Create materialized view

Create a materialized view.

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For detailed documentation that includes this code sample, see the following:

Code sample

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"
)

// createMaterializedView demonstrates generated a materialized view based on an existing
// base table.
func createMaterializedView(projectID, datasetID, baseTableID, viewID string) error {
	// projectID := "my-project-id"
	// datasetID := "mydatasetid"
	// baseTableID := "mytableid"
	// viewID := "myviewid"
	ctx := context.Background()

	client, err := bigquery.NewClient(ctx, projectID)
	if err != nil {
		return fmt.Errorf("bigquery.NewClient: %w", err)
	}
	defer client.Close()

	// Get an appropriately escaped table identifier suitable for use in a standard SQL query.
	tableStr, err := client.Dataset(datasetID).Table(baseTableID).Identifier(bigquery.StandardSQLID)
	if err != nil {
		return fmt.Errorf("couldn't construct identifier: %w", err)
	}

	metaData := &bigquery.TableMetadata{
		MaterializedView: &bigquery.MaterializedViewDefinition{
			Query: fmt.Sprintf(`SELECT MAX(TimestampField) AS TimestampField, StringField, 
					  MAX(BooleanField) AS BooleanField FROM %s GROUP BY StringField`, tableStr),
		}}

	viewRef := client.Dataset(datasetID).Table(viewID)
	if err := viewRef.Create(ctx, metaData); 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.MaterializedViewDefinition;
import com.google.cloud.bigquery.TableId;
import com.google.cloud.bigquery.TableInfo;

// Sample to create materialized view
public class CreateMaterializedView {

  public static void main(String[] args) {
    // TODO(developer): Replace these variables before running the sample.
    String datasetName = "MY_DATASET_NAME";
    String tableName = "MY_TABLE_NAME";
    String materializedViewName = "MY_MATERIALIZED_VIEW_NAME";
    String query =
        String.format(
            "SELECT MAX(TimestampField) AS TimestampField, StringField, "
                + "MAX(BooleanField) AS BooleanField "
                + "FROM %s.%s GROUP BY StringField",
            datasetName, tableName);
    createMaterializedView(datasetName, materializedViewName, query);
  }

  public static void createMaterializedView(
      String datasetName, String materializedViewName, String query) {
    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 tableId = TableId.of(datasetName, materializedViewName);

      MaterializedViewDefinition materializedViewDefinition =
          MaterializedViewDefinition.newBuilder(query).build();

      bigquery.create(TableInfo.of(tableId, materializedViewDefinition));
      System.out.println("Materialized view created successfully");
    } catch (BigQueryException e) {
      System.out.println("Materialized view was not created. \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.

from google.cloud import bigquery

bigquery_client = bigquery.Client()

view_id = "my-project.my_dataset.my_materialized_view"
base_table_id = "my-project.my_dataset.my_base_table"
view = bigquery.Table(view_id)
view.mview_query = f"""
SELECT product_id, SUM(clicks) AS sum_clicks
FROM  `{base_table_id}`
GROUP BY 1
"""

# Make an API request to create the materialized view.
view = bigquery_client.create_table(view)
print(f"Created {view.table_type}: {str(view.reference)}")

Terraform

To learn how to apply or remove a Terraform configuration, see Basic Terraform commands. For more information, see the Terraform provider reference documentation.

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            = "my_materialized_view"
  deletion_protection = false # set to "true" in production

  materialized_view {
    query                            = "SELECT ID, description, date_created FROM `myproject.orders.items`"
    enable_refresh                   = "true"
    refresh_interval_ms              = 172800000 # 2 days
    allow_non_incremental_definition = "false"
  }

}

What's next

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