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Labs

View Sample Billing Data with BigQuery

In this lab, we are going to use BigQuery to view a public dataset with sample billing data from a Google Cloud organization. Note: Make sure you right-click on the green "Open GCP Window" button and choose "Open Link in Incognito Window." If the legal agreement hangs for over a minute, just use the refresh page on your browser.

Labs

Path Info

Level
Clock icon Beginner
Duration
Clock icon 45m
Published
Clock icon Feb 21, 2019

Contact sales

By filling out this form and clicking submit, you acknowledge our privacy policy.

Table of Contents

  1. Challenge

    Launch BigQuery

    Launch BigQuery

    • From the top left menu, scroll down to Big Data, and select BigQuery.
  2. Challenge

    Run queries and view results

    Run queries and view results

    Now that we are in BigQuery, let's look at the sample dataset we are going to work with. We are going to view all columns in our example table to see what fields are included. From the large Query Editor box, copy and paste the following query, then click the Run button:

    SELECT *  
    FROM `cloud-training-prod-bucket.arch_infra.billing_data`
    

    The field FROMcloud-training-prod-bucket.arch_infra.billing_data`` is the public dataset we are working with.

    If we click the Results tab underneath, we can view the entire table we are going to work with. Feel free to experiment with other queries such as ordering by cost or usage amount by adding the below string to your query to sort by the column of your choice:

    SELECT *  
    FROM `cloud-training-prod-bucket.arch_infra.billing_data`
    ORDER BY cost DESC
    

    In this query, we are bringing up the entire table contents, but sorting by the highest cost first. You can experiment with other fields as well.

    Let's now do some specific queries. In the same Query editor box, delete the existing contents, and enter the below query to find all charges that were more than 3 dollars:

    SELECT product, resource_type, start_time, end_time,  
    cost, project_id, project_name, project_labels_key, currency, currency_conversion_rate,
    usage_amount, usage_unit
    FROM `cloud-training-prod-bucket.arch_infra.billing_data`
    WHERE (cost > 3)
    

    Next let’s find which product had the highest total number of records:

    SELECT product, COUNT(*)
    FROM `cloud-training-prod-bucket.arch_infra.billing_data`
    GROUP BY product
    LIMIT 200
    

    Looks like Pub/Sub is pretty popular here...

    Finally, let’s see which product most frequently cost more than a dollar:

    SELECT product, cost, COUNT(*)
    FROM `cloud-training-prod-bucket.arch_infra.billing_data`
    WHERE (cost > 1)
    GROUP BY cost, product
    LIMIT 200
    

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