Update dataset properties

This document describes how to update dataset properties in BigQuery. After you create a dataset, you can update the following dataset properties:

Before you begin

Grant Identity and Access Management (IAM) roles that give users the necessary permissions to perform each task in this document.

Required permissions

To update dataset properties, you need the following IAM permissions:

  • bigquery.datasets.update
  • bigquery.datasets.setIamPolicy (only required when updating dataset access controls in the Google Cloud console)

The roles/bigquery.dataOwner predefined IAM role includes the permissions that you need to update dataset properties.

Additionally, if you have the bigquery.datasets.create permission, you can update properties of the datasets that you create.

For more information on IAM roles and permissions in BigQuery, see Predefined roles and permissions.

Update dataset descriptions

You can update a dataset's description in the following ways:

  • Using the Google Cloud console.
  • Using the bq command-line tool's bq update command.
  • Calling the datasets.patch API method.
  • Using the client libraries.

To update a dataset's description:

Console

  1. In the left pane, click Explorer:

    Highlighted button for the Explorer pane.

    If you don't see the left pane, click Expand left pane to open the pane.

  2. In the Explorer pane, expand your project, click Datasets, and then click a dataset.

  3. In the Details pane, click Edit details to edit the description text.

    In the Edit detail dialog that appears, do the following:

    1. In the Description field, enter a description or edit the existing description.
    2. To save the new description text, click Save.

SQL

To update a dataset's description, use the ALTER SCHEMA SET OPTIONS statement to set the description option.

The following example sets the description on a dataset named mydataset:

  1. In the Google Cloud console, go to the BigQuery page.

    Go to BigQuery

  2. In the query editor, enter the following statement:

    ALTERSCHEMAmydataset
SETOPTIONS(
description='Description of mydataset');

  3. Click Run.

For more information about how to run queries, see Run an interactive query.

bq

Issue the bq update command with the --description flag. If you are updating a dataset in a project other than your default project, add the project ID to the dataset name in the following format: project_id:dataset.

bqupdate\
--description"string"\
project_id:dataset

Replace the following:

  • string: the text that describes the dataset, in quotes
  • project_id: your project ID
  • dataset: the name of the dataset that you're updating

Examples:

Enter the following command to change the description of mydataset to "Description of mydataset." mydataset is in your default project.

bq update --description "Description of mydataset" mydataset

Enter the following command to change the description of mydataset to "Description of mydataset." The dataset is in myotherproject, not your default project.

bq update \
--description "Description of mydataset" \
myotherproject:mydataset

API

Call datasets.patch and update the description property in the dataset resource. Because the datasets.update method replaces the entire dataset resource, the datasets.patch method is preferred.

Go

Before trying this sample, follow the Go setup instructions in the BigQuery quickstart using client libraries. For more information, see the BigQuery Go API reference documentation.

To authenticate to BigQuery, set up Application Default Credentials. For more information, see Set up authentication for client libraries. 

import(
"context"
"fmt"
"cloud.google.com/go/bigquery"
)
// updateDatasetDescription demonstrates how the Description metadata of a dataset can
// be read and modified.
funcupdateDatasetDescription(projectID,datasetIDstring)error{
// projectID := "my-project-id"
// datasetID := "mydataset"
ctx:=context.Background()
client,err:=bigquery.NewClient(ctx,projectID)
iferr!=nil{
returnfmt.Errorf("bigquery.NewClient: %v",err)
}
deferclient.Close()
ds:=client.Dataset(datasetID)
meta,err:=ds.Metadata(ctx)
iferr!=nil{
returnerr
}
update:=bigquery.DatasetMetadataToUpdate {
Description:"Updated Description.",
}
if_,err=ds.Update(ctx,update,meta.ETag);err!=nil{
returnerr
}
returnnil
}

Java

Before trying this sample, follow the Java setup instructions in the BigQuery quickstart using client libraries. For more information, see the BigQuery Java API reference documentation.

To authenticate to BigQuery, set up Application Default Credentials. For more information, see Set up authentication for client libraries.

Create a Dataset.Builder instance from an existing Dataset instance with the Dataset.toBuilder() method. Configure the dataset builder object. Build the updated dataset with the Dataset.Builder.build() method, and call the Dataset.update() method to send the update to the API. 
importcom.google.cloud.bigquery.BigQuery ;
importcom.google.cloud.bigquery.BigQueryException ;
importcom.google.cloud.bigquery.BigQueryOptions ;
importcom.google.cloud.bigquery.Dataset ;
publicclass UpdateDatasetDescription{
publicstaticvoidrunUpdateDatasetDescription(){
// TODO(developer): Replace these variables before running the sample.
StringdatasetName="MY_DATASET_NAME";
StringnewDescription="this is the new dataset description";
updateDatasetDescription(datasetName,newDescription);
}
publicstaticvoidupdateDatasetDescription(StringdatasetName,StringnewDescription){
try{
// Initialize client that will be used to send requests. This client only needs to be created
// once, and can be reused for multiple requests.
BigQuery bigquery=BigQueryOptions .getDefaultInstance().getService();
Dataset dataset=bigquery.getDataset (datasetName);
bigquery.update (dataset.toBuilder().setDescription(newDescription).build());
System.out.println("Dataset description updated successfully to "+newDescription);
}catch(BigQueryException e){
System.out.println("Dataset description was not updated \n"+e.toString());
}
}
}

Node.js

Before trying this sample, follow the Node.js setup instructions in the BigQuery quickstart using client libraries. For more information, see the BigQuery Node.js API reference documentation.

To authenticate to BigQuery, set up Application Default Credentials. For more information, see Set up authentication for client libraries. 

// Import the Google Cloud client library
const{BigQuery}=require('@google-cloud/bigquery');
constbigquery=newBigQuery ();
asyncfunctionupdateDatasetDescription(){
// Updates a dataset's description.
// Retreive current dataset metadata
constdataset=bigquery.dataset(datasetId);
const[metadata]=awaitdataset.getMetadata();
// Set new dataset description
constdescription='New dataset description.';
metadata.description=description;
const[apiResponse]=awaitdataset.setMetadata(metadata);
constnewDescription=apiResponse.description;
console.log(`${datasetId} description: ${newDescription}`);
}

Python

Before trying this sample, follow the Python setup instructions in the BigQuery quickstart using client libraries. For more information, see the BigQuery Python API reference documentation.

To authenticate to BigQuery, set up Application Default Credentials. For more information, see Set up authentication for client libraries.

Configure the Dataset.description property and call Client.update_dataset() to send the update to the API. 

fromgoogle.cloudimport bigquery
# Construct a BigQuery client object.
client = bigquery .Client ()
# TODO(developer): Set dataset_id to the ID of the dataset to fetch.
# dataset_id = 'your-project.your_dataset'
dataset = client.get_dataset (dataset_id) # Make an API request.
dataset.description = "Updated description."
dataset = client.update_dataset (dataset, ["description"]) # Make an API request.
full_dataset_id = "{}.{}".format(dataset.project, dataset.dataset_id)
print(
 "Updated dataset '{}' with description '{}'.".format(
 full_dataset_id, dataset.description
 )
)

Update default table expiration times

You can update a dataset's default table expiration time in the following ways:

  • Using the Google Cloud console.
  • Using the bq command-line tool's bq update command.
  • Calling the datasets.patch API method.
  • Using the client libraries.

You can set a default table expiration time at the dataset level, or you can set a table's expiration time when the table is created. If you set the expiration when the table is created, the dataset's default table expiration is ignored. If you don't set a default table expiration at the dataset level, and you don't set a table expiration when the table is created, the table never expires and you must delete the table manually. When a table expires, it's deleted along with all of the data it contains.

When you update a dataset's default table expiration setting:

  • If you change the value from Never to a defined expiration time, any tables that already exist in the dataset won't expire unless the expiration time was set on the table when it was created.
  • If you are changing the value for the default table expiration, any tables that already exist expire according to the original table expiration setting. Any new tables created in the dataset have the new table expiration setting applied unless you specify a different table expiration on the table when it is created.

The value for default table expiration is expressed differently depending on where the value is set. Use the method that gives you the appropriate level of granularity:

  • In the Google Cloud console, expiration is expressed in days.
  • In the bq command-line tool, expiration is expressed in seconds.
  • In the API, expiration is expressed in milliseconds.

To update the default expiration time for a dataset:

Console

  1. In the left pane, click Explorer:

    Highlighted button for the Explorer pane.

  2. In the Explorer pane, expand your project, click Datasets, and then click a dataset.

  3. In the Details tab, click Edit details to edit the expiration time.

  4. In the Edit detail dialog, in the Default table expiration section, select Enable table expiration and enter a value for Default maximum table age.

  5. Click Save.

SQL

To update the default table expiration time, use the ALTER SCHEMA SET OPTIONS statement to set the default_table_expiration_days option.

The following example updates the default table expiration for a dataset named mydataset.

  1. In the Google Cloud console, go to the BigQuery page.

    Go to BigQuery

  2. In the query editor, enter the following statement:

    ALTERSCHEMAmydataset
SETOPTIONS(
default_table_expiration_days=3.75);

  3. Click Run.

For more information about how to run queries, see Run an interactive query.

bq

To update the default expiration time for newly created tables in a dataset, enter the bq update command with the --default_table_expiration flag. If you are updating a dataset in a project other than your default project, add the project ID to the dataset name in the following format: project_id:dataset.

bqupdate\
--default_table_expirationinteger\
project_id:dataset

Replace the following:

  • integer: the default lifetime, in seconds, for newly created tables. The minimum value is 3600 seconds (one hour). The expiration time evaluates to the current UTC time plus the integer value. Specify 0 to remove the existing expiration time. Any table created in the dataset is deleted integer seconds after its creation time. This value is applied if you do not set a table expiration when the table is created.
  • project_id: your project ID.
  • dataset: the name of the dataset that you're updating.

Examples:

Enter the following command to set the default table expiration for new tables created in mydataset to two hours (7200 seconds) from the current time. The dataset is in your default project.

bq update --default_table_expiration 7200 mydataset

Enter the following command to set the default table expiration for new tables created in mydataset to two hours (7200 seconds) from the current time. The dataset is in myotherproject, not your default project.

bq update --default_table_expiration 7200 myotherproject:mydataset

API

Call datasets.patch and update the defaultTableExpirationMs property in the dataset resource. The expiration is expressed in milliseconds in the API. Because the datasets.update method replaces the entire dataset resource, the datasets.patch method is preferred.

Go

Before trying this sample, follow the Go setup instructions in the BigQuery quickstart using client libraries. For more information, see the BigQuery Go API reference documentation.

To authenticate to BigQuery, set up Application Default Credentials. For more information, see Set up authentication for client libraries. 

import(
"context"
"fmt"
"time"
"cloud.google.com/go/bigquery"
)
// updateDatasetDefaultExpiration demonstrats setting the default expiration of a dataset
// to a specific retention period.
funcupdateDatasetDefaultExpiration(projectID,datasetIDstring)error{
// projectID := "my-project-id"
// datasetID := "mydataset"
ctx:=context.Background()
client,err:=bigquery.NewClient(ctx,projectID)
iferr!=nil{
returnfmt.Errorf("bigquery.NewClient: %v",err)
}
deferclient.Close()
ds:=client.Dataset(datasetID)
meta,err:=ds.Metadata(ctx)
iferr!=nil{
returnerr
}
update:=bigquery.DatasetMetadataToUpdate {
DefaultTableExpiration:24*time.Hour,
}
if_,err:=client.Dataset(datasetID).Update(ctx,update,meta.ETag);err!=nil{
returnerr
}
returnnil
}

Java

Before trying this sample, follow the Java setup instructions in the BigQuery quickstart using client libraries. For more information, see the BigQuery Java API reference documentation.

To authenticate to BigQuery, set up Application Default Credentials. For more information, see Set up authentication for client libraries.

Create a Dataset.Builder instance from an existing Dataset instance with the Dataset.toBuilder() method. Configure the dataset builder object. Build the updated dataset with the Dataset.Builder.build() method, and call the Dataset.update() method to send the update to the API.

Configure the default expiration time with the Dataset.Builder.setDefaultTableLifetime() method. 

importcom.google.cloud.bigquery.BigQuery ;
importcom.google.cloud.bigquery.BigQueryException ;
importcom.google.cloud.bigquery.BigQueryOptions ;
importcom.google.cloud.bigquery.Dataset ;
importjava.util.concurrent.TimeUnit;
publicclass UpdateDatasetExpiration{
publicstaticvoidrunUpdateDatasetExpiration(){
// TODO(developer): Replace these variables before running the sample.
StringdatasetName="MY_DATASET_NAME";
updateDatasetExpiration(datasetName);
}
publicstaticvoidupdateDatasetExpiration(StringdatasetName){
try{
// Initialize client that will be used to send requests. This client only needs to be created
// once, and can be reused for multiple requests.
BigQuery bigquery=BigQueryOptions .getDefaultInstance().getService();
// Update dataset expiration to one day
LongnewExpiration=TimeUnit.MILLISECONDS.convert (1,TimeUnit.DAYS);
Dataset dataset=bigquery.getDataset (datasetName);
bigquery.update (dataset.toBuilder().setDefaultTableLifetime(newExpiration).build());
System.out.println("Dataset description updated successfully to "+newExpiration);
}catch(BigQueryException e){
System.out.println("Dataset expiration was not updated \n"+e.toString());
}
}
}

Node.js

Before trying this sample, follow the Node.js setup instructions in the BigQuery quickstart using client libraries. For more information, see the BigQuery Node.js API reference documentation.

To authenticate to BigQuery, set up Application Default Credentials. For more information, see Set up authentication for client libraries. 

// Import the Google Cloud client library
const{BigQuery}=require('@google-cloud/bigquery');
constbigquery=newBigQuery ();
asyncfunctionupdateDatasetExpiration(){
// Updates the lifetime of all tables in the dataset, in milliseconds.
/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const datasetId = "my_dataset";
// Retreive current dataset metadata
constdataset=bigquery.dataset(datasetId);
const[metadata]=awaitdataset.getMetadata();
// Set new dataset metadata
constexpirationTime=24*60*60*1000;
metadata.defaultTableExpirationMs=expirationTime.toString();
const[apiResponse]=awaitdataset.setMetadata(metadata);
constnewExpirationTime=apiResponse.defaultTableExpirationMs;
console.log(`${datasetId} expiration: ${newExpirationTime}`);
}

Python

Before trying this sample, follow the Python setup instructions in the BigQuery quickstart using client libraries. For more information, see the BigQuery Python API reference documentation.

To authenticate to BigQuery, set up Application Default Credentials. For more information, see Set up authentication for client libraries.

Configure the Dataset.default_table_expiration_ms property and call Client.update_dataset() to send the update to the API. 

fromgoogle.cloudimport bigquery
# Construct a BigQuery client object.
client = bigquery .Client ()
# TODO(developer): Set dataset_id to the ID of the dataset to fetch.
# dataset_id = 'your-project.your_dataset'
dataset = client.get_dataset (dataset_id) # Make an API request.
dataset.default_table_expiration_ms = 24 * 60 * 60 * 1000 # In milliseconds.
dataset = client.update_dataset (
 dataset, ["default_table_expiration_ms"]
) # Make an API request.
full_dataset_id = "{}.{}".format(dataset.project, dataset.dataset_id)
print(
 "Updated dataset {} with new expiration {}".format(
 full_dataset_id, dataset.default_table_expiration_ms
 )
)

Update default partition expiration times

You can update a dataset's default partition expiration in the following ways:

  • Using the bq command-line tool's bq update command.
  • Calling the datasets.patch API method.
  • Using the client libraries.

Setting or updating a dataset's default partition expiration isn't currently supported by the Google Cloud console.

You can set a default partition expiration time at the dataset level that affects all newly created partitioned tables, or you can set a partition expiration time for individual tables when the partitioned tables are created. If you set the default partition expiration at the dataset level, and you set the default table expiration at the dataset level, new partitioned tables will only have a partition expiration. If both options are set, the default partition expiration overrides the default table expiration.

If you set the partition expiration time when the partitioned table is created, that value overrides the dataset-level default partition expiration if it exists.

If you do not set a default partition expiration at the dataset level, and you do not set a partition expiration when the table is created, the partitions never expire and you must delete the partitions manually.

When you set a default partition expiration on a dataset, the expiration applies to all partitions in all partitioned tables created in the dataset. When you set the partition expiration on a table, the expiration applies to all partitions created in the specified table. Currently, you cannot apply different expiration times to different partitions in the same table.

When you update a dataset's default partition expiration setting:

  • If you change the value from never to a defined expiration time, any partitions that already exist in partitioned tables in the dataset will not expire unless the partition expiration time was set on the table when it was created.
  • If you are changing the value for the default partition expiration, any partitions in existing partitioned tables expire according to the original default partition expiration. Any new partitioned tables created in the dataset have the new default partition expiration setting applied unless you specify a different partition expiration on the table when it is created.

The value for default partition expiration is expressed differently depending on where the value is set. Use the method that gives you the appropriate level of granularity:

  • In the bq command-line tool, expiration is expressed in seconds.
  • In the API, expiration is expressed in milliseconds.

To update the default partition expiration time for a dataset:

Console

Updating a dataset's default partition expiration is not currently supported by the Google Cloud console.

SQL

To update the default partition expiration time, use the ALTER SCHEMA SET OPTIONS statement to set the default_partition_expiration_days option.

The following example updates the default partition expiration for a dataset named mydataset:

  1. In the Google Cloud console, go to the BigQuery page.

    Go to BigQuery

  2. In the query editor, enter the following statement:

    ALTERSCHEMAmydataset
SETOPTIONS(
default_partition_expiration_days=3.75);

  3. Click Run.

For more information about how to run queries, see Run an interactive query.

bq

To update the default expiration time for a dataset, enter the bq update command with the --default_partition_expiration flag. If you are updating a dataset in a project other than your default project, add the project ID to the dataset name in the following format: project_id:dataset.

bqupdate\
--default_partition_expirationinteger\
project_id:dataset

Replace the following:

  • integer: the default lifetime, in seconds, for partitions in newly created partitioned tables. This flag has no minimum value. Specify 0 to remove the existing expiration time. Any partitions in newly created partitioned tables are deleted integer seconds after the partition's UTC date. This value is applied if you do not set a partition expiration on the table when it is created.
  • project_id: your project ID.
  • dataset: the name of the dataset that you're updating.

Examples:

Enter the following command to set the default partition expiration for new partitioned tables created in mydataset to 26 hours (93,600 seconds). The dataset is in your default project.

bq update --default_partition_expiration 93600 mydataset

Enter the following command to set the default partition expiration for new partitioned tables created in mydataset to 26 hours (93,600 seconds). The dataset is in myotherproject, not your default project.

bq update --default_partition_expiration 93600 myotherproject:mydataset

API

Call datasets.patch and update the defaultPartitionExpirationMs property in the dataset resource. The expiration is expressed in milliseconds. Because the datasets.update method replaces the entire dataset resource, the datasets.patch method is preferred.

Update rounding mode

You can update a dataset's default rounding mode by using the ALTER SCHEMA SET OPTIONS DDL statement. The following example updates the default rounding mode for mydataset to ROUND_HALF_EVEN.

ALTERSCHEMAmydataset
SETOPTIONS(
default_rounding_mode="ROUND_HALF_EVEN");

This sets the default rounding mode for new tables created in the dataset. It has no impact on new columns added to existing tables. Setting the default rounding mode on a table in the dataset overrides this option.

Update time travel windows

You can update a dataset's time travel window in the following ways:

  • Using the Google Cloud console.
  • Using the ALTER SCHEMA SET OPTIONS statement.
  • Using the bq command-line tool's bq update command.
  • Calling the datasets.patch or datasets.update API method. The update method replaces the entire dataset resource, whereas the patch method only replaces fields that are provided in the submitted dataset resource.

For more information on the time travel window, see Configure the time travel window.

To update the time travel window for a dataset:

Console

  1. In the left pane, click Explorer:

    Highlighted button for the Explorer pane.

  2. In the Explorer pane, expand your project, click Datasets, and then click a dataset.

  3. In the Details tab, click Edit details.

  4. Expand Advanced options, then select the Time travel window to use.

  5. Click Save.

SQL

Use the ALTER SCHEMA SET OPTIONS statement with the max_time_travel_hours option to specify the time travel window when altering a dataset. The max_time_travel_hours value must be an integer expressed in multiples of 24 (48, 72, 96, 120, 144, 168) between 48 (2 days) and 168 (7 days).

  1. In the Google Cloud console, go to the BigQuery page.

    Go to BigQuery

  2. In the query editor, enter the following statement:

    ALTERSCHEMADATASET_NAME
SETOPTIONS(
max_time_travel_hours=HOURS);

    Replace the following:

    • DATASET_NAME: the name of the dataset that you're updating
    • HOURS with the time travel window's duration in hours.

  3. Click Run.

For more information about how to run queries, see Run an interactive query.

bq

Use the bq update command with the --max_time_travel_hours flag to specify the time travel window when altering a dataset. The --max_time_travel_hours value must be an integer expressed in multiples of 24 (48, 72, 96, 120, 144, 168) between 48 (2 days) and 168 (7 days).

bq update \
--dataset=true --max_time_travel_hours=HOURS \
PROJECT_ID:DATASET_NAME

Replace the following:

  • PROJECT_ID: your project ID
  • DATASET_NAME: the name of the dataset that you're updating
  • HOURS with the time travel window's duration in hours

API

Call the datasets.patch or datasets.update method with a defined dataset resource in which you have specified a value for the maxTimeTravelHours field. The maxTimeTravelHours value must be an integer expressed in multiples of 24 (48, 72, 96, 120, 144, 168) between 48 (2 days) and 168 (7 days).

Update storage billing models

You can alter the storage billing model for a dataset. Set the storage_billing_model value to PHYSICAL to use physical bytes when calculating storage changes, or to LOGICAL to use logical bytes. LOGICAL is the default.

When you change a dataset's billing model, it takes 24 hours for the change to take effect.

Once you change a dataset's storage billing model, you must wait 14 days before you can change the storage billing model again.

Console

  1. In the left pane, click Explorer:

    Highlighted button for the Explorer pane.

  2. In the Explorer pane, expand your project, click Datasets, and then click a dataset.

  3. In the Details tab, click Edit details.

  4. Expand Advanced options.

  5. In the Storage billing model menu, select Physical to use physical storage billing, or select Logical to use logical storage billing. You can also select Storage_billing_model_unspecified.

  6. Click Save.

SQL

To update the billing model for a dataset, use the ALTER SCHEMA SET OPTIONS statement and set the storage_billing_model option:

  1. In the Google Cloud console, go to the BigQuery page.

    Go to BigQuery

  2. In the query editor, enter the following statement:

    ALTERSCHEMADATASET_NAME
SETOPTIONS(
storage_billing_model='BILLING_MODEL');

    Replace the following:

    • DATASET_NAME with the name of the dataset that you are changing
    • BILLING_MODEL with the type of storage you want to use, either LOGICAL or PHYSICAL

  3. Click Run.

For more information about how to run queries, see Run an interactive query.

To update the storage billing model for all datasets in a project, use the following SQL query for every region, where datasets are located:

FORrecordIN
(SELECTCONCAT(catalog_name,'.',schema_name)ASdataset_path
FROMPROJECT_ID.region-REGION.INFORMATION_SCHEMA.SCHEMATA)
DO
EXECUTEIMMEDIATE
"ALTER SCHEMA `"||record.dataset_path||"` SET OPTIONS(storage_billing_model = 'BILLING_MODEL')";
ENDFOR;

Replace the following:

  • PROJECT_ID with your project ID
  • REGION with a region qualifier
  • BILLING_MODEL with the type of storage you want to use, either LOGICAL or PHYSICAL

bq

To update the billing model for a dataset, use the bq update command and set the --storage_billing_model flag:

bqupdate-d--storage_billing_model=BILLING_MODELPROJECT_ID:DATASET_NAME

Replace the following:

  • PROJECT_ID: your project ID
  • DATASET_NAME: the name of the dataset that you're updating
  • BILLING_MODEL: the type of storage you want to use, either LOGICAL or PHYSICAL

API

Call the datasets.update method with a defined dataset resource where the storageBillingModel field is set.

The following example shows how to call datasets.update using curl:

curl-H"Authorization: Bearer $(gcloudauthprint-access-token)"-H"Content-Type: application/json"-L-XPUThttps://bigquery.googleapis.com/bigquery/v2/projects/PROJECT_ID/datasets/DATASET_ID-d'{"datasetReference": {"projectId": "PROJECT_ID", "datasetId": "DATASET_NAME"}, "storageBillingModel": "BILLING_MODEL"}'

Replace the following:

  • PROJECT_ID: your project ID
  • DATASET_NAME: the name of the dataset that you're updating
  • BILLING_MODEL: the type of storage you want to use, either LOGICAL or PHYSICAL

Update access controls

To control access to datasets in BigQuery, see Controlling access to datasets. For information about data encryption, see Encryption at rest.

What's next

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Last updated 2025年10月16日 UTC.