Console

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

   Go to BigQuery

2. Clickadd_boxSQL query.

3. In the query editor, enter a valid SQL query.

   Alternatively, you canopen a saved query.

4. ClickSave> Save view.

   

5. In theSave view dialog:

   • In theProject menu, select a project to store the view.
   • In theDataset menu, select a dataset or create a new dataset tostore the view. The destination dataset for a saved view must be inthe sameregion as the source.
   • In theTable field, enter the name of the view.
   • ClickSave.

SQL

Use theCREATE VIEW statement.The followingexample creates a view namedusa_male_names from the USA namespublic dataset:

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

   Go to BigQuery

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

   CREATEVIEWmydataset.usa_male_names(name,number)AS(SELECTname,numberFROM`bigquery-public-data.usa_names.usa_1910_current`WHEREgender='M'ORDERBYnumberDESC);

3. Clickplay_circleRun.

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

bq

Use thebq mk commandwith the--view flag. For GoogleSQL queries,add the--use_legacy_sql flag and set it tofalse. Some optionalparameters include--add_tags,--expiration,--description, and--label. For a full list of parameters, see thebq mk commandreference.

If your query references external user-defined function (UDF) resourcesstored in Cloud Storage or in local files, use the--view_udf_resource flag to specify those resources. The--view_udf_resource flag is not demonstrated here. For more information aboutusing UDFs, seeUDFs.

If you are creating a view in a project other than your default project,specify the project ID using the--project_id flag.

bqmk\--use_legacy_sql=false\--view_udf_resource=PATH_TO_FILE\--expiration=INTEGER\--description="DESCRIPTION"\--label=KEY_1:VALUE_1\--add_tags=KEY_2:VALUE_2[,...]\--view='QUERY'\--project_id=PROJECT_ID\DATASET.VIEW

Replace the following:

• PATH_TO_FILE is the URI or local file system pathto a code file to be loaded and evaluated immediately as a UDF resourceused by the view. Repeat the flag to specify multiple files.
• INTEGER sets the lifetime (in seconds) forthe view. IfINTEGER is0, the view doesn'texpire. If you don't include the--expiration flag, BigQuerycreates the view with the dataset's default table lifetime.
• DESCRIPTION is a description of the view in quotes.
• KEY_1:VALUE_1 is the key-value pair thatrepresents alabel.Repeat the--label flag to specify multiple labels.
• KEY_2:VALUE_2 is the key-value pair thatrepresents atag.Add multiple tags under the same flag with commas between key:value pairs.
• QUERY is a valid query.
• PROJECT_ID is your project ID (if you don't havea default project configured).
• DATASET is a dataset in your project.
• VIEW is the name of the view that you want tocreate.

Examples:

Enter the following command to create a view namedmyview inmydataset in your default project. The expiration time is set to3600 seconds (1 hour), the description is set toThis is my view, and thelabel is set toorganization:development. The query used to create the viewqueries data from theUSA Name Data public dataset.

bq mk \--use_legacy_sql=false \--expiration 3600 \--description "This is my view" \--label organization:development \--view \'SELECT  name,  numberFROM`bigquery-public-data.usa_names.usa_1910_current`WHERE  gender = "M"ORDER BY  number DESC' \mydataset.myview

Enter the following command to create a view namedmyview inmydataset inmyotherproject. The description is set toThis is my view, the label is set toorganization:development,and the view's expiration is set to the dataset's default tableexpiration.The query used to create the viewqueries data from theUSA Name Data public dataset.

bq mk \--use_legacy_sql=false \--description "This is my view" \--label organization:development \--project_id myotherproject \--view \'SELECT  name,  numberFROM`bigquery-public-data.usa_names.usa_1910_current`WHERE  gender = "M"ORDER BY  number DESC' \mydataset.myview

After the view is created, you can update the view'sexpiration, description, and labels. For more information, seeUpdating views.

Terraform

Use thegoogle_bigquery_tableresource.

To authenticate to BigQuery, set up Application DefaultCredentials. For more information, seeSet up authentication for client libraries.

The following example creates a view namedmyview:

resource "google_bigquery_dataset" "default" {  dataset_id                      = "mydataset"  default_partition_expiration_ms = 2592000000  # 30 days  default_table_expiration_ms     = 31536000000 # 365 days  description                     = "dataset description"  location                        = "US"  max_time_travel_hours           = 96 # 4 days  labels = {    billing_group = "accounting",    pii           = "sensitive"  }}resource "google_bigquery_table" "default" {  dataset_id          = google_bigquery_dataset.default.dataset_id  table_id            = "myview"  deletion_protection = false # set to "true" in production  view {    query          = "SELECT global_id, faa_identifier, name, latitude, longitude FROM `bigquery-public-data.faa.us_airports`"    use_legacy_sql = false  }}

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

Prepare Cloud Shell

1. LaunchCloud Shell.

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

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

   export GOOGLE_CLOUD_PROJECT=PROJECT_ID

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

Prepare the directory

Each Terraform configuration file must have its own directory (alsocalled aroot module).

1. InCloud Shell, create a directory and a new file within that directory. The filename must have the.tf extension—for examplemain.tf. In this tutorial, the file is referred to asmain.tf.

   mkdirDIRECTORY && cdDIRECTORY && touch main.tf

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

   Copy the sample code into the newly createdmain.tf.

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

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

   terraform init

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

   terraform init -upgrade

Apply the changes

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

   terraform plan

   Make corrections to the configuration as necessary.

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

   terraform apply

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

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

API

Call thetables.insert methodwith atable resource thatcontains aview property.

Go

import("context""fmt""cloud.google.com/go/bigquery")// createView demonstrates creation of a BigQuery logical view.funccreateView(projectID,datasetID,tableIDstring)error{// projectID := "my-project-id"// datasetID := "mydatasetid"// tableID := "mytableid"ctx:=context.Background()client,err:=bigquery.NewClient(ctx,projectID)iferr!=nil{returnfmt.Errorf("bigquery.NewClient: %v",err)}deferclient.Close()meta:=&bigquery.TableMetadata{// This example shows how to create a view of the shakespeare sample dataset, which// provides word frequency information.  This view restricts the results to only contain// results for works that contain the "king" in the title, e.g. King Lear, King Henry V, etc.ViewQuery:"SELECT word, word_count, corpus, corpus_date FROM `bigquery-public-data.samples.shakespeare` WHERE corpus LIKE '%king%'",}iferr:=client.Dataset(datasetID).Table(tableID).Create(ctx,meta);err!=nil{returnerr}returnnil}

Java

importcom.google.cloud.bigquery.BigQuery;importcom.google.cloud.bigquery.BigQueryException;importcom.google.cloud.bigquery.BigQueryOptions;importcom.google.cloud.bigquery.TableId;importcom.google.cloud.bigquery.TableInfo;importcom.google.cloud.bigquery.ViewDefinition;// Sample to create a viewpublicclassCreateView{publicstaticvoidmain(String[]args){// TODO(developer): Replace these variables before running the sample.StringdatasetName="MY_DATASET_NAME";StringtableName="MY_TABLE_NAME";StringviewName="MY_VIEW_NAME";Stringquery=String.format("SELECT TimestampField, StringField, BooleanField FROM %s.%s",datasetName,tableName);createView(datasetName,viewName,query);}publicstaticvoidcreateView(StringdatasetName,StringviewName,Stringquery){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.BigQuerybigquery=BigQueryOptions.getDefaultInstance().getService();TableIdtableId=TableId.of(datasetName,viewName);ViewDefinitionviewDefinition=ViewDefinition.newBuilder(query).setUseLegacySql(false).build();bigquery.create(TableInfo.of(tableId,viewDefinition));System.out.println("View created successfully");}catch(BigQueryExceptione){System.out.println("View was not created. \n"+e.toString());}}}

Node.js

// Import the Google Cloud client library and create a clientconst{BigQuery}=require('@google-cloud/bigquery');constbigquery=newBigQuery();asyncfunctioncreateView(){// Creates a new view named "my_shared_view" in "my_dataset"./**   * TODO(developer): Uncomment the following lines before running the sample.   */// const myDatasetId = "my_table"// const myTableId = "my_table"// const projectId = "bigquery-public-data";// const sourceDatasetId = "usa_names"// const sourceTableId = "usa_1910_current";constmyDataset=awaitbigquery.dataset(myDatasetId);// For all options, see https://cloud.google.com/bigquery/docs/reference/v2/tables#resourceconstoptions={view:`SELECT name    FROM \`${projectId}.${sourceDatasetId}.${sourceTableId}\`    LIMIT 10`,};// Create a new view in the datasetconst[view]=awaitmyDataset.createTable(myTableId,options);console.log(`View${view.id} created.`);}

Python

fromgoogle.cloudimportbigqueryclient=bigquery.Client()view_id="my-project.my_dataset.my_view"source_id="my-project.my_dataset.my_table"view=bigquery.Table(view_id)# The source table in this example is created from a CSV file in Google# Cloud Storage located at# `gs://cloud-samples-data/bigquery/us-states/us-states.csv`. It contains# 50 US states, while the view returns only those states with names# starting with the letter 'W'.view.view_query=f"SELECT name, post_abbr FROM `{source_id}` WHERE name LIKE 'W%'"# Make an API request to create the view.view=client.create_table(view)print(f"Created{view.table_type}:{str(view.reference)}")