Structure of Standard data export

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

Schema of the standard usage cost data

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:

  • 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.
Field Type Description
billing_account_id String

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.
invoice.month String

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.
invoice.publisher_type String

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.

The possible values are:
  • GOOGLE: First-party, unregulated transaction by Google Cloud.
  • PARTNER: A third-party, regulated or unregulated transaction by a partner.
cost_type String

The type of cost this line item represents: regular, tax, adjustment, or rounding error.
service.id String The ID of the service that the usage is associated with.
service.description String The Google Cloud service that reported the Cloud Billing data.
sku.id String The ID of the resource used by the service. For the full list of SKUs, see Google Cloud SKUs.
sku.description String A description of the resource type used by the service. For example, a resource type for Cloud Storage is Standard Storage US.
usage_start_time Timestamp The start time of the hourly usage window within which the given cost was calculated. The usage and costs for all services is displayed with hourly granularity, which means long running service usage is spread across multiple hourly windows.

For more information, see the BigQuery documentation on timestamp data types. See also, Differences between exported data and invoices.
usage_end_time Timestamp The end time of the hourly usage window within which the given cost was calculated. The usage and costs for all services is displayed with hourly granularity, which means long running service usage is spread across multiple hourly windows.

For more information, see the BigQuery documentation on timestamp data types. See also, Differences between exported data and invoices.
project Struct project contains fields that describe the Cloud Billing project, such as ID, number, name, ancestry_numbers, and labels.
project.id String The ID of the Google Cloud project that generated the Cloud Billing data.
project.number String An internally generated, anonymized, unique identifier for the Google Cloud project that generated the Cloud Billing data. In your support cases and other customer communication, Google will refer to your projects by this project number.
project.name String The name of the Google Cloud project that generated the Cloud Billing data.
project.ancestry_numbers String The ancestors in the resource hierarchy for the project identified by the specified project.id (for example, my-project-123).

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

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).

project.ancestors.resource_name String The relative resource name for each ancestor in the format 'resourceType/resourceNumber'. Using project.ancestors.resource_name will offer a more complete view of project.ancestry_numbers.
project.ancestors.display_name String The name that you created for your resource in your console.
project.labels.key String If labels are present, the key portion of the key-value pair that comprises the label on the Google Cloud project where the usage occurred. For more information about using labels, see Using Labels.
project.labels.value String If labels are present, the value portion of the key-value pair that comprises the label on the Google Cloud project where the usage occurred. For more information about using labels, see Using Labels.
labels.key String If labels are present, the key portion of the key-value pair that comprises the label on the Google Cloud resource where the usage occurred. For more information about using labels, see Using Labels.
labels.value String If labels are present, the value portion of the key-value pair that comprises the label on the Google Cloud resource where the usage occurred. For more information about using labels, see Using Labels.
system_labels.key String If system labels are present, the key portion of the key-value pair that comprises the system-generated label on the resource where the usage occurred. See also, Available system labels.
system_labels.value String If system labels are present, the value portion of the key-value pair that comprises the system-generated label on the resource where the usage occurred. See also, Available system labels.
location.location String Location of usage at the level of a multi-region, country, region, or zone; or global for resources don't have a specific location. For more information, see Geography and regions and Google Cloud locations.
location.country String When location.location is a country, region, or zone, this field is the country of usage, e.g. US. For more information, see Geography and regions and Google Cloud locations.
location.region String When location.location is a region or zone, this field is the region of usage, e.g. us-central1. For more information, see Geography and regions and Google Cloud locations.
location.zone String When location.location is a zone, this field is the zone of usage, e.g. us-central1-a. For more information, see Geography and regions and Google Cloud locations.
cost Float The cost of the usage before any credits, to a precision of up to six decimal places. To get the total cost including credits, any credits.amount should be added to cost. See this example query for more information.
currency String The currency that the cost is billed in. For more information, see Local Currency for Billing and Payments.
currency_conversion_rate Float The exchange rate from US dollars to the local currency. That is, cost ÷ currency_conversion_rate is the cost in US dollars.
usage.amount Float The quantity of usage.unit used.
usage.unit String The base unit in which resource usage is measured. For example, the base unit for standard storage is byte-seconds.
usage.amount_in_pricing_units Float The quantity of usage.pricing_unit used.
usage.pricing_unit String The unit in which resource usage is measured, according to the Cloud Billing Catalog API.
credits Struct credits contains fields that describe the structure and value of the credits associated with Google Cloud and Google Maps Platform SKUs.
credits.id String If present, indicates that a credit is associated with the product SKU. credits.id values are either an alphanumeric unique identifier (for example, 12-b34-c56-d78), or a description of the credit type (such as Committed Usage Discount: CPU).

If the credits.id field is empty, then the product SKU isn't associated with a credit.
credits.full_name String The name of the credit associated with the product SKU. This is a human-readable description of an alphanumeric credits.id. Examples include Free trial credit or Spend-based committed use discount.

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.

credits.type String This field describes the purpose or origin of the credits.id. Credit types include:
  • 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.
credits.name String A description of the credit applied to the Cloud Billing account.
credits.amount Float The amount of the credit applied to the usage.
adjustment_info Struct adjustment_info contains fields that describe the structure and value of an adjustment to cost line items associated with a Cloud Billing account.

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.

adjustment_info.id String If present, indicates that an adjustment is associated with a cost line item. adjustment_info.id is the unique ID for all the adjustments associated with an issue.
adjustment_info.description String A description of the adjustment and its cause.
adjustment_info.type String

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.
adjustment_info.mode String

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.
export_time Timestamp A processing time associated with an append of Cloud Billing data. This will always increase with each new export.
See also, Differences between exported data and invoices below.
tags Struct

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

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

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

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.
tags.namespace String

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 Float

The list prices associated with all line items charged to your Cloud Billing account.
transaction_type String

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.
seller_name String

The legal name of the seller.

Understand standard and detailed usage cost data

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

About labels

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.

Available system labels

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.

system_labels.key Example system_labels.value Description
compute.googleapis.com/machine_spec n1-standard-1, custom-2-2048 Configuration of the virtual machine. See Machine Types for more information.
compute.googleapis.com/cores for n1-standard-4 this is 4; for custom-2-2048 this is 2 The number of vCPUs available to the virtual machine.
compute.googleapis.com/memory for n1-standard-4 this is 15360 (i.e. 15 GB * 1024 MB/GB); for custom-2-2048 this is 2048 The amount of memory (in MB) available to the virtual machine.
compute.googleapis.com/is_unused_reservation true; false Indicates usage that was reserved through Zonal Reservations but not used.
storage.googleapis.com/object_state live; noncurrent; soft_deleted; multipart The state of the storage object being charged.

Differences between exported data and invoices

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.

Taxes

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.

billing_account_id project.id cost_type cost
123456-ABCDEF-123456 example-project Regular $60
123456-ABCDEF-123456 test-project Regular $40
123456-ABCDEF-123456 [empty] Tax $10

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

billing_account_id project.id cost_type cost
123456-ABCDEF-123456 example-project Regular $60
123456-ABCDEF-123456 test-project Regular $40
123456-ABCDEF-123456 example-project Tax $6
123456-ABCDEF-123456 test-project Tax $4

Errors and adjustments

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

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

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."

About promotional credits in custom pricing contracts

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.

About tags

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.

Available tags

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
  • Cloud Run services and jobs
  • Cloud Storage buckets
  • Compute Engine instances
  • Memorystore for Redis instances
  • Secret Manager secrets
  • Spanner instances

Tags limitations

  • 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.

Standard usage cost query examples

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

Specifying the table name to use in your queries

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.

Common values used in the example standard cost queries

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.

Return the total costs on an invoice

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.

Example 1: Sum of all costs, per invoice

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:

Row month total total_exact
1 201901 $1005.004832999999984 $1005.00
2 201902 $992.3101739999999717 $992.31
3 201903 $1220.761089999999642 $1220.76

Example 2: Return details by cost type, per invoice month

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:

Row month cost_type total total_exact
1 201901 regular $1000.501209987994782 $1000.50
2 201901 rounding_error –$0.500489920049387 –$0.50
3 201901 tax $10.000329958477891 $10.00
4 201901 adjustment –$5.002572999387045 –$5.00

Query examples with labels

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:

Instance Labels Total Cost
Small instance with 1 VCPU running in Americas None $4
Small instance with 1 VCPU running in Americas app: chocolate-masher
environment: dev		 $2
Small instance with 1 VCPU running in Americas app: grapefruit-squeezer
environment: dev		 $3
Small instance with 1 VCPU running in Americas app: chocolate-masher
environment: prod		 $3.25
Small instance with 1 VCPU running in Asia app: chocolate-masher
environment: prod		 $3.75
Small instance with 1 VCPU running in Americas app: grapefruit-squeezer
environment: prod		 $3.50
Small instance with 1 VCPU running in Asia app: grapefruit-squeezer
environment: prod		 $4.50

Query every row without grouping

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.
Row sku.description labels cost
1 Small instance with 1 VCPU running in Americas [] $4
2 Small instance with 1 VCPU running in Americas [{"key":"app","value":"chocolate-masher"},{"key":"environment","value":"dev"}] $2
3 Small instance with 1 VCPU running in Americas [{"key":"app","value":"grapefruit-squeezer"},{"key":"environment","value":"dev"}] $3
4 Small instance with 1 VCPU running in Americas [{"key":"app","value":"chocolate-masher"},{"key":"environment","value":"prod"}] $3.25
5 Small instance with 1 VCPU running in Asia [{"key":"app","value":"chocolate-masher"},{"key":"environment","value":"prod"}] $3.75
6 Small instance with 1 VCPU running in Americas [{"key":"app","value":"grapefruit-squeezer"},{"key":"environment","value":"prod"}] $3.50
7 Small instance with 1 VCPU running in Asia [{"key":"app","value":"grapefruit-squeezer"},{"key":"environment","value":"prod"}] $4.50
TOTAL $24

Group by label map as a JSON string

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.
Row labels cost
1 [] $4
2 [{"key":"app","value":"chocolate-masher"},{"key":"environment","value":"dev"}] $2
3 [{"key":"app","value":"grapefruit-squeezer"},{"key":"environment","value":"dev"}] $3
4 [{"key":"app","value":"chocolate-masher"},{"key":"environment","value":"prod"}] $7
5 [{"key":"app","value":"grapefruit-squeezer"},{"key":"environment","value":"prod"}] $8
TOTAL $24

Group by label value for a specific key

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;
Row environment cost
1 prod $15
2 dev $5
3 null $4
TOTAL $24

Group by key/value pairs

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;
Row key value cost
1 null null $4
2 app chocolate-masher $9
3 app grapefruit-squeezer $11
4 environment dev $5
5 environment prod $15
TOTAL $44

Note that the total sum is greater than your bill.

Committed use discount queries

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.

Viewing commitment fees

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

Viewing commitment credits

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

Use resource hierarchy filters to review ancestry

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.

Example 1: Filter by resource name

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.

String method

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

UNNEST method

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

Example 2: Filter by display name

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.

String matching method

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

UNNEST method

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

Query examples with tags

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

Calculate costs by invoice month 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:

Row invoice_month cost_center net_cost
1 202208 android_mobile_apps 9.93
2 202208 ios_mobile_apps 9.93
3 202209 android_mobile_apps 25.42
4 202209 ios_mobile_apps 25.4
5 202209 personalization 16.08

View costs of untagged resources

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:

Row invoice_month net_cost
1 202202 0
2 202203 16.81
3 202204 54.09
4 202205 55.82
5 202206 54.09
6 202207 55.83
7 202208 31.49

Additional query examples

Query costs and credits by project for a specified invoice month

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.
Row name project_labels total_cost total_credits
1 CTG - Dev [{"key":"ctg_p_env","value":"dev"}] 79.140979 -4.763796
2 CTG - Prod [{"key":"ctg_p_env","value":"prod"},{"key":"ctg_team","value":"eng"}] 32.466272 -3.073356
3 CTG - Sandbox [{"key":"ctg_p_env","value":"dev"}] 0 0
4 CTG - Storage [{"key":"ctg_p_env","value":"prod"},{"key":"ctg_team","value":"data"}] 7.645793 -0.003761

Cost and pricing reports available in the Google Cloud console

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