创建视图

在数据集中创建视图。

深入探索

如需查看包含此代码示例的详细文档，请参阅以下内容：

• 创建视图

代码示例

Go

试用此示例之前，请按照 BigQuery 快速入门：使用客户端库中的 Go 设置说明进行操作。如需了解详情，请参阅 BigQuery Go API 参考文档。

如需向 BigQuery 进行身份验证，请设置应用默认凭据。 如需了解详情，请参阅为客户端库设置身份验证。

import (
	"context"
	"fmt"

	"cloud.google.com/go/bigquery"
)

// createView demonstrates creation of a BigQuery logical view.
func createView(projectID, datasetID, tableID string) error {
	// projectID := "my-project-id"
	// datasetID := "mydatasetid"
	// tableID := "mytableid"
	ctx := context.Background()

	client, err := bigquery.NewClient(ctx, projectID)
	if err != nil {
		return fmt.Errorf("bigquery.NewClient: %w", err)
	}
	defer client.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%'",
	}
	if err := client.Dataset(datasetID).Table(tableID).Create(ctx, meta); err != nil {
		return err
	}
	return nil
}

Java

试用此示例之前，请按照 BigQuery 快速入门：使用客户端库中的 Java 设置说明进行操作。如需了解详情，请参阅 BigQuery Java API 参考文档。

如需向 BigQuery 进行身份验证，请设置应用默认凭据。 如需了解详情，请参阅为客户端库设置身份验证。

import com.google.cloud.bigquery.BigQuery;
import com.google.cloud.bigquery.BigQueryException;
import com.google.cloud.bigquery.BigQueryOptions;
import com.google.cloud.bigquery.TableId;
import com.google.cloud.bigquery.TableInfo;
import com.google.cloud.bigquery.ViewDefinition;

// Sample to create a view
public class CreateView {

  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 viewName = "MY_VIEW_NAME";
    String query =
        String.format(
            "SELECT TimestampField, StringField, BooleanField FROM %s.%s", datasetName, tableName);
    createView(datasetName, viewName, query);
  }

  public static void createView(String datasetName, String viewName, 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, viewName);

      ViewDefinition viewDefinition =
          ViewDefinition.newBuilder(query).setUseLegacySql(false).build();

      bigquery.create(TableInfo.of(tableId, viewDefinition));
      System.out.println("View created successfully");
    } catch (BigQueryException e) {
      System.out.println("View was not created. \n" + e.toString());
    }
  }
}

Node.js

试用此示例之前，请按照 BigQuery 快速入门：使用客户端库中的 Node.js 设置说明进行操作。如需了解详情，请参阅 BigQuery Node.js API 参考文档。

如需向 BigQuery 进行身份验证，请设置应用默认凭据。 如需了解详情，请参阅为客户端库设置身份验证。

// Import the Google Cloud client library and create a client
const {BigQuery} = require('@google-cloud/bigquery');
const bigquery = new BigQuery();

async function createView() {
  // Creates a new view named "my_shared_view" in "my_dataset".

  /**
   * TODO(developer): Uncomment the following lines before running the sample.
   */
  // const myDatasetId = "my_dataset"
  // const myTableId = "my_shared_view"
  // const projectId = "bigquery-public-data";
  // const sourceDatasetId = "usa_names"
  // const sourceTableId = "usa_1910_current";
  const myDataset = await bigquery.dataset(myDatasetId);

  // For all options, see https://cloud.google.com/bigquery/docs/reference/v2/tables#resource
  const options = {
    view: `SELECT name
    FROM \`${projectId}.${sourceDatasetId}.${sourceTableId}\`
    LIMIT 10`,
  };

  // Create a new view in the dataset
  const [view] = await myDataset.createTable(myTableId, options);

  console.log(`View ${view.id} created.`);
}

Python

试用此示例之前，请按照 BigQuery 快速入门：使用客户端库中的 Python 设置说明进行操作。如需了解详情，请参阅 BigQuery Python API 参考文档。

如需向 BigQuery 进行身份验证，请设置应用默认凭据。 如需了解详情，请参阅为客户端库设置身份验证。

from google.cloud import bigquery

client = 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)}")

Terraform

如需了解如何应用或移除 Terraform 配置，请参阅基本 Terraform 命令。 如需了解详情，请参阅 Terraform 提供程序参考文档。

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
  }

}

后续步骤

如需搜索和过滤其他 Google Cloud 产品的代码示例，请参阅 Google Cloud 示例浏览器。