Customer-managed Cloud KMS keys

Note: This feature may not be available when using reservations that are created with certain BigQuery editions. For more information about which features are enabled in each edition, see Introduction to BigQuery editions.

By default, BigQuery encrypts your content stored at rest. BigQuery handles and manages this default encryption for you without any additional actions on your part. First, data in a BigQuery table is encrypted using a data encryption key. Then, those data encryption keys are encrypted with key encryption keys, which is known as envelope encryption. Key encryption keys don't directly encrypt your data but are used to encrypt the data encryption keys that Google uses to encrypt your data.

If you want to control encryption yourself, you can use customer-managed encryption keys (CMEK) for BigQuery. Instead of Google owning and managing the key encryption keys that protect your data, you control and manage key encryption keys in Cloud KMS. This document provides details about manually creating Cloud KMS keys for BigQuery.

Learn more about encryption options on Google Cloud. For specific information about CMEK, including its advantages and limitations, see Customer-managed encryption keys.

Before you begin

• All data assets residing in BigQuery managed storage support CMEK. However, if you are also querying data stored in an external data source such as Cloud Storage that has CMEK-encrypted data, then the data encryption is managed by Cloud Storage. For example, BigLake tables support data encrypted with CMEK in Cloud Storage.

  BigQuery and BigLake tables don't support Customer-Supplied Encryption Keys (CSEK).

• Decide whether you are going to run BigQuery and Cloud KMS in the same Google Cloud project, or in different projects. For documentation example purposes, the following convention is used:

  • PROJECT_ID: the project ID of the project running BigQuery
  • PROJECT_NUMBER: the project number of the project running BigQuery
  • KMS_PROJECT_ID: the project ID of the project running Cloud KMS (even if this is the same project running BigQuery)
  For information about Google Cloud project IDs and project numbers, see Identifying projects.

• BigQuery is automatically enabled in new projects. If you are using a pre-existing project to run BigQuery, enable the BigQuery API.

• For the Google Cloud project that runs Cloud KMS, enable the Cloud Key Management Service API.

A decryption call is performed using Cloud KMS once per query to a CMEK-encrypted table. For more information, see Cloud KMS pricing.

Encryption specification

Cloud KMS keys used to protect your data in BigQuery are AES-256 keys. These keys are used as key encryption keys in BigQuery, in that they encrypt the data encryption keys that encrypt your data.

Manual or automated key creation

You can either create your CMEK keys manually or use Cloud KMS Autokey. Autokey simplifies creating and managing your CMEK keys by automating provisioning and assignment. With Autokey, you don't need to provision key rings, keys, and service accounts ahead of time. Instead, they are generated on demand as part of BigQuery resource creation. For more information, see the Autokey overview.

Manually create key ring and key

For the Google Cloud project that runs Cloud KMS, create a key ring and a key as described in Creating key rings and keys. Create the key ring in a location that matches the location of your BigQuery dataset:

• Any multi-regional dataset should use a multi-regional key ring from a matching location. For examples, a dataset in region US should be protected with a key ring from region us, and a dataset in region EU should be protected with a key ring from region europe.

• Regional datasets should use matching regional keys. For example, a dataset in region asia-northeast1 should be protected with a key ring from region asia-northeast1.

• You can't use the global region when configuring CMEK for BigQuery in the Google Cloud console. However, you can use the global region when configuring CMEK for BigQuery by using the bq command-line tool or GoogleSQL.

For more information about the supported locations for BigQuery and Cloud KMS, see Cloud locations.

Grant encryption and decryption permission

To protect your BigQuery data with a CMEK key, grant the BigQuery service account permission to encrypt and decrypt using that key. The Cloud KMS CryptoKey Encrypter/Decrypter role grants this permission.

Make sure your service account has been created, and then use the Google Cloud console to determine the BigQuery service account ID. Next, provide the service account with the appropriate role to encrypt and decrypt using Cloud KMS.

Trigger creation of your service account

Your BigQuery service account is not initially created when you create a project. To trigger the creation of your service account, enter a command that uses it, such as the bq show --encryption_service_account command, or call the projects.getServiceAccount API method. For example:

bq show --encryption_service_account --project_id=PROJECT_ID

Determine the service account ID

The BigQuery service account ID is of the form:

[e-mail]

The following techniques show how you can determine the BigQuery service account ID for your project.

Console

1. Go to the Dashboard page in the Google Cloud console.

   Go to the Dashboard page

2. Click the Select from drop-down list at the top of the page. In the Select From window that appears, select your project.

3. Both the project ID and project number are displayed on the project Dashboard Project info card:

   

4. In the following string, replace PROJECT_NUMBER with your project number. The new string identifies your BigQuery service account ID.

   [e-mail]
   

bq

Use the bq show command with the --encryption_service_account flag to determine the service account ID:

bq show --encryption_service_account

The command displays the service account ID:

                  ServiceAccountID
-------------------------------------------------------------
[e-mail]

Assign the Encrypter/Decrypter role

Assign the Cloud KMS CryptoKey Encrypter/Decrypter role to the BigQuery system service account that you copied to your clipboard. This account is of the form:

[e-mail]

Console

1. Open the Cryptographic Keys page in the Google Cloud console.

   Open the Cryptographic Keys page

2. Click the name of the key ring that contains the key.

3. Click the checkbox for the encryption key to which you want to add the role. The Permissions tab opens.

4. Click Add member.

5. Enter the email address of the service account, [e-mail].

   • If the service account is already on the members list, it has existing roles. Click the current role drop-down list for the [e-mail] service account.

6. Click the drop-down list for Select a role, click Cloud KMS, and then click the Cloud KMS CryptoKey Encrypter/Decrypter role.

7. Click Save to apply the role to the [e-mail] service account.

gcloud

You can use the Google Cloud CLI to assign the role:

gcloud kms keys add-iam-policy-binding \
--project=KMS_PROJECT_ID \
--member serviceAccount:[e-mail] \
--role roles/cloudkms.cryptoKeyEncrypterDecrypter \
--location=KMS_KEY_LOCATION \
--keyring=KMS_KEY_RING \
KMS_KEY

Replace the following:

• KMS_PROJECT_ID: the ID of your Google Cloud project that is running Cloud KMS
• PROJECT_NUMBER: the project number (not project ID) of your Google Cloud project that is running BigQuery
• KMS_KEY_LOCATION: the location name of your Cloud KMS key
• KMS_KEY_RING: the key ring name of your Cloud KMS key
• KMS_KEY: the key name of your Cloud KMS key

Key resource ID

The resource ID for the Cloud KMS key is required for CMEK use, as shown in the examples. This key is case-sensitive and in the form:

projects/KMS_PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY

Note: You cannot specify a key resource ID that includes the /cryptoKeyVersions/ token. BigQuery always uses the key version marked as primary to protect a table when it is created.

Retrieve the key resource ID

1. Open the Cryptographic Keys page in the Google Cloud console.

   Open the Cryptographic Keys page

2. Click the name of the key ring that contains the key.

3. For the key whose resource ID you are retrieving, click More .

4. Click Copy Resource Name. The resource ID for the key is copied to your clipboard. The resource ID is also known as the resource name.

Create a table protected by Cloud KMS

To create a table that is protected by Cloud KMS:

Console

1. Open the BigQuery page in the Google Cloud console.

   Go to the BigQuery page

2. In the Explorer panel, expand your project and select a dataset.

3. Expand the Actions option and click Open.

4. In the details panel, click Create table .

5. On the Create table page, fill in the information needed to create an empty table with a schema definition. Before you click Create Table, set the encryption type and specify the Cloud KMS key to use with the table:

   1. Click Advanced options.
   2. Click Customer-managed key.
   3. Select the key. If the key you want to use is not listed, enter the resource ID for the key.

6. Click Create table.

SQL

Use the CREATE TABLE statement with the kms_key_name option:

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

   Go to BigQuery

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

   CREATE TABLE DATASET_ID.TABLE_ID (
     name STRING, value INT64
   ) OPTIONS (
       kms_key_name
         = 'projects/KMS_PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY');

3. Click Run.

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

bq

You can use the bq command-line tool with the --destination_kms_key flag to create the table. The --destination_kms_key flag specifies the resource ID of the key to use with the table.

To create an empty table with a schema:

bq mk --schema name:string,value:integer -t \
--destination_kms_key projects/KMS_PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY \
DATASET_ID.TABLE_ID

To create a table from a query:

bq query --destination_table=DATASET_ID.TABLE_ID \
--destination_kms_key projects/KMS_PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY \
"SELECT name,count FROM DATASET_ID.TABLE_ID WHERE gender = 'M' ORDER BY count DESC LIMIT 6"

For more information about the bq command-line tool, see Using the bq command-line tool.

Terraform

Use the google_bigquery_table resource.

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

The following example creates a table named mytable, and also uses the google_kms_crypto_key and google_kms_key_ring resources to specify a Cloud Key Management Service key for the table.

To run this example, you must enable the Cloud Resource Manager API and the Cloud Key Management Service API.

resource "google_bigquery_dataset" "default" {
  dataset_id                      = "mydataset"
  default_partition_expiration_ms = 2592000000  # 30 days
  default_table_expiration_ms     = 31536000000 # 365 days
  description                     = "dataset description"
  location                        = "US"
  max_time_travel_hours           = 96 # 4 days

  labels = {
    billing_group = "accounting",
    pii           = "sensitive"
  }
}

resource "google_bigquery_table" "default" {
  dataset_id          = google_bigquery_dataset.default.dataset_id
  table_id            = "mytable"
  deletion_protection = false # set to "true" in production

  schema = <<EOF
[
  {
    "name": "ID",
    "type": "INT64",
    "mode": "NULLABLE",
    "description": "Item ID"
  },
  {
    "name": "Item",
    "type": "STRING",
    "mode": "NULLABLE"
  }
]
EOF

  encryption_configuration {
    kms_key_name = google_kms_crypto_key.crypto_key.id
  }

  depends_on = [google_project_iam_member.service_account_access]
}

resource "google_kms_crypto_key" "crypto_key" {
  name     = "example-key"
  key_ring = google_kms_key_ring.key_ring.id
}

resource "random_id" "default" {
  byte_length = 8
}

resource "google_kms_key_ring" "key_ring" {
  name     = "${random_id.default.hex}-example-keyring"
  location = "us"
}

# Enable the BigQuery service account to encrypt/decrypt Cloud KMS keys
data "google_project" "project" {
}

resource "google_project_iam_member" "service_account_access" {
  project = data.google_project.project.project_id
  role    = "roles/cloudkms.cryptoKeyEncrypterDecrypter"
  member  = "serviceAccount:bq-${data.google_project.project.number}@bigquery-encryption.iam.gserviceaccount.com"
}

To apply your Terraform configuration in a Google Cloud project, complete the steps in the following sections.

Prepare Cloud Shell

1. Launch Cloud Shell.

2. Set the default Google Cloud project where you want to apply your Terraform configurations.

   You only need to run this command once per project, and you can run it in any directory.

   export GOOGLE_CLOUD_PROJECT=PROJECT_ID

   Environment variables are overridden if you set explicit values in the Terraform configuration file.

Prepare the directory

Each Terraform configuration file must have its own directory (also called a root module).

1. In Cloud Shell, create a directory and a new file within that directory. The filename must have the .tf extension—for example main.tf. In this tutorial, the file is referred to as main.tf.

   mkdir DIRECTORY && cd DIRECTORY && touch main.tf

2. If you are following a tutorial, you can copy the sample code in each section or step.

   Copy the sample code into the newly created main.tf.

   Optionally, copy the code from GitHub. This is recommended when the Terraform snippet is part of an end-to-end solution.

3. Review and modify the sample parameters to apply to your environment.
4. Save your changes.
5. Initialize Terraform. You only need to do this once per directory.

   terraform init

   Optionally, to use the latest Google provider version, include the -upgrade option:

   terraform init -upgrade

Apply the changes

1. Review the configuration and verify that the resources that Terraform is going to create or update match your expectations:

   terraform plan

   Make corrections to the configuration as necessary.

2. Apply the Terraform configuration by running the following command and entering yes at the prompt:

   terraform apply

   Wait until Terraform displays the "Apply complete!" message.

3. Open your Google Cloud project to view the results. In the Google Cloud console, navigate to your resources in the UI to make sure that Terraform has created or updated them.

Note: Terraform samples typically assume that the required APIs are enabled in your Google Cloud project.

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"
)

// createTableWithCMEK demonstrates creating a table protected with a customer managed encryption key.
func createTableWithCMEK(projectID, datasetID, tableID string) error {
	// projectID := "my-project-id"
	// datasetID := "mydatasetid"
	// tableID := "mytableid"
	ctx := context.Background()

	client, err := bigquery.NewClient(ctx, projectID)
	if err != nil {
		return fmt.Errorf("bigquery.NewClient: %v", err)
	}
	defer client.Close()

	tableRef := client.Dataset(datasetID).Table(tableID)
	meta := &bigquery.TableMetadata{
		EncryptionConfig: &bigquery.EncryptionConfig{
			// TODO: Replace this key with a key you have created in Cloud KMS.
			KMSKeyName: "projects/cloud-samples-tests/locations/us/keyRings/test/cryptoKeys/test",
		},
	}
	if err := tableRef.Create(ctx, meta); err != nil {
		return err
	}
	return nil
}

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.

import com.google.cloud.bigquery.BigQuery;
import com.google.cloud.bigquery.BigQueryException;
import com.google.cloud.bigquery.BigQueryOptions;
import com.google.cloud.bigquery.EncryptionConfiguration;
import com.google.cloud.bigquery.Field;
import com.google.cloud.bigquery.Schema;
import com.google.cloud.bigquery.StandardSQLTypeName;
import com.google.cloud.bigquery.StandardTableDefinition;
import com.google.cloud.bigquery.TableDefinition;
import com.google.cloud.bigquery.TableId;
import com.google.cloud.bigquery.TableInfo;

// Sample to create a cmek table
public class CreateTableCMEK {

  public static void runCreateTableCMEK() {
    // TODO(developer): Replace these variables before running the sample.
    String datasetName = "MY_DATASET_NAME";
    String tableName = "MY_TABLE_NAME";
    String kmsKeyName = "MY_KEY_NAME";
    Schema schema =
        Schema.of(
            Field.of("stringField", StandardSQLTypeName.STRING),
            Field.of("booleanField", StandardSQLTypeName.BOOL));
    // i.e. projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{cryptoKey}
    EncryptionConfiguration encryption =
        EncryptionConfiguration.newBuilder().setKmsKeyName(kmsKeyName).build();
    createTableCMEK(datasetName, tableName, schema, encryption);
  }

  public static void createTableCMEK(
      String datasetName, String tableName, Schema schema, EncryptionConfiguration configuration) {
    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();

      TableId tableId = TableId.of(datasetName, tableName);
      TableDefinition tableDefinition = StandardTableDefinition.of(schema);
      TableInfo tableInfo =
          TableInfo.newBuilder(tableId, tableDefinition)
              .setEncryptionConfiguration(configuration)
              .build();

      bigquery.create(tableInfo);
      System.out.println("Table cmek created successfully");
    } catch (BigQueryException e) {
      System.out.println("Table cmek was not created. \n" + e.toString());
    }
  }
}

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.

Protect a new table with a customer-managed encryption key by setting the Table.encryption_configuration property to an EncryptionConfiguration object before creating the table.

from google.cloud import bigquery

client = bigquery.Client()

# TODO(dev): Change table_id to the full name of the table you want to create.
table_id = "your-project.your_dataset.your_table_name"

# Set the encryption key to use for the table.
# TODO: Replace this key with a key you have created in Cloud KMS.
kms_key_name = "projects/your-project/locations/us/keyRings/test/cryptoKeys/test"

table = bigquery.Table(table_id)
table.encryption_configuration = bigquery.EncryptionConfiguration(
    kms_key_name=kms_key_name
)
table = client.create_table(table)  # API request

print(f"Created {table_id}.")
print(f"Key: {table.encryption_configuration.kms_key_name}.")

Query a table protected by a Cloud KMS key

No special arrangements are required to query a table protected by Cloud KMS. BigQuery stores the name of the key used to encrypt the table content and uses that key when a table protected by Cloud KMS is queried.

All existing tools, the BigQuery console, and the bq command-line tool run the same way as with default-encrypted tables, as long as BigQuery has access to the Cloud KMS key used to encrypt the table content.

Protect query results with a Cloud KMS key

By default, query results are stored in a temporary table encrypted with a Google-owned and Google-managed key. If the project already has a default key, the key is applied to the temporary (default) query results table. To use a Cloud KMS key to encrypt your query results instead, select one of the following options:

Console

1. Open the BigQuery page in the Google Cloud console.

   Go to the BigQuery page

2. Click Compose new query.

3. Enter a valid GoogleSQL query in the query text area.

4. Click More, click Query settings, then click Advanced options.

5. Select Customer-managed encryption.

6. Select the key. If the key you want to use is not listed, enter the resource ID for the key.

7. Click Save.

8. Click Run.

bq

Specify the flag --destination_kms_key to protect the destination table or query results (if using a temporary table) with your Cloud KMS key. The --destination_kms_key flag specifies the resource ID of the key to use with the destination or resulting table.

Optionally use the --destination_table flag to specify the destination for query results. If --destination_table is not used, the query results are written to a temporary table.

To query a table:

bq query \
--destination_table=DATASET_ID.TABLE_ID \
--destination_kms_key projects/KMS_PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY \
"SELECT name,count FROM DATASET_ID.TABLE_ID WHERE gender = 'M' ORDER BY count DESC LIMIT 6"

For more information about the bq command-line tool, see Using the bq command-line tool.

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.

Protect a new table with a customer-managed encryption key by setting the Table.encryption_configuration property to an EncryptionConfiguration object before creating the table.

import (
	"context"
	"fmt"
	"io"

	"cloud.google.com/go/bigquery"
	"google.golang.org/api/iterator"
)

// queryWithDestinationCMEK demonstrates saving query results to a destination table and protecting those results
// by specifying a customer managed encryption key.
func queryWithDestinationCMEK(w io.Writer, projectID, dstDatasetID, dstTableID string) error {
	// projectID := "my-project-id"
	// datasetID := "mydataset"
	// tableID := "mytable"
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, projectID)
	if err != nil {
		return fmt.Errorf("bigquery.NewClient: %v", err)
	}
	defer client.Close()

	q := client.Query("SELECT 17 as my_col")
	q.Location = "US" // Location must match the dataset(s) referenced in query.
	q.QueryConfig.Dst = client.Dataset(dstDatasetID).Table(dstTableID)
	q.DestinationEncryptionConfig = &bigquery.EncryptionConfig{
		// TODO: Replace this key with a key you have created in Cloud KMS.
		KMSKeyName: "projects/cloud-samples-tests/locations/us-central1/keyRings/test/cryptoKeys/test",
	}
	// Run the query and print results when the query job is completed.
	job, err := q.Run(ctx)
	if err != nil {
		return err
	}
	status, err := job.Wait(ctx)
	if err != nil {
		return err
	}
	if err := status.Err(); err != nil {
		return err
	}
	it, err := job.Read(ctx)
	for {
		var row []bigquery.Value
		err := it.Next(&row)
		if err == iterator.Done {
			break
		}
		if err != nil {
			return err
		}
		fmt.Fprintln(w, row)
	}
	return nil
}

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.

Protect a new table with a customer-managed encryption key by setting the Table.encryption_configuration property to an EncryptionConfiguration object before creating the table.

import com.google.cloud.bigquery.BigQuery;
import com.google.cloud.bigquery.BigQueryException;
import com.google.cloud.bigquery.BigQueryOptions;
import com.google.cloud.bigquery.EncryptionConfiguration;
import com.google.cloud.bigquery.QueryJobConfiguration;
import com.google.cloud.bigquery.TableResult;

// Sample to query on destination table with encryption key
public class QueryDestinationTableCMEK {

  public static void runQueryDestinationTableCMEK() {
    // TODO(developer): Replace these variables before running the sample.
    String datasetName = "MY_DATASET_NAME";
    String tableName = "MY_TABLE_NAME";
    String kmsKeyName = "MY_KMS_KEY_NAME";
    String query =
        String.format("SELECT stringField, booleanField FROM %s.%s", datasetName, tableName);
    EncryptionConfiguration encryption =
        EncryptionConfiguration.newBuilder().setKmsKeyName(kmsKeyName).build();
    queryDestinationTableCMEK(query, encryption);
  }

  public static void queryDestinationTableCMEK(String query, EncryptionConfiguration encryption) {
    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();

      QueryJobConfiguration config =
          QueryJobConfiguration.newBuilder(query)
              // Set the encryption key to use for the destination.
              .setDestinationEncryptionConfiguration(encryption)
              .build();

      TableResult results = bigquery.query(config);

      results
          .iterateAll()
          .forEach(row -> row.forEach(val -> System.out.printf("%s,", val.toString())));
      System.out.println("Query performed successfully with encryption key.");
    } catch (BigQueryException | InterruptedException e) {
      System.out.println("Query not performed \n" + e.toString());
    }
  }
}

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.

Protect a query destination table with a customer-managed encryption key by setting the QueryJobConfig.destination_encryption_configuration property to an EncryptionConfiguration and run the query.

from google.cloud import bigquery

# Construct a BigQuery client object.
client = bigquery.Client()

# TODO(developer): Set table_id to the ID of the destination table.
# table_id = "your-project.your_dataset.your_table_name"

# Set the encryption key to use for the destination.
# TODO(developer): Replace this key with a key you have created in KMS.
# kms_key_name = "projects/{}/locations/{}/keyRings/{}/cryptoKeys/{}".format(
#     your-project, location, your-ring, your-key
# )

job_config = bigquery.QueryJobConfig(
    destination=table_id,
    destination_encryption_configuration=bigquery.EncryptionConfiguration(
        kms_key_name=kms_key_name
    ),
)

# Start the query, passing in the extra configuration.
query_job = client.query(
    "SELECT 17 AS my_col;", job_config=job_config
)  # Make an API request.
query_job.result()  # Wait for the job to complete.

table = client.get_table(table_id)  # Make an API request.
if table.encryption_configuration.kms_key_name == kms_key_name:
    print("The destination table is written using the encryption configuration")

Load a table protected by Cloud KMS

To load a data file into a table that is protected by Cloud KMS:

Console

Protect a load job destination table with a customer-managed encryption key by specifying the key when you load the table.

1. Open the BigQuery page in the Google Cloud console.

   Go to the BigQuery page

2. In the Explorer panel, expand your project and select a dataset.

3. In the details panel, click Create table.

4. Enter the options you want to use for loading the table, but before you click Create table, click Advanced options.

5. Under Encryption, select Customer-managed key.

6. Click the Select a customer-managed key drop-down list and select the key to use. If you don't see any keys available, enter a key resource ID.

   

7. Click Create table.

bq

Protect a load job destination table with a customer-managed encryption key by setting the --destination_kms_key flag.

bq --location=LOCATION load \
--autodetect \
--source_format=FORMAT \
--destination_kms_key projects/KMS_PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY \
DATASET.TABLE \
path_to_source

For example:

bq load \
--autodetect \
--source_format=NEWLINE_DELIMITED_JSON \
--destination_kms_key projects/KMS_PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY \
test2.table4 \
gs://cloud-samples-data/bigquery/us-states/us-states.json

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"
)

// importJSONWithCMEK demonstrates loading newline-delimited JSON from Cloud Storage,
// and protecting the data with a customer-managed encryption key.
func importJSONWithCMEK(projectID, datasetID, tableID string) error {
	// projectID := "my-project-id"
	// datasetID := "mydataset"
	// tableID := "mytable"
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, projectID)
	if err != nil {
		return fmt.Errorf("bigquery.NewClient: %v", err)
	}
	defer client.Close()

	gcsRef := bigquery.NewGCSReference("gs://cloud-samples-data/bigquery/us-states/us-states.json")
	gcsRef.SourceFormat = bigquery.JSON
	gcsRef.AutoDetect = true
	loader := client.Dataset(datasetID).Table(tableID).LoaderFrom(gcsRef)
	loader.WriteDisposition = bigquery.WriteEmpty
	loader.DestinationEncryptionConfig = &bigquery.EncryptionConfig{
		// TODO: Replace this key with a key you have created in KMS.
		KMSKeyName: "projects/cloud-samples-tests/locations/us-central1/keyRings/test/cryptoKeys/test",
	}

	job, err := loader.Run(ctx)
	if err != nil {
		return err
	}
	status, err := job.Wait(ctx)
	if err != nil {
		return err
	}

	if status.Err() != nil {
		return fmt.Errorf("job completed with error: %v", status.Err())
	}

	return nil
}

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.

import com.google.cloud.bigquery.BigQuery;
import com.google.cloud.bigquery.BigQueryException;
import com.google.cloud.bigquery.BigQueryOptions;
import com.google.cloud.bigquery.EncryptionConfiguration;
import com.google.cloud.bigquery.FormatOptions;
import com.google.cloud.bigquery.Job;
import com.google.cloud.bigquery.JobInfo;
import com.google.cloud.bigquery.LoadJobConfiguration;
import com.google.cloud.bigquery.TableId;

// Sample to load JSON data with configuration key from Cloud Storage into a new BigQuery table
public class LoadJsonFromGCSCMEK {

  public static void runLoadJsonFromGCSCMEK() {
    // TODO(developer): Replace these variables before running the sample.
    String datasetName = "MY_DATASET_NAME";
    String tableName = "MY_TABLE_NAME";
    String kmsKeyName = "MY_KMS_KEY_NAME";
    String sourceUri = "gs://cloud-samples-data/bigquery/us-states/us-states.json";
    // i.e. projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{cryptoKey}
    EncryptionConfiguration encryption =
        EncryptionConfiguration.newBuilder().setKmsKeyName(kmsKeyName).build();
    loadJsonFromGCSCMEK(datasetName, tableName, sourceUri, encryption);
  }

  public static void loadJsonFromGCSCMEK(
      String datasetName, String tableName, String sourceUri, EncryptionConfiguration encryption) {
    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();

      TableId tableId = TableId.of(datasetName, tableName);
      LoadJobConfiguration loadConfig =
          LoadJobConfiguration.newBuilder(tableId, sourceUri)
              // Set the encryption key to use for the destination.
              .setDestinationEncryptionConfiguration(encryption)
              .setFormatOptions(FormatOptions.json())
              .setAutodetect(true)
              .build();

      // Load data from a GCS JSON file into the table
      Job job = bigquery.create(JobInfo.of(loadConfig));
      // Blocks until this load table job completes its execution, either failing or succeeding.
      job = job.waitFor();
      if (job.isDone()) {
        System.out.println("Table loaded succesfully from GCS with configuration key");
      } else {
        System.out.println(
            "BigQuery was unable to load into the table due to an error:"
                + job.getStatus().getError());
      }
    } catch (BigQueryException | InterruptedException e) {
      System.out.println("Column not added during load append \n" + e.toString());
    }
  }
}

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.

Protect a load job destination table with a customer-managed encryption key by setting the LoadJobConfig.destination_encryption_configuration property to an EncryptionConfiguration and load the table.

from google.cloud import bigquery

# Construct a BigQuery client object.
client = bigquery.Client()

# TODO(developer): Set table_id to the ID of the table to create.
# table_id = "your-project.your_dataset.your_table_name

# Set the encryption key to use for the destination.
# TODO: Replace this key with a key you have created in KMS.
# kms_key_name = "projects/{}/locations/{}/keyRings/{}/cryptoKeys/{}".format(
#     "cloud-samples-tests", "us", "test", "test"
# )

job_config = bigquery.LoadJobConfig(
    autodetect=True,
    source_format=bigquery.SourceFormat.NEWLINE_DELIMITED_JSON,
    destination_encryption_configuration=bigquery.EncryptionConfiguration(
        kms_key_name=kms_key_name
    ),
)

uri = "gs://cloud-samples-data/bigquery/us-states/us-states.json"

load_job = client.load_table_from_uri(
    uri,
    table_id,
    location="US",  # Must match the destination dataset location.
    job_config=job_config,
)  # Make an API request.

assert load_job.job_type == "load"

load_job.result()  # Waits for the job to complete.

assert load_job.state == "DONE"
table = client.get_table(table_id)

if table.encryption_configuration.kms_key_name == kms_key_name:
    print("A table loaded with encryption configuration key")

Stream into a table protected by Cloud KMS

You can stream data into your CMEK-protected BigQuery table without specifying any additional parameters. Note that this data is encrypted using your Cloud KMS key in the buffer as well as in the final location. Before using streaming with a CMEK table, review the requirements on key availability and accessibility.

Learn more about streaming at Streaming data using the BigQuery Storage Write API.

Change a table from default encryption to Cloud KMS protection

bq

You can use the bq cp command with the --destination_kms_key flag to copy a table protected by default encryption into a new table, or into the original table, protected by Cloud KMS. The --destination_kms_key flag specifies the resource ID of the key to use with the destination table.

To copy a table that has default encryption to a new table that has Cloud KMS protection:

bq cp \
--destination_kms_key projects/KMS_PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY \
SOURCE_DATASET_ID.SOURCE_TABLE_ID DESTINATION_DATASET_ID.DESTINATION_TABLE_ID

In you want to copy a table that has default encryption to the same table with Cloud KMS protection:

bq cp -f \
--destination_kms_key projects/KMS_PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY \
DATASET_ID.TABLE_ID DATASET_ID.TABLE_ID

If you want to change a table from Cloud KMS protection to default encryption, copy the file to itself by running bq cp without using the --destination_kms_key flag.

For more information about the bq command-line tool, see Using the bq command-line tool.

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"
)

// copyTableWithCMEK demonstrates creating a copy of a table and ensuring the copied data is
// protected with a customer managed encryption key.
func copyTableWithCMEK(projectID, datasetID, tableID string) error {
	// projectID := "my-project-id"
	// datasetID := "mydataset"
	// tableID := "mytable"
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, projectID)
	if err != nil {
		return fmt.Errorf("bigquery.NewClient: %v", err)
	}
	defer client.Close()

	srcTable := client.DatasetInProject("bigquery-public-data", "samples").Table("shakespeare")
	copier := client.Dataset(datasetID).Table(tableID).CopierFrom(srcTable)
	copier.DestinationEncryptionConfig = &bigquery.EncryptionConfig{
		// TODO: Replace this key with a key you have created in Cloud KMS.
		KMSKeyName: "projects/cloud-samples-tests/locations/us-central1/keyRings/test/cryptoKeys/test",
	}
	job, err := copier.Run(ctx)
	if err != nil {
		return err
	}
	status, err := job.Wait(ctx)
	if err != nil {
		return err
	}
	if err := status.Err(); err != nil {
		return err
	}
	return nil
}

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.

import com.google.cloud.bigquery.BigQuery;
import com.google.cloud.bigquery.BigQueryException;
import com.google.cloud.bigquery.BigQueryOptions;
import com.google.cloud.bigquery.CopyJobConfiguration;
import com.google.cloud.bigquery.EncryptionConfiguration;
import com.google.cloud.bigquery.Job;
import com.google.cloud.bigquery.JobInfo;
import com.google.cloud.bigquery.TableId;

// Sample to copy a cmek table
public class CopyTableCMEK {

  public static void runCopyTableCMEK() {
    // TODO(developer): Replace these variables before running the sample.
    String destinationDatasetName = "MY_DESTINATION_DATASET_NAME";
    String destinationTableId = "MY_DESTINATION_TABLE_NAME";
    String sourceDatasetName = "MY_SOURCE_DATASET_NAME";
    String sourceTableId = "MY_SOURCE_TABLE_NAME";
    String kmsKeyName = "MY_KMS_KEY_NAME";
    EncryptionConfiguration encryption =
        EncryptionConfiguration.newBuilder().setKmsKeyName(kmsKeyName).build();
    copyTableCMEK(
        sourceDatasetName, sourceTableId, destinationDatasetName, destinationTableId, encryption);
  }

  public static void copyTableCMEK(
      String sourceDatasetName,
      String sourceTableId,
      String destinationDatasetName,
      String destinationTableId,
      EncryptionConfiguration encryption) {
    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();

      TableId sourceTable = TableId.of(sourceDatasetName, sourceTableId);
      TableId destinationTable = TableId.of(destinationDatasetName, destinationTableId);

      // For more information on CopyJobConfiguration see:
      // https://googleapis.dev/java/google-cloud-clients/latest/com/google/cloud/bigquery/JobConfiguration.html
      CopyJobConfiguration configuration =
          CopyJobConfiguration.newBuilder(destinationTable, sourceTable)
              .setDestinationEncryptionConfiguration(encryption)
              .build();

      // For more information on Job see:
      // https://googleapis.dev/java/google-cloud-clients/latest/index.html?com/google/cloud/bigquery/package-summary.html
      Job job = bigquery.create(JobInfo.of(configuration));

      // Blocks until this job completes its execution, either failing or succeeding.
      Job completedJob = job.waitFor();
      if (completedJob == null) {
        System.out.println("Job not executed since it no longer exists.");
        return;
      } else if (completedJob.getStatus().getError() != null) {
        System.out.println(
            "BigQuery was unable to copy table due to an error: \n" + job.getStatus().getError());
        return;
      }
      System.out.println("Table cmek copied successfully.");
    } catch (BigQueryException | InterruptedException e) {
      System.out.println("Table cmek copying job was interrupted. \n" + e.toString());
    }
  }
}

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.

Protect the destination of a table copy with a customer-managed encryption key by setting the QueryJobConfig.destination_encryption_configuration property to an EncryptionConfiguration and copy the table.

from google.cloud import bigquery

# Construct a BigQuery client object.
client = bigquery.Client()

# TODO(developer): Set dest_table_id to the ID of the destination table.
# dest_table_id = "your-project.your_dataset.your_table_name"

# TODO(developer): Set orig_table_id to the ID of the original table.
# orig_table_id = "your-project.your_dataset.your_table_name"

# Set the encryption key to use for the destination.
# TODO(developer): Replace this key with a key you have created in KMS.
# kms_key_name = "projects/{}/locations/{}/keyRings/{}/cryptoKeys/{}".format(
#     your-project, location, your-ring, your-key
# )

job_config = bigquery.CopyJobConfig(
    destination_encryption_configuration=bigquery.EncryptionConfiguration(
        kms_key_name=kms_key_name
    )
)
job = client.copy_table(orig_table_id, dest_table_id, job_config=job_config)
job.result()  # Wait for the job to complete.

dest_table = client.get_table(dest_table_id)  # Make an API request.
if dest_table.encryption_configuration.kms_key_name == kms_key_name:
    print("A copy of the table created")

Determine if a table is protected by Cloud KMS

1. In the Google Cloud console, click the blue arrow to the left of your dataset to expand it, or double-click the dataset name. This displays the tables and views in the dataset.

2. Click the table name.

3. Click Details. The Table Details page displays the table's description and table information.

4. If the table is protected by Cloud KMS, the Customer-Managed Encryption Key field displays the key resource ID.

   

For each of the keys you've created or that protect your tables, you can see what resources that key protects with key usage tracking. For more information, see View key usage.

Change the Cloud KMS key for a BigQuery table

To change the Cloud KMS key of an existing CMEK-protected table, you can run an ALTER TABLE query, use the API, or use the bq command-line tool. There are two ways to modify the Cloud KMS key using the API and the bq command-line tool: update or cp.

If you use update, you can change the Cloud KMS key used for a CMEK-protected table.

If you use cp, you can change the Cloud KMS key used for a CMEK-protected table, change a table from default encryption to CMEK-protection, or change a table from CMEK-protection to default encryption.

An advantage of update is it is faster than cp and it lets you use table decorators.

SQL

Use the ALTER TABLE SET OPTIONS statement to update the kms_key_name field for a table:

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

   Go to BigQuery

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

   ALTER TABLE DATASET_ID.mytable
   SET OPTIONS (
     kms_key_name
       = 'projects/KMS_PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY');

3. Click Run.

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

bq

You can use the bq cp command with the --destination_kms_key flag to change the key for a table protected by Cloud KMS. The --destination_kms_key flag specifies the resource ID of the key to use with the table.

bq update \
--destination_kms_key projects/KMS_PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY \
-t DATASET_ID.TABLE_ID

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"
)

// updateTableChangeCMEK demonstrates how to change the customer managed encryption key that protects a table.
func updateTableChangeCMEK(projectID, datasetID, tableID string) error {
	// projectID := "my-project-id"
	// datasetID := "mydatasetid"
	// tableID := "mytableid"
	ctx := context.Background()

	client, err := bigquery.NewClient(ctx, projectID)
	if err != nil {
		return fmt.Errorf("bigquery.NewClient: %v", err)
	}
	defer client.Close()

	tableRef := client.Dataset(datasetID).Table(tableID)
	meta, err := tableRef.Metadata(ctx)
	if err != nil {
		return err
	}
	update := bigquery.TableMetadataToUpdate{
		EncryptionConfig: &bigquery.EncryptionConfig{
			// TODO: Replace this key with a key you have created in Cloud KMS.
			KMSKeyName: "projects/cloud-samples-tests/locations/us-central1/keyRings/test/cryptoKeys/otherkey",
		},
	}
	if _, err := tableRef.Update(ctx, update, meta.ETag); err != nil {
		return err
	}
	return nil
}

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.

import com.google.cloud.bigquery.BigQuery;
import com.google.cloud.bigquery.BigQueryException;
import com.google.cloud.bigquery.BigQueryOptions;
import com.google.cloud.bigquery.EncryptionConfiguration;
import com.google.cloud.bigquery.Table;
import com.google.cloud.bigquery.TableId;

// Sample to update a cmek table
public class UpdateTableCMEK {

  public static void runUpdateTableCMEK() {
    // TODO(developer): Replace these variables before running the sample.
    String datasetName = "MY_DATASET_NAME";
    String tableName = "MY_TABLE_NAME";
    String kmsKeyName = "MY_KEY_NAME";
    // Set a new encryption key to use for the destination.
    // i.e. projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{cryptoKey}
    EncryptionConfiguration encryption =
        EncryptionConfiguration.newBuilder().setKmsKeyName(kmsKeyName).build();
    updateTableCMEK(datasetName, tableName, encryption);
  }

  public static void updateTableCMEK(
      String datasetName, String tableName, EncryptionConfiguration encryption) {
    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();

      Table table = bigquery.getTable(TableId.of(datasetName, tableName));
      bigquery.update(table.toBuilder().setEncryptionConfiguration(encryption).build());
      System.out.println("Table cmek updated successfully");
    } catch (BigQueryException e) {
      System.out.println("Table cmek was not updated. \n" + e.toString());
    }
  }
}

Python

Change the customer-managed encryption key for a table by changing the Table.encryption_configuration property to a new EncryptionConfiguration object and update the table.

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.

# from google.cloud import bigquery
# client = bigquery.Client()

assert table.encryption_configuration.kms_key_name == original_kms_key_name

# Set a new encryption key to use for the destination.
# TODO: Replace this key with a key you have created in KMS.
updated_kms_key_name = (
    "projects/cloud-samples-tests/locations/us/keyRings/test/cryptoKeys/otherkey"
)
table.encryption_configuration = bigquery.EncryptionConfiguration(
    kms_key_name=updated_kms_key_name
)

table = client.update_table(table, ["encryption_configuration"])  # API request

assert table.encryption_configuration.kms_key_name == updated_kms_key_name
assert original_kms_key_name != updated_kms_key_name

Set a dataset default key

You can set a dataset-wide default Cloud KMS key that applies to all newly created tables within the dataset, unless a different Cloud KMS key is specified when you create the table. The default key does not apply to existing tables. Changing the default key does not modify any existing tables and applies only to new tables created after the change.

You can apply, change, or remove a dataset default key by

• specifying the default key in the EncryptionConfiguration.kmsKeyName field when you call the datasets.insert or datasets.patch methods

• specifying the default key in the --default_kms_key flag when you run the bq mk --dataset command.

  bq mk \
  --default_kms_key projects/KMS_PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY \
  --dataset DATASET_ID
  

  bq update \
  --default_kms_key projects/KMS_PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY \
  --dataset DATASET_ID
  

Note: Within a dataset that has a default Cloud KMS key applied, it is not possible to encrypt new tables with a key other than a customer-managed encryption key. That is, if the dataset has a default Cloud KMS key, you cannot use a non-customer-managed encryption key to encrypt new tables in the dataset.

Set a project default key

You can set project-default Cloud KMS keys that apply to all query results and newly created tables in the project for that location, unless you specify a different Cloud KMS key. The default key does not apply to existing tables. Changing the default key does not modify any existing tables and applies only to new tables created after the change.

SQL

Use the ALTER PROJECT SET OPTIONS statement to update the default_kms_key_name field for a project. You can find the resource name for the key on the Cloud KMS page.

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

   Go to BigQuery

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

   ALTER PROJECT PROJECT_ID
   SET OPTIONS (
     region-<var>LOCATION</var>.default_kms_key_name
       = 'projects/KMS_PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY');

3. Click Run.

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

bq

You can use the bq command to run an ALTER PROJECT SET OPTIONS statement to update the default_kms_key_name field for a project:

bq query --nouse_legacy_sql \
  'ALTER PROJECT PROJECT_ID
  SET OPTIONS (
  `region-LOCATION.default_kms_key_name`
    ="projects/KMS_PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY");'

Use CMEK to protect BigQuery ML models

BigQuery ML supports CMEK. Along with the default encryption provided by BigQuery, you can use your own Cloud Key Management Service keys for encrypting machine learning models, including imported TensorFlow models.

Create an encrypted model with a Cloud KMS key

To create an encrypted model, use the CREATE MODEL statement and specify KMS_KEY_NAME in the training options:

    CREATE MODEL my_dataset.my_model
    OPTIONS(
      model_type='linear_reg',
      input_label_cols=['your_label'],
      kms_key_name='projects/my_project/locations/my_location/keyRings/my_ring/cryptoKeys/my_key')
    AS SELECT * FROM my_dataset.my_data

The same syntax also applies to imported TensorFlow models:

    CREATE MODEL my_dataset.my_model
    OPTIONS(
      model_type='tensorflow',
      path='gs://bucket/path/to/saved_model/*',
      kms_key_name='projects/my_project/locations/my_location/keyRings/my_ring/cryptoKeys/my_key')
    AS SELECT * FROM my_dataset.my_data

Limitations

Customer-managed encryption keys have the following restrictions when encrypting machine learning models:

• Global region CMEK keys are not supported for the following types of models:

  • DNN
  • Wide-and-Deep
  • Autoencoder
  • Boosted tree

• Global region CMEK keys and multi-region CMEK keys, for example EU or US, are not supported when creating the following types of models:

  • AutoML Tables models

• CMEK keys aren't supported for remote models:

  • Remote models over Vertex AI built-in models
  • Remote models over Vertex AI hosted models
  • Remote models over Cloud AI services

Change a model from default encryption to Cloud KMS protection

You can use the bq cp command with the --destination_kms_key flag to copy a model protected by default encryption into a new model that is protected by Cloud KMS. Alternatively, you can use the bq cp command with the -f flag to overwrite a model protected by default encryption and update it to use Cloud KMS protection instead. The --destination_kms_key flag specifies the resource ID of the key to use with the destination model.

To copy a model that has default encryption to a new model that has Cloud KMS protection:

bq cp \
--destination_kms_key projects/KMS_PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY \
SOURCE_DATASET_ID.SOURCE_MODEL_ID DESTINATION_DATASET_ID.DESTINATION_MODEL_ID

To overwrite a model that has default encryption to the same model with Cloud KMS protection:

bq cp -f \
--destination_kms_key projects/KMS_PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY \
DATASET_ID.MODEL_ID DATASET_ID.MODEL_ID

To change a model from Cloud KMS protection to default encryption:

bq cp -f \
DATASET_ID.MODEL_ID DATASET_ID.MODEL_ID

For more information about the bq command-line tool, see Using the bq command-line tool.

Determine if a model is protected by Cloud KMS

Use the bq show command to see if a model is protected by Cloud KMS key. The encryption key is in the kmsKeyName field.

bq show -m my_dataset.my_model

You can also use the Google Cloud console to find the Cloud KMS key for an encrypted model. CMEK information is in the Customer-managed key field in the Model Details section of the model's Details pane.

Change the Cloud KMS key for an encrypted model

Use the bq update command with the --destination_kms_key flag to change the key for a model protected by Cloud KMS:

bq update --destination_kms_key \
projects/my_project/locations/my_location/keyRings/my_ring/cryptoKeys/my_key \
-t my_dataset.my_model

Use default project or dataset keys

If you have a default Cloud KMS key set at the project or dataset level, BigQuery ML automatically uses this key when creating models. Use the CREATE MODEL statement to specify a different key to encrypt the model if you don't want to use the default key.

Use BigQuery ML functions with encrypted models

You can use all BigQuery ML functions with an encrypted model without specifying an encryption key.

Use CMEK to protect BigQuery Connection API

For Cloud SQL connections, you can protect your BigQuery Connection API credentials using CMEK.

For more information about how to create a CMEK-protected connection, see Create Cloud SQL connections.

Remove BigQuery's access to the Cloud KMS key

You can remove BigQuery's access to the Cloud KMS key at any time, by revoking the Identity and Access Management (IAM) permission for that key.

Note: If you remove BigQuery's access to a key, this change doesn't take place instantly, but happens within an hour while the IAM permission change propagates. If you are running a query at the time the query still completes, but the results might not be viewable.

If BigQuery loses access to the Cloud KMS key, the user experience can suffer significantly and data loss can occur:

• Data in these CMEK-protected tables can no longer be accessed: query, cp, extract, and tabledata.list will all fail.

• No new data can be added to these CMEK-protected tables.

• After access is granted back, the performance of queries to these tables can be degraded for multiple days.

Control CMEK use with organization policy

BigQuery integrates with CMEK organization policy constraints to let you specify encryption compliance requirements for BigQuery resources in your organization.

This integration lets you do the following:

• Require CMEKs for all BigQuery resources in a project.

• Restrict which Cloud KMS keys can be used to protect resources in a project.

Require CMEKs for all resources

A common policy is to require CMEKs to be used to protect all resources in a specific set of projects. You can use the constraints/gcp.restrictNonCmekServices constraint to enforce this policy in BigQuery.

If set, this organization policy causes all resource creation requests without a specified Cloud KMS key to fail.

After you set this policy, it applies only to new resources in the project. Any existing resources without Cloud KMS keys set continue to exist and are accessible without issue.

Note: This constraint only applies to resources that contain data. Resources that only use their specified Cloud KMS key as a default for new resources (for instance, datasets and project config) can still be created or updated without a Cloud KMS key.

Console

1. Open the Organization policies page.

   Go to Organization policies

2. In the Filter field, enter constraints/gcp.restrictNonCmekServices, and then click Restrict which services may create resources without CMEK.

3. Click Edit.

4. Select Customize, select Replace, and then click Add Rule.

5. Select Custom, then click Deny.

6. In the Custom Value field, enter is:bigquery.googleapis.com.

7. Click Done, and then click Save.

gcloud

  gcloud resource-manager org-policies --project=PROJECT_ID \
    deny gcp.restrictNonCmekServices is:bigquery.googleapis.com

To verify that the policy is successfully applied, you can try to create a table in the project. The process fails unless you specify a Cloud KMS key.

This policy also applies to query results tables in the project. You can specify a project default key so users don't have to manually specify a key each time they execute a query in the project.

Restrict Cloud KMS keys for a BigQuery project

You can use the constraints/gcp.restrictCmekCryptoKeyProjects constraint to restrict the Cloud KMS keys that you can use to protect a resource in a BigQuery project.

You might specify a rule - for example, "For all BigQuery resources in projects/my-company-data-project, Cloud KMS keys used in this project must come from projects/my-company-central-keys OR projects/team-specific-keys."

Console

1. Open the Organization policies page.

   Go to Organization policies

2. In the Filter field, enter constraints/gcp.restrictCmekCryptoKeyProjects, and then click Restrict which projects may supply KMS CryptoKeys for CMEK.

3. Click Edit.

4. Select Customize, select Replace, and then click Add Rule.

5. Select Custom, then click Allow.

6. In the Custom Value field, enter under:projects/<var>KMS_PROJECT_ID</var>.

7. Click Done, and then click Save.

gcloud

  gcloud resource-manager org-policies --project=PROJECT_ID \
    allow gcp.restrictCmekCryptoKeyProjects under:projects/KMS_PROJECT_ID

To verify that the policy is successfully applied, you can try to create a table using a Cloud KMS key from a different project. The process will fail.

Limitations of organization policies

There are limitations associated with setting an organization policy.

Propagation delay

After you set or update an organization policy, it can take up to 15 minutes for the new policy to take effect. BigQuery caches policies in order to not negatively affect query and table creation latency.

Required permissions to set an organization policy

The permission to set or update the organization policy might be difficult to acquire for testing purposes. You must be granted the Organization Policy Administrator role, which can only be granted at the organization level (rather than the project or folder level).

Although the role must be granted at the organization level, it is still possible to specify a policy that only applies to a specific project or folder.

Impact of Cloud KMS key rotation

BigQuery doesn't automatically rotate a table encryption key when the Cloud KMS key associated with the table is rotated. All data in the existing tables continue to be protected by the key version with which they were created.

Any newly-created tables use the primary key version at the time of their creation.

To update a table to use the most recent key version, change the table to a different Cloud KMS key and then back to the original.

Impact on Cloud KMS billing

When you create or truncate a CMEK-protected table, BigQuery generates an intermediate key-encryption key which is then encrypted with the specified Cloud KMS key.

For billing purposes, this means that neither your calls to Cloud KMS nor their associated costs scale with the table size. For CMEK-protected tables, You can expect one call to Cloud KMS cryptoKeys.encrypt for each table creation or truncation and one call to Cloud KMS cryptoKeys.decrypt for each table involved in a query. These methods both belong to the category of Key operations: Cryptographic listed in Cloud KMS Pricing.

Either reading from or writing to an existing CMEK-protected table invokes Cloud KMS cryptoKeys.decrypt because the intermediate key must be decrypted.

Limitations

BigQuery access to the Cloud KMS key

A Cloud KMS key is considered available and accessible by BigQuery under the following conditions:

• The key is enabled
• The BigQuery service account has encrypt and decrypt permissions on the key

The following sections describe impact to streaming inserts and long-term inaccessible data when a key is inaccessible.

Impact to streaming inserts

The Cloud KMS key must be available and accessible for at least 24 consecutive hours in the 48-hour period following a streaming insertion request. If the key is not available and accessible, the streamed data might not be fully persisted and can be lost. For more information about streaming inserts, see Streaming data into BigQuery.

Impact to long-term inaccessible data

As BigQuery provides managed storage, long-term inaccessible data is not compatible with BigQuery's architecture. If the Cloud KMS key of a given BigQuery table is not available and not accessible for 60 consecutive days, BigQuery might choose to delete the table and its associated data. At least 7 days before the data is deleted, BigQuery sends an email to the email address associated with the billing account.

Using external data sources

If you are querying data stored in an external data source such as Cloud Storage that has CMEK-encrypted data, then the data encryption is managed by Cloud Storage. For example, BigLake tables support data encrypted with CMEK in Cloud Storage.

BigQuery and BigLake tables don't support Customer-Supplied Encryption Keys (CSEK).

Switching between CMEK-protected and default encryption

You cannot switch a table in place between default encryptions and CMEK encryption. To switch encryption, copy the table with destination encryption information set or use a SELECT * query to select the table into itself with WRITE_TRUNCATE disposition.

Using table decorators

If you protect a table with Cloud KMS and then replace the data in the table by using the value WRITE_TRUNCATE for a load, cp, or query operation, then range decorators don't work across the encryption change boundary. You can still use table decorators, including range decorators, to query the data before or after the boundary, or query the snapshot at a point in time.

Wildcard table queries

CMEK-protected tables cannot be queried with a wildcard suffix.

Editions support

CMEK support for BigQuery is only available for BigQuery Enterprise Plus and BigQuery On-Demand. BigQuery customers of legacy flat-rate reservations prior to July 5, 2023, retain all existing support for CMEK in the Enterprise tier.

BigQuery Studio support

BigQuery Studio code assets, including saved queries and notebooks, don't support CMEK.

Frequently asked questions

Who needs permission to the Cloud KMS key?

With customer-managed encryption keys, specifying permissions repeatedly is not required. As long as the BigQuery service account has permission to use the Cloud KMS key to encrypt and decrypt, anyone with permission to the BigQuery table can access the data, even if they don't have direct access to the Cloud KMS key.

Which service account is used?

The BigQuery service account associated with the Google Cloud project of the table is used to decrypt that table's data. The BigQuery service accounts are unique for each project. For a job that writes data into a Cloud KMS-protected anonymous table, the job's project's service account is used.

As an example, consider three CMEK-protected tables: table1, table2, and table3. To query data from {project1.table1, project2.table2} with destination table {project3.table3}:

• Use the project1 service account for project1.table1
• Use the project2 service account for project2.table2
• Use the project3 service account for project3.table3

In what ways can BigQuery use my Cloud KMS key?

BigQuery uses the Cloud KMS key to decrypt data in response to a user query, for example, tabledata.list or jobs.insert.

BigQuery can also use the key for data maintenance and storage optimization tasks, like data conversion into a read-optimized format.

What cryptography libraries are used?

BigQuery relies on Cloud KMS for CMEK functionality. Cloud KMS uses Tink for encryption.

How to get more help?

If you have questions that are not answered here, see BigQuery support.

Troubleshooting errors

The following describes common errors and recommended mitigations.

Error	Recommendation
Please grant Cloud KMS CryptoKey Encrypter/Decrypter role	The BigQuery service account associated with your project doesn't have sufficient IAM permission to operate on the specified Cloud KMS key. Follow the instructions in the error or in this documentation to grant the proper IAM permission.
Existing table encryption settings do not match encryption settings specified in the request	This can occur in scenarios where the destination table has encryption settings that don't match the encryption settings in your request. As mitigation, use write disposition TRUNCATE to replace the table, or specify a different destination table.
This region is not supported	The region of the Cloud KMS key does not match the region of the BigQuery dataset of the destination table. As a mitigation, select a key in a region that matches your dataset, or load into a dataset that matches the key region.
Your administrator requires that you specify an encryption key for queries in project PROJECT_ID.	An organization policy prevented creating a resource or running a query. To learn more about this policy, see Requiring CMEKs for all resources in a BigQuery project.
Your administrator prevents using KMS keys from project KMS_PROJECT_ID to protect resources in project PROJECT_ID.	An organization policy prevented creating a resource or running a query. To learn more about this policy, see Restrict Cloud KMS keys for a BigQuery project.