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⇱ Excel Spreadsheet Automation on Databricks Data with the QUERY Formula

Excel Spreadsheet Automation on Databricks Data with the QUERY Formula

👁 Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Pull data from Databricks, automate spreadsheets, and more with the QUERY formula.

The CData Excel Add-In for Databricks provides formulas that can edit, save, and delete Databricks data. The following three steps show how you can automate the following task: Search Databricks data for a user-specified value and then organize the results into an Excel spreadsheet.

About Databricks Data Integration

Accessing and integrating live data from Databricks has never been easier with CData. Customers rely on CData connectivity to:

  • Access all versions of Databricks from Runtime Versions 9.1 - 13.X to both the Pro and Classic Databricks SQL versions.
  • Leave Databricks in their preferred environment thanks to compatibility with any hosting solution.
  • Secure authenticate in a variety of ways, including personal access token, Azure Service Principal, and Azure AD.
  • Upload data to Databricks using Databricks File System, Azure Blog Storage, and AWS S3 Storage.

While many customers are using CData's solutions to migrate data from different systems into their Databricks data lakehouse, several customers use our live connectivity solutions to federate connectivity between their databases and Databricks. These customers are using SQL Server Linked Servers or Polybase to get live access to Databricks from within their existing RDBMs.

Read more about common Databricks use-cases and how CData's solutions help solve data problems in our blog: What is Databricks Used For? 6 Use Cases.


Getting Started


The syntax of the CDATAQUERY formula is the following: 

=CDATAQUERY(Query, [Connection], [Parameters], [ResultLocation]);

This formula requires three inputs:

  • Query: The declaration of the Databricks data records you want to retrieve or the modifications to be made, written in standard SQL.

  • Connection: Either the connection name, such as DatabricksConnection1, or a connection string. The connection string consists of the required properties for connecting to Databricks data, separated by semicolons.

    To connect to a Databricks cluster, set the properties as described below.

    Note: The needed values can be found in your Databricks instance by navigating to Clusters, and selecting the desired cluster, and selecting the JDBC/ODBC tab under Advanced Options.

    • Server: Set to the Server Hostname of your Databricks cluster.
    • HTTPPath: Set to the HTTP Path of your Databricks cluster.
    • Token: Set to your personal access token (this value can be obtained by navigating to the User Settings page of your Databricks instance and selecting the Access Tokens tab).
  • ResultLocation: The cell that the output of results should start from.

Pass Spreadsheet Cells as Inputs to the Query

The procedure below results in a spreadsheet that organizes all the formula inputs in the first column.

  1. Define cells for the formula inputs. In addition to the connection inputs, add another input to define a criterion for a filter to be used to search Databricks data, such as Country.
  2. In another cell, write the formula, referencing the cell values from the user input cells defined above. Single quotes are used to enclose values such as addresses that may contain spaces.
    3. =CDATAQUERY("SELECT * FROM Customers WHERE Country = '"&B8&"'","Server="&B1&";Port="&B2&";TransportMode="&B3&";HTTPPath="&B4&";UseSSL="&B5&";User="&B6&";Password="&B7&";Provider=Databricks",B9)
    👁 Formula inputs used in this example. (Google Apps is shown.)
  3. Change the filter to change the data. 👁 The outputs of the formula. (Google Apps is shown.)

Ready to get started?

Download a free trial of the Excel Add-In for Databricks to get started:

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Learn more:

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Excel Add-In for Databricks

The Databricks Excel Add-In is a powerful tool that allows you to connect with live Databricks data, directly from Microsoft Excel.

Use Excel to read, write, and update Databricks. Perfect for mass imports / exports / updates, data cleansing & de-duplication, Excel based data analysis, and more!