Create a Cloud Run function that uses BigQuery to submit a query and return results.

This tutorial shows you how to write an HTTP Cloud Run function that submits a query to BigQuery.

Prepare the application

Clone the sample application repository to your local machine:
```
git clone https://github.com/GoogleCloudPlatform/nodejs-docs-samples.git
```
Alternatively, download the sample as a zip file and extract it.
Change to the directory that contains the sample code:
```
cd nodejs-docs-samples/functions/v2/helloBigQuery
```

Take a look at the sample code. The sample submits a query for words that occur at least 400 times in the specified dataset, and returns the result.

// Import the Google Cloud client library
const {BigQuery} = require('@google-cloud/bigquery');
const bigquery = new BigQuery();

const functions = require('@google-cloud/functions-framework');

/**
 * HTTP Cloud Function that returns BigQuery query results
 *
 * @param {Object} req Cloud Function request context.
 * @param {Object} res Cloud Function response context.
 */
functions.http('helloBigQuery', async (req, res) => {
  // Define the SQL query
  // Queries the public Shakespeare dataset using named query parameter
  const sqlQuery = `
      SELECT word, word_count
            FROM \`bigquery-public-data.samples.shakespeare\`
            WHERE corpus = @corpus
            AND word_count >= @min_word_count
            ORDER BY word_count DESC`;

  const options = {
    query: sqlQuery,
    // Location must match that of the dataset(s) referenced in the query.
    location: 'US',
    params: {corpus: 'romeoandjuliet', min_word_count: 400},
  };

  // Execute the query
  try {
    const [rows] = await bigquery.query(options);
    // Send the results
    res.status(200).send(rows);
  } catch (err) {
    console.error(err);
    res.status(500).send(`Error querying BigQuery: ${err}`);
  }
});

Deploy the function

To deploy the function with an HTTP trigger:

Run the following command in the directory that contains the sample code:
```
gcloud run deploy FUNCTION \
   --source . \
   --function FUNCTION_ENTRYPOINT \
   --base-image BASE_IMAGE \
   --region REGION \
   --allow-unauthenticated
```
Replace:
- FUNCTION with the name of the function you are deploying, for example my-bigquery-function. You can omit this parameter entirely, but you will be prompted for the name if you omit it.
- FUNCTION_ENTRYPOINT with the entry point to your function in your source code. This is the code Cloud Run executes when your function runs. The value of this flag must be a function name or fully-qualified class name that exists in your source code. The entry point you must specify for the sample function is helloBigQuery.
- BASE_IMAGE with the base image environment for your function, for example, nodejs22. For details about base images and the packages included in each image, see Runtimes base images.
- REGION with the Google Cloud region where you want to deploy your function. For example, europe-west1.
Optional:
- If you are creating a public HTTP function, for example a webhook, specify the --allow-unauthenticated flag. This flag assigns the Cloud Run IAM Invoker role to the special identifier allUser. You can use IAM to edit this setting later after you create the service.

Test the function

When the function finishes deploying, copy the uri property.
Visit this URI in your browser.

You should see a list of the words that match the query criteria, and how many times each word appears in the target dataset.