.
  7. Click Add File.
  8. Browse to the databricksJDBC42.jar file that you extracted earlier and click Open.
  9. Click Find Class.
  10. In the Driver class list, confirm that com.simba.spark.jdbc.Driver is selected.
  11. On the Settings tab, for Driver Name, enter Databricks.
  12. On the Settings tab, for Class Name, enter com.simba.spark.jdbc.Driver.
  13. Click OK.
  14. In the Driver Manager dialog box, click Close.

Step 3: Connect DBeaver to your Lakehouse SQL endpoint​

Use DBeaver to connect to the Lakehouse SQL endpoint to access the databases in your Databricks workspace.

  1. In DBeaver, click Database > New Database Connection.

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  1. In the Connect to a database dialog box, on the All tab, click Azure Databricks (Native), and then click Next.

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  1. Click the Main tab and enter credentials to connect.

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  1. To find credentials such as JDBC URL and Personal access token, follow the below steps:
    1. Open Skypoint Studio.
    2. In the left pane, go to Lakehouse > SQL Access.
    3. Click Show fields to copy your credentials to your clipboard. For more information, refer to Getting started with Skypoint AI Lakehouse SQL.

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  1. Enter JDBC URL and do the following:
ToDo
Validate UsernameType token. This token is just the word token only.
Validate PasswordEnter the Personal Access token that you have taken from the Skypoint Platform.
  1. Check Save password locally.
  2. Click Test Connection.
  3. If the connection succeeds, click OK in the Connection Test dialog box.
  4. In the Connect to a database dialog box, click Finish.

In the Database Navigator window, a new entry is displayed.

Step 4: Use DBeaver to browse databases and their objects​

Use DBeaver to access databases and database objects in your Lakehouse SQL workspaces such as tables and table properties, views, indexes, data types, and other object types.

  1. In the Database Navigator window, right-click Azure Databricks.

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  1. If Connect is enabled, click it. (If Connect is disabled, you are already connected.)
  2. Expand hive_metastore.

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  1. Expand the database that you want to browse.
  2. Expand Tables.
  3. Right-click on the table you wish to query and click on read data in SQL editor.
  4. Repeat the instructions in this step to access additional databases and database objects.