Query a public dataset with the BigQuery Node.js client library

Open the Cloud Shell Editor

1. In Cloud Shell, create a new Node.js project and file:

   mkdir bigquery-node-quickstart \
       && touch \
       bigquery-node-quickstart/app.js
   

   This command creates a Node.js project that's named bigquery-node-quickstart and a file that's named app.js.

2. Open the Cloud Shell Editor:

   cloudshell workspace bigquery-node-quickstart
   

To learn how to prepare files for queries, click Next.

Prepare files for queries

1. To open a terminal in the Cloud Shell Editor, click Open Terminal.

2. Open your project directory:

   cd bigquery-node-quickstart
   

3. Install the BigQuery client library for Node.js:

   npm install @google-cloud/bigquery
   

   The output is similar to the following:

   added 63 packages in 2s
   

To learn how to query a public dataset in BigQuery, click Next.

Query a public dataset in BigQuery

1. Click Open Editor.

2. In the Explorer pane, locate your BIGQUERY-NODE-QUICKSTART project.

3. Click the app.js file to open it.

4. To create a query against the bigquery-public-data.stackoverflow dataset that returns the top 10 most viewed Stack Overflow pages and their view counts, copy the following code into the app.js file:

   // Import the Google Cloud client library
   const {BigQuery} = require('@google-cloud/bigquery');
   
   async function queryStackOverflow() {
     // Queries a public Stack Overflow dataset.
   
     // Create a client
     const bigqueryClient = new BigQuery();
   
     // The SQL query to run
     const sqlQuery = `SELECT
       CONCAT(
         'https://stackoverflow.com/questions/',
         CAST(id as STRING)) as url,
       view_count
       FROM \`bigquery-public-data.stackoverflow.posts_questions\`
       WHERE tags like '%google-bigquery%'
       ORDER BY view_count DESC
       LIMIT 10`;
   
     const options = {
       query: sqlQuery,
       // Location must match that of the dataset(s) referenced in the query.
       location: 'US',
     };
   
     // Run the query
     const [rows] = await bigqueryClient.query(options);
   
     console.log('Query Results:');
     rows.forEach(row => {
       const url = row['url'];
       const viewCount = row['view_count'];
       console.log(`url: ${url}, ${viewCount} views`);
     });
   }
   queryStackOverflow();

5. Click Open Terminal.

6. In the terminal, run the app.js script. If you are prompted to authorize Cloud Shell and agree to the terms, click Authorize.

   node app.js
   

   The result is similar to the following:

   Query Results:
   url: https://stackoverflow.com/questions/35159967, 170023 views
   url: https://stackoverflow.com/questions/22879669, 142581 views
   url: https://stackoverflow.com/questions/10604135, 132406 views
   url: https://stackoverflow.com/questions/44564887, 128781 views
   url: https://stackoverflow.com/questions/27060396, 127008 views
   url: https://stackoverflow.com/questions/12482637, 120766 views
   url: https://stackoverflow.com/questions/20673986, 115720 views
   url: https://stackoverflow.com/questions/39109817, 108368 views
   url: https://stackoverflow.com/questions/11057219, 105175 views
   url: https://stackoverflow.com/questions/43195143, 101878 views
   

You have successfully queried a public dataset with the BigQuery Node.js client library.

To avoid incurring charges to your account and learn about next steps, click Next.