Create a Cloud Run function that returns Spanner results

This tutorial shows you how to write an HTTP Cloud Run function that returns Spanner results.

Objectives

Write, deploy, and trigger an HTTP 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, 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

   gitclonehttps://github.com/GoogleCloudPlatform/nodejs-docs-samples.git

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

   Python

   gitclonehttps://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

   cdnodejs-docs-samples/functions/spanner

   Python

   cdpython-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
   constfunctions=require('@google-cloud/functions-framework');
   // Instantiates a client
   constspanner=newSpanner ();
   // Your Cloud Spanner instance ID
   constinstanceId='test-instance';
   // Your Cloud Spanner database ID
   constdatabaseId='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
   constinstance=spanner.instance(instanceId);
   constdatabase=instance.database(databaseId);
   // The query to execute
   constquery={
   sql:'SELECT * FROM Albums',
   };
   // Execute the query
   try{
   constresults=awaitdatabase.run(query);
   constrows=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

   importfunctions_framework
   fromgoogle.cloudimport 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
   defspanner_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:

gcloudrundeploynodejs-spanner-function\
--source.\
--regionREGION\
--functionspannerQuickstart\
--base-imageRUNTIME_ID\
--log-http

gcloudrundeploypython-spanner-function\
--source.\
--regionREGION\
--functionspanner_read_data\
--base-imageRUNTIME_ID\
--log-http

Replace:

• REGION with the name of the Google Cloud region where you want to deploy your function (for example, us-west1).

• RUNTIME_ID with the appropriate runtime ID (for example, nodejs22). See Supported language runtimes and base images.

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:ForeverHoldYourPeace
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:TotalJunk

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

   gcloudrunservicesdeletenodejs-spanner-function

   Python

   gcloudrunservicesdeletepython-spanner-function

What's next

• Learn more about writing Cloud Run functions.
• Learn more about deploying Cloud Run functions.
• Learn more about triggering Cloud Run functions.