模擬測試查詢

執行模擬測試查詢。

深入探索

如需包含這個程式碼範例的詳細說明文件，請參閱下列內容：

程式碼範例

Go

在試行這個範例之前，請先按照 BigQuery 快速入門導覽課程：使用用戶端程式庫中的 Go 設定說明進行操作。詳情請參閱 BigQuery Go API 參考說明文件。

如要向 BigQuery 進行驗證，請設定應用程式預設憑證。 詳情請參閱「設定用戶端程式庫的驗證機制」。

import (
	"context"
	"fmt"
	"io"

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

// queryDryRun demonstrates issuing a dry run query to validate query structure and
// provide an estimate of the bytes scanned.
func queryDryRun(w io.Writer, projectID string) error {
	// projectID := "my-project-id"
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, projectID)
	if err != nil {
		return fmt.Errorf("bigquery.NewClient: %w", err)
	}
	defer client.Close()

	q := client.Query(`
	SELECT
		name,
		COUNT(*) as name_count
	FROM ` + "`bigquery-public-data.usa_names.usa_1910_2013`" + `
	WHERE state = 'WA'
	GROUP BY name`)
	q.DryRun = true
	// Location must match that of the dataset(s) referenced in the query.
	q.Location = "US"

	job, err := q.Run(ctx)
	if err != nil {
		return err
	}
	// Dry run is not asynchronous, so get the latest status and statistics.
	status := job.LastStatus()
	if err := status.Err(); err != nil {
		return err
	}
	fmt.Fprintf(w, "This query will process %d bytes\n", status.Statistics.TotalBytesProcessed)
	return nil
}

Java

在試行這個範例之前，請先按照 BigQuery 快速入門導覽課程：使用用戶端程式庫中的 Java 設定說明進行操作。詳情請參閱 BigQuery Java API 參考說明文件。

如要向 BigQuery 進行驗證，請設定應用程式預設憑證。 詳情請參閱「設定用戶端程式庫的驗證機制」。

import com.google.cloud.bigquery.BigQuery;
import com.google.cloud.bigquery.BigQueryException;
import com.google.cloud.bigquery.BigQueryOptions;
import com.google.cloud.bigquery.Job;
import com.google.cloud.bigquery.JobInfo;
import com.google.cloud.bigquery.JobStatistics;
import com.google.cloud.bigquery.QueryJobConfiguration;

// Sample to run dry query on the table
public class QueryDryRun {

  public static void main(String[] args) {
    String query =
        "SELECT name, COUNT(*) as name_count "
            + "FROM `bigquery-public-data.usa_names.usa_1910_2013` "
            + "WHERE state = 'WA' "
            + "GROUP BY name";
    queryDryRun(query);
  }

  public static void queryDryRun(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();

      QueryJobConfiguration queryConfig =
          QueryJobConfiguration.newBuilder(query).setDryRun(true).setUseQueryCache(false).build();

      Job job = bigquery.create(JobInfo.of(queryConfig));
      JobStatistics.QueryStatistics statistics = job.getStatistics();

      System.out.println(
          "Query dry run performed successfully." + statistics.getTotalBytesProcessed());
    } catch (BigQueryException e) {
      System.out.println("Query not performed \n" + e.toString());
    }
  }
}

Node.js

在試行這個範例之前，請先按照 BigQuery 快速入門導覽課程：使用用戶端程式庫中的 Node.js 設定說明進行操作。詳情請參閱 BigQuery Node.js API 參考說明文件。

如要向 BigQuery 進行驗證，請設定應用程式預設憑證。 詳情請參閱「設定用戶端程式庫的驗證機制」。

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

async function queryDryRun() {
  // Runs a dry query of the U.S. given names dataset for the state of Texas.

  const query = `SELECT name
    FROM \`bigquery-public-data.usa_names.usa_1910_2013\`
    WHERE state = 'TX'
    LIMIT 100`;

  // For all options, see https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/query
  const options = {
    query: query,
    // Location must match that of the dataset(s) referenced in the query.
    location: 'US',
    dryRun: true,
  };

  // Run the query as a job
  const [job] = await bigquery.createQueryJob(options);

  // Print the status and statistics
  console.log('Status:');
  console.log(job.metadata.status);
  console.log('\nJob Statistics:');
  console.log(job.metadata.statistics);
}

PHP

在試行這個範例之前，請先按照 BigQuery 快速入門導覽課程：使用用戶端程式庫中的 PHP 設定說明進行操作。詳情請參閱 BigQuery PHP API 參考說明文件。

如要向 BigQuery 進行驗證，請設定應用程式預設憑證。 詳情請參閱「設定用戶端程式庫的驗證機制」。

use Google\Cloud\BigQuery\BigQueryClient;

/**
 * Dry runs the given query
 *
 * @param string $projectId The project Id of your Google Cloud Project.
 * @param string $query The query to be run. For eg: $query = 'SELECT id, view_count FROM `bigquery-public-data.stackoverflow.posts_questions`'
 */
function dry_run_query(string $projectId, string $query): void
{
    // Construct a BigQuery client object.
    $bigQuery = new BigQueryClient([
      'projectId' => $projectId,
    ]);

    // Set job configs
    $jobConfig = $bigQuery->query($query);
    $jobConfig->useQueryCache(false);
    $jobConfig->dryRun(true);

    // Extract query results
    $queryJob = $bigQuery->startJob($jobConfig);
    $info = $queryJob->info();

    printf('This query will process %s bytes' . PHP_EOL, $info['statistics']['totalBytesProcessed']);
}

Python

在試行這個範例之前，請先按照 BigQuery 快速入門導覽課程：使用用戶端程式庫中的 Python 設定說明進行操作。詳情請參閱 BigQuery Python API 參考說明文件。

如要向 BigQuery 進行驗證，請設定應用程式預設憑證。 詳情請參閱「設定用戶端程式庫的驗證機制」。

from google.cloud import bigquery

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

job_config = bigquery.QueryJobConfig(dry_run=True, use_query_cache=False)

# Start the query, passing in the extra configuration.
query_job = client.query(
    (
        "SELECT name, COUNT(*) as name_count "
        "FROM `bigquery-public-data.usa_names.usa_1910_2013` "
        "WHERE state = 'WA' "
        "GROUP BY name"
    ),
    job_config=job_config,
)  # Make an API request.

# A dry run query completes immediately.
print("This query will process {} bytes.".format(query_job.total_bytes_processed))

後續步驟

如要搜尋及篩選其他 Google Cloud 產品的程式碼範例，請參閱Google Cloud 範例瀏覽器。