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Extend Google Sheets with BigQuery Data
Make calls to the API Server from Google Apps Script.
Interact with BigQuery data from Google Sheets through macros, custom functions, and add-ons. The CData API Server, when paired with the ADO.NET Provider for BigQuery (or any of 200+ other ADO.NET Providers), enables connectivity to BigQuery data from cloud-based and mobile applications like Google Sheets. The API Server is a lightweight Web application that produces OData services for BigQuery and any source supported by the CData ADO.NET Providers.
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 Orders data and, as you make changes, executes updates to BigQuery data.
About BigQuery Data Integration
CData simplifies access and integration of live Google BigQuery data. Our customers leverage CData connectivity to:
- Simplify access to BigQuery with broad out-of-the-box support for authentication schemes, including OAuth, OAuth JWT, and GCP Instance.
- Enhance data workflows with Bi-directional data access between BigQuery and other applications.
- Perform key BigQuery actions like starting, retrieving, and canceling jobs; deleting tables; or insert job loads through SQL stored procedures.
Most CData customers are using Google BigQuery as their data warehouse and so use CData solutions to migrate business data from separate sources into BigQuery for comprehensive analytics. Other customers use our connectivity to analyze and report on their Google BigQuery data, with many customers using both solutions.
For more details on how CData enhances your Google BigQuery experience, check out our blog post: https://www.cdata.com/blog/what-is-bigquery
Getting Started
Set Up the API Server
Follow the steps below to begin producing secure BigQuery OData services:
Deploy
The API Server runs on your own server. On Windows, you can deploy using the stand-alone server or IIS. On a Java servlet container, drop in the API Server WAR file. See the help documentation for more information and how-tos.
The API Server is also easy to deploy on Microsoft Azure, Amazon EC2, and Heroku.
Connect to BigQuery
After you deploy the API Server and the ADO.NET Provider for BigQuery, provide authentication values and other connection properties needed to connect to BigQuery by clicking Settings -> Connections and adding a new connection in the API Server administration console.
Google uses the OAuth authentication standard. To access Google APIs on behalf of individual users, you can use the embedded credentials or you can register your own OAuth app.
OAuth also enables you to use a service account to connect on behalf of users in a Google Apps domain. To authenticate with a service account, register an application to obtain the OAuth JWT values.
In addition to the OAuth values, specify the DatasetId and ProjectId. See the "Getting Started" chapter of the help documentation for a guide to using OAuth.
You can then choose the BigQuery entities you want to allow the API Server to access by clicking Settings -> Resources.
Authorize API Server Users
After determining the OData services you want to produce, authorize users by clicking Settings -> Users. The API Server uses authtoken-based authentication and supports the major authentication schemes. Access can also be restricted based on IP address: Connections from all addresses except localhost are blocked by default, so you will need to allow connections from Google's servers for this article. You can authenticate as well as encrypt connections with SSL.
Retrieve BigQuery 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/Orders?select=Id,OrderName,Freight,ShipCity";
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 orders = JSON.parse(json).value;
var cols = [["Id","OrderName","Freight","ShipCity"]];
sheet.getRange(1,1,1,4).setValues(cols);
row=2;
for(var i in orders){
for (var j in orders[i]) {
switch (j) {
case "Id":
a1.offset(row,0).setValue(account[i][j]);
break;
case "OrderName":
a1.offset(row,1).setValue(account[i][j]);
break;
case "Freight":
a1.offset(row,2).setValue(account[i][j]);
break;
case "ShipCity":
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:
- Click Resources -> Current Project's Triggers -> Add a New Trigger.
- Select retrieve in the Run menu.
- Select From Spreadsheet.
- Select On open.
After closing the dialog, you are prompted to allow access to the application.
Post Changes to BigQuery Data
Add the following function to post changes to cells back to the API Server:
function buildReq(e){
var sheet = SpreadsheetApp.getActiveSheet();
var changes = e.range;
var id = sheet.getRange(changes.getRow(),1).getValue();
var col = sheet.getRange(1,changes.getColumn()).getValue();
var url = "http://MyServer/api.rsc/Orders("+id+")";
var putdata = "{\"@odata.type\" : \"CDataAPI.Orders\", \""+col+"\": \""+changes.getValue()+"\"}";;
UrlFetchApp.fetch(url,{
method: "put",
contentType: "application/json",
payload: putdata,
headers: {"Authorization": "Basic " + Utilities.base64Encode("MyUser:MyAuthtoken")}
});
}
Follow the steps below to add the update trigger:
- Click Resources -> Current Project's Triggers.
- Select buildReq in the Run menu.
- Select From Spreadsheet.
- Select On edit.
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.
As you make changes to cells, the API Server executes updates to BigQuery data.
