Dry run query

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Run a dry run query.

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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. 

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

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. 

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

Before trying this sample, follow the Node.js setup instructions in the BigQuery quickstart using client libraries. For more information, see the BigQuery Node.js API reference documentation. 

// 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

Before trying this sample, follow the PHP setup instructions in the BigQuery quickstart using client libraries. For more information, see the BigQuery PHP API reference documentation. 

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

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. 

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))

What's next

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