In this section, we will explore how to automate the execution of BigQuery queries using Google Cloud Scheduler. This is particularly useful for running periodic reports, data transformations, or any other recurring tasks.

Cloud Scheduler is a fully managed cron job service that allows you to schedule virtually any job, including BigQuery queries, with a high degree of reliability and accuracy.

• Fully Managed: No need to manage infrastructure.
• Flexible Scheduling: Supports cron syntax for flexible scheduling.
• Integrated with Google Cloud: Easily integrates with other Google Cloud services.

Before you can use Cloud Scheduler, you need to enable the Cloud Scheduler API in your Google Cloud project.

1. Go to the Cloud Scheduler API page.
2. Click "Enable".

1. Navigate to the Cloud Scheduler page.
2. Click "Create Job".

Job Configuration Fields:

• Name: A unique name for your job.
• Frequency: The schedule in cron format (e.g., 0 9 * * 1 for every Monday at 9 AM).
• Timezone: The timezone for the schedule.
• Target: Select "HTTP".
• URL: The endpoint to trigger the BigQuery query (we will set this up next).
• HTTP Method: POST.
• Body: The payload containing the query details.

To execute BigQuery queries, we will use a Cloud Function that will be triggered by the Cloud Scheduler job.

1. Navigate to the Cloud Functions page.
2. Click "Create Function".

Function Configuration Fields:

• Name: A unique name for your function.
• Trigger: HTTP.
• Runtime: Choose your preferred runtime (e.g., Python 3.8).

Below is an example of a Cloud Function written in Python that executes a BigQuery query:

1. Click "Deploy".

After deployment, note the URL of the Cloud Function. This will be used as the target URL in the Cloud Scheduler job.

1. Go back to the Cloud Scheduler job configuration.
2. Set the URL field to the Cloud Function URL.
3. Click "Create".

1. Enable Cloud Scheduler API.
2. Create a Cloud Function that runs a BigQuery query to count the number of rows in a specific table.
3. Create a Cloud Scheduler job to trigger the Cloud Function every day at midnight.

Solution:

1. Enable Cloud Scheduler API: Follow the steps mentioned above.
2. Create a Cloud Function:

   import os
   from google.cloud import bigquery
   from flask import Flask, request
   
   app = Flask(__name__)
   
   @app.route('/', methods=['POST'])
   def run_query():
       client = bigquery.Client()
       query = """
       SELECT COUNT(*) as row_count
       FROM `your_dataset.your_table`
       """
       query_job = client.query(query)
       results = query_job.result()
       for row in results:
           print(f"row_count: {row.row_count}")
       return 'Query executed successfully', 200
   
   if __name__ == '__main__':
       app.run(debug=True)
   

3. Create a Cloud Scheduler job:
   • Name: daily-query-job
   • Frequency: 0 0 * * *
   • Timezone: Your preferred timezone
   • Target: HTTP
   • URL: The URL of your Cloud Function
   • HTTP Method: POST
   • Body: Leave empty

In this section, we learned how to use Cloud Scheduler to automate the execution of BigQuery queries. We covered the setup process, creating a Cloud Function to run the queries, and linking it with Cloud Scheduler. This automation can significantly enhance productivity by ensuring that recurring tasks are performed reliably and on schedule.