Creating and using ingestion-time partitioned tables

This document describes how to create and use ingestion-time partitioned tables in BigQuery. For information on partitioned tables, see Creating and using partitioned tables.

After creating an ingestion-time partitioned table, you can:

Control access to your table data
Get information about your partitioned tables
List the partitioned tables in a dataset
Get partitioned table metadata using meta-tables

For more information on managing partitioned tables including updating partitioned table properties, copying a partitioned table, and deleting a partitioned table, see Managing partitioned tables.

Creating ingestion-time partitioned tables

You can create an ingestion-time partitioned table in BigQuery:

By using a DDL CREATE TABLE statement with a partition_expression
Manually using the GCP Console, the classic BigQuery web UI, or the command-line tool's bq mk command
Programmatically by calling the tables.insert API method
From query results
When you load data
By converting date-sharded tables into a partitioned tables

When you create an ingestion-time partitioned table in BigQuery, the table name must be unique per dataset. The table name can:

Contain up to 1,024 characters
Contain letters (upper or lower case), numbers, and underscores

Required permissions

To create an ingestion-time partitioned table, you must have WRITER access at the dataset level, or you must be assigned a project-level IAM role that includes bigquery.tables.create permissions. The following predefined, project-level IAM roles include bigquery.tables.create permissions:

bigquery.dataEditor
bigquery.dataOwner
bigquery.admin

In addition, because the bigquery.user role has bigquery.datasets.create permissions, a user assigned to the bigquery.user role can create partitioned tables in any dataset that user creates. When a user assigned to the bigquery.user role creates a dataset, that user is given OWNER access to the dataset. OWNER access to a dataset gives the user full control over it and all the tables in it.

For more information on IAM roles and permissions in BigQuery, see Access control. For more information on dataset-level roles, see Primitive roles for datasets.

Creating an empty ingestion-time partitioned table with a schema definition

When you create an empty time-partitioned table with a schema definition, you can:

Enter the schema by using the GCP Console or the classic BigQuery web UI
Provide the schema inline using the command-line tool
Submit a JSON schema file using the command-line tool
Provide the schema in a table resource when calling the API's tables.insert method.

For more information on specifying a table schema, see Specifying a schema.

After the time-partitioned table is created, you can:

Load data into it
Write query results to it
Copy data into it

To create an empty time-partitioned table with a schema definition:

Console

Select a dataset from the Resources section of the navigation panel. Click Create table on the right side of the window.
On the Create table page, in the Source section, select Create empty table.
On the Create table page, in the Destination section:
- For Dataset name, choose the appropriate dataset.
- In the Table name field, enter the name of the table you're creating in BigQuery.
- Verify that Table type is set to Native table.
In the Schema section, enter the schema definition.
- Enter schema information manually by:
  - Enabling Edit as text and entering the table schema as a JSON array.
    
    Note: You can view the schema of an existing table in JSON format by entering the following CLI command: bq show --format=prettyjson [DATASET].[TABLE].
  - Using Add field to manually input the schema.
In the Partition and cluster settings section:
- For Partitioning, click No partitioning and select Partition by ingestion time.
Click Create table.

After the table is created, you can update the partitioned table's table expiration, description, and labels. You cannot add a partition expiration after a table is created using the BigQuery web UI.

Classic UI

Click the down arrow icon next to your dataset name in the navigation and click Create new table.
On the Create Table page, in the Source Data section, click Create empty table.
On the Create Table page, in the Destination Table section:
- For Table name, choose the appropriate dataset, and in the table name field, enter the name of the table you're creating.
- Verify that Table type is set to Native table.
In the Schema section, manually enter the schema definition.
- You can enter schema information manually by:
  - Clicking Edit as text and entering the table schema as a JSON array:
    
    Note: You can view the schema of an existing table in JSON format by entering the following CLI command: bq show --schema \ --format=prettyjson \ [PROJECT_ID]:[DATASET].[TABLE].
  - Using Add Field to input the schema:
In the Options section:
- For Partitioning, click None and select Day.
- For Encryption Type, leave the Default option. This property is for customer-managed encryption keys. By default, BigQuery encrypts customer content stored at rest.
Click Create Table.

After the table is created, you can update the partitioned table's table expiration, description, and labels. You cannot add a partition expiration after a table is created using the BigQuery web UI.

CLI

Use the mk command with the --table flag (or -t shortcut), and the --time_partitioning_type=DAY flag. Currently, DAY is the only supported value for --time_partitioning_type. You can supply table's schema definition inline or via a JSON schema file. Optional parameters include --expiration, --description, --time_partitioning_expiration, --destination_kms_key, and --label. If you are creating a table in a project other than your default project, add the project ID to the dataset in the following format: [PROJECT_ID]:[DATASET].

--destination_kms_key is not demonstrated here. For more information on using this flag, see customer-managed encryption keys.

Enter the following command to create an empty ingestion-time partitioned table with a schema definition:

bq mk --table \
--expiration [INTEGER1] \
--time_partitioning_type=DAY \
--time_partitioning_expiration [INTEGER2] \
--description "[DESCRIPTION]" \
-label [KEY:VALUE, KEY:VALUE] \
[PROJECT_ID]:[DATASET].[TABLE] \
[SCHEMA]

Where:

[INTEGER1] is the default lifetime (in seconds) for the table. The minimum value is 3600 seconds (one hour). The expiration time evaluates to the current UTC time plus the integer value. If you set the table's expiration time when you create a partitioned table, the dataset's default table expiration setting is ignored. Setting this value deletes the table and all partitions after the specified time.
[INTEGER2] 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. The partition expiration is independent of the table's expiration but does not override it. If you set a partition expiration that is longer than the table's expiration, the table expiration takes precedence.
[DESCRIPTION] is a description of the table in quotes.
[KEY:VALUE] is the key:value pair that represents a label. You can enter multiple labels using a comma-separated list.
[PROJECT_ID] is your project ID.
[DATASET] is a dataset in your project.
[TABLE] is the name of the time-partitioned table you're creating.
[SCHEMA] is an inline schema definition in the format [FIELD]:[DATA_TYPE],[FIELD]:[DATA_TYPE] or the path to the JSON schema file on your local machine.

When you specify the schema on the command line, you cannot include a RECORD (STRUCT) type, you cannot include a column description, and you cannot specify the column's mode. All modes default to NULLABLE. To include descriptions, modes, and RECORD types, supply a JSON schema file instead.

Examples:

Enter the following command to create an ingestion-time partitioned table named mytable in mydataset in your default project. The partitioning expiration is set to 259,200 seconds (3 days), the table's expiration is set to 2,592,000 (1 30-day month), the description is set to This is my time-partitioned table, and the label is set to organization:development. The command uses the -t shortcut instead of --table. The schema is specified inline as: qtr:STRING,sales:FLOAT,year:STRING.

bq mk -t \
--expiration 2592000 \
--time_partitioning_type=DAY \
--time_partitioning_expiration 259200 \
--description "This is my time-partitioned table" \
--label organization:development \
mydataset.mytable \
qtr:STRING,sales:FLOAT,year:STRING

Enter the following command to create a time-partitioned table named mytable in myotherproject, not your default project. The partitioning expiration is set to 259,200 seconds (3 days), the description is set to This is my time-partitioned table, and the label is set to organization:development. The command uses the -t shortcut instead of --table. This command does not specify a table expiration. If the dataset has a default table expiration, it is applied. If the dataset has no default table expiration, the table will never expire, but the partitions will expire in 3 days. The path to the schema file is /tmp/myschema.json.

bq mk -t \
--time_partitioning_type=DAY \
--time_partitioning_expiration 259200 \
--description "This is my time-partitioned table" \
--label organization:development \
myotherproject:mydataset.mytable \
/tmp/myschema.json

After the table is created, you can update the ingestion-time partitioned table's table expiration, partition expiration, description, and labels.

API

Call the tables.insert method with a defined table resource that specifies the timePartitioning property and the schema property.

Creating an ingestion-time partitioned table from a query result

To create a partitioned table from a query result, write the results to a new destination table. You can create a new partitioned table by querying a partitioned table or a non-partitioned table. You cannot change an existing table to a partitioned table using query results.

For more information on querying time-partitioned tables, see Querying partitioned tables.

Console

You cannot specify partitioning options for a destination table when you query data using the console BigQuery web UI.

Classic UI

You cannot specify partitioning options for a destination table when you query data using the classic BigQuery web UI.

CLI

Enter the bq query command, specify the --destination_table flag to create a permanent table based on the query results, and specify the --time_partitioning_type=DAY flag to create an ingestion-time partitioned destination table. Currently, DAY is the only supported value for --time_partitioning_type.

Specify the use_legacy_sql=false flag to use standard SQL syntax. To write the query results to a table that is not in your default project, add the project ID to the dataset name in the following format: [PROJECT_ID]:[DATASET].

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

Enter the following command to create a new, ingestion-time partitioned destination table from a query result:

    bq --location=[LOCATION] query \
    --destination_table [PROJECT_ID]:[DATASET].[TABLE] \
    --time_partitioning_type=DAY \
    --use_legacy_sql=false \
    '[QUERY]'

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 dataset that will contain the new time-partitioned table.
[TABLE] is the name of the time-partitioned table you're creating using the query results.
[QUERY] is a query in standard SQL syntax.

Examples:

Enter the following command to write query results to an ingestion-time partitioned destination table named mytable in mydataset. The dataset is in your default project. The query retrieves data from a non-partitioned table — the USA Name Data public dataset.

bq query \
--destination_table mydataset.mytable \
--time_partitioning_type=DAY \
--use_legacy_sql=false \
'SELECT
   name,
   number
 FROM
   `bigquery-public-data`.usa_names.usa_1910_current
 WHERE
   gender = "M"
 ORDER BY
   number DESC'

Enter the following command to write query results to an ingestion-time partitioned destination table named mytable in mydataset. The dataset is in myotherproject, not your default project. The query retrieves data from a non-partitioned table — the USA Name Data public dataset.

bq query \
--destination_table myotherproject:mydataset.mytable \
--time_partitioning_type=DAY \
--use_legacy_sql=false \
'SELECT
   name,
   number
 FROM
   `bigquery-public-data`.usa_names.usa_1910_current
 WHERE
   gender = "M"
 ORDER BY
   number DESC'

API

To save query results to a permanent, ingestion-time partitioned table, call the jobs.insert method, configure a query job, and include a value for the destinationTable and timePartitioning properties.

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

Creating an ingestion-time partitioned table when loading data

You can create an ingestion time-partitioned table by specifying partitioning options when you load data into a new table. You do not need to create an empty partitioned table before loading data into it. You can create the partitioned table and load your data at the same time.

When you load data into BigQuery, you can supply the table schema, or for supported data formats, you can use schema auto-detection.

Partition decorators enable you to load data into a specific partition. To adjust for timezones, use a partition decorator to load data into a partition based on your preferred timezone. For example, if you are on Pacific Standard Time (PST), load all data that is generated on May 1, 2016 PST into the partition for that date by using the corresponding partition decorator:

[TABLE_NAME]$20160501

For more information on loading data, see Introduction to loading data into BigQuery.

Converting date-sharded tables into ingestion-time partitioned tables

If you have previously created date-sharded tables, you can convert the entire set of related tables into a single ingestion-time partitioned table by using the partition command in the bq command-line tool. The date-sharded tables must use the following naming convention: [TABLE]_YYYYMMDD. For example, mytable_20160101, ... , mytable_20160331.

Optional parameters include --time_partitioning_expiration, --location, and --time_partitioning_type. Since --time_partitioning_type=DAY is currently the only supported value, this parameter is optional. If your source tables or your destination table are in a project other than your default project, add the project ID to the dataset name in the following format: [PROJECT_ID]:[DATASET].

Enter the following command to convert a series of date-sharded tables to a single ingestion-time partitioned table:

bq --location=[LOCATION] partition \
--time_partitioning_type=DAY \
--time_partitioning_expiration [INTEGER] \
[PROJECT_ID]:[DATASET].[SOURCE_TABLE]_ \
[PROJECT_ID]:[DATASET].[DESTINATION_TABLE]

Where:

[LOCATION] is the name of your location. The --location flag is optional. For example, if you are using BigQuery in the Tokyo region, set the flag's value to asia-northeast1. You can set a default value for the location using the .bigqueryrc file.
[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 UTC date plus the integer value. The partition expiration is independent of the table's expiration but does not override it. If you set a partition expiration that is longer than the table's expiration, the table expiration takes precedence.
[PROJECT_ID] is your project ID.
[DATASET] is a dataset in your project.
[SOURCE_TABLE]_ is the prefix of your date-sharded table.
[DESTINATION_TABLE] is the name of the partitioned table you're creating.

Examples:

Enter the following command to create an ingestion-time partitioned table named mytable_partitioned in mydataset in your default project. The partitioning expiration is set to 259,200 seconds (3 days). The date sharded source tables are prefixed with sourcetable_. The source tables are also in your default project.

bq partition \
--time_partitioning_type=DAY \
--time_partitioning_expiration 259200 \
mydataset.sourcetable_ \
mydataset.mytable_partitioned

When you run the command, a copy job is created that generates partitions from the sharded tables. For example, if the date-sharded tables were sourcetable_20180126 and sourcetable_20180127, the copy job would create the following partitions: mydataset.mytable_partitioned$20180126 and mydataset.mytable_partitioned$20180127.

Enter the following command to create an ingestion-time partitioned table named mytable_partitioned in mydataset. mydataset is in myotherproject, not your default project. The partitioning expiration is set to 86,400 seconds (1 day). The date sharded source tables are prefixed with sourcetable_. The source tables are in your default project.

bq partition \
--time_partitioning_type=DAY \
--time_partitioning_expiration 86400 \
mydataset.sourcetable_ \
myotherproject:mydataset.mytable_partitioned

Enter the following command to create an ingestion-time partitioned table named mytable_partitioned in mydataset in your default project. mydataset was created in the asia-northeast1 region. The partitioning expiration is set to 259,200 seconds (3 days). The date sharded source tables are prefixed with sourcetable_. The source tables are also in your default project.

bq --location=asia-northeast1 partition \
--time_partitioning_type=DAY \
--time_partitioning_expiration 259200 \
mydataset.sourcetable_ \
mydataset.mytable_partitioned

Controlling access to time-partitioned tables

You cannot assign access controls directly to tables or partitions. You can control table access by configuring access controls at the dataset level or at the project level.

Dataset-level access controls specify the operations users, groups, and service accounts are allowed to perform on tables in that specific dataset. If you assign only dataset-level permissions, you must also assign a primitive or predefined, project-level role that provides access to the project, for example, bigquery.user.

Instead of granting access to individual datasets, you can assign predefined, project-level IAM roles that grant permissions to all table data in all datasets in a project.

You can also create IAM custom roles. If you create a custom role, the permissions you grant depend on the table operations you want the user, group, or service account to be able to perform.

For more information on roles and permissions, see:

Understanding roles in the IAM documentation
BigQuery Access controls
Assigning access controls to datasets.

Using ingestion-time partitioned tables

Getting information about ingestion-time partitioned tables

You can get information about tables using the GCP Console, the classic BigQuery web UI, using the bq show CLI command or by calling the tables.get API method.

Required permissions

To get information about tables, you must be assigned the READER role on the dataset, or you must be assigned a project-level IAM role that includes bigquery.tables.get permissions. If you are granted bigquery.tables.get permissions at the project level, you can get information about all tables in the project. All predefined, project-level IAM roles include bigquery.tables.get permissions except for bigquery.jobUser and bigquery.user.

In addition, a user assigned the bigquery.user role has bigquery.datasets.create permissions. This allows a user assigned to the bigquery.user role to get information about tables in any dataset that user creates. When a user assigned to the bigquery.user role creates a dataset, that user is given OWNER access to the dataset. OWNER access to a dataset gives the user full control over it and all the tables in it.

For more information on IAM roles and permissions in BigQuery, see Access control. For more information on dataset- level roles, see Primitive roles for datasets.

Getting ingestion-time partitioned table information

To view information about an ingestion-time partitioned table:

Console

Open the BigQuery web UI in the GCP Console.
Go to the BigQuery web UI
In the navigation panel, in the Resources section, expand your project and select a dataset to list the tables and views it contains.
Click the table name.
Click Details. This tab displays the table's description and table information.
Click the Schema tab to view the table's schema definition. Notice the additional pseudo column _PARTITIONTIME that contains the date-based timestamp for data that is loaded into the table.

Classic UI

In the navigation pane, down arrow icon to the left of your dataset to expand it, or double-click the dataset name. This displays the tables and views in the dataset.
Click the table name.
Click Details. The Table Details page displays the table's description and table information.
Click the Schema tab to view the table's schema definition. Notice the additional pseudo column _PARTITIONTIME that contains the date-based timestamp for data that is loaded into the table.

CLI

Issue the bq show command to display all table information. Use the --schema flag to display only table schema information. The --format flag can be used to control the output.

If you are getting information about a table in a project other than your default project, add the project ID to the dataset in the following format: [PROJECT_ID]:[DATASET].

bq show --schema --format=prettyjson [PROJECT_ID]:[DATASET].[TABLE]

Where:

[PROJECT_ID] is your project ID.
[DATASET] is the name of the dataset.
[TABLE] is the name of the table.

Examples:

Enter the following command to display all information about mytable in mydataset. mydataset is in your default project.

bq show --format=prettyjson mydataset.mytable

Enter the following command to display all information about mytable in mydataset. mydataset is in myotherproject, not your default project.

bq show --format=prettyjson myotherproject:mydataset.mytable

Enter the following command to display only schema information about mytable in mydataset. mydataset is in myotherproject, not your default project.

When you show schema information for a time-partitioned table, the _PARTITIONTIME pseudo column is not displayed.

bq show --schema --format=prettyjson myotherproject:mydataset.mytable

API

Call the bigquery.tables.get method and provide any relevant parameters.

Listing ingestion-time partitioned tables in a dataset

You can list tables in datasets (including partitioned tables) by using the GCP Console, the classic BigQuery web UI, the bq ls CLI command, or by calling the tables.list API method.

Required permissions

To list tables in a dataset, you must be assigned the READER role on the dataset, or you must be assigned a project-level IAM role that includes bigquery.tables.list permissions. If you are granted bigquery.tables.list permissions at the project level, you can list tables in any dataset in the project. All predefined, project-level IAM roles include bigquery.tables.list permissions except for bigquery.jobUser.

For more information on IAM roles and permissions in BigQuery, see Access control. For more information on dataset-level roles, see Primitive roles for datasets.

Listing partitioned tables

To list the tables in a dataset (including partitioned tables):

Console

Open the BigQuery web UI in the GCP Console.
Go to the BigQuery web UI
In the navigation panel, in the Resources section, expand your project and click on your dataset.
Scroll through the list to see the tables in the dataset. Tables, partitioned tables, models, and views are identified by different icons.

Classic UI

In the web UI, in the navigation pane, down arrow icon to the left of your dataset to expand it, or double-click the dataset name. This displays the tables and views in the dataset.
Scroll through the list to see the tables in the dataset. Tables and views are identified by different icons.

CLI

Issue the bq ls command. The --format flag can be used to control the output. If you are listing tables in a project other than your default project, add the project ID to the dataset in the following format: [PROJECT_ID]:[DATASET].

bq ls --format=pretty [PROJECT_ID]:[DATASET]

Where:

[PROJECT_ID] is your project ID.
[DATASET] is the name of the dataset.

When you run the command, the Type field displays either TABLE or VIEW. For ingestion-time partitioned tables, the Time Partitioning field displays DAY and the partition expiration time in milliseconds, if a partition expiration is specified.

For example:

+-------------------------+-------+----------------------+--------------------------------+
|         tableId         | Type  |        Labels        | Time Partitioning              |
+-------------------------+-------+----------------------+--------------------------------+
| mytable                 | TABLE | department:shipping  |  DAY (expirationMs: 259200000) |
| myview                  | VIEW  |                      |                                |
+-------------------------+-------+----------------------+--------------------------------+

Examples:

Enter the following command to list tables in dataset mydataset in your default project.

bq ls --format=pretty mydataset

Enter the following command to list tables in dataset mydataset in myotherproject.

bq ls --format=pretty myotherproject:mydataset

API

To list tables using the API, call the tables.list method.

Listing partitions in ingestion-time partitioned tables

You can list the partitions in an ingestion-time partitioned table by querying the _PARTITIONTIME pseudo column in standard SQL or the __PARTITIONS_SUMMARY__ meta table in legacy SQL.

You can run the query in the GCP Console, the classic BigQuery web UI, using the bq query command, or by calling the jobs.insert method and configuring a query job.

Required permissions

To run a query job that uses the __PARTITIONS_SUMMARY__ meta table, or the _PARTITIONTIME pseudo column, you must have bigquery.jobs.create permissions. The following predefined, project-level IAM roles include bigquery.jobs.create permissions:

bigquery.user
bigquery.jobUser
bigquery.admin

You must also be assigned the READER role at the dataset level, or you must be assigned a project-level IAM role that includes bigquery.tables.getData permissions. All predefined, project-level IAM roles include bigquery.tables.getData permissions except for bigquery.user, bigquery.jobUser, and bigquery.metadataViewer.

For more information on IAM roles and permissions in BigQuery, see Access control. For more information on dataset-level roles, see Primitive roles for datasets.

Listing partitions in an ingestion-time partitioned table

You can list partitions in an ingestion-time partitioned table using standard SQL (preferred) or legacy SQL. To list partitions:

Standard SQL:

Console

Open the BigQuery web UI in the GCP Console.
Go to the BigQuery web UI
Click the Compose new query button.
Enter the following text into the Query editor box to query the _PARTITIONTIME pseudo column:
```
SELECT
  _PARTITIONTIME as pt
FROM
  `[DATASET].[TABLE]`
GROUP BY 1
```
Where:
- [DATASET] is the dataset that contains the table.
- [TABLE] is the name of the table.
(Optional) Click More and select Query settings.
(Optional) For Processing location, click Auto-select and choose your data's location. You can leave processing location set to auto-select to detect your location for you.
Click Run.

Classic UI

Go to the BigQuery web UI.

Go to the BigQuery web UI
Click the Compose query button.
Enter the following text into the New Query box to query a table's _PARTITIONTIME pseudo column:
```
#standardSQL
SELECT
  _PARTITIONTIME as pt
FROM
  `[DATASET].[TABLE]`
GROUP BY 1
```
Where:
- [DATASET] is the dataset that contains the table.
- [TABLE] is the name of the table.
Click Show Options.
(Optional) For Processing Location, click Unspecified and choose your data's location.
Click Run query.

CLI

Enter the following query using the bq query command:

bq --location=[LOCATION] query --use_legacy_sql=false '
SELECT
  _PARTITIONTIME as pt
FROM
  `[DATASET].[TABLE]`
GROUP BY 1'

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](/bigquery/docs/bq-command-line-tool#setting_default_values_for_command-line_flags).
  + `[DATASET]` is the dataset that contains the table.
  + `[TABLE]` is the name of the table.

API

Call the jobs.insert method and configure a query job that queries the table's _PARTITIONTIME pseudo column.

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

Legacy SQL:

Console

Open the BigQuery web UI in the GCP Console.
Go to the BigQuery web UI
Click the Compose new query button.
Enter the following text into the Query editor box to query the __PARTITIONS_SUMMARY__ meta-table:
```
#legacySQL
SELECT
  partition_id
FROM
  [[DATASET].[TABLE]$__PARTITIONS_SUMMARY__]
```
Where:
- [DATASET] is the dataset that contains the table.
- [TABLE] is the name of the table.
Click More and select Query settings.
For Processing location, click Auto-select and choose your data's location. You can leave processing location set to auto-select if your data is in the US or EU multi-region location. When your data is in the US or the EU, the processing location is automatically detected.
Click Run.

Classic UI

Go to the BigQuery web UI.

Go to the BigQuery web UI
Click the Compose query button.
Enter the following text into the New Query box to query a table's __PARTITIONS_SUMMARY__ meta table:
```
#legacySQL
SELECT
   partition_id
 FROM
   [[DATASET].[TABLE]$__PARTITIONS_SUMMARY__]
```
Where:
- [DATASET] is the dataset that contains the table.
- [TABLE] is the name of the table.
Click Show Options.
(Optional) For Processing Location, click Unspecified and choose your data's location.
Click Run query.

CLI

Enter the following query using the bq query command:

bq --location=[LOCATION] query --use_legacy_sql=true '
SELECT
   partition_id
 FROM
   [[DATASET].[TABLE]$__PARTITIONS_SUMMARY__]'

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](/bigquery/docs/bq-command-line-tool#setting_default_values_for_command-line_flags).
  + `[DATASET]` is the dataset that contains the table.
  + `[TABLE]` is the name of the table.

API

Call the jobs.insert method and configure a query job that queries the __PARTITIONS_SUMMARY__ meta table.

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

Getting table metadata using meta tables

You can get information about partitioned tables by using special tables called meta tables. Meta tables contain metadata such as the list of tables and views in a dataset. The meta tables are read only.

Getting partition metadata using meta tables

The __PARTITIONS_SUMMARY__ meta table is a special table whose contents represent metadata about partitions in a time-partitioned table. The __PARTITIONS_SUMMARY__ meta table is read-only.

To access metadata about the partitions in a time-partitioned table, use the __PARTITIONS_SUMMARY__ meta-table in a query's SELECT statement. You can run the query by using the console, the classic BigQuery web UI, the command-line tool's bq query command, or by calling the jobs.insert API method and configuring a query job.

Currently, standard SQL does not support the partition decorator separator ($) so you cannot query __PARTITIONS_SUMMARY__ in standard SQL. A legacy SQL query that uses the __PARTITIONS_SUMMARY__ meta-table looks like the following:

    SELECT [COLUMN] FROM [[DATASET].[TABLE]$__PARTITIONS_SUMMARY__]

Where:

[DATASET] is the name of your dataset.
[TABLE] is the name of the time-partitioned table.
[COLUMN] is one of the following:

Value	Description
`project_id`	Name of the project.
`dataset_id`	Name of the dataset.
`table_id`	Name of the time-partitioned table.
`partition_id`	Name (date) of the partition.
`creation_time`	The time at which the partition was created, in milliseconds since January 1, 1970 UTC.
`last_modified_time`	The time at which the partition was last modified, in milliseconds since January 1, 1970 UTC.

Partition meta table permissions

To run a query job that uses the __PARTITIONS_SUMMARY__ meta-table, you must have bigquery.jobs.create permissions. The following predefined, project-level IAM roles include bigquery.jobs.create permissions:

bigquery.user
bigquery.jobUser
bigquery.admin

Partition meta table examples

The following query retrieves all partition metadata for a time-partitioned table named mydataset.mytable.

Console

#legacySQL
SELECT
  *
FROM
  [mydataset.mytable$__PARTITIONS_SUMMARY__]

Classic UI

#legacySQL
SELECT
  *
FROM
  [mydataset.mytable$__PARTITIONS_SUMMARY__]

CLI

bq query --use_legacy_sql=true '
SELECT
  *
FROM
  [mydataset.mytable$__PARTITIONS_SUMMARY__]'

The output looks like the following:

+----------------+------------+----------------+--------------+---------------+--------------------+
|   project_id   | dataset_id |    table_id    | partition_id | creation_time | last_modified_time |
+----------------+------------+----------------+--------------+---------------+--------------------+
| myproject      | mydataset  | mytable        | 20160314     | 1517190224120 | 1517190224997      |
| myproject      | mydataset  | mytable        | 20160315     | 1517190224120 | 1517190224997      |
+----------------+------------+----------------+--------------+---------------+--------------------+

The following query lists the times when the partitions in mydataset.mytable were last modified.

Console

#legacySQL
SELECT
  partition_id,
  last_modified_time
FROM
  [mydataset.mytable$__PARTITIONS_SUMMARY__]

Classic UI

#legacySQL
SELECT
  partition_id,
  last_modified_time
FROM
  [mydataset.mytable$__PARTITIONS_SUMMARY__]

CLI

bq query --use_legacy_sql=true '
SELECT
  partition_id,
  last_modified_time
FROM
  [mydataset.mytable$__PARTITIONS_SUMMARY__]'

The output looks like the following:

+--------------+--------------------+
| partition_id | last_modified_time |
+--------------+--------------------+
| 20160102     |      1471632556179 |
| 20160101     |      1471632538142 |
| 20160103     |      1471632570463 |
+--------------+--------------------+

To display the last_modified_time field in human-readable format, use the FORMAT_UTC_USEC function. For example:

Console

#legacySQL
SELECT
  partition_id,
  FORMAT_UTC_USEC(last_modified_time*1000) AS last_modified
FROM
  [mydataset.table1$__PARTITIONS_SUMMARY__]

Classic UI

#legacySQL
SELECT
  partition_id,
  FORMAT_UTC_USEC(last_modified_time*1000) AS last_modified
FROM
  [mydataset.table1$__PARTITIONS_SUMMARY__]

CLI

bq query --use_legacy_sql=true '
SELECT
  partition_id,
  FORMAT_UTC_USEC(last_modified_time*1000) AS last_modified
FROM
  [mydataset.mytable$__PARTITIONS_SUMMARY__]'

The output looks like the following:

+--------------+----------------------------+
| partition_id |       last_modified        |
+--------------+----------------------------+
| 20160103     | 2016-08-19 18:49:30.463000 |
| 20160102     | 2016-08-19 18:49:16.179000 |
| 20160101     | 2016-08-19 18:48:58.142000 |
+--------------+----------------------------+

Example: Creating an ingestion-time partitioned table using query results

In this example, you create an ingestion-time partitioned table by using the command-line tool, and you add data to three partitions using query results. The table will contain weather data, partitioned by date, for the first three days in 2016.

This example queries the NOAA GSOD weather dataset for temperatures for the first three days of 2016 and writes the results to the a partitioned table.

Step 1. Create an empty ingestion-time partitioned table named temps in a dataset named mydataset. There is no need to specify a schema for the table. The schema from the query results is used as the schema definition for the table.

bq mk --time_partitioning_type=DAY mydataset.temps

To view the configuration settings, use the bq show command:

bq show --format=prettyjson mydataset.temps

Look for the timePartitioning entry in the bq show command output:

{
  ...
  "timePartitioning": {
    "type": "DAY"
  },
  "type": "TABLE"
}

Step 2. Query the NOAA GSOD weather dataset for temperatures for the first three days of 2016 and write the results to the respective partitions in the temps table. The following queries use the --destination_table option and standard SQL syntax to write 100 rows of query results to a partition.

Run the following query to write January 1, 2016 temperatures to partition mydataset.temps$20160101:

bq query --use_legacy_sql=false \
--destination_table 'mydataset.temps$20160101' \
'SELECT
   stn,
   temp
 FROM
   `bigquery-public-data`.noaa_gsod.gsod2016
 WHERE
   mo="01"
   AND da="01"
 LIMIT
   100'

Run the following query to write January 2, 2016 temperatures to partition mydataset.temps$20160102:

bq --location=US query --use_legacy_sql=false \
--destination_table 'mydataset.temps$20160102' \
'SELECT
   stn,
   temp
 FROM
   `bigquery-public-data`.noaa_gsod.gsod2016
 WHERE
   mo="01"
   AND da="02"
 LIMIT
   100'

Run the following query to write January 3, 2016 temperatures to partition mydataset.temps$20160103:

bq --location=US query --use_legacy_sql=false \
--destination_table 'mydataset.temps$20160103' \
'SELECT
   stn,
   temp
 FROM
   `bigquery-public-data`.noaa_gsod.gsod2016
 WHERE
   mo="01"
   AND da="03"
 LIMIT
   100'

Step 3. Confirm that you have 300 rows in your table by using the bq show command.

bq show mydataset.temps

The results show the Schema and Total Rows.

  Last modified        Schema       Total Rows   Total Bytes     Expiration      Time Partitioning   Labels   kmsKeyName
 ----------------- ---------------- ------------ ------------- ----------------- ------------------- -------- ------------
  28 Jan 15:03:45   |- stn: string   300          4800          29 Jan 15:00:32   DAY
                    |- temp: float

Next steps

For an overview of partitioned table support in BigQuery, see Introduction to partitioned tables.
To learn how to create and use partitioned tables, see Creating and using partitioned tables.
To learn how to manage and update partitioned tables, see Managing partitioned tables.
For information on querying partitioned tables, see Querying partitioned tables.

Creating ingestion-time partitioned tables

Required permissions

Creating an empty ingestion-time partitioned table with a schema definition

Console

Classic UI

CLI

API

Creating an ingestion-time partitioned table from a query result

Console

Classic UI

CLI

API

Creating an ingestion-time partitioned table when loading data

Converting date-sharded tables into ingestion-time partitioned tables

Controlling access to time-partitioned tables

Using ingestion-time partitioned tables

Getting information about ingestion-time partitioned tables

Required permissions

Getting ingestion-time partitioned table information

Console

Classic UI

CLI

API

Listing ingestion-time partitioned tables in a dataset

Required permissions

Listing partitioned tables

Console

Classic UI

CLI

API

Listing partitions in ingestion-time partitioned tables

Required permissions

Listing partitions in an ingestion-time partitioned table

Console

Classic UI

CLI

API

Console

Classic UI

CLI

API

Getting table metadata using meta tables

Getting partition metadata using meta tables

Partition meta table permissions

Partition meta table examples

Console

Classic UI

CLI

Console

Classic UI

CLI

Console

Classic UI

CLI

Example: Creating an ingestion-time partitioned table using query results

Next steps

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