Databricks SQL

AgenticBI facilitates data discovery, query, aggregation, visualization, and reporting automation from Databricks along with other unstructured and structured datasources.

Overview

  1. Connect, extract and transform data from your Databricks SQL database through our UI to connect directly.

  2. Visualize and Automate your Reporting instantly.

UI Based Approach

Connecting

Step 1: Log in to AgenticBI and select Queries from the left sidebar.

Step 2: Click on New Datasource + button and a new page with a list of datasources will open.

Step 3: Select databricks in Data Warehouses.

A new datasource page will open.

data-strategy

Step 4:Configure the following details to set up connectivity to your Databricks SQL database:

a. Datasource Name: Enter a name for your datasource
b. Host: Enter the DatabricksSQL host to connect to. For example: https://dbc-123ab4c5-d67f.cloud.databricks.com
c. Warehouse ID: Enter the Databricks SQL warehouse ID. For example: 9c7235e6e6e49147
d. Auth Token: Enter the personal access token
e. Schema Name: Enter the schema name
f. Catalog: Enter the name of the catalog
g. Connection String: Optional. Additional connection properties/url parameters. For example (in seconds), readTimeout=1800&connectTimeout=30.

Step 5: Click the Test Connection button and a connection successful pop-up message will appear.

adding-elasticsearch

For more information, please refer to the documentation on Connectivity & Datasources.

Step 6: Click on Save and start Querying.

adding-elasticsearch

Query

Set up Query using a visual builder or query editor

Visual Builder

Step 1: After connecting to the Databricks SQL datasource, AgenticBI will pull out a list of tables along with field samples. Using these tables, you can automatically generate queries through our visual builder in a no-code environment by either dragging and dropping fields or making your selections through the drop-down.

Tip: You can also write queries directly in the Query Editor, a versatile text editor that offers more advanced editing functionalities like SQLServer Query, support for multiple language modes, Cloud9QL, and more.

Step 2: Define data execution strategy by using any of the following two options:

  • Direct Execution: Directly execute the Query on the original Datasource, without any storage in between. In this case, when a widget is displayed, it will fetch the data in real time from the underlying Datasource.

  • Non-Direct Execution: For non-direct queries, results will be stored in AgenticBI's data Store. Benefits include- long-running queries, reduced load on your database, and more. Non-direct execution can be put into action if you choose to run the Query once or at scheduled intervals.

For more information, check out the documentation Defining Data Execution Strategy

Step 3: Click on the Preview button to analyze the results of your Query and fine-tune the desired output, if required. The result of your Query is called Dataset.

Step 4: After reviewing the results, name your dataset and hit the Save & Run button.

Query Editor

A versatile text editor designed for editing code that comes with a number of language modes including Databricks SQL and add-ons like Cloud9QL.

Use External Links to fetch data: Select this option to use External Links disposition when fetching data from Databricks SQL. This allows fetching larger data but uses cloud storage.

Step 1: Write your query using Databricks SQL in the Query Editor. Optionally, apply Cloud9QL on top for additional transformations.

Step 2: Define data execution strategy by using any of the following two options:

  • Direct Execution: Directly execute the Query on the original Datasource, without any storage in between. In this case, when a widget is displayed, it will fetch the data in real time from the underlying Datasource.

  • Non-Direct Execution: For non-direct queries, results will be stored in AgenticBI's data Store. Benefits include- long-running queries, reduced load on your database, and more. Non-direct execution can be put into action if you choose to run the Query once or at scheduled intervals.

For more information, check out the documentation Defining Data Execution Strategy

Step 3: Click on the Preview button to analyze the results of your Query and fine-tune the desired output, if required.