Create a Cloud Run function that returns Spanner results

Objectives

Write, deploy, and trigger an HTTP Cloud Function that accesses Spanner.

Costs

This document uses Spanner and Cloud Run, which are billable components of Google Cloud.

  • For information on the cost of using Spanner, see Spanner pricing.

  • For information on the cost of using Cloud Run, including free invocations, see Cloud Run pricing.

Before you begin

  1. This document assumes you have a Spanner instance named test-instance and a database named example-db that uses the music application schema. For instructions on creating an instance and database with the music application schema, see Quickstart using the console or the tutorials for Getting Started in Node.js, or Python.

  2. Enable the Cloud Run functions, Cloud Run, and Cloud Build APIs.

    Enable the APIs

  3. Install and initialize the gcloud CLI.

    If you already have the gcloud CLI installed, update it by running the following command:

    gcloud components update
    
  4. Prepare your development environment:

    Node.js

    See the Node.js setup guide.

    Python

    See the Python setup guide.

Prepare the application

  1. Clone the sample app repository to your local machine:

    Node.js

    git clone https://github.com/GoogleCloudPlatform/nodejs-docs-samples.git

    Alternatively, you can download the sample as a zip file and extract it.

    Python

    git clone https://github.com/GoogleCloudPlatform/python-docs-samples.git

    Alternatively, you can download the sample as a zip file and extract it.

  2. Change to the directory that contains the Cloud Run functions sample code for accessing Spanner:

    Node.js

    cd nodejs-docs-samples/functions/spanner

    Python

    cd python-docs-samples/functions/spanner
  3. Take a look at the sample code:

    Node.js

    // Imports the Google Cloud client library
    const {Spanner} = require('@google-cloud/spanner');
    
    // Imports the functions framework to register your HTTP function
    const functions = require('@google-cloud/functions-framework');
    
    // Instantiates a client
    const spanner = new Spanner();
    
    // Your Cloud Spanner instance ID
    const instanceId = 'test-instance';
    
    // Your Cloud Spanner database ID
    const databaseId = 'example-db';
    
    /**
     * HTTP Cloud Function.
     *
     * @param {Object} req Cloud Function request context.
     * @param {Object} res Cloud Function response context.
     */
    functions.http('spannerQuickstart', async (req, res) => {
      // Gets a reference to a Cloud Spanner instance and database
      const instance = spanner.instance(instanceId);
      const database = instance.database(databaseId);
    
      // The query to execute
      const query = {
        sql: 'SELECT * FROM Albums',
      };
    
      // Execute the query
      try {
        const results = await database.run(query);
        const rows = results[0].map(row => row.toJSON());
        rows.forEach(row => {
          res.write(
            `SingerId: ${row.SingerId}, ` +
              `AlbumId: ${row.AlbumId}, ` +
              `AlbumTitle: ${row.AlbumTitle}\n`
          );
        });
        res.status(200).end();
      } catch (err) {
        res.status(500).send(`Error querying Spanner: ${err}`);
      }
    });

    Python

    import functions_framework
    from google.cloud import spanner
    
    instance_id = "test-instance"
    database_id = "example-db"
    
    client = spanner.Client()
    instance = client.instance(instance_id)
    database = instance.database(database_id)
    
    
    @functions_framework.http
    def spanner_read_data(request):
        query = "SELECT * FROM Albums"
    
        outputs = []
        with database.snapshot() as snapshot:
            results = snapshot.execute_sql(query)
    
            for row in results:
                output = "SingerId: {}, AlbumId: {}, AlbumTitle: {}".format(*row)
                outputs.append(output)
    
        return "\n".join(outputs)
    
    

    The function sends a SQL query to fetch all Albums data from your database. The function is executed when you make an HTTP request to the function's endpoint.

Deploy the function

To deploy the function with an HTTP trigger, run the following command in the spanner directory:

Node.js

gcloud beta run deploy nodejs-spanner-function \
    --source . \
    --region REGION \
    --function spannerQuickstart \
    --base-image RUNTIME_ID \
    --log-http

Python

gcloud beta run deploy python-spanner-function \
    --source . \
    --region REGION \
    --function spanner_read_data \
    --base-image RUNTIME_ID \
    --log-http

Replace:

Function deployment might take up to two minutes.

Note the url value returned when your function finishes deploying. You will use it when you trigger the function.

You can view your deployed functions on the Cloud Run page in the Google Cloud console. You can also create and edit functions on that page, and get details and diagnostics for your functions.

Trigger the function

Make an HTTP request to your function:

curl URL

Replace URL with the URL value returned when your function finishes deploying.

You should see output that shows the results of the SQL query, assuming you worked through a Getting Started tutorial and populated the database:

SingerId: 2, AlbumId: 2, AlbumTitle: Forever Hold Your Peace
SingerId: 1, AlbumId: 2, AlbumTitle: Go, Go, Go
SingerId: 2, AlbumId: 1, AlbumTitle: Green
SingerId: 2, AlbumId: 3, AlbumTitle: Terrified
SingerId: 1, AlbumId: 1, AlbumTitle: Total Junk

You can also visit the function's URL in your browser to see the result of your SQL query.

Clean up

To avoid incurring additional charges to your Google Cloud account for the Spanner and Cloud Run functions resources used in this document:

  1. Delete the instance:

    gcloud CLI instances delete test-instance
    
  2. Delete the Cloud Run service you deployed in this tutorial:

    Node.js

    gcloud run services delete nodejs-spanner-function

    Python

    gcloud run services delete python-spanner-function

What's next