Extend Google Sheets with Azure Data Lake Storage Data

Interact with Azure Data Lake Storage data from Google Sheets through macros, custom functions, and add-ons. The CData API Server enables connectivity to Azure Data Lake Storage data from cloud-based and mobile applications like Google Sheets. The API Server is a lightweight Web application that produces OData services for Azure Data Lake Storage.

Google Apps Script can consume these OData services in the JSON format. This article shows how to create a simple add-on that populates a Google Spreadsheet with Resources data.

Set Up the API Server

If you have not already done so, download the CData API Server. Once you have installed the API Server, follow the steps below to begin producing secure Azure Data Lake Storage OData services:

Connect to Azure Data Lake Storage

To work with Azure Data Lake Storage data from Google Sheets, we start by creating and configuring a Azure Data Lake Storage connection. Follow the steps below to configure the API Server to connect to Azure Data Lake Storage data:

1. First, navigate to the Connections page.
2. Click Add Connection and then search for and select the Azure Data Lake Storage connection. 👁 Selecting a data source (SQLite is shown)
   
3. Enter the necessary authentication properties to connect to Azure Data Lake Storage.

   Authenticating to a Gen 1 DataLakeStore Account

   Gen 1 uses OAuth 2.0 in Entra ID (formerly Azure AD) for authentication.

   For this, an Active Directory web application is required. You can create one as follows:

   1. Sign in to your Azure Account through the
   2. Select "Entra ID" (formerly Azure AD).
   3. Select "App registrations".
   4. Select "New application registration".
   5. Provide a name and URL for the application. Select Web app for the type of application you want to create.
   6. Select "Required permissions" and change the required permissions for this app. At a minimum, "Azure Data Lake" and "Windows Azure Service Management API" are required.
   7. Select "Key" and generate a new key. Add a description, a duration, and take note of the generated key. You won't be able to see it again.

   To authenticate against a Gen 1 DataLakeStore account, the following properties are required:

   • Schema: Set this to ADLSGen1.
   • Account: Set this to the name of the account.
   • OAuthClientId: Set this to the application Id of the app you created.
   • OAuthClientSecret: Set this to the key generated for the app you created.
   • TenantId: Set this to the tenant Id. See the property for more information on how to acquire this.
   • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.

   Authenticating to a Gen 2 DataLakeStore Account

   To authenticate against a Gen 2 DataLakeStore account, the following properties are required:

   • Schema: Set this to ADLSGen2.
   • Account: Set this to the name of the account.
   • FileSystem: Set this to the file system which will be used for this account.
   • AccessKey: Set this to the access key which will be used to authenticate the calls to the API. See the property for more information on how to acquire this.
   • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.
   👁 Connecting to a datasource (SQLite is shown)
   
4. After configuring the connection, click Save & Test to confirm a successful connection.

Configure API Server Users

Next, create a user to access your Azure Data Lake Storage data through the API Server. You can add and configure users on the Users page. Follow the steps below to configure and create a user:

1. On the Users page, click Add User to open the Add User dialog.
2. Next, set the Role, Username, and Privileges properties and then click Add User. 👁 Configure a new user
   
3. An Authtoken is then generated for the user. You can find the Authtoken and other information for each user on the Users page: 👁 API Server user settings
   

Creating API Endpoints for Azure Data Lake Storage

Having created a user, you are ready to create API endpoints for the Azure Data Lake Storage tables:

1. First, navigate to the API page and then click Add Table . 👁 Add tables
   
2. Select the connection you wish to access and click Next. 👁 Select the connection (SQLite is shown)
   
3. With the connection selected, create endpoints by selecting each table and then clicking Confirm. 👁 Adding tables from the connection (SQLite is shown)
   

Gather the OData Url

Having configured a connection to Azure Data Lake Storage data, created a user, and added resources to the API Server, you now have an easily accessible REST API based on the OData protocol for those resources. From the API page in API Server, you can view and copy the API Endpoints for the API:

Retrieve Azure Data Lake Storage Data

Open the Script Editor from your spreadsheet by clicking Tools -> Script Editor. In the Script Editor, add the following function to populate a spreadsheet with the results of an OData query:

function retrieve(){
 var url = "https://MyUrl/api.rsc/Resources?select=Id,FullPath,Permission,Type";
 var response = UrlFetchApp.fetch(url,{
 headers: {"Authorization": "Basic " + Utilities.base64Encode("MyUser:MyAuthtoken")}
 }); 
 var json = response.getContentText();
 var sheet = SpreadsheetApp.getActiveSheet();
 var a1 = sheet.getRange('a1');
 var index=1;
 var resources = JSON.parse(json).value;

 var cols = [["Id","FullPath","Permission","Type"]]; 
 sheet.getRange(1,1,1,4).setValues(cols);

 row=2;
 for(var i in resources){
 for (var j in resources[i]) {
 switch (j) {
 case "Id":
 a1.offset(row,0).setValue(account[i][j]);
 break;
 case "FullPath":
 a1.offset(row,1).setValue(account[i][j]);
 break;
 case "Permission":
 a1.offset(row,2).setValue(account[i][j]);
 break;
 case "Type":
 a1.offset(row,3).setValue(account[i][j]);
 break;
 } 
 }
 row++;
 }
}

Follow the steps below to add an installable trigger to populate the spreadsheet when opened:

1. Click Resources -> Current Project's Triggers -> Add a New Trigger.
2. Select retrieve in the Run menu.
3. Select From Spreadsheet.
4. Select On open.

After closing the dialog, you are prompted to allow access to the application.

You can test the script by clicking Publish -> Test as Add-On. Select the version, installation type, and spreadsheet to create a test configuration. You can then select and run the test configuration.