Managing partitioned tables

This document describes how to manage partitioned tables in BigQuery. Both ingestion-time partitioned and partitioned tables are managed the same way. You can perform the following management tasks for partitioned tables:

• Update a time-partitioned table's:
  • Description
  • Table expiration time
  • Partition expiration time
  • Partition filter requirements
  • Schema definition
  • Labels
• Rename (copy) a time-partitioned table
• Copy a time-partitioned table
• Copy partitions
• Delete a time-partitioned table
• Delete partitions in a time-partitioned table

For more information on creating and using partitioned tables including getting table information, listing tables, and controlling access to table data, see Creating and using ingestion-time partitioned tables or Creating and using partitioned tables.

Updating partitioned table properties

You can update a partitioned table's:

• Description
• Table expiration time
• Partition expiration time
• Schema definition
• Labels

Required permissions

At a minimum, to update table properties, you must be granted bigquery.tables.update and bigquery.tables.get permissions. The following predefined IAM roles include bigquery.tables.update and bigquery.tables.get permissions:

• bigquery.dataEditor
• bigquery.dataOwner
• bigquery.admin

In addition, if a user has bigquery.datasets.create permissions, when that user creates a dataset, they are granted bigquery.dataOwner access to it. bigquery.dataOwner access gives the user the ability to update the properties on tables in that dataset.

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

Updating a partitioned table's description

The process for updating a partitioned table's description is the same as updating a standard table's description. For information on adding or changing a table's description, see Updating a table's description.

Currently, you cannot create descriptions for individual partitions.

Updating the table expiration

The process for updating a partitioned table's expiration is the same as updating a standard table's expiration. For information on adding or changing a table's expiration, see Updating a table's expiration time.

Updating the partition expiration

When you create a table partitioned by ingestion time or date/timestamp column, you can specify a partition expiration. This setting specifies how long BigQuery keeps the data in each partition. The setting applies to all partitions in the table. When a partition expires, BigQuery deletes the data in that partition.

A partition's expiration time is calculated from the partition boundary in UTC. For example, with daily partitioning, the partition boundary is at midnight (00:00:00 UTC). If the table's partition expiration is 6 hours, then each partition expires at 06:00:00 UTC the following day.

You can also specify a default partition expiration at the dataset level. If you set the partition expiration on a table, then the value overrides the default partition expiration. If you don't specify any partition expiration (on the table or dataset), then partitions never expire.

Note: Integer-range partitioned tables do not support partition expiration times.

If you set a table expiration, that value takes precedence over the partition expiration. For example, if the table expiration is set to 5 days, and the partition expiration is set to 7 days, then the table and all partitions in it are deleted after 5 days.

At any point after a table is created, you can update the table's partition expiration. The new setting applies to all partitions in that table, regardless of when they were created. Existing partitions expire immediately if they are older than the new expiration time.

For projects that were created before December 13, 2016, partition expiration is based on the last date that the partition was modified. This behavior applies to both existing and new tables created in the project. To migrate your project to the newer behavior, open a request in the BigQuery issue tracker.

To update a partitioned table's partition expiration:

Console

You cannot update the partition expiration in the Cloud Console.

SQL

Data definition language (DDL) statements allow you to create and modify tables and views using standard SQL query syntax.

See more on Using Data Definition Language statements.

To update a partitioned table's partition expiration by using a DDL statement:

1. Open the BigQuery page in the Cloud Console.

   Go to the BigQuery page

2. Click Compose new query.

3. Type your DDL statement into the Query editor text area.

    ALTER TABLE mydataset.mytable
    SET OPTIONS (
      -- Sets partition expiration to 5 days
      partition_expiration_days=5
    )
    

4. Click Run.

bq

Issue the bq update command with the --time_partitioning_expiration flag. If you are updating a partitioned 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 \
--time_partitioning_expiration integer \
--time_partitioning_type unit_time \
project_id:dataset.table

Where:

• integer is the default lifetime (in seconds) for the table's partitions. There is no minimum value. The expiration time evaluates to the partition's date plus the integer value. If you specify 0, the partition expiration is removed, and the partition never expires. Partitions with no expiration must be manually deleted.
• unit_time is either DAY, HOUR, MONTH, or YEAR, based on the table's partitioning granularity. This value must match the granularity that you set when you created the table.
• project_id is your project ID.
• dataset is the name of the dataset that contains the table you're updating.
• table is the name of the table you're updating.

Examples:

Enter the following command to update the expiration time of partitions in mydataset.mytable to 5 days (432000 seconds). mydataset is in your default project.

bq update --time_partitioning_expiration 432000 mydataset.mytable

Enter the following command to update the expiration time of partitions in mydataset.mytable to 5 days (432000 seconds). mydataset is in myotherproject, not your default project.

bq update \
--time_partitioning_expiration 432000 \
myotherproject:mydataset.mytable

API

Call the tables.patch method and use the timePartitioning.expirationMs property to update the partition expiration in milliseconds. Because the tables.update method replaces the entire table resource, the tables.patch method is preferred.

Updating partition filter requirements

When you create a partitioned table, you can require the use of predicate filters by enabling the Require partition filter option. When this option is applied, attempts to query the partitioned table without specifying a WHERE clause produce the following error: Cannot query over table 'project_id.dataset.table' without a filter that can be used for partition elimination.

For more information on adding the Require partition filter option when you create a partitioned table, see Creating partitioned tables.

If you do not enable the Require partition filter option when you create a partitioned table, you can update the table to add the option.

Updating the require partition filter option

To update a partitioned table to require queries that contain a WHERE clause that prunes partitions:

Console

You cannot use the Cloud Console to require partition filters after a partitioned table is created.

bq

To update a partitioned table to require partition filters by using the bq command-line tool, enter the bq update command and supply the --require_partition_filter flag.

To update a partitioned table in a project other than your default project, add the project ID to the dataset in the following format: project_id:dataset.

For example:

To update mypartitionedtable in mydataset in your default project, enter:

bq update --require_partition_filter mydataset.mytable

To update mypartitionedtable in mydataset in myotherproject, enter:

bq update --require_partition_filter myotherproject:mydataset.mytable

API

Call the tables.patch method and set the requirePartitionFilter property to true to require partition filters. Because the tables.update method replaces the entire table resource, the tables.patch method is preferred.

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.

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

// Sample to update require partition filter on a table.
public class UpdateTableRequirePartitionFilter {

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

  public static void updateTableRequirePartitionFilter(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();

      Table table = bigquery.getTable(datasetName, tableName);
      table.toBuilder().setRequirePartitionFilter(true).build().update();

      System.out.println("Table require partition filter updated successfully");
    } catch (BigQueryException e) {
      System.out.println("Table require partition filter was not updated \n" + e.toString());
    }
  }
}

Updating the schema definition

The process for updating the schema definition for a partitioned table is the same as the process for updating the schema definition of a standard table. For more information, see Modifying table schemas.

Renaming a partitioned table

Currently, you cannot change the name of an existing partitioned table. If you need to change the table name, follow the steps to copy the table. When you specify the destination table in the copy operation, use the new table name.

Copying partitioned tables

Copying a single partitioned table

The process for copying a partitioned table is the same as the process for copying a standard table. For more information, see Copying a table.

When you copy a partitioned table, note the following:

• The source and destination tables must be in datasets in the same location.

• Copying a partitioned table into a new, partitioned destination table

  If you copy a time-partitioned table to a new table, all of the partitioning information is copied with the table. The new table and the old table will have identical partitions.

• Copying a non-partitioned table into a partitioned table

  If you copy a non-partitioned table into a partitioned table, BigQuery copies the source data into the partition that represents the current date.

• Copying a partitioned table to another partitioned table

  To copy a partitioned table into another partitioned table, the partition specifications for the source and destination tables must match. You can specify whether to append or overwrite the destination table.

• Copying a partitioned table into a non-partitioned table

  If you copy a partitioned table into a non-partitioned table, the destination table remains unpartitioned. The data is either appended to the non-partitioned table or used to overwrite the non-partitioned table, depending on your settings.

Copying multiple partitioned tables

The process for copying multiple partitioned tables is the same as the process for copying multiple standard tables. For more information, see Copying multiple source tables.

When you copy multiple partitioned tables, note the following:

• If you copy multiple source tables into a partitioned table in the same job, the source tables can't contain a mixture of partitioned and non-partitioned tables.
• If all of the source tables are partitioned tables, the partition specifications for all source tables must match the destination table's partition specification. Your settings determine whether the destination table is appended or overwritten.
• The source and destination tables must be in datasets in the same location.

Copying partitions

You can copy one or more partitions by:

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

Currently, copying partitions is not supported by the Cloud Console.

Required permissions

At a minimum, to copy tables and partitions, you must be granted the following permissions.

On the source dataset:

• bigquery.tables.get
• bigquery.tables.getData

On the destination dataset:

• bigquery.tables.create to create the copy of the table or partition in the destination dataset

The following predefined IAM roles include bigquery.tables.create, bigquery.tables.get, and bigquery.tables.getData permissions:

• bigquery.dataEditor
• bigquery.dataOwner
• bigquery.admin

Also, to run the copy job, you must be granted bigquery.jobs.create permissions.

The following predefined IAM roles include bigquery.jobs.create permissions:

• bigquery.user
• bigquery.jobUser
• bigquery.admin

In addition, if a user has bigquery.datasets.create permissions, when that user creates a dataset, they are granted bigquery.dataOwner access to it. bigquery.dataOwner access gives the user the ability to copy tables and partitions in the dataset, but access to the destination dataset is required unless the user also created the destination dataset.

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

Copying a single partition

Console

Copying partitions is not supported by the Cloud Console.

bq

To copy a partition, use the bq command-line tool's bq cp (copy) command with a partition decorator ($date) such as $20160201.

Optional flags can be used to control the write disposition of the destination partition:

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

The cp command does not support the --time_partitioning_field or --time_partitioning_type flags. You cannot use a copy job to convert an ingestion-time partitioned table into a partitioned table.

--destination_kms_key is not demonstrated here. See Protecting data with Cloud KMS 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$source_partition \
project_id:dataset.destination_table$destination_partition

Where:

• location is 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 is your project ID.
• dataset is the name of the source or destination dataset.
• source_table is the table you're copying.
• source_partition is the partition decorator of the source partition.
• destination_table is the name of the table in the destination dataset.
• destination_partition is the partition decorator of the destination partition.

Examples:

Note: The partition decorator separator ($) is a special variable in the unix shell. You might have to escape the decorator when you use the command- line tool. The following examples escape the partition decorator: mydataset.table\$20160519, 'mydataset.table$20160519'.

Copying a partition to a new table

Enter the following command to copy the January 30, 2018 partition from mydataset.mytable to a new table — mydataset.mytable2. mydataset is in your default project.

bq cp -a 'mydataset.mytable$20180130' mydataset.mytable2

Copying a partition to a non-partitioned table

Enter the following command to copy the January 30, 2018 partition from mydataset.mytable to a non-partitioned table — mydataset2.mytable2. The -a shortcut is used to append the partition's data to the non-partitioned destination table. Both datasets are in your default project.

bq cp -a 'mydataset.mytable$20180130' mydataset2.mytable2

Enter the following command to copy the January 30, 2018 partition from mydataset.mytable to a non-partitioned table — mydataset2.mytable2. The -f shortcut is used to overwrite the non-partitioned destination table without prompting.

bq --location=US cp -f 'mydataset.mytable$20180130' mydataset2.mytable2

Copying a partition to another partitioned table

Enter the following command to copy the January 30, 2018 partition from mydataset.mytable to another partitioned table — mydataset2.mytable2. The -a shortcut is used to append the partition's data to the destination table. Since no partition decorator is specified on the destination table, the source partition key is preserved and the data is copied to the January 30, 2018 partition in the destination table. You can also specify a partition decorator on the destination table to copy data to a specific partition. mydataset is in your default project. mydataset2 is in myotherproject, not your default project.

bq --location=US cp \
-a \
'mydataset.mytable$20180130' \
myotherproject:mydataset2.mytable2

Enter the following command to copy the January 30, 2018 partition from mydataset.mytable to the February 20, 2018 partition of another partitioned table — mydataset2.mytable2. The -f shortcut is used to overwrite the February 20, 2018 partition in the destination table without prompting. If no partition decorator is used, all data in the destination table is overwritten. mydataset is in your default project. mydataset2 is in myotherproject, not your default project.

bq cp \
-f \
'mydataset.mytable$20180130' \
'myotherproject:mydataset2.mytable2$20180220'

Enter the following command to copy the January 30, 2018 partition from mydataset.mytable to another partitioned table — mydataset2.mytable2. mydataset is in your default project. mydataset2 is in myotherproject, not your default project. If there is data in the destination table, the default behavior is to prompt you to overwrite.

bq cp \
'mydataset.mytable$20180130' \
myotherproject:mydataset2.mytable2

Note: The bq cp command with a partition decorator works on column-based partitions in which the source partition and destination partition are identical. The bq cp command also works on ingestion-time based partitions where the partition represents either the same time unit or a coarser time unit that contains the source partition. For example, if $20180130 is the source partition decorator, valid destination partition decorators include $20180130, $201801, and $2018. To copy a column-based partition to a completely different partition decorator or to a time-unit partition with finer granularity, use an INSERT SELECT statement.

API

Call the jobs.insert method, and configure a copy job. (Optional) Specify your region in the location property in the jobReference section of the job resource.

Specify the following properties in your job configuration:

• Enter the source dataset, table, and partition in the sourceTables property.
• Enter the destination dataset and table in the destinationTable property.
• Use the writeDisposition property to specify whether to append or overwrite the destination table or partition.

Copying multiple partitions

To copy multiple partitions:

Console

Currently, copying partitions is not supported by the Cloud Console.

bq

Copying multiple partitions is the same process as copying a single partition, but you specify multiple source partitions as a comma-separated list:

bq cp \
'mydataset.mytable$20180130,mydataset.mytable$20180131' \
myotherproject:mydataset.mytable2

API

Call the jobs.insert method, and configure a copy job. Specify your region in the location property in the jobReference section of the job resource.

Specify the following properties in your job configuration:

• Enter multiple source partitions (including the dataset and table names) in the sourceTables property.
• Enter the destination dataset and table in the destinationTable property.
• Use the writeDisposition property to specify whether to append or overwrite the destination table or partition.

Deleting a partitioned table

The process for deleting a time-partitioned table and all the partitions in it is the same as the process for deleting a standard table. For information on deleting a table, see Deleting tables.

Deleting partitions in partitioned tables

You can delete partitions in partitioned tables using the bq command-line tool's bq rm command, or by calling the tables.delete API method.

You can use the partition decorator to delete a specific partition. For example, the partition for March 1, 2016 ($20160301) in a partitioned table named mydataset.mytable can be deleted using the command:

bq rm 'mydataset.mytable$20160301'

To retrieve a list of partitions in a partitioned table, see Listing partitions in ingestion-time partitioned tables or Listing partitions in partitioned tables.

Currently, you can only delete one partition at a time.

Required permissions

At a minimum, to delete a partition, you must be granted bigquery.tables.delete and bigquery.tables.get permissions. The following predefined IAM roles include bigquery.tables.delete and bigquery.tables.get permissions:

• bigquery.dataOwner
• bigquery.dataEditor
• bigquery.admin

In addition, if a user has bigquery.datasets.create permissions, when that user creates a dataset, they are granted bigquery.dataOwner access to it. bigquery.dataOwner access gives the user the ability to delete tables and partitions in the dataset.

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

Deleting a partition in a partitioned table

You can delete a partition by specifying the partition's decorator unless it is one of the two special partitions. Currently, you cannot delete the __NULL__ or __UNPARTITIONED__ partitions.

To delete a partition in a partitioned table:

Console

Deleting partitions is not supported by the Cloud Console.

bq

Use the bq rm command with the --table flag (or -t shortcut) and reference the partition decorator ($date) to delete a specific partition in a partitioned table. When you use the bq command-line tool to remove a partition, you must confirm the action. You can use the --force flag (or -f shortcut) to skip confirmation.

If the partitioned 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$date

Where:

• project_id is your project ID.
• dataset is the name of the dataset that contains the table.
• table is the name of the table.
• $date is the partition decorator of the partition you're deleting.

Examples:

Note: The partition decorator separator ($) is a special variable in the unix shell. You might have to escape the decorator when you use the command- line tool. The following examples escape the partition decorator: mydataset.table\$20160519, 'mydataset.table$20160519'.

Enter the following command to delete the partition for March 1, 2016 ($20160301) in a partitioned table named mydataset.mytable. mydataset is in your default project.

bq rm 'mydataset.mytable$20160301'

Enter the following command to delete the partition for January 1, 2017 ($20170101) in a partitioned table named mydataset.mytable. mydataset is in myotherproject, not your default project.

bq rm 'myotherproject:mydataset.mytable$20170101'

Enter the following command to delete the partition for January 18, 2018 ($20180118) in a partitioned table named mydataset.mytable. mydataset is in myotherproject, not your default project. The -f shortcut is used to skip confirmation.

bq rm -f 'myotherproject:mydataset.mytable$20180118'

API

Call the tables.delete method and specify the table and partition decorator using the tableId parameter.