Manage tables

This document describes how to manage tables in BigQuery. You can manage your BigQuery tables in the following ways:

• Update table properties:
  • Expiration time
  • Description
  • Schema definition
  • Labels
  • Default rounding mode
• Rename (copy) a table
• Copy a table
• Delete a table
• Restore a deleted table

For more information about creating and using tables including getting table information, listing tables, and controlling access to table data, see Creating and using tables.

Before you begin

Grant Identity and Access Management (IAM) roles that give users the necessary permissions to perform each task in this document. The permissions required to perform a task (if any) are listed in the "Required permissions" section of the task.

Update table properties

You can update the following elements of a table:

• Description
• Expiration time
• Schema definition
• Labels
• Table name
• Tags

Required permissions

To get the permissions that you need to update table properties, ask your administrator to grant you the Data Editor (roles/bigquery.dataEditor) IAM role on a table. For more information about granting roles, see Manage access to projects, folders, and organizations.

This predefined role contains the permissions required to update table properties. To see the exact permissions that are required, expand the Required permissions section:

Required permissions

The following permissions are required to update table properties:

• bigquery.tables.update
• bigquery.tables.get

You might also be able to get these permissions with custom roles or other predefined roles.

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

Update a table's description

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

• Using the Google Cloud console.
• Using a data definition language (DDL) ALTER TABLE statement.
• Using the bq command-line tool's bq update command.
• Calling the tables.patch API method.
• Using the client libraries.

To update a table's description:

Console

You can't add a description when you create a table using the Google Cloud console. After the table is created, you can add a description on the Details page.

1. In the Explorer panel, expand your project and dataset, then select the table.

2. In the details panel, click Details.

3. In the Description section, click the pencil icon to edit the description.

   

4. Enter a description in the box, and click Update to save.

SQL

Use the ALTER TABLE SET OPTIONS statement. The following example updates the description of a table named mytable:

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 mydataset.mytable
     SET OPTIONS (
       description = 'Description of mytable');
   

3. Click Run.

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

bq

1. In the Google Cloud console, activate Cloud Shell.

   Activate Cloud Shell

   At the bottom of the Google Cloud console, a Cloud Shell session starts and displays a command-line prompt. Cloud Shell is a shell environment with the Google Cloud CLI already installed and with values already set for your current project. It can take a few seconds for the session to initialize.

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

   bq update \
   --description "description" \
   project_id:dataset.table
   

   Replace the following:

   • description: the text describing the table in quotes
   • project_id: your project ID
   • dataset: the name of the dataset that contains the table you're updating
   • table: the name of the table you're updating

   Examples:

   To change the description of the mytable table in the mydataset dataset to "Description of mytable", enter the following command. The mydataset dataset is in your default project.

   bq update --description "Description of mytable" mydataset.mytable
   

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

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

API

Call the tables.patch method and use the description property in the table resource to update the table's description. Because the tables.update method replaces the entire table resource, the tables.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"
)

// updateTableDescription demonstrates how to fetch a table's metadata and updates the Description metadata.
func updateTableDescription(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()

	tableRef := client.Dataset(datasetID).Table(tableID)
	meta, err := tableRef.Metadata(ctx)
	if err != nil {
		return err
	}
	update := bigquery.TableMetadataToUpdate{
		Description: "Updated description.",
	}
	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.Table;

public class UpdateTableDescription {

  public static void runUpdateTableDescription() {
    // TODO(developer): Replace these variables before running the sample.
    String datasetName = "MY_DATASET_NAME";
    String tableName = "MY_TABLE_NAME";
    String newDescription = "this is the new table description";
    updateTableDescription(datasetName, tableName, newDescription);
  }

  public static void updateTableDescription(
      String datasetName, String tableName, String newDescription) {
    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(datasetName, tableName);
      bigquery.update(table.toBuilder().setDescription(newDescription).build());
      System.out.println("Table description updated successfully to " + newDescription);
    } catch (BigQueryException e) {
      System.out.println("Table description was not updated \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.

Configure the Table.description property and call Client.update_table() to send the update to the API.

# from google.cloud import bigquery
# client = bigquery.Client()
# project = client.project
# dataset_ref = bigquery.DatasetReference(project, dataset_id)
# table_ref = dataset_ref.table('my_table')
# table = client.get_table(table_ref)  # API request

assert table.description == "Original description."
table.description = "Updated description."

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

assert table.description == "Updated description."

Update a table's expiration time

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. A table's expiration time is often referred to as "time to live" or TTL.

When a table expires, it is deleted along with all of the data it contains. If necessary, you can undelete the expired table within the time travel window specified for the dataset, see Restore deleted tables for more information.

If you set the expiration when the table is created, the dataset's default table expiration is ignored. If you do not set a default table expiration at the dataset level, and you do not set a table expiration when the table is created, the table never expires and you must delete the table manually.

At any point after the table is created, you can update the table's expiration time in the following ways:

• Using the Google Cloud console.
• Using a data definition language (DDL) ALTER TABLE statement.
• Using the bq command-line tool's bq update command.
• Calling the tables.patch API method.
• Using the client libraries.

Note: If you set an expiration time that has already passed, the table is deleted immediately.

To update a table's expiration time:

Console

You can't add an expiration time when you create a table using the Google Cloud console. After a table is created, you can add or update a table expiration on the Table Details page.

1. In the Explorer panel, expand your project and dataset, then select the table.

2. In the details panel, click Details.

3. Click the pencil icon next to Table info

4. For Table expiration, select Specify date. Then select the expiration date using the calendar widget.

5. Click Update to save. The updated expiration time appears in the Table info section.

SQL

Use the ALTER TABLE SET OPTIONS statement. The following example updates the expiration time of a table named mytable:

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 mydataset.mytable
     SET OPTIONS (
       -- Sets table expiration to timestamp 2025-02-03 12:34:56
       expiration_timestamp = TIMESTAMP '2025-02-03 12:34:56');
   

3. Click Run.

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

bq

1. In the Google Cloud console, activate Cloud Shell.

   Activate Cloud Shell

   At the bottom of the Google Cloud console, a Cloud Shell session starts and displays a command-line prompt. Cloud Shell is a shell environment with the Google Cloud CLI already installed and with values already set for your current project. It can take a few seconds for the session to initialize.

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

   bq update \
   --expiration integer \
   project_id:dataset.table
   

   Replace the following:

   • integer: the default lifetime (in seconds) for the table. The minimum value is 3600 seconds (one hour). The expiration time evaluates to the current time plus the integer value. If you specify 0, the table expiration is removed, and the table never expires. Tables with no expiration must be manually deleted.
   • project_id: your project ID.
   • dataset: the name of the dataset that contains the table you're updating.
   • table: the name of the table you're updating.

   Examples:

   To update the expiration time of the mytable table in the mydataset dataset to 5 days (432000 seconds), enter the following command. The mydataset dataset is in your default project.

   bq update --expiration 432000 mydataset.mytable
   

   To update the expiration time of the mytable table in the mydataset dataset to 5 days (432000 seconds), enter the following command. The mydataset dataset is in the myotherproject project, not your default project.

   bq update --expiration 432000 myotherproject:mydataset.mytable
   

API

Call the tables.patch method and use the expirationTime property in the table resource to update the table expiration in milliseconds. Because the tables.update method replaces the entire table resource, the tables.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"
)

// updateTableExpiration demonstrates setting the table expiration of a table to a specific point in time
// in the future, at which time it will be deleted.
func updateTableExpiration(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()

	tableRef := client.Dataset(datasetID).Table(tableID)
	meta, err := tableRef.Metadata(ctx)
	if err != nil {
		return err
	}
	update := bigquery.TableMetadataToUpdate{
		ExpirationTime: time.Now().Add(time.Duration(5*24) * time.Hour), // table expiration in 5 days.
	}
	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.Table;
import java.util.concurrent.TimeUnit;

public class UpdateTableExpiration {

  public static void runUpdateTableExpiration() {
    // TODO(developer): Replace these variables before running the sample.
    String datasetName = "MY_DATASET_NAME";
    String tableName = "MY_TABLE_NAME";
    // Update table expiration to one day.
    Long newExpiration = TimeUnit.MILLISECONDS.convert(1, TimeUnit.DAYS);
    updateTableExpiration(datasetName, tableName, newExpiration);
  }

  public static void updateTableExpiration(
      String datasetName, String tableName, Long newExpiration) {
    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(datasetName, tableName);
      bigquery.update(table.toBuilder().setExpirationTime(newExpiration).build());

      System.out.println("Table expiration updated successfully to " + newExpiration);
    } catch (BigQueryException e) {
      System.out.println("Table 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');
const bigquery = new BigQuery();

async function updateTableExpiration() {
  // Updates a table's expiration.

  /**
   * TODO(developer): Uncomment the following lines before running the sample.
   */
  // const datasetId = 'my_dataset', // Existing dataset
  // const tableId = 'my_table', // Existing table
  // const expirationTime = Date.now() + 1000 * 60 * 60 * 24 * 5 // 5 days from current time in ms

  // Retreive current table metadata
  const table = bigquery.dataset(datasetId).table(tableId);
  const [metadata] = await table.getMetadata();

  // Set new table expiration to 5 days from current time
  metadata.expirationTime = expirationTime.toString();
  const [apiResponse] = await table.setMetadata(metadata);

  const newExpirationTime = apiResponse.expirationTime;
  console.log(`${tableId} 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 Table.expires property and call Client.update_table() to send the update to the API.

# Copyright 2022 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import datetime


def update_table_expiration(table_id, expiration):
    orig_table_id = table_id
    orig_expiration = expiration

    from google.cloud import bigquery

    client = bigquery.Client()

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

    # TODO(dev): Set table to expire for desired days days from now.
    expiration = datetime.datetime.now(datetime.timezone.utc) + datetime.timedelta(
        days=5
    )

    table_id = orig_table_id
    expiration = orig_expiration

    table = client.get_table(table_id)  # Make an API request.
    table.expires = expiration
    table = client.update_table(table, ["expires"])  # API request

    print(f"Updated {table_id}, expires {table.expires}.")

To update the default dataset partition expiration time:

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.Dataset;
import java.util.concurrent.TimeUnit;

// Sample to update partition expiration on a dataset.
public class UpdateDatasetPartitionExpiration {

  public static void main(String[] args) {
    // TODO(developer): Replace these variables before running the sample.
    String datasetName = "MY_DATASET_NAME";
    // Set the default partition expiration (applies to new tables, only) in
    // milliseconds. This example sets the default expiration to 90 days.
    Long newExpiration = TimeUnit.MILLISECONDS.convert(90, TimeUnit.DAYS);
    updateDatasetPartitionExpiration(datasetName, newExpiration);
  }

  public static void updateDatasetPartitionExpiration(String datasetName, Long newExpiration) {
    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().setDefaultPartitionExpirationMs(newExpiration).build());
      System.out.println(
          "Dataset default partition expiration updated successfully to " + newExpiration);
    } catch (BigQueryException e) {
      System.out.println("Dataset partition expiration was not updated \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.

# Copyright 2019 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.


def update_dataset_default_partition_expiration(dataset_id: str) -> None:

    from google.cloud import 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.

    # Set the default partition expiration (applies to new tables, only) in
    # milliseconds. This example sets the default expiration to 90 days.
    dataset.default_partition_expiration_ms = 90 * 24 * 60 * 60 * 1000

    dataset = client.update_dataset(
        dataset, ["default_partition_expiration_ms"]
    )  # Make an API request.

    print(
        "Updated dataset {}.{} with new default partition expiration {}".format(
            dataset.project, dataset.dataset_id, dataset.default_partition_expiration_ms
        )
    )

Update a table's rounding mode

You can update a table's default rounding mode by using the ALTER TABLE SET OPTIONS DDL statement. The following example updates the default rounding mode for mytable to ROUND_HALF_EVEN:

ALTER TABLE mydataset.mytable
SET OPTIONS (
  default_rounding_mode = "ROUND_HALF_EVEN");

When you add a NUMERIC or BIGNUMERIC field to a table and do not specify a rounding mode, then the rounding mode is automatically set to the table's default rounding mode. Changing a table's default rounding mode doesn't alter the rounding mode of existing fields.

Update a table's schema definition

For more information about updating a table's schema definition, see Modifying table schemas.

Rename a table

You can rename a table after it has been created by using the ALTER TABLE RENAME TO statement. The following example renames mytable to mynewtable:

ALTER TABLE mydataset.mytable
RENAME TO mynewtable;

Limitations on renaming tables

• If you want to rename a table that has data streaming into it, you must stop the streaming, commit any pending streams, and wait for BigQuery to indicate that streaming is not in use.
• While a table can usually be renamed 5 hours after the last streaming operation, it might take longer.
• Existing table ACLs and row access policies are preserved, but table ACL and row access policy updates made during the table rename are not preserved.
• You can't concurrently rename a table and run a DML statement on that table.
• Renaming a table removes all Data Catalog tags on the table.
• You can't rename external tables.

Copy a table

This section describes how to create a full copy of a table. For information about other types of table copies, see table clones and table snapshots.

You can copy a table in the following ways:

• Use the Google Cloud console.
• Use the bq cp command.
• Use a data definition language (DDL) CREATE TABLE COPY statement.
• Call the jobs.insert API method and configure a copy job.
• Use the client libraries.

Limitations on copying tables

Table copy jobs are subject to the following limitations:

• When you copy a table, the name of the destination table must adhere to the same naming conventions as when you create a table.
• Table copies are subject to BigQuery limits on copy jobs.
• The Google Cloud console supports copying only one table at a time. You can't overwrite an existing table in the destination dataset. The table must have a unique name in the destination dataset.
• Copying multiple source tables into a destination table is not supported by the Google Cloud console.

• When copying multiple source tables to a destination table using the API, bq command-line tool, or the client libraries, all source tables must have identical schemas, including any partitioning or clustering.

  Certain table schema updates, such as dropping or renaming columns, can cause tables to have apparently identical schemas but different internal representations. This might cause a table copy job to fail with the error Maximum limit on diverging physical schemas reached. In this case, you can use the CREATE TABLE LIKE statement to ensure that your source table's schema matches the destination table's schema exactly.

• The time that BigQuery takes to copy tables might vary significantly across different runs because the underlying storage is managed dynamically.

• You can't copy and append a source table to a destination table that has more columns than the source table, and the additional columns have default values. Instead, you can run INSERT destination_table SELECT * FROM source_table to copy over the data.

• If the copy operation overwrites an existing table, then the table-level access for the existing table is maintained. Tags from the source table aren't copied to the overwritten table, while tags on the existing table are retained. However, when you copy tables across regions, tags on the existing table are removed.

• If the copy operation creates a new table, then the table-level access for the new table is determined by the access policies of the dataset in which the new table is created. Additionally, tags are copied from the source table to the new table.

• When you copy multiple source tables to a destination table, all source tables must have identical tags.

Required roles

To perform the tasks in this document, you need the following permissions.

Roles to copy tables and partitions

To get the permissions that you need to copy tables and partitions, ask your administrator to grant you the Data Editor (roles/bigquery.dataEditor) IAM role on the source and destination datasets. For more information about granting roles, see Manage access to projects, folders, and organizations.

This predefined role contains the permissions required to copy tables and partitions. To see the exact permissions that are required, expand the Required permissions section:

Required permissions

The following permissions are required to copy tables and partitions:

• bigquery.tables.getData on the source and destination datasets
• bigquery.tables.get on the source and destination datasets
• bigquery.tables.create on the destination dataset
• bigquery.tables.update on the destination dataset

You might also be able to get these permissions with custom roles or other predefined roles.

Permission to run a copy job

To get the permission that you need to run a copy job, ask your administrator to grant you the Job User (roles/bigquery.jobUser) IAM role on the source and destination datasets. For more information about granting roles, see Manage access to projects, folders, and organizations.

This predefined role contains the bigquery.jobs.create permission, which is required to run a copy job.

You might also be able to get this permission with custom roles or other predefined roles.

Copy a single source table

You can copy a single table in the following ways:

• Using the Google Cloud console.
• Using the bq command-line tool's bq cp command.
• Using a data definition language (DDL) CREATE TABLE COPY statement.
• Calling the jobs.insert API method, configuring a copy job, and specifying the sourceTable property.
• Using the client libraries.

The Google Cloud console and the CREATE TABLE COPY statement support only one source table and one destination table in a copy job. To copy multiple source files to a destination table, you must use the bq command-line tool or the API.

To copy a single source table:

Console

1. In the Explorer panel, expand your project and dataset, then select the table.

2. In the details panel, click Copy table.

3. In the Copy table dialog, under Destination:

   • For Project name, choose the project that will store the copied table.
   • For Dataset name, select the dataset where you want to store the copied table. The source and destination datasets must be in the same location.
   • For Table name, enter a name for the new table. The name must be unique in the destination dataset. You can't overwrite an existing table in the destination dataset using the Google Cloud console. For more information about table name requirements, see Table naming.

4. Click Copy to start the copy job.

SQL

Use the CREATE TABLE COPY statement to copy a table named table1 to a new table named table1copy:

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 myproject.mydataset.table1copy
   COPY myproject.mydataset.table1;
   

3. Click Run.

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

bq

1. In the Google Cloud console, activate Cloud Shell.

   Activate Cloud Shell

   At the bottom of the Google Cloud console, a Cloud Shell session starts and displays a command-line prompt. Cloud Shell is a shell environment with the Google Cloud CLI already installed and with values already set for your current project. It can take a few seconds for the session to initialize.

2. Issue the bq cp command. Optional flags can be used to control the write disposition of the destination table:

   • -a or --append_table appends the data from the source table to an existing table in the destination dataset.
   • -f or --force overwrites an existing table in the destination dataset and doesn't prompt you for confirmation.
   • -n or --no_clobber returns the following error message if the table exists in the destination dataset: Table 'project_id:dataset.table' already exists, skipping. If -n is not specified, the default behavior is to prompt you to choose whether to replace the destination table.
   • --destination_kms_key is the customer-managed Cloud KMS key used to encrypt the destination table.

   --destination_kms_key is not demonstrated here. See Protecting data with Cloud Key Management Service keys for more information.

   If the source or destination dataset is in a project other than your default project, add the project ID to the dataset names in the following format: project_id:dataset.

   (Optional) Supply the --location flag and set the value to your location.

   bq --location=location cp \
   -a -f -n \
   project_id:dataset.source_table \
   project_id:dataset.destination_table
   

   Replace the following:

   • location: the name of your location. The --location flag is optional. For example, if you are using BigQuery in the Tokyo region, you can set the flag's value to asia-northeast1. You can set a default value for the location using the .bigqueryrc file.
   • project_id: your project ID.
   • dataset: the name of the source or destination dataset.
   • source_table: the table you're copying.
   • destination_table: the name of the table in the destination dataset.

   Examples:

   To copy the mydataset.mytable table to the mydataset2.mytable2 table, enter the following command. Both datasets are in your default project.

   bq cp mydataset.mytable mydataset2.mytable2
   

   To copy the mydataset.mytable table and to overwrite a destination table with the same name, enter the following command. The source dataset is in your default project. The destination dataset is in the myotherproject project. The -f shortcut is used to overwrite the destination table without a prompt.

   bq cp -f \
   mydataset.mytable \
   myotherproject:myotherdataset.mytable
   

   To copy the mydataset.mytable table and to return an error if the destination dataset contains a table with the same name, enter the following command. The source dataset is in your default project. The destination dataset is in the myotherproject project. The -n shortcut is used to prevent overwriting a table with the same name.

   bq cp -n \
   mydataset.mytable \
   myotherproject:myotherdataset.mytable
   

   To copy the mydataset.mytable table and to append the data to a destination table with the same name, enter the following command. The source dataset is in your default project. The destination dataset is in the myotherproject project. The - a shortcut is used to append to the destination table.

   bq cp -a mydataset.mytable myotherproject:myotherdataset.mytable
   

API

You can copy an existing table through the API by calling the bigquery.jobs.insert method, and configuring a copy job. Specify your location in the location property in the jobReference section of the job resource.

You must specify the following values in your job configuration:

"copy": {
      "sourceTable": {       // Required
        "projectId": string, // Required
        "datasetId": string, // Required
        "tableId": string    // Required
      },
      "destinationTable": {  // Required
        "projectId": string, // Required
        "datasetId": string, // Required
        "tableId": string    // Required
      },
      "createDisposition": string,  // Optional
      "writeDisposition": string,   // Optional
    },

Where sourceTable provides information about the table to be copied, destinationTable provides information about the new table, createDisposition specifies whether to create the table if it doesn't exist, and writeDisposition specifies whether to overwrite or append to an existing table.

C#

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

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

using Google.Apis.Bigquery.v2.Data;
using Google.Cloud.BigQuery.V2;
using System;

public class BigQueryCopyTable
{
    public void CopyTable(
        string projectId = "your-project-id",
        string destinationDatasetId = "your_dataset_id"
    )
    {
        BigQueryClient client = BigQueryClient.Create(projectId);
        TableReference sourceTableRef = new TableReference()
        {
            TableId = "shakespeare",
            DatasetId = "samples",
            ProjectId = "bigquery-public-data"
        };
        TableReference destinationTableRef = client.GetTableReference(
            destinationDatasetId, "destination_table");
        BigQueryJob job = client.CreateCopyJob(
            sourceTableRef, destinationTableRef)
            .PollUntilCompleted() // Wait for the job to complete.
            .ThrowOnAnyError();

        // Retrieve destination table
        BigQueryTable destinationTable = client.GetTable(destinationTableRef);
        Console.WriteLine(
            $"Copied {destinationTable.Resource.NumRows} rows from table "
            + $"{sourceTableRef.DatasetId}.{sourceTableRef.TableId} "
            + $"to {destinationTable.FullyQualifiedId}."
        );
    }
}

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"
)

// copyTable demonstrates copying a table from a source to a destination, and
// allowing the copy to overwrite existing data by using truncation.
func copyTable(projectID, datasetID, srcID, dstID string) error {
	// projectID := "my-project-id"
	// datasetID := "mydataset"
	// srcID := "sourcetable"
	// dstID := "destinationtable"
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, projectID)
	if err != nil {
		return fmt.Errorf("bigquery.NewClient: %v", err)
	}
	defer client.Close()

	dataset := client.Dataset(datasetID)
	copier := dataset.Table(dstID).CopierFrom(dataset.Table(srcID))
	copier.WriteDisposition = bigquery.WriteTruncate
	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.Job;
import com.google.cloud.bigquery.JobInfo;
import com.google.cloud.bigquery.TableId;

public class CopyTable {

  public static void runCopyTable() {
    // 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";

    copyTable(sourceDatasetName, sourceTableId, destinationDatasetName, destinationTableId);
  }

  public static void copyTable(
      String sourceDatasetName,
      String sourceTableId,
      String destinationDatasetName,
      String destinationTableId) {
    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).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 copied successfully.");
    } catch (BigQueryException | InterruptedException e) {
      System.out.println("Table copying job was interrupted. \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 and create a client
const {BigQuery} = require('@google-cloud/bigquery');
const bigquery = new BigQuery();

async function copyTable() {
  // Copies src_dataset:src_table to dest_dataset:dest_table.

  /**
   * TODO(developer): Uncomment the following lines before running the sample
   */
  // const srcDatasetId = "my_src_dataset";
  // const srcTableId = "my_src_table";
  // const destDatasetId = "my_dest_dataset";
  // const destTableId = "my_dest_table";

  // Copy the table contents into another table
  const [job] = await bigquery
    .dataset(srcDatasetId)
    .table(srcTableId)
    .copy(bigquery.dataset(destDatasetId).table(destTableId));

  console.log(`Job ${job.id} completed.`);

  // Check the job's status for errors
  const errors = job.status.errors;
  if (errors && errors.length > 0) {
    throw errors;
  }
}

PHP

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

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

use Google\Cloud\BigQuery\BigQueryClient;
use Google\Cloud\Core\ExponentialBackoff;

/** Uncomment and populate these variables in your code */
// $projectId = 'The Google project ID';
// $datasetId = 'The BigQuery dataset ID';
// $sourceTableId   = 'The BigQuery table ID to copy from';
// $destinationTableId = 'The BigQuery table ID to copy to';

$bigQuery = new BigQueryClient([
    'projectId' => $projectId,
]);
$dataset = $bigQuery->dataset($datasetId);
$sourceTable = $dataset->table($sourceTableId);
$destinationTable = $dataset->table($destinationTableId);
$copyConfig = $sourceTable->copy($destinationTable);
$job = $sourceTable->runJob($copyConfig);

// poll the job until it is complete
$backoff = new ExponentialBackoff(10);
$backoff->execute(function () use ($job) {
    print('Waiting for job to complete' . PHP_EOL);
    $job->reload();
    if (!$job->isComplete()) {
        throw new Exception('Job has not yet completed', 500);
    }
});
// check if the job has errors
if (isset($job->info()['status']['errorResult'])) {
    $error = $job->info()['status']['errorResult']['message'];
    printf('Error running job: %s' . PHP_EOL, $error);
} else {
    print('Table copied successfully' . PHP_EOL);
}

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.

from google.cloud import bigquery

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

# TODO(developer): Set source_table_id to the ID of the original table.
# source_table_id = "your-project.source_dataset.source_table"

# TODO(developer): Set destination_table_id to the ID of the destination table.
# destination_table_id = "your-project.destination_dataset.destination_table"

job = client.copy_table(source_table_id, destination_table_id)
job.result()  # Wait for the job to complete.

print("A copy of the table created.")

Copy multiple source tables

You can copy multiple source tables to a destination table in the following ways:

• Using the bq command-line tool's bq cp command.
• Calling the jobs.insert method, configuring a copy job, and specifying the sourceTables property.
• Using the client libraries.

All source tables must have identical schemas and tags, and only one destination table is allowed.

Source tables must be specified as a comma-separated list. You can't use wildcards when you copy multiple source tables.

To copy multiple source tables, select one of the following choices:

bq

1. In the Google Cloud console, activate Cloud Shell.

   Activate Cloud Shell

   At the bottom of the Google Cloud console, a Cloud Shell session starts and displays a command-line prompt. Cloud Shell is a shell environment with the Google Cloud CLI already installed and with values already set for your current project. It can take a few seconds for the session to initialize.

2. Issue the bq cp command and include multiple source tables as a comma-separated list. Optional flags can be used to control the write disposition of the destination table:

   • -a or --append_table appends the data from the source tables to an existing table in the destination dataset.
   • -f or --force overwrites an existing destination table in the destination dataset and doesn't prompt you for confirmation.
   • -n or --no_clobber returns the following error message if the table exists in the destination dataset: Table 'project_id:dataset.table' already exists, skipping. If -n is not specified, the default behavior is to prompt you to choose whether to replace the destination table.
   • --destination_kms_key is the customer-managed Cloud Key Management Service key used to encrypt the destination table.

   --destination_kms_key is not demonstrated here. See Protecting data with Cloud Key Management Service keys for more information.

   If the source or destination dataset is in a project other than your default project, add the project ID to the dataset names in the following format: project_id:dataset.

   (Optional) Supply the --location flag and set the value to your location.

   bq --location=location cp \
   -a -f -n \
   project_id:dataset.source_table,project_id:dataset.source_table \
   project_id:dataset.destination_table
   

   Replace the following:

   • location: the name of your location. The --location flag is optional. For example, if you are using BigQuery in the Tokyo region, you can set the flag's value to asia-northeast1. You can set a default value for the location using the .bigqueryrc file.
   • project_id: your project ID.
   • dataset: the name of the source or destination dataset.
   • source_table: the table that you're copying.
   • destination_table: the name of the table in the destination dataset.

   Examples:

   To copy the mydataset.mytable table and the mydataset.mytable2 table to mydataset2.tablecopy table, enter the following command . All datasets are in your default project.

   bq cp \
   mydataset.mytable,mydataset.mytable2 \
   mydataset2.tablecopy
   

   To copy the mydataset.mytable table and the mydataset.mytable2 table to myotherdataset.mytable table and to overwrite a destination table with the same name, enter the following command. The destination dataset is in the myotherproject project, not your default project. The -f shortcut is used to overwrite the destination table without a prompt.

   bq cp -f \
   mydataset.mytable,mydataset.mytable2 \
   myotherproject:myotherdataset.mytable
   

   To copy the myproject:mydataset.mytable table and the myproject:mydataset.mytable2 table and to return an error if the destination dataset contains a table with the same name, enter the following command. The destination dataset is in the myotherproject project. The -n shortcut is used to prevent overwriting a table with the same name.

   bq cp -n \
   myproject:mydataset.mytable,myproject:mydataset.mytable2 \
   myotherproject:myotherdataset.mytable
   

   To copy the mydataset.mytable table and the mydataset.mytable2 table and to append the data to a destination table with the same name, enter the following command. The source dataset is in your default project. The destination dataset is in the myotherproject project. The -a shortcut is used to append to the destination table.

   bq cp -a \
   mydataset.mytable,mydataset.mytable2 \
   myotherproject:myotherdataset.mytable
   

API

To copy multiple tables using the API, call the jobs.insert method, configure a table copy job, and specify the sourceTables property.

Specify your region in the location property in the jobReference section of the job resource.

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"
)

// copyMultiTable demonstrates using a copy job to copy multiple source tables into a single destination table.
func copyMultiTable(projectID, srcDatasetID string, srcTableIDs []string, dstDatasetID, dstTableID string) error {
	// projectID := "my-project-id"
	// srcDatasetID := "sourcedataset"
	// srcTableIDs := []string{"table1","table2"}
	// dstDatasetID = "destinationdataset"
	// dstTableID = "destinationtable"
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, projectID)
	if err != nil {
		return fmt.Errorf("bigquery.NewClient: %v", err)
	}
	defer client.Close()

	srcDataset := client.Dataset(srcDatasetID)
	dstDataset := client.Dataset(dstDatasetID)
	var tableRefs []*bigquery.Table
	for _, v := range srcTableIDs {
		tableRefs = append(tableRefs, srcDataset.Table(v))
	}
	copier := dstDataset.Table(dstTableID).CopierFrom(tableRefs...)
	copier.WriteDisposition = bigquery.WriteTruncate
	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.Job;
import com.google.cloud.bigquery.JobInfo;
import com.google.cloud.bigquery.TableId;
import java.util.Arrays;

public class CopyMultipleTables {

  public static void runCopyMultipleTables() {
    // TODO(developer): Replace these variables before running the sample.
    String destinationDatasetName = "MY_DATASET_NAME";
    String destinationTableId = "MY_TABLE_NAME";
    copyMultipleTables(destinationDatasetName, destinationTableId);
  }

  public static void copyMultipleTables(String destinationDatasetName, String destinationTableId) {
    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 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,
                  Arrays.asList(
                      TableId.of(destinationDatasetName, "table1"),
                      TableId.of(destinationDatasetName, "table2")))
              .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 tables due to an error: \n" + job.getStatus().getError());
        return;
      }
      System.out.println("Table copied successfully.");
    } catch (BigQueryException | InterruptedException e) {
      System.out.println("Table copying job was interrupted. \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');
const bigquery = new BigQuery();

async function copyTableMultipleSource() {
  // Copy multiple source tables to a given destination.

  /**
   * TODO(developer): Uncomment the following lines before running the sample.
   */
  // const datasetId = "my_dataset";
  // sourceTable = 'my_table';
  // destinationTable = 'testing';

  // Create a client
  const dataset = bigquery.dataset(datasetId);

  const metadata = {
    createDisposition: 'CREATE_NEVER',
    writeDisposition: 'WRITE_TRUNCATE',
  };

  // Create table references
  const table = dataset.table(sourceTable);
  const yourTable = dataset.table(destinationTable);

  // Copy table
  const [apiResponse] = await table.copy(yourTable, metadata);
  console.log(apiResponse.configuration.copy);
}

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.

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 table_ids to the list of the IDs of the original tables.
# table_ids = ["your-project.your_dataset.your_table_name", ...]

job = client.copy_table(table_ids, dest_table_id)  # Make an API request.
job.result()  # Wait for the job to complete.

print("The tables {} have been appended to {}".format(table_ids, dest_table_id))

Copy tables across regions

Preview

This product or feature is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of the Service Specific Terms. Pre-GA products and features are available "as is" and might have limited support. For more information, see the launch stage descriptions.

You can copy a table, table snapshot, or table clone from one BigQuery region or multi-region to another. This includes any tables that have customer-managed Cloud KMS (CMEK) applied. Doing so incurs additional charges according to BigQuery pricing.

To copy a table across regions, select one of the following options:

bq

1. In the Google Cloud console, activate Cloud Shell.

   Activate Cloud Shell

   At the bottom of the Google Cloud console, a Cloud Shell session starts and displays a command-line prompt. Cloud Shell is a shell environment with the Google Cloud CLI already installed and with values already set for your current project. It can take a few seconds for the session to initialize.

2. Run the bq cp command:

   bq cp \
   -f -n \
   SOURCE_PROJECT:SOURCE_DATASET.SOURCE_TABLE \
   DESTINATION_PROJECT:DESTINATION_DATASET.DESTINATION_TABLE
   

Replace the following:

• SOURCE_PROJECT: source project ID. If the source dataset is in a project other than your default project, add the project ID to the source dataset name.

• DESTINATION_PROJECT: destination project ID. If the destination dataset is in a project other than your default project, add the project ID to the destination dataset name.

• SOURCE_DATASET: the name of the source dataset.

• DESTINATION_DATASET: the name of the destination dataset.

• SOURCE_TABLE: the table that you are copying.

• DESTINATION_TABLE: the name of the table in the destination dataset.

  Examples:

  To copy the mydataset_us.mytable table from the us multi-region to the mydataset_eu.mytable2 table in the eu multi-region, enter the following command. Both datasets are in your default project.

  bq cp --sync=false mydataset_us.mytable mydataset_eu.mytable2
  

  To copy a CMEK enabled table, you can either create a key using Cloud KMS and specify the key in the bq cp command or use a destination dataset with default CMEK configured. The following example specifies the destination CMEK in the bq cp command.

  bq cp --destination_kms_key=projects/testing/locations/us/keyRings/us_key/cryptoKeys/eu_key mydataset_us.mytable mydataset_eu.mytable2
  

API

To copy a table across regions using the API, call the jobs.insert method and configure a table copy job.

Specify your region in the location property in the jobReference section of the job resource.

C#

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

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

using Google.Apis.Bigquery.v2.Data;
using Google.Cloud.BigQuery.V2;
using System;

public class BigQueryCopyTable
{
    public void CopyTable(
        string projectId = "your-project-id",
        string destinationDatasetId = "your_dataset_id"
    )
    {
        BigQueryClient client = BigQueryClient.Create(projectId);
        TableReference sourceTableRef = new TableReference()
        {
            TableId = "shakespeare",
            DatasetId = "samples",
            ProjectId = "bigquery-public-data"
        };
        TableReference destinationTableRef = client.GetTableReference(
            destinationDatasetId, "destination_table");
        BigQueryJob job = client.CreateCopyJob(
            sourceTableRef, destinationTableRef)
            .PollUntilCompleted() // Wait for the job to complete.
            .ThrowOnAnyError();

        // Retrieve destination table
        BigQueryTable destinationTable = client.GetTable(destinationTableRef);
        Console.WriteLine(
            $"Copied {destinationTable.Resource.NumRows} rows from table "
            + $"{sourceTableRef.DatasetId}.{sourceTableRef.TableId} "
            + $"to {destinationTable.FullyQualifiedId}."
        );
    }
}

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"
)

// copyTable demonstrates copying a table from a source to a destination, and
// allowing the copy to overwrite existing data by using truncation.
func copyTable(projectID, datasetID, srcID, dstID string) error {
	// projectID := "my-project-id"
	// datasetID := "mydataset"
	// srcID := "sourcetable"
	// dstID := "destinationtable"
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, projectID)
	if err != nil {
		return fmt.Errorf("bigquery.NewClient: %v", err)
	}
	defer client.Close()

	dataset := client.Dataset(datasetID)
	copier := dataset.Table(dstID).CopierFrom(dataset.Table(srcID))
	copier.WriteDisposition = bigquery.WriteTruncate
	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.Job;
import com.google.cloud.bigquery.JobInfo;
import com.google.cloud.bigquery.TableId;

public class CopyTable {

  public static void runCopyTable() {
    // 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";

    copyTable(sourceDatasetName, sourceTableId, destinationDatasetName, destinationTableId);
  }

  public static void copyTable(
      String sourceDatasetName,
      String sourceTableId,
      String destinationDatasetName,
      String destinationTableId) {
    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).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 copied successfully.");
    } catch (BigQueryException | InterruptedException e) {
      System.out.println("Table copying job was interrupted. \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 and create a client
const {BigQuery} = require('@google-cloud/bigquery');
const bigquery = new BigQuery();

async function copyTable() {
  // Copies src_dataset:src_table to dest_dataset:dest_table.

  /**
   * TODO(developer): Uncomment the following lines before running the sample
   */
  // const srcDatasetId = "my_src_dataset";
  // const srcTableId = "my_src_table";
  // const destDatasetId = "my_dest_dataset";
  // const destTableId = "my_dest_table";

  // Copy the table contents into another table
  const [job] = await bigquery
    .dataset(srcDatasetId)
    .table(srcTableId)
    .copy(bigquery.dataset(destDatasetId).table(destTableId));

  console.log(`Job ${job.id} completed.`);

  // Check the job's status for errors
  const errors = job.status.errors;
  if (errors && errors.length > 0) {
    throw errors;
  }
}

PHP

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

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

use Google\Cloud\BigQuery\BigQueryClient;
use Google\Cloud\Core\ExponentialBackoff;

/** Uncomment and populate these variables in your code */
// $projectId = 'The Google project ID';
// $datasetId = 'The BigQuery dataset ID';
// $sourceTableId   = 'The BigQuery table ID to copy from';
// $destinationTableId = 'The BigQuery table ID to copy to';

$bigQuery = new BigQueryClient([
    'projectId' => $projectId,
]);
$dataset = $bigQuery->dataset($datasetId);
$sourceTable = $dataset->table($sourceTableId);
$destinationTable = $dataset->table($destinationTableId);
$copyConfig = $sourceTable->copy($destinationTable);
$job = $sourceTable->runJob($copyConfig);

// poll the job until it is complete
$backoff = new ExponentialBackoff(10);
$backoff->execute(function () use ($job) {
    print('Waiting for job to complete' . PHP_EOL);
    $job->reload();
    if (!$job->isComplete()) {
        throw new Exception('Job has not yet completed', 500);
    }
});
// check if the job has errors
if (isset($job->info()['status']['errorResult'])) {
    $error = $job->info()['status']['errorResult']['message'];
    printf('Error running job: %s' . PHP_EOL, $error);
} else {
    print('Table copied successfully' . PHP_EOL);
}

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.

from google.cloud import bigquery

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

# TODO(developer): Set source_table_id to the ID of the original table.
# source_table_id = "your-project.source_dataset.source_table"

# TODO(developer): Set destination_table_id to the ID of the destination table.
# destination_table_id = "your-project.destination_dataset.destination_table"

job = client.copy_table(source_table_id, destination_table_id)
job.result()  # Wait for the job to complete.

print("A copy of the table created.")

Limitations

Copying a table across regions is subject to the following limitations:

• You can't copy a table using the Google Cloud console or the TABLE COPY DDL statement.
• You can't copy a table if there are any policy tags on the source table.
• You can't copy a table if the source table is larger than 20 physical TiB. See get information about tables for the source table physical size.
• You can't copy IAM policies associated with the tables. You can apply the same policies to the destination after the copy is completed.
• If the copy operation overwrites an existing table, tags on the existing table are removed.
• You can't copy multiple source tables into a single destination table.
• You can't copy tables in append mode.
• Time travel information is not copied to the destination region.
• Table clones are converted to a full copy at the destination region.

View current quota usage

You can view your current usage of query, load, extract, or copy jobs by running an INFORMATION_SCHEMA query to view metadata about the jobs ran over a specified time period. You can compare your current usage against the quota limit to determine your quota usage for a particular type of job. The following example query uses the INFORMATION_SCHEMA.JOBS view to list the number of query, load, extract, and copy jobs by project:

SELECT
  sum(case  when job_type="QUERY" then 1 else 0 end) as QRY_CNT,
  sum(case  when job_type="LOAD" then 1 else 0 end) as LOAD_CNT,
  sum(case  when job_type="EXTRACT" then 1 else 0 end) as EXT_CNT,
  sum(case  when job_type="COPY" then 1 else 0 end) as CPY_CNT
FROM `region-eu`.INFORMATION_SCHEMA.JOBS_BY_PROJECT
WHERE date(creation_time)= CURRENT_DATE()

Note: The INFORMATION_SCHEMA view does not display cross-region copy jobs.

To view the quota limits for copy jobs, see Quotas and limits - Copy jobs.

Delete tables

You can delete a table in the following ways:

• Using the Google Cloud console.
• Using a data definition language (DDL) DROP TABLE statement.
• Using the bq command-line tool bq rm command.
• Calling the tables.delete API method.
• Using the client libraries.

To delete all of the tables in the dataset, delete the dataset.

When you delete a table, any data in the table is also deleted. To automatically delete tables after a specified period of time, set the default table expiration for the dataset or set the expiration time when you create the table.

Deleting a table also deletes any permissions associated with this table. When you recreate a deleted table, you must also manually reconfigure any access permissions previously associated with it.

Required roles

To get the permissions that you need to delete a table, ask your administrator to grant you the Data Editor (roles/bigquery.dataEditor) IAM role on the dataset. For more information about granting roles, see Manage access to projects, folders, and organizations.

This predefined role contains the permissions required to delete a table. To see the exact permissions that are required, expand the Required permissions section:

Required permissions

The following permissions are required to delete a table:

• bigquery.tables.delete
• bigquery.tables.get

You might also be able to get these permissions with custom roles or other predefined roles.

Delete a table

To delete a table:

Console

1. In the Explorer panel, expand your project and dataset, then select the table.

2. In the details panel, click Delete table.

3. Type "delete" in the dialog, then click Delete to confirm.

SQL

Use the DROP TABLE statement. The following example deletes a table named mytable:

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

   Go to BigQuery

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

   DROP TABLE mydataset.mytable;
   

3. Click Run.

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

bq

1. In the Google Cloud console, activate Cloud Shell.

   Activate Cloud Shell

   At the bottom of the Google Cloud console, a Cloud Shell session starts and displays a command-line prompt. Cloud Shell is a shell environment with the Google Cloud CLI already installed and with values already set for your current project. It can take a few seconds for the session to initialize.

2. Use the bq rm command with the --table flag (or -t shortcut) to delete a table. When you use the bq command-line tool to remove a table, you must confirm the action. You can use the --force flag (or -f shortcut) to skip confirmation.

   If the table is in 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.

   bq rm \
   -f \
   -t \
   project_id:dataset.table
   

   Replace the following:

   • project_id: your project ID
   • dataset: the name of the dataset that contains the table
   • table: the name of the table that you're deleting

   Examples:

   To delete the mytable table from the mydataset dataset, enter the following command. The mydataset dataset is in your default project.

   bq rm -t mydataset.mytable
   

   To delete the mytable table from the mydataset dataset, enter the following command. The mydataset dataset is in the myotherproject project, not your default project.

   bq rm -t myotherproject:mydataset.mytable
   

   To delete the mytable table from the mydataset dataset, enter the following command. The mydataset dataset is in your default project. The command uses the -f shortcut to bypass confirmation.

   bq rm -f -t mydataset.mytable
   

   Note: You can enter the bq ls dataset command in the bq command-line tool to confirm that a table was removed from a dataset.

API

Call the tables.delete API method and specify the table to delete using the tableId parameter.

C#

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

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

using Google.Cloud.BigQuery.V2;
using System;

public class BigQueryDeleteTable
{
    public void DeleteTable(
        string projectId = "your-project-id",
        string datasetId = "your_dataset_id",
        string tableId = "your_table_id"
    )
    {
        BigQueryClient client = BigQueryClient.Create(projectId);
        client.DeleteTable(datasetId, tableId);
        Console.WriteLine($"Table {tableId} deleted.");
    }
}

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"
)

// deleteTable demonstrates deletion of a BigQuery table.
func deleteTable(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()

	table := client.Dataset(datasetID).Table(tableID)
	if err := table.Delete(ctx); 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.TableId;

public class DeleteTable {

  public static void runDeleteTable() {
    // TODO(developer): Replace these variables before running the sample.
    String datasetName = "MY_DATASET_NAME";
    String tableName = "MY_TABLE_NAME";
    deleteTable(datasetName, tableName);
  }

  public static void deleteTable(String datasetName, String tableName) {
    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();
      boolean success = bigquery.delete(TableId.of(datasetName, tableName));
      if (success) {
        System.out.println("Table deleted successfully");
      } else {
        System.out.println("Table was not found");
      }
    } catch (BigQueryException e) {
      System.out.println("Table was not deleted. \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');
const bigquery = new BigQuery();

async function deleteTable() {
  // Deletes "my_table" from "my_dataset".

  /**
   * TODO(developer): Uncomment the following lines before running the sample.
   */
  // const datasetId = "my_dataset";
  // const tableId = "my_table";

  // Delete the table
  await bigquery
    .dataset(datasetId)
    .table(tableId)
    .delete();

  console.log(`Table ${tableId} deleted.`);
}

PHP

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

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

use Google\Cloud\BigQuery\BigQueryClient;

/** Uncomment and populate these variables in your code */
// $projectId = 'The Google project ID';
// $datasetId = 'The BigQuery dataset ID';
// $tableId = 'The BigQuery table ID';

$bigQuery = new BigQueryClient([
    'projectId' => $projectId,
]);
$dataset = $bigQuery->dataset($datasetId);
$table = $dataset->table($tableId);
$table->delete();
printf('Deleted table %s.%s' . PHP_EOL, $datasetId, $tableId);

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.

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 fetch.
# table_id = 'your-project.your_dataset.your_table'

# If the table does not exist, delete_table raises
# google.api_core.exceptions.NotFound unless not_found_ok is True.
client.delete_table(table_id, not_found_ok=True)  # Make an API request.
print("Deleted table '{}'.".format(table_id))

Ruby

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

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

require "google/cloud/bigquery"

def delete_table dataset_id = "my_dataset_id", table_id = "my_table_id"
  bigquery = Google::Cloud::Bigquery.new
  dataset  = bigquery.dataset dataset_id
  table    = dataset.table table_id

  table.delete

  puts "Table #{table_id} deleted."
end

Restore deleted tables

You can undelete a table within the time travel window specified for the dataset, including explicit deletions and implicit deletions due to table expiration. You have the ability to configure the time travel window. To undelete an entire dataset, see Undelete datasets.

The time travel window can have a duration between two and seven days. After the time travel window has passed, BigQuery provides a fail-safe period where the deleted data is automatically retained for an additional seven days. Once the fail-safe period has passed, it isn't possible to undelete a table using any method, including opening a support ticket.

When you restore a table from historical data, tags from the source table aren't copied to the destination table.

You can restore a table that was deleted but is still within the time travel window by copying the table to a new table, using the @<time> time decorator. To copy the table, you can use the bq command-line tool or the client libraries:

Console

You can't undelete a table by using the Google Cloud console.

bq

1. In the Google Cloud console, activate Cloud Shell.

   Activate Cloud Shell

   At the bottom of the Google Cloud console, a Cloud Shell session starts and displays a command-line prompt. Cloud Shell is a shell environment with the Google Cloud CLI already installed and with values already set for your current project. It can take a few seconds for the session to initialize.

2. To restore a table, first determine a UNIX timestamp of when the table existed (in milliseconds). You can use the Linux date command to generate the Unix timestamp from a regular timestamp value:

   date -d '2023-08-04 16:00:34.456789Z' +%s000
   

3. Then, use the bq copy command with the @<time> time travel decorator to perform the table copy operation.

   For example, enter the following command to copy the mydataset.mytable table at the time 1418864998000 into a new table mydataset.newtable.

   bq cp mydataset.mytable@1418864998000 mydataset.newtable
   

   (Optional) Supply the --location flag and set the value to your location.

   You can also specify a relative offset. The following example copies the version of a table from one hour ago:

   bq cp mydataset.mytable@-3600000 mydataset.newtable
   

   For more information, see Restore a table from a point in time.

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"
)

// deleteAndUndeleteTable demonstrates how to recover a deleted table by copying it from a point in time
// that predates the deletion event.
func deleteAndUndeleteTable(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()

	ds := client.Dataset(datasetID)
	if _, err := ds.Table(tableID).Metadata(ctx); err != nil {
		return err
	}
	// Record the current time.  We'll use this as the snapshot time
	// for recovering the table.
	snapTime := time.Now()

	// "Accidentally" delete the table.
	if err := client.Dataset(datasetID).Table(tableID).Delete(ctx); err != nil {
		return err
	}

	// Construct the restore-from tableID using a snapshot decorator.
	snapshotTableID := fmt.Sprintf("%s@%d", tableID, snapTime.UnixNano()/1e6)
	// Choose a new table ID for the recovered table data.
	recoverTableID := fmt.Sprintf("%s_recovered", tableID)

	// Construct and run a copy job.
	copier := ds.Table(recoverTableID).CopierFrom(ds.Table(snapshotTableID))
	copier.WriteDisposition = bigquery.WriteTruncate
	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
	}

	ds.Table(recoverTableID).Delete(ctx)
	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.Job;
import com.google.cloud.bigquery.JobInfo;
import com.google.cloud.bigquery.TableId;

// Sample to undeleting a table
public class UndeleteTable {

  public static void runUndeleteTable() {
    // TODO(developer): Replace these variables before running the sample.
    String datasetName = "MY_DATASET_NAME";
    String tableName = "MY_TABLE_TABLE";
    String recoverTableName = "MY_RECOVER_TABLE_TABLE";
    undeleteTable(datasetName, tableName, recoverTableName);
  }

  public static void undeleteTable(String datasetName, String tableName, String recoverTableName) {
    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();

      // "Accidentally" delete the table.
      bigquery.delete(TableId.of(datasetName, tableName));

      // Record the current time.  We'll use this as the snapshot time
      // for recovering the table.
      long snapTime = System.currentTimeMillis();

      // Construct the restore-from tableID using a snapshot decorator.
      String snapshotTableId = String.format("%s@%d", tableName, snapTime);

      // Construct and run a copy job.
      CopyJobConfiguration configuration =
          CopyJobConfiguration.newBuilder(
                  // Choose a new table ID for the recovered table data.
                  TableId.of(datasetName, recoverTableName),
                  TableId.of(datasetName, snapshotTableId))
              .build();

      Job job = bigquery.create(JobInfo.of(configuration));
      job = job.waitFor();
      if (job.isDone() && job.getStatus().getError() == null) {
        System.out.println("Undelete table recovered successfully.");
      } else {
        System.out.println(
            "BigQuery was unable to copy the table due to an error: \n"
                + job.getStatus().getError());
        return;
      }
    } catch (BigQueryException | InterruptedException e) {
      System.out.println("Table not found. \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');
const bigquery = new BigQuery();

async function undeleteTable() {
  // Undeletes "my_table_to_undelete" from "my_dataset".

  /**
   * TODO(developer): Uncomment the following lines before running the sample.
   */
  // const datasetId = "my_dataset";
  // const tableId = "my_table_to_undelete";
  // const recoveredTableId = "my_recovered_table";

  /**
   * TODO(developer): Choose an appropriate snapshot point as epoch milliseconds.
   * For this example, we choose the current time as we're about to delete the
   * table immediately afterwards.
   */
  const snapshotEpoch = Date.now();

  // Delete the table
  await bigquery
    .dataset(datasetId)
    .table(tableId)
    .delete();

  console.log(`Table ${tableId} deleted.`);

  // Construct the restore-from table ID using a snapshot decorator.
  const snapshotTableId = `${tableId}@${snapshotEpoch}`;

  // Construct and run a copy job.
  await bigquery
    .dataset(datasetId)
    .table(snapshotTableId)
    .copy(bigquery.dataset(datasetId).table(recoveredTableId));

  console.log(
    `Copied data from deleted table ${tableId} to ${recoveredTableId}`
  );
}

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.

import time

from google.cloud import bigquery

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

# TODO(developer): Choose a table to recover.
# table_id = "your-project.your_dataset.your_table"

# TODO(developer): Choose a new table ID for the recovered table data.
# recovered_table_id = "your-project.your_dataset.your_table_recovered"

# TODO(developer): Choose an appropriate snapshot point as epoch
# milliseconds. For this example, we choose the current time as we're about
# to delete the table immediately afterwards.
snapshot_epoch = int(time.time() * 1000)

# ...

# "Accidentally" delete the table.
client.delete_table(table_id)  # Make an API request.

# Construct the restore-from table ID using a snapshot decorator.
snapshot_table_id = "{}@{}".format(table_id, snapshot_epoch)

# Construct and run a copy job.
job = client.copy_table(
    snapshot_table_id,
    recovered_table_id,
    # Must match the source and destination tables location.
    location="US",
)  # Make an API request.

job.result()  # Wait for the job to complete.

print(
    "Copied data from deleted table {} to {}".format(table_id, recovered_table_id)
)

If you anticipate that you might want to restore a table later than what is allowed by the time travel window, then create a table snapshot of the table. For more information, see Table snapshots.

Table security

To control access to tables in BigQuery, see Introduction to table access controls.

What's next

• For more information about creating and using tables, see Creating and using tables.
• For more information about handling data, see Working With table data.
• For more information about specifying table schemas, see Specifying a schema.
• For more information about modifying table schemas, see Modifying table schemas.
• For more information about datasets, see Introduction to datasets.
• For more information about views, see Introduction to views.