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Structure of Standard data export | Cloud Billing

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This document provides reference information for the schema of Cloud Billing standard usage cost data that's exported to each table in BigQuery.

In your BigQuery dataset, your standard Google Cloud usage cost data is loaded into a data table named gcp_billing_export_v1_<BILLING_ACCOUNT_ID>.

The following information describes the schema of the Google Cloud standard usage cost data that's exported to BigQuery. The schema contains standard Cloud Billing account cost usage information, such as account ID, invoice date, services, SKUs, projects, labels, locations, cost, usage, credits, adjustments, and currency.

When you use the standard usage cost data in BigQuery, note the following:

• The table schema for the standard Cloud Billing data export can change over time, such as when new fields are added to the standard export. To protect your queries from future schema changes, rather than relying on queries that directly reference the exported columns, we recommend that you use BigQuery views to normalize the data so that the table presents the same schema to your queries. Learn more about this limitation.
• When selecting or creating a BigQuery dataset for your standard usage cost data, you can select any dataset location that's supported for use with Cloud Billing data.
• When you enable the standard usage cost data export for the first time in Cloud Billing, if you select a dataset configured to use a multi-region location (EU or US), Cloud Billing data will be available retroactively from the start of the previous month. Data is exported in chronological order. For the initial backfill of exported data, it might take up to five days for your retroactive Cloud Billing data to finish exporting before you start seeing your most recent usage data.
• If you enable the standard usage cost data export and select a dataset that's configured to use a supported region location, your Cloud Billing data will be available starting from the date when you enabled the export.
• If you enabled, disabled, and subsequently re-enabled the standard usage cost data export, the Cloud Billing data might not be available for the period when data export was explicitly disabled.
• Learn more about the frequency of the data loads into your BigQuery tables.
• The standard usage cost data doesn't include any resource-level cost data, like a virtual machine or SSD that generates service usage. If you're interested in exporting resource-level cost data to BigQuery for analysis, consider enabling the export of detailed usage cost data. The exported detailed usage cost data includes all of the fields and information contained in the standard usage cost data.
• See other limitations that might impact exporting your billing data to BigQuery, such as datasets with customer-managed encryption keys (CMEK) enabled.

The Cloud Billing account ID that the usage is associated with.

For resellers: For usage costs generated by a Cloud Billing subaccount, this is the ID of the subaccount, not the ID of the parent reseller Cloud Billing account.

The year and month (YYYYMM) of the invoice that includes the cost line items. For example: "201901" is equivalent to January, 2019.

You can use this field to get the total charges on the invoice. See Cloud Billing Export to BigQuery Query Examples.

Indicates the publisher associated with the transaction. This field supports the splitting of invoices between transactions made directly with Google (first party), and transactions made with a partner (third party), which also signals what regulations might apply to the transaction.

• GOOGLE: First-party, unregulated transaction by Google Cloud.
• PARTNER: A third-party, regulated or unregulated transaction by a partner.

The type of cost this line item represents: regular, tax, adjustment, or rounding error.

• The first full month of data with this field is January 2019.
• Starting on September 1, 2020, you see a separate line item for taxes, for each of your projects.

For more information, see the BigQuery documentation on timestamp data types. See also, Differences between exported data and invoices.

For more information, see the BigQuery documentation on timestamp data types. See also, Differences between exported data and invoices.

For examples of how to manage your Cloud Billing data exports to BigQuery after the schema update, see Handling schema changes to BigQuery export data tables.

For example: /ParentOrgNumber/ParentFolderNumber/. Learn more about the Resource Hierarchy.

This field describes the structure and value of the resource hierarchy of a cost line item, including projects, folders, and organizations. Ancestors are ordered from node to root (project, folder, then organization).

Cost per the applicable consumption model inclusive of any negotiated discounts reflected in the custom pricing in the contract linked to your Cloud Billing account (if applicable).

If the credits.id field is empty, then the product SKU isn't associated with a credit.

credits.full_name values are only present for SKUs with an alphanumeric credits.id. If the value of the credits.id is a description of the credit type (such as Committed Usage Discount: CPU), then the credits.full_name field is empty.

• COMMITTED_USAGE_DISCOUNT: Resource-based committed use contracts purchased for Compute Engine in return for deeply discounted prices for VM usage.
• COMMITTED_USAGE_DISCOUNT_DOLLAR_BASE: Spend-based committed use contracts purchased for services in exchange for your commitment to spend a minimum amount.
• DISCOUNT: The discount credit type is used for credits earned after a contractual spending threshold is reached. Note that in the Cloud Billing reports available in the Google Cloud console, the discount credit type is listed as Spending based discounts (contractual).
• FREE_TIER: Some services offer free resource usage up to specified limits. For these services, credits are applied to implement the free tier usage.
• PROMOTION: The promotion credit type includes Google Cloud Free Trial and marketing campaign credits, or other grants to use Google Cloud. When available, promotional credits are considered a form of payment and are automatically applied to reduce your total bill.
• RESELLER_MARGIN: If you're a reseller, the reseller margin credit type indicates the Reseller Program Discounts earned on every eligible line item.
• SUBSCRIPTION_BENEFIT: Credits earned by purchasing long-term subscriptions to services in exchange for discounts.
• SUSTAINED_USAGE_DISCOUNT: The sustained use discounts credit type is an automatic discount that you earn for running specific Compute Engine resources for a significant portion of the billing month.

adjustment_info values are only present if the cost line item was generated for a Cloud Billing modification. A modification can happen for correction or non-correction reasons. The adjustment_info type contains details about the adjustment, whether it was issued for correcting an error or other reasons.

For examples of how to manage your Cloud Billing data exports to BigQuery after the schema update, see Handling schema changes to BigQuery export data tables.

The type of adjustment.

Types include:

• USAGE_CORRECTION: A correction due to incorrect reported usage.
• PRICE_CORRECTION: A correction due to incorrect pricing rules.
• METADATA_CORRECTION: A correction to fix metadata without changing the cost.
• GOODWILL: A credit issued to the customer for goodwill.
• SALES_BASED_GOODWILL: A credit issued to the customer for goodwill, as part of a contract.
• SLA_VIOLATION: A credit issued to the customer due to a service-level objective (SLO) violation.
• BALANCE_TRANSFER: An adjustment to transfer funds from one payment account to another.
• ACCOUNT_CLOSURE: An adjustment to bring a closed account to a zero balance.
• GENERAL_ADJUSTMENT: A general billing account modification.

How the adjustment was issued.

Modes include:

• PARTIAL_CORRECTION: The correction partially negates the original usage and cost.
• COMPLETE_NEGATION_WITH_REMONETIZATION: The correction fully negates the original usage and cost, and issues corrected line items with updated usage and cost.
• COMPLETE_NEGATION: The correction fully negates the original usage and cost, and no further usage is remonetized.
• MANUAL_ADJUSTMENT: The adjustment is allocated to cost and usage manually.

Fields that describe the tag, such as key, value, and namespace.

The short name or display name of the key associated with this particular tag.

The resources attached to a tags.key. At any given time, exactly one value can be attached to a resource for a given key.

Indicates whether a tag binding is inherited (Tags Inherited = True) or direct/non-inherited (Tags Inherited = False). You can create a tag binding to a parent resource in the resource hierarchy.

Represents the resource hierarchy that define tag key and values. Namespace can be combined with tag key and tag value short names to create a globally unique, fully qualified name for the tag key or tag value.

Cost at list price per the default consumption model.

The transaction type of the seller. The transaction type might be one of the following:

• GOOGLE = 1: Services sold by Google Cloud.
• THIRD_PARTY_RESELLER = 2: Third party services resold by Google Cloud.
• THIRD_PARTY_AGENCY = 3: Third party services sold by a partner, with Google Cloud acting as the agent.

The legal name of the seller.

Fields that describe the structure and values related to the prices charged for usage.

SKU list price per the default consumption model.

SKU price per the default consumption model inclusive of any negotiated discounts reflected in the custom pricing in the contract linked to your Cloud Billing account (if applicable).

SKU list price per the applicable consumption model before any negotiated discounts reflected in the custom pricing in the contract linked to your Cloud Billing account (if applicable).

SKU price per the applicable consumption model inclusive of any negotiated discounts reflected in the custom pricing in the contract linked to your Cloud Billing account (if applicable).

The lower bound number of units for a SKU's pricing tier. For more information, see About pricing tiers.

The unit of usage in which the pricing is specified and resource usage is measured.

The lower bound number of units for a SKU's pricing tier. For more information, see About pricing tiers.

Cost per the default consumption model inclusive of any negotiated discounts reflected in the custom pricing in the contract linked to your Cloud Billing account (if applicable).

Cost per the applicable consumption model before any negotiated discounts reflected in the custom pricing in the contract linked to your Cloud Billing account (if applicable).

Fields that describe the applicable consumption model.

The ID of the consumption model.

The description of the consumption model.

The following sections describe the standard and detailed usage cost data exported to BigQuery.

The cost data for a specific label only shows usage from the date that the label was applied to a resource. For example, if you add the label environment:dev to a Compute Engine VM on January 15, 2024, any analysis for environment:dev includes only the usage for that VM since January 15.

You might also see label data at different times for different services, depending on when each service provides it.

System labels are key-value pairs for important metadata about the resource that generated the usage. The following system labels are automatically included on applicable usage.

Google Cloud products report usage and cost data to Cloud Billing processes at varying intervals. As a result, you might see a delay between your use of Google Cloud services, and the usage and costs being available to view in Cloud Billing. Typically, your costs are available within a day, but can sometimes take more than 24 hours.

At the end of a calendar month, late-reported usage might not be included on that month's invoice and instead might roll over to the next month's invoice.

When you query your costs using timestamp fields, your returned data might pick up late-reported usage that wasn't originally included on the invoice that was generated for the same usage month. As a result, the Cloud Billing data returned might not map directly to that invoice.

Timestamp fields include:

• usage_start_time
• usage_end_time
• export_time

To return Cloud Billing data that maps directly to an invoice, query on invoice.month instead of timestamp fields.

As of September 1, 2020, your usage cost data shows your tax liability for each of your projects, instead of as a single line item. If you have queries or visualizations that depend on tax data, you might need to update the queries to account for these changes.

For example, for costs recorded before September 1, your usage cost data looks similar to the following example, which shows a total tax liability of $10.

For costs recorded after September 1, the $10 is broken down to $6 for example-project, and $4 for test-project:

In the rare event that your Cloud Billing data contains an error or requires an adjustment, it's appended with corrective data. These adjustments fall under one of two categories: billing modifications or corrections.

Billing modifications appear as separate line items. If you received a billing modification, a new line item in your Cloud Billing export to BigQuery shows the change. The adjustments shown correspond to the invoice, credit memo, and debit memo documents available in the Documents area of the Billing section in the Google Cloud console.

For more information on billing modifications and how they're applied, see Understand memos and adjustments.

Corrections appear as new data that negates incorrect data on the source SKUs. In some cases, new data replaces the incorrect charge. All columns in the billing data export will match the original data, except for the following columns:

• cost
• credit
• usage.amount
• export_time

For example, imagine that you're charged $10 for your usage of SKU A on January 1. On your January invoice (issued in early February), you'll see a charge of $10 for SKU A. However, on February 2, Google Cloud issued a correction against SKU A, reducing the usage cost to $5. You'll receive two additional line items on your February invoice (issued in early March):

• -$10 for usage on January 1 (negating the original charge)
• $5 for usage on January 1 (stating the intended charge)

These new items have an adjustment_info column in the billing data export. The original January invoice, showing the overcharge, won't be adjusted. You can verify your charges in your billing data export by viewing your costs by usage_start_time and grouping by Day. In these views, any corrections or charges for late-monetized usage are accumulated, and you don't need to worry about any temporarily incorrect data.

If you want more detailed information on your corrections, view all charges in an invoice month, and look for charges where the usage date occurred before the invoice month. These charges are the results of corrections or late-monetized usage.

The following code sample shows how to create a basic query that returns the total cost of corrections or late-monetized usage:

SELECT
  SUM(cost)
    + SUM(IFNULL((SELECT SUM(c.amount)
      FROM   UNNEST(credits) c), 0))
    AS total
FROM `project.dataset.gcp_billing_export_v1_XXXXXX-XXXXXX-XXXXXX`
WHERE
  invoice.month = '202311' AND
  DATE(TIMESTAMP_TRUNC(usage_start_time, Day, 'US/Pacific')) < '2023-11-01';

For a query example that returns a cost breakdown by service, for invoice charges, where the usage date occurred before the invoice month, see Query cost details to view corrections or late-monetized usage by service for a specified invoice month in "Example queries for Cloud Billing data export."

If you have a custom pricing contract, you might receive promotional credits to use on Google Cloud as part of the contract. For example, you might receive $1,000 to use on Compute Engine resources. Promotional credits are typically considered a form of payment. When available, promotional credits are automatically applied to reduce your total bill.

The terms of your contract specify whether the promotional credits apply to your costs calculated at the list price of a SKU, or the net price (after discounts).

If your promotional credits apply to costs that are calculated at the list price, in the Cost table report, there's a service called Invoice, with a SKU called Contract billing adjustment. This SKU adjusts your credits so that they apply to the costs at list price. To see the usage that the adjustment is for, query the system.labels columns. The key in system.labels.key is cloud-invoice.googleapis.com/sku_id, and the value in system.labels.value contains the SKU ID that the credit and the adjustment applied to.

Tags are resources in the form of key-value pairs that can be attached to resources directly or through inheritance. You can use tags to perform chargebacks, audits, and other cost allocation analysis. You can also use tags and conditional enforcement of policies for fine-grained control across your resource hierarchy.

Tags have a robust permissions model and can support inheritance, centralized management, nomenclature standardization, and policy engine integration, while labels are a separate tool that allow you to annotate resources.

Tags data appears in BigQuery exports for Resources, Projects, Folders, and Organizations.

The Standard costs and Detailed costs exports for Resources, Projects, Folders, and Organizations include these fields for tags data: Tags Key, Tags Value, Tags Inherited, and Tags Namespace.

Resource-level tags in the Cloud Billing data export are available for the following resources:

• AlloyDB for PostgreSQL clusters, instances, and backups
• Artifact Registry repositories
• Bigtable instances
• Cloud Run services and jobs
• Cloud Storage buckets
• Compute Engine instances
• Memorystore for Redis instances
• Secret Manager global and regional secrets
• Spanner instances
• Firestore databases

• Tags might take up to an hour to propagate to BigQuery exports. If a tag has been added or removed within an hour, or if a resource has existed for less than an hour, it might not appear in the export.

This section provides examples of how to query the Cloud Billing standard usage cost data exported to BigQuery.

• Return the total costs on an invoice
  • Example 1: Sum of all costs, per invoice
  • Example 2: Return details by cost type, per invoice month
• Query examples with labels
  • Query every row without grouping
  • Group by label map as a JSON string
  • Group by label value for a specific key
  • Group by key/value pairs
• Committed use discount queries
  • Viewing commitment fees
  • Viewing commitment credits
• Use resource hierarchy filters to review ancestry
• Example 1: Filter by resource name
• Example 2: Filter by display name
• Additional query examples
  • Query costs and credits by project for a specified invoice month

In these examples, to query the Cloud Billing data in BigQuery, you need to specify the table name in the FROM clause. The table name is determined using three values: project.dataset.BQ_table_name.

• project is the ID of the Google Cloud project you set up that contains your BigQuery dataset.
• dataset is the name of the BigQuery dataset you set up to contain the BigQuery tables with your exported Cloud Billing data.
• BQ_table_name is the name of the BigQuery table that contains the exported Cloud Billing data that you want to query. There are three BigQuery tables that contain Cloud Billing data:
  • Standard usage cost table: In your BigQuery dataset, this table is named gcp_billing_export_v1_<BILLING_ACCOUNT_ID>.
  • Detailed usage cost table: In your BigQuery dataset, this table is named gcp_billing_export_resource_v1_<BILLING_ACCOUNT_ID>.
  • Pricing table: In your BigQuery dataset, this table is named cloud_pricing_export.

The query examples in this section use the following value for Table name: project.dataset.gcp_billing_export_v1_XXXXXX_XXXXXX_XXXXXX

These query examples also work with the detailed usage cost data exported to BigQuery, although they aren't written to retrieve any of the resource-level information that's provided with the detailed usage cost export option.

The following queries demonstrate two ways of viewing cost and credit values using exported billing data.

• The total field directly sums the floating point cost and credit values, which can result in floating point rounding errors.
• The total_exact field converts costs and credit values to micros before summing, then converts back to dollars after summing, avoiding the floating point rounding error.

This query shows the invoice total for each month, as a sum of regular costs, taxes, adjustments, and rounding errors.

Standard SQL

SELECT
  invoice.month,
  SUM(cost)
    + SUM(IFNULL((SELECT SUM(c.amount)
                  FROM UNNEST(credits) c), 0))
    AS total,
  (SUM(CAST(cost * 1000000 AS int64))
    + SUM(IFNULL((SELECT SUM(CAST(c.amount * 1000000 as int64))
                  FROM UNNEST(credits) c), 0))) / 1000000
    AS total_exact
FROM `project.dataset.gcp_billing_export_v1_XXXXXX_XXXXXX_XXXXXX`
GROUP BY 1
ORDER BY 1 ASC
;

For example, the result of the preceding query might be:

This query shows the totals for each cost_type for each month. Cost types include regular costs, taxes, adjustments, and rounding errors.

Standard SQL

SELECT
  invoice.month,
  cost_type,
  SUM(cost)
    + SUM(IFNULL((SELECT SUM(c.amount)
                  FROM   UNNEST(credits) c), 0))
    AS total,
  (SUM(CAST(cost * 1000000 AS int64))
    + SUM(IFNULL((SELECT SUM(CAST(c.amount * 1000000 as int64))
                  FROM UNNEST(credits) c), 0))) / 1000000
    AS total_exact
FROM `project.dataset.gcp_billing_export_v1_XXXXXX_XXXXXX_XXXXXX`
GROUP BY 1, 2
ORDER BY 1 ASC, 2 ASC
;

For example, the result of the preceding query might be:

The following examples illustrate other ways to query your data with labels.

For the examples in this section, assume the following:

• You have two apps (grapefruit-squeezer and chocolate-masher).
• For each app, you have two environments (dev and prod).
• The dev environment has one small instance per app.
• The prod environment has one small instance in Americas and one small instance in Asia.
• Each instance is labeled with the app and environment.
• You have one instance with no labels that you use for experimentation.

Your total bill is $24 with the following breakdown:

The most granular view of these costs would be to query every row without grouping. Assume all fields, except labels and sku description, are the same (project, service, and so on).

Standard SQL

SELECT
  sku.description,
  TO_JSON_STRING(labels) as labels,
 cost as cost
FROM `project.dataset.gcp_billing_export_v1_XXXXXX_XXXXXX_XXXXXX`;

Legacy SQL

TO_JSON_STRING not supported.

This is a quick and easy way to break down cost by each label combination.

Standard SQL

SELECT
  TO_JSON_STRING(labels) as labels,
  sum(cost) as cost
FROM `project.dataset.gcp_billing_export_v1_XXXXXX_XXXXXX_XXXXXX`
GROUP BY labels;

Legacy SQL

TO_JSON_STRING not supported.

Breaking down costs for values of a specific label key is a common use case. By using a LEFT JOIN and putting the key filter in the JOIN condition (rather than WHERE), you include cost that doesn't contain this key, and so receive a complete view of your cost.

Standard SQL

SELECT
  labels.value as environment,
  SUM(cost) as cost
FROM `project.dataset.gcp_billing_export_v1_XXXXXX_XXXXXX_XXXXXX`
LEFT JOIN UNNEST(labels) as labels
  ON labels.key = "environment"
GROUP BY environment;

Legacy SQL

SELECT
  labels.value as environment,
  SUM(cost) as cost
FROM [project:dataset.gcp_billing_export_v1_XXXXXX_XXXXXX_XXXXXX]
WHERE labels.key = "environment" OR labels.key IS NULL
GROUP BY environment;

Be careful when interpreting or exporting these results. An individual row here shows a valid sum without any double counting, but shouldn't be combined with other rows (except possibly if the key is the same, or if you're certain the keys are never set on the same resource).

Standard SQL

SELECT
  labels.key as key,
  labels.value as value,
  SUM(cost) as cost
FROM `project.dataset.gcp_billing_export_v1_XXXXXX_XXXXXX_XXXXXX`
LEFT JOIN UNNEST(labels) as labels
GROUP BY key, value;

Legacy SQL

SELECT
  labels.key as key,
  labels.value as value,
  SUM(cost)
FROM [project:dataset.gcp_billing_export_v1_XXXXXX_XXXXXX_XXXXXX]
GROUP BY key, value;

Note that the total sum is greater than your bill.

The following queries demonstrate ways of viewing the fees and credits associated with committed use discounts in exported billing data. To understand how your commitment fees and credits are attributed to your Cloud Billing account and projects, see Attribution of committed use discounts.

To view the commitment fees for your committed use discounts in your billing data export, use the following sample query.

Standard SQL

SELECT
    invoice.month AS invoice_month,
    SUM(cost) as commitment_fees
FROM `project.dataset.gcp_billing_export_v1_XXXXXX_XXXXXX_XXXXXX`
WHERE LOWER(sku.description) LIKE "commitment%"
GROUP BY 1

To view your committed use discount credits in your billing data export, use the following sample query.

Standard SQL

SELECT
    invoice.month AS invoice_month,
    SUM(credits.amount) as CUD_credits
FROM `project.dataset.gcp_billing_export_v1_XXXXXX_XXXXXX_XXXXXX`
LEFT JOIN UNNEST(credits) AS credits
WHERE LOWER(credits.name) LIKE "committed use discount%"
GROUP BY 1

You can use resource hierarchy filters to aggregate costs by hierarchy elements such as projects, folders, and organizations. These query examples show methods for summing costs filtered by resource hierarchy elements and displaying project ancestries.

This example demonstrates queries that group costs by project ancestry and filter for only costs generated under a specified hierarchy element, identified by the relative resource name.

SELECT
    invoice.month AS invoice_month,
    TO_JSON_STRING(project.ancestors) as ancestors,
    SUM(cost)
        + SUM(IFNULL((SELECT SUM(c.amount) FROM UNNEST(credits) c), 0))
        AS net_cost
  FROM `project.dataset.gcp_billing_export_v1_XXXXXX_XXXXXX_XXXXXX` as bq
  WHERE TO_JSON_STRING(project.ancestors) like "%resource_name\":\"folders/1234"
  GROUP BY invoice_month, ancestors
  ORDER BY invoice_month, ancestors

SELECT
    invoice.month AS invoice_month,
    TO_JSON_STRING(project.ancestors) as ancestors,
    SUM(cost)
        + SUM(IFNULL((SELECT SUM(c.amount) FROM UNNEST(credits) c), 0))
        AS net_cost
  FROM `project.dataset.gcp_billing_export_v1_XXXXXX_XXXXXX_XXXXXX` as bq, UNNEST(project.ancestors) as ancestor
  WHERE ancestor.resource_name = "folders/1234"
  GROUP BY invoice_month, ancestors
  ORDER BY invoice_month, ancestors

This example demonstrates queries that group costs by project ancestry and filter for only costs generated under a specified hierarchy element, identified by the user-provided display name.

SELECT
    invoice.month AS invoice_month,
    TO_JSON_STRING(project.ancestors) as ancestors,
    SUM(cost)
        + SUM(IFNULL((SELECT SUM(c.amount) FROM UNNEST(credits) c), 0))
        AS net_cost
  FROM `project.dataset.gcp_billing_export_v1_XXXXXX_XXXXXX_XXXXXX` as bq
  WHERE TO_JSON_STRING(project.ancestors) like "%display_name\":\"MyFolderName%"
  GROUP BY invoice_month, ancestors
  ORDER BY invoice_month, ancestors

SELECT
    invoice.month AS invoice_month,
    TO_JSON_STRING(project.ancestors) as ancestors,
    SUM(cost)
        + SUM(IFNULL((SELECT SUM(c.amount) FROM UNNEST(credits) c), 0))
        AS net_cost
  FROM `project.dataset.gcp_billing_export_v1_XXXXXX_XXXXXX_XXXXXX` as bq, UNNEST(project.ancestors) as ancestor
  WHERE ancestor.display_name = "MyFolderName"
  GROUP BY invoice_month, ancestors
  ORDER BY invoice_month, ancestors

The following examples illustrate ways to query your data with tags.

The following query demonstrates how you can use return costs by invoice month for the cost_center tag.

SELECT
  invoice.month AS invoice_month,
  tag.value AS cost_center,
  ROUND((SUM(CAST(cost AS NUMERIC))
    + SUM(IFNULL((SELECT SUM (CAST(c.amount AS NUMERIC))
                  FROM UNNEST(credits) AS c), 0))), 2)
    AS net_cost
FROM `project-ID.dataset.gcp_billing_export_resource_v1_XXXXXX-XXXXXX-XXXXXX`, UNNEST(tags) AS tag
WHERE tag.key = "cost_center" AND tag.namespace = "821092389413"
GROUP BY invoice.month, tag.value
ORDER BY invoice.month, tag.value;

For example, the result of the preceding query might be:

This query shows the invoice total for untagged resources, grouped by invoice month.

SELECT
 invoice.month AS invoice_month,
 ROUND((SUM(CAST(cost AS NUMERIC))
   + SUM(IFNULL((SELECT SUM(CAST(c.amount AS NUMERIC))
                 FROM UNNEST(credits) AS c), 0))), 2)
   AS net_cost
FROM
 `project-ID.dataset.gcp_billing_export_v1_XXXXXX-XXXXXX-XXXXXX`
WHERE "color" NOT IN (SELECT key FROM UNNEST(tags))
GROUP BY invoice_month
ORDER BY invoice_month;

For example, the result of the preceding query might be:

By providing a specific invoice month of June 2020 (in the format YYYYMM), this query will return a view of the costs and credits grouped by project along with showing project labels.

Standard SQL

SELECT
  project.name,
  TO_JSON_STRING(project.labels) as project_labels,
  sum(cost) as total_cost,
  SUM(IFNULL((SELECT SUM(c.amount) FROM UNNEST(credits) c), 0)) as total_credits
FROM `project.dataset.gcp_billing_export_v1_XXXXXX_XXXXXX_XXXXXX`
WHERE invoice.month = "202006"
GROUP BY 1, 2
ORDER BY 1;

Legacy SQL

TO_JSON_STRING not supported.

• Set up Cloud Billing data export to BigQuery
• Example queries for Cloud Billing data export to BigQuery
• Visualize spend over time with Looker Studio

• View your Cloud Billing reports and cost trends
• View and download the cost details of your invoice or statement
• View and download prices for Google's cloud services
• Understand your savings with cost breakdown reports
• Analyze the effectiveness of your committed use discounts
• View your cost and payment history

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2025-08-07 UTC.

[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-07 UTC."],[[["This document outlines the schema for Cloud Billing standard usage cost data, which is exported to BigQuery and loaded into a table named `gcp_billing_export_v1_\u003cBILLING_ACCOUNT_ID\u003e`."],["The standard usage cost data includes details such as account ID, invoice date, services, SKUs, projects, labels, locations, cost, usage, credits, adjustments, and currency, but does not include resource-level costs."],["Key concepts for understanding the data include the use of labels for cost analysis, potential data delays in cost availability, the timing of invoices, the handling of taxes and adjustments, the use of promotional credits, and the application of tags for resource management."],["The schema defines fields that describe the cost breakdown, including the services, resources, and projects involved in the billing, as well as the credits and adjustment made to the invoice, with available data from different moments."],["Several query examples are provided to analyze the data, including total costs per invoice, cost details per invoice month, grouping by labels, committed use discounts, resource hierarchy filters, costs by tag, and costs/credits by project."]]],[]]

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