Listing views

This document describes how to list views in BigQuery.

You can list views in datasets by:

• Using the GCP Console or the classic BigQuery web UI
• Using the bq ls CLI command
• Calling the tables.list API method.

Required permissions

To list views 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 views in any dataset in the project. All predefined BigQuery 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 views

Listing views is identical to the process for listing tables.

To list the views in a dataset:

Console

1. In the navigation panel, in the Resources section, expand your project and click on a dataset. This displays the tables and views in the dataset.

2. Scroll through the list to see the tables in the dataset. Tables and views are identified by different icons.

   

Classic UI

1. In the BigQuery web UI, in the navigation pane, click the blue arrow to the left of your dataset to expand it, or double-click the dataset name. This displays the tables and views in the dataset.

2. Scroll through the list to see the tables in the dataset. Tables and views are identified by different icons.

   

Command-line

Issue the bq ls command. The --format flag can be used to control the output. If you are listing views 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 example:

+-------------------------+-------+----------------------+-------------------+
|         tableId         | Type  |        Labels        | Time Partitioning |
+-------------------------+-------+----------------------+-------------------+
| mytable                 | TABLE | department:shipping  |                   |
| myview                  | VIEW  |                      |                   |
+-------------------------+-------+----------------------+-------------------+

Examples:

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

bq ls --format=pretty mydataset

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

bq ls --format=pretty myotherproject:mydataset

API

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

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 .

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// To run this sample, you will need to create (or reuse) a context and
// an instance of the bigquery client.  For example:
// import "cloud.google.com/go/bigquery"
// ctx := context.Background()
// client, err := bigquery.NewClient(ctx, "your-project-id")
ts := client.Dataset(datasetID).Tables(ctx)
for {
	t, err := ts.Next()
	if err == iterator.Done {
		break
	}
	if err != nil {
		return err
	}
	fmt.Fprintf(w, "Table: %q\n", t.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 .

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from google.cloud import bigquery

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

# TODO(developer): Set dataset_id to the ID of the dataset that contains
#                  the tables you are listing.
# dataset_id = 'your-project.your_dataset'

tables = client.list_tables(dataset_id)

print("Tables contained in '{}':".format(dataset_id))
for table in tables:
    print("{}.{}.{}".format(table.project, table.dataset_id, table.table_id))

Next steps

• For information on creating views, see Creating views.
• For information on creating an authorized view, see Creating authorized views.
• For information on getting view metadata, see Getting information about views.
• For information on updating views, see Updating views.
• For more information on managing views, see Managing views.