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URL: https://www.cdata.com/kb/tech/bigquery-cloud-nodejs.rst

โ‡ฑ Query BigQuery Data as a SQL Server Database in Node.js


Query BigQuery Data as a SQL Server Database in Node.js

๐Ÿ‘ Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Execute SQL Server queries against BigQuery data from Node.js.

You can use CData Connect AI to query BigQuery data through a SQL Server interface. Follow the procedure below to create a virtual database for BigQuery in Connect AI and start querying using Node.js.

CData Connect AI provides a pure MySQL, cloud-to-cloud interface for BigQuery, allowing you to easily query live BigQuery data in Node.js โ€” without replicating the data to a natively supported database. As you query data in Node.js, CData Connect AI pushes all supported SQL operations (filters, JOINs, etc) directly to BigQuery, leveraging server-side processing to quickly return 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


Configure BigQuery Connectivity for NodeJS

Connectivity to BigQuery from NodeJS is made possible through CData Connect AI. To work with BigQuery data from NodeJS, we start by creating and configuring a BigQuery connection.

  1. Log into Connect AI, click Sources, and then click Add Connection
  2. ๐Ÿ‘ Adding a Connection
  3. Select "BigQuery" from the Add Connection panel
  4. ๐Ÿ‘ Selecting a data source
  5. BigQuery uses OAuth to authenticate. Click "Sign in" to authenticate with BigQuery. ๐Ÿ‘ Authenticating with OAuth (Salesforce is shown).
  6. Navigate to the Permissions tab in the Add BigQuery Connection page and update the User-based permissions. ๐Ÿ‘ Updating permissions

Add a Personal Access Token

When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. It is best practice to create a separate PAT for each service to maintain granularity of access.

  1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
  2. On the Settings page, go to the Access Tokens section and click Create PAT.
  3. Give the PAT a name and click Create. ๐Ÿ‘ Creating a new PAT
  4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, you are ready to connect to BigQuery data from Node.js.

Query BigQuery from Node.js

The following example shows how to define a connection and execute queries to BigQuery with the SQL Server module. You will need the following information:

  • server: tds.cdata.com
  • port: 14333
  • user: a Connect AI user (e.g. [email protected])
  • password: the PAT for the above user
  • database: The connection you configured for BigQuery (GoogleBigQuery1)

Connect to BigQuery data and start executing queries with the code below:

var sql = require('mssql')
var config = {
	server: 'tds.cdata.com',
	port: 14333, 
	user: '[email protected]', //update me
	password: 'CONNECT_USER_PAT', //update me	
	options: {
		encrypt: true,
		database: 'GoogleBigQuery1'
	}
}

sql.connect(config, err => { 
 if(err){
 throw err ;
 }
 new sql.Request().query('SELECT * FROM Orders', (err, result) => {
 console.dir(result)
 })
 
});

sql.on('error', err => {
 console.log("SQL Error: " ,err);
})