How to access Spark Database from Power BI ?

What is Spark Database : Spark Database is a cloud Warehouse. Can store Raw data, Aggregated data, Incremental and Historical data.

What is Power BI : Power BI is a cloud analytics and dashboarding platform. Can also perform AI based Copilot operations for Big Data Analytics and In-depth Mining.. !

In this article, we shall understand how to connect Spark Databases from Power BI Desktop Tool...

Step 1: Format Spark Connection String from Databricks Cluster

Step 2: Generate Spark Workspace Access Token

Step 3: Connect to Spark Database from Power BI, Analyze Data.

We connect Power BI Desktop to Databricks clusters using the built-in Spark Connector.

Implementation steps:

Get Databricks connection information

STEP 1:? CREATE AZURE DATABRICKS ACCOUNT

GO TO WORKSPACE > CREATE A CLUSTER

UPLOAD A FILE > CONVERT TO TABLE USING PYTHON SCRIPT. RESULTS IN TEMP VIEW, TABLE.

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STEP 2: GET AZURE DATABRICKS CONNECTION INFORMATION:

1. Get Personal Access Token?

Azure Databricks Workspace Settings > Left: ?Users > Advanced > Generate Token

2. Get Cluster’s Info: Azure Databricks Workspace > Clusters > Advanced > Navigate to JDBC/ODBC Connections > document serverhostname, port, http path

3. Construct the server address to use in the Spark cluster connection in Power BI Desktop Tool:

Format: Scheme/ServerHostname:port/HTTPPath

Example: https://adb-8181190058846624.4.azuredatabricks.net:443/sql/protocolv1/o/8181190058846624/0514-013426-wanna996

STEP 3: Configure connection in Power BI Desktop to a Databricks cluster

Get Data > search, select the Spark connector. Click Connect. In Spark dialog, configure your cluster connection.

??????????????? ??????????????? User name ???????? : ????????????? token        

??????????????????????????????? Password??????????? :????????????? token from above        

?Thats it ! Connect, Read > Format > Add color to your data (Reports & Visulazations) > Analyse.

Related Video from our #Youtube : https://youtu.be/yAksb_CH_e4?si=d9HggRd4jLB0Tte6

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