Query Azure Data Lake Storage Data as a SQL Server in Node.js

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

CData Connect Server provides a pure SQL Server interface for Azure Data Lake Storage, allowing you to easily build reports from live Azure Data Lake Storage data in Node.js — without replicating the data to a natively supported database. As you build visualizations, Node.js generates SQL queries to gather data. Using optimized data processing out of the box, CData Connect Server pushes all supported SQL operations (filters, JOINs, etc) directly to Azure Data Lake Storage, leveraging server-side processing to quickly return the requested Azure Data Lake Storage data.

Create a Virtual SQL Server Database for Azure Data Lake Storage Data

CData Connect Server uses a straightforward, point-and-click interface to connect to data sources and generate APIs.

1. Login to Connect Server and click Connections.
2. Select "Azure Data Lake Storage" from Available Data Sources.
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 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 "Azure Active Directory".
   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.
4. Click Save Changes
5. Click Privileges -> Add and add the new user (or an existing user) with the appropriate permissions.

With the virtual database created, you are ready to connect to Azure Data Lake Storage data from Node.js.

Query Azure Data Lake Storage from Node.js

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

• Host name, or address, and port: The address of your Connect Server instance and the port (1433)
• Username and password: The username and password of a user you authorized on Connect Server
• Database name: The database you configured for Azure Data Lake Storage (ADLS1)

Connect to Azure Data Lake Storage data and start executing queries with the code below:

const sql = require('mssql');

const config = {
    user: 'your_connect_username', 
    password: 'your_connect_password', 
    server: 'connect_server_url', 
    port: 1433, // optional, defaults to 1433
    database: 'ADLS1',
    authentication: {
        type: 'default'
    },
    options: {
        encrypt: true
    }
}

console.log("Starting...");
connectAndQuery();

async function connectAndQuery() {
    try {
        var poolConnection = await sql.connect(config);

        console.log("Reading rows from the table...");
        var resultSet = await poolConnection.request().query(`SELECT * FROM table_name`);

        console.log(`${resultSet.recordset.length} rows returned.`);

        // output column headers
        var columns = "";
        for (var column in resultSet.recordset.columns) {
            columns += column + ", ";
        }
        console.log("%s	", columns.substring(0, columns.length - 2));

        // ouput row contents from default record set
        resultSet.recordset.forEach(row => {
            console.log("%s	%s", row.CategoryName, row.ProductName);
        });

        // close connection only when we're certain application is finished
        poolConnection.close();
    } catch (err) {
        console.error(err.message);
    }
}

SQL Server Access to Azure Data Lake Storage Data from Node.js

You have retrieved live Azure Data Lake Storage Data using Node.js. Now, you can easily access data sources and more — all without replicating Azure Data Lake Storage data.

To get SQL data access to 200+ SaaS, Big Data, and NoSQL sources directly from your applications, try CData Connect Server.