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:
billing_account_idThe 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.monthThe 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_typeIndicates 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_typeThe type of cost this line item represents: regular, tax, adjustment, or rounding error.
service.idservice.descriptionsku.idsku.descriptionusage_start_timeFor more information, see the BigQuery documentation on timestamp data types. See also, Differences between exported data and invoices.
usage_end_timeFor more information, see the BigQuery documentation on timestamp data types. See also, Differences between exported data and invoices.
projectproject contains fields that describe the
Cloud Billing project, such as ID, number, name, ancestry_numbers,
and labels.
project.idproject.numberproject.nameproject.ancestry_numbersproject.id (for example, my-project-123).
For example: /ParentOrgNumber/ParentFolderNumber/. Learn more about the Resource Hierarchy.
project.ancestorsThis 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_nameproject.ancestors.resource_name will offer a more complete view of
project.ancestry_numbers. project.ancestors.display_nameproject.labelsproject.labels.keyproject.labels.valuelabelslabels.keylabels.valuesystem_labelssystem_labels.keysystem_labels.valuelocation.locationglobal for
resources don't have a specific location.
For more information, see
Geography and regions and
Google Cloud locations.
location.countrylocation.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.regionlocation.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.zonelocation.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.
costCost 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).
currencycurrency_conversion_ratecost ÷ currency_conversion_rate
is the cost in US dollars.usage.amountusage.unit used.usage.unitusage.amount_in_pricing_units
usage.pricing_unit used.
usage.pricing_unit
creditscredits contains fields that describe the structure and
value of the credits associated with Google Cloud and Google Maps
Platform SKUs.credits.idcredits.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_namecredits.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.typecredits.id.
Credit types include:
FEE_UTILIZATION_OFFSET
For the new Spend-based CUD discounts,
this credit is used to offset the fees paid to purchase CUDs. With the
new model, you purchase commitments at a discounted price. As you use
the SKUs covered by the CUD, this credit offsets the fee. When you fully
utilize your commitment, the offset reduces the fee to zero, with your
eligible SKU usage charged at the discounted price.COMMITTED_USAGE_DISCOUNT_DOLLAR_BASE:
For legacy spend-based committed use discounts (CUDs) that aren't part
of the
new pricing model,
this is the credit earned in exchange for your commitment to spend a
minimum amount for a service in a particular region.COMMITTED_USAGE_DISCOUNT:
Resource-based committed use contracts purchased for
Compute Engine in return for deeply discounted prices for VM
usage.
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.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
spend-based milestone credits,
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 receive for running
eligible Compute Engine resources for a significant portion of
the billing month, with no commitment required.
credits.namecredits.amountadjustment_infoadjustment_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.idadjustment_info.id is the unique ID for all
the adjustments associated with an issue.
adjustment_info.descriptionadjustment_info.typeThe 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.modeHow 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_timetagsFields that describe the tag, such as key, value, and namespace.
tags.keyThe short name or display name of the key associated with this particular tag.
tags.valueThe resources attached to a tags.key. At any given time, exactly one
value can be attached to a resource for a given key.
tags.inheritedIndicates 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.namespaceRepresents 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_listCost at list price per the default consumption model.
transaction_typeGOOGLE = 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.cost_type =
regular and it can be missing for other cost_types.
seller_nameThe legal name of the seller.
This field is populated for Marketplace-related cost line items, which is set for countries where Google or an affiliate can act as the vendor's agent. For more information, see Agency Jurisdictions.
priceFields that describe the structure and values related to the prices charged for usage.
price.list_priceSKU list price per the default consumption model.
price.effective_price_defaultSKU 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).
price.list_price_consumption_modelSKU 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).
price.effective_priceSKU 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).
price.tier_start_amountThe lower bound number of units for a SKU's pricing tier. For more information, see About pricing tiers.
price.unitThe unit of usage in which the pricing is specified and resource usage is measured.
price.pricing_unit_quantityThe SKU's pricing unit quantity. For example, if the price is $1 per 1000000 Bytes, then this column shows 1000000.
cost_at_effective_price_defaultCost 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_at_list_consumption_modelCost 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).
consumption_modelFields that describe the applicable consumption model.
consumption_model.idThe ID of the consumption model.
consumption_model.descriptionThe 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.
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. |
compute.googleapis.com/reservation_name |
my-a2-reservation | The short name of the Compute Engine reservation. For first-party (1P)
scenarios, this also includes shared reservations consumed by instances created
by Google Cloud services, such as Vertex AI. For more information
about how to share reservations with first-parties (1P) in Vertex AI, see the following: |
compute.googleapis.com/reservation_project_id |
my-gcp-project | The Project ID owning the Compute Engine reservation. For first-party (1P)
scenarios, this also includes shared reservations consumed by instances created
by Google Cloud services, such as Vertex AI. For more information
about how to share reservations with first-parties (1P) in Vertex AI, see the following: |
storage.googleapis.com/object_state |
live; noncurrent; soft_deleted; multipart | The state of the storage object being charged. |
Google Cloud and billing-eligible products such as Google Maps Platform, Google AI Studio, and Firebase report usage data to Cloud Billing at varying intervals. Due to the complexity of our billing and processing systems, you might see a delay between your use of services, the usage charges being applied to your Google payments accounts, and the usage and costs being available to view in the various cost reports and dashboards.
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_timeusage_end_timeexport_timeTo 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.
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 |
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:
costcreditusage.amountexport_timeFor 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):
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:
This section provides examples of how to query the Cloud Billing standard usage cost data exported to BigQuery.
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:
gcp_billing_export_v1_<BILLING_ACCOUNT_ID>.gcp_billing_export_resource_v1_<BILLING_ACCOUNT_ID>.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.
total field directly sums the floating point cost and credit values,
which can result in floating point rounding errors.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:
| Row | month | total | total_exact |
|---|---|---|---|
| 1 | 201901 | $1005.004832999999984 | $1005.00 |
| 2 | 201902 | $992.3101739999999717 | $992.31 |
| 3 | 201903 | $1220.761089999999642 | $1220.76 |
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 |
The following examples illustrate other ways to query your data with labels.
For the examples in this section, assume the following:
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 |
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 |
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 |
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 |
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.
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:
| 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 |
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 |
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 |
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Last updated 2026-06-09 UTC.