Query a public dataset with the BigQuery client libraries

Query a public dataset with the BigQuery client libraries

Learn how to query a public dataset with the BigQuery client libraries.

---

To follow step-by-step guidance for this task directly in the Google Cloud console, select your preferred programming language:

C#

Take the C# tour

Go

Take the Go tour

Java

Take the Java tour

Node.js

Take the Node.js tour

PHP

Take the PHP tour

Python

Take the Python tour

Ruby

Take the Ruby tour

---

Before you begin

1. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

   Go to project selector

2. Choose whether to use the BigQuery sandbox at no charge, or to enable billing for your Google Cloud project.

   If you do not enable billing for a project, you automatically work in the BigQuery sandbox. The BigQuery sandbox lets you learn BigQuery with a limited set of BigQuery features at no charge. If you do not plan to use your project beyond this document, we recommend that you use the BigQuery sandbox.

3. Enable the BigQuery API.

   Enable the API

   For new projects, the BigQuery API is automatically enabled.

4. In the Google Cloud console, activate Cloud Shell.

   Activate Cloud Shell

5. Activate your Google Cloud project in Cloud Shell:

   gcloud config set project PROJECT_ID
   

   Replace PROJECT_ID with the project that you selected for this walkthrough.

   The output is similar to the following:

   Updated property [core/project].
   

Query a public dataset

Select one of the following languages:

C#

1. In Cloud Shell, create a new C# project and file:

   dotnet new console -n BigQueryCsharpDemo
   

   The output is similar to the following. Several lines are omitted to simplify the output.

   Welcome to .NET 6.0!
   ---------------------
   SDK Version: 6.0.407
   ...
   The template "Console App" was created successfully.
   ...
   

   This command creates a C# project that's named BigQueryCsharpDemo and a file that's named Program.cs.

2. Open the Cloud Shell Editor:

   cloudshell workspace BigQueryCsharpDemo
   

3. To open a terminal in the Cloud Shell Editor, click the icon, and then click Terminal > New Terminal:

   

4. Install the BigQuery client library for C#:

   dotnet add package Google.Cloud.BigQuery.V2
   

   The output is similar to the following. Several lines are omitted to simplify the output.

   Determining projects to restore...
   Writing /tmp/tmpF7EKSd.tmp
   ...
   info : Writing assets file to disk.
   ...
   

5. Set the variable GOOGLE_PROJECT_ID to the value GOOGLE_CLOUD_PROJECT and export the variable:

   export GOOGLE_PROJECT_ID=$GOOGLE_CLOUD_PROJECT
   

6. In the Explorer pane, locate your BIGQUERYCSHARPDEMO project.

7. Click the Program.cs file to open it.

8. To create a query against the bigquery-public-data.stackoverflow dataset that returns the top 10 most viewed Stack Overflow pages and their view counts, replace the contents of the file with the following code:

   
   using System;
   using Google.Cloud.BigQuery.V2;
   
   namespace GoogleCloudSamples
   {
       public class Program
       {
           public static void Main(string[] args)
           {
               string projectId = Environment.GetEnvironmentVariable("GOOGLE_PROJECT_ID");
               var client = BigQueryClient.Create(projectId);
               string query = @"SELECT
                   CONCAT(
                       'https://stackoverflow.com/questions/',
                       CAST(id as STRING)) as url, view_count
                   FROM `bigquery-public-data.stackoverflow.posts_questions`
                   WHERE tags like '%google-bigquery%'
                   ORDER BY view_count DESC
                   LIMIT 10";
               var result = client.ExecuteQuery(query, parameters: null);
               Console.Write("\nQuery Results:\n------------\n");
               foreach (var row in result)
               {
                   Console.WriteLine($"{row["url"]}: {row["view_count"]} views");
               }
           }
       }
   }
   

9. In the terminal, run the Program.cs script. If you are prompted to authorize Cloud Shell and agree to the terms, click Authorize.

   dotnet run
   

   The result is similar to the following:

   Query Results:
   ------------
   https://stackoverflow.com/questions/35159967: 170023 views
   https://stackoverflow.com/questions/22879669: 142581 views
   https://stackoverflow.com/questions/10604135: 132406 views
   https://stackoverflow.com/questions/44564887: 128781 views
   https://stackoverflow.com/questions/27060396: 127008 views
   https://stackoverflow.com/questions/12482637: 120766 views
   https://stackoverflow.com/questions/20673986: 115720 views
   https://stackoverflow.com/questions/39109817: 108368 views
   https://stackoverflow.com/questions/11057219: 105175 views
   https://stackoverflow.com/questions/43195143: 101878 views
   

You have successfully queried a public dataset with the BigQuery C# client library.

Go

1. In Cloud Shell, create a new Go project and file:

   mkdir bigquery-go-quickstart \
       && touch \
       bigquery-go-quickstart/app.go
   

   This command creates a Go project that's named bigquery-go-quickstart and a file that's named app.go.

2. Open the Cloud Shell Editor:

   cloudshell workspace bigquery-go-quickstart
   

3. To open a terminal in the Cloud Shell Editor, click the icon, and then click Terminal > New Terminal:

   

4. Create a go.mod file:

   go mod init quickstart
   

   The output is similar to the following:

   go: creating new go.mod: module quickstart
   go: to add module requirements and sums:
           go mod tidy
   

5. Install the BigQuery client library for Go:

   go get cloud.google.com/go/bigquery
   

   The output is similar to the following. Several lines are omitted to simplify the output.

   go: downloading cloud.google.com/go/bigquery v1.49.0
   go: downloading cloud.google.com/go v0.110.0
   ...
   go: added cloud.google.com/go/bigquery v1.49.0
   go: added cloud.google.com/go v0.110.0
   

6. In the Explorer pane, locate your BIGQUERY-GO-QUICKSTART project.

7. Click the app.go file to open it.

8. To create a query against the bigquery-public-data.stackoverflow dataset that returns the top 10 most viewed Stack Overflow pages and their view counts, copy the following code into the app.go file:

   
   // Command simpleapp queries the Stack Overflow public dataset in Google BigQuery.
   package main
   
   import (
   	"context"
   	"fmt"
   	"io"
   	"log"
   	"os"
   
   	"cloud.google.com/go/bigquery"
   	"google.golang.org/api/iterator"
   )
   
   
   func main() {
   	projectID := os.Getenv("GOOGLE_CLOUD_PROJECT")
   	if projectID == "" {
   		fmt.Println("GOOGLE_CLOUD_PROJECT environment variable must be set.")
   		os.Exit(1)
   	}
   
   	ctx := context.Background()
   
   	client, err := bigquery.NewClient(ctx, projectID)
   	if err != nil {
   		log.Fatalf("bigquery.NewClient: %v", err)
   	}
   	defer client.Close()
   
   	rows, err := query(ctx, client)
   	if err != nil {
   		log.Fatal(err)
   	}
   	if err := printResults(os.Stdout, rows); err != nil {
   		log.Fatal(err)
   	}
   }
   
   // query returns a row iterator suitable for reading query results.
   func query(ctx context.Context, client *bigquery.Client) (*bigquery.RowIterator, error) {
   
   	query := client.Query(
   		`SELECT
   			CONCAT(
   				'https://stackoverflow.com/questions/',
   				CAST(id as STRING)) as url,
   			view_count
   		FROM ` + "`bigquery-public-data.stackoverflow.posts_questions`" + `
   		WHERE tags like '%google-bigquery%'
   		ORDER BY view_count DESC
   		LIMIT 10;`)
   	return query.Read(ctx)
   }
   
   type StackOverflowRow struct {
   	URL       string `bigquery:"url"`
   	ViewCount int64  `bigquery:"view_count"`
   }
   
   // printResults prints results from a query to the Stack Overflow public dataset.
   func printResults(w io.Writer, iter *bigquery.RowIterator) error {
   	for {
   		var row StackOverflowRow
   		err := iter.Next(&row)
   		if err == iterator.Done {
   			return nil
   		}
   		if err != nil {
   			return fmt.Errorf("error iterating through results: %w", err)
   		}
   
   		fmt.Fprintf(w, "url: %s views: %d\n", row.URL, row.ViewCount)
   	}
   }
   

9. In the terminal, run the app.go script. If you are prompted to authorize Cloud Shell and agree to the terms, click Authorize.

   go run app.go
   

   The result is similar to the following:

   https://stackoverflow.com/questions/35159967 : 170023 views
   https://stackoverflow.com/questions/22879669 : 142581 views
   https://stackoverflow.com/questions/10604135 : 132406 views
   https://stackoverflow.com/questions/44564887 : 128781 views
   https://stackoverflow.com/questions/27060396 : 127008 views
   https://stackoverflow.com/questions/12482637 : 120766 views
   https://stackoverflow.com/questions/20673986 : 115720 views
   https://stackoverflow.com/questions/39109817 : 108368 views
   https://stackoverflow.com/questions/11057219 : 105175 views
   https://stackoverflow.com/questions/43195143 : 101878 views
   

You have successfully queried a public dataset with the BigQuery Go client library.

Java

1. In Cloud Shell, create a new Java project using Apache Maven:

   mvn archetype:generate \
       -DgroupId=com.google.app \
       -DartifactId=bigquery-java-quickstart \
       -DinteractiveMode=false
   

   This command creates a Maven project that's named bigquery-java-quickstart.

   The output is similar to the following. Several lines are omitted to simplify the output.

   [INFO] Scanning for projects...
   ...
   [INFO] Building Maven Stub Project (No POM) 1
   ...
   [INFO] BUILD SUCCESS
   ...
   

   There are many dependency management systems that you can use other than Maven. For more information, learn how to set up a Java development environment to use with client libraries.

2. Rename the App.java file that Maven creates by default:

   mv \
       bigquery-java-quickstart/src/main/java/com/google/app/App.java \
       bigquery-java-quickstart/src/main/java/com/google/app/SimpleApp.java
   

3. Open the Cloud Shell Editor:

   cloudshell workspace bigquery-java-quickstart
   

4. If you are prompted whether to synchronize the Java classpath or configuration, click Always.

   If you are not prompted and encounter an error that is related to the classpath during this walkthrough, do the following:

   1. Click File > Preferences > Open Settings (UI).
   2. Click Extensions > Java.
   3. Scroll to Configuration: Update Build Configuration and select automatic.

5. In the Explorer pane, locate your BIGQUERY-JAVA-QUICKSTART project.

6. Click the pom.xml file to open it.

7. Inside the <dependencies> tag, add the following dependency after any existing ones. Do not replace any existing dependencies.

   <dependency>
     <groupId>com.google.cloud</groupId>
     <artifactId>google-cloud-bigquery</artifactId>
   </dependency>
   

8. On the line following the closing tag (</dependencies>), add the following:

   <dependencyManagement>
     <dependencies>
       <dependency>
         <groupId>com.google.cloud</groupId>
         <artifactId>libraries-bom</artifactId>
         <version>26.1.5</version>
         <type>pom</type>
         <scope>import</scope>
       </dependency>
     </dependencies>
   </dependencyManagement>
   

9. In the Explorer pane, in your BIGQUERY-JAVA-QUICKSTART project, click src > main/java/com/google/app > SimpleApp.java. The file opens.

10. To create a query against the bigquery-public-data.stackoverflow dataset, leave the first line of the file (package com.google.app;), and replace the remaining contents of the file with the following code:

    
    import com.google.cloud.bigquery.BigQuery;
    import com.google.cloud.bigquery.BigQueryException;
    import com.google.cloud.bigquery.BigQueryOptions;
    import com.google.cloud.bigquery.FieldValueList;
    import com.google.cloud.bigquery.Job;
    import com.google.cloud.bigquery.JobId;
    import com.google.cloud.bigquery.JobInfo;
    import com.google.cloud.bigquery.QueryJobConfiguration;
    import com.google.cloud.bigquery.TableResult;
    
    
    public class SimpleApp {
    
      public static void main(String... args) throws Exception {
        // TODO(developer): Replace these variables before running the app.
        String projectId = "MY_PROJECT_ID";
        simpleApp(projectId);
      }
    
      public static void simpleApp(String projectId) {
        try {
          BigQuery bigquery = BigQueryOptions.getDefaultInstance().getService();
          QueryJobConfiguration queryConfig =
              QueryJobConfiguration.newBuilder(
                      "SELECT CONCAT('https://stackoverflow.com/questions/', "
                          + "CAST(id as STRING)) as url, view_count "
                          + "FROM `bigquery-public-data.stackoverflow.posts_questions` "
                          + "WHERE tags like '%google-bigquery%' "
                          + "ORDER BY view_count DESC "
                          + "LIMIT 10")
                  // Use standard SQL syntax for queries.
                  // See: https://cloud.google.com/bigquery/sql-reference/
                  .setUseLegacySql(false)
                  .build();
    
          JobId jobId = JobId.newBuilder().setProject(projectId).build();
          Job queryJob = bigquery.create(JobInfo.newBuilder(queryConfig).setJobId(jobId).build());
    
          // Wait for the query to complete.
          queryJob = queryJob.waitFor();
    
          // Check for errors
          if (queryJob == null) {
            throw new RuntimeException("Job no longer exists");
          } else if (queryJob.getStatus().getError() != null) {
            // You can also look at queryJob.getStatus().getExecutionErrors() for all
            // errors, not just the latest one.
            throw new RuntimeException(queryJob.getStatus().getError().toString());
          }
    
          // Get the results.
          TableResult result = queryJob.getQueryResults();
    
          // Print all pages of the results.
          for (FieldValueList row : result.iterateAll()) {
            // String type
            String url = row.get("url").getStringValue();
            String viewCount = row.get("view_count").getStringValue();
            System.out.printf("%s : %s views\n", url, viewCount);
          }
        } catch (BigQueryException | InterruptedException e) {
          System.out.println("Simple App failed due to error: \n" + e.toString());
        }
      }
    }

    The query returns the top 10 most viewed Stack Overflow pages and their view counts.

11. Right-click SimpleApp.java and click Run Java. If you are prompted to authorize Cloud Shell and agree to the terms, click Authorize.

    The result is similar to the following:

    https://stackoverflow.com/questions/35159967 : 170023 views
    https://stackoverflow.com/questions/22879669 : 142581 views
    https://stackoverflow.com/questions/10604135 : 132406 views
    https://stackoverflow.com/questions/44564887 : 128781 views
    https://stackoverflow.com/questions/27060396 : 127008 views
    https://stackoverflow.com/questions/12482637 : 120766 views
    https://stackoverflow.com/questions/20673986 : 115720 views
    https://stackoverflow.com/questions/39109817 : 108368 views
    https://stackoverflow.com/questions/11057219 : 105175 views
    https://stackoverflow.com/questions/43195143 : 101878 views
    

You have successfully queried a public dataset with the BigQuery Java client library.

Node.js

1. In Cloud Shell, create a new Node.js project and file:

   mkdir bigquery-node-quickstart \
       && touch \
       bigquery-node-quickstart/app.js
   

   This command creates a Node.js project that's named bigquery-node-quickstart and a file that's named app.js.

2. Open the Cloud Shell Editor:

   cloudshell workspace bigquery-node-quickstart
   

3. To open a terminal in the Cloud Shell Editor, click the icon, and then click Terminal > New Terminal:

   

4. Install the BigQuery client library for Node.js:

   npm install --save @google-cloud/bigquery
   

   The output is similar to the following:

   added 63 packages in 2s
   

5. In the Explorer pane, locate your BIGQUERY-NODE-QUICKSTART project.

6. Click the app.js file to open it.

7. To create a query against the bigquery-public-data.stackoverflow dataset that returns the top 10 most viewed Stack Overflow pages and their view counts, copy the following code into the app.js file:

   // Import the Google Cloud client library
   const {BigQuery} = require('@google-cloud/bigquery');
   
   async function queryStackOverflow() {
     // Queries a public Stack Overflow dataset.
   
     // Create a client
     const bigqueryClient = new BigQuery();
   
     // The SQL query to run
     const sqlQuery = `SELECT
       CONCAT(
         'https://stackoverflow.com/questions/',
         CAST(id as STRING)) as url,
       view_count
       FROM \`bigquery-public-data.stackoverflow.posts_questions\`
       WHERE tags like '%google-bigquery%'
       ORDER BY view_count DESC
       LIMIT 10`;
   
     const options = {
       query: sqlQuery,
       // Location must match that of the dataset(s) referenced in the query.
       location: 'US',
     };
   
     // Run the query
     const [rows] = await bigqueryClient.query(options);
   
     console.log('Query Results:');
     rows.forEach(row => {
       const url = row['url'];
       const viewCount = row['view_count'];
       console.log(`url: ${url}, ${viewCount} views`);
     });
   }
   queryStackOverflow();

8. In the terminal, run the app.js script. If you are prompted to authorize Cloud Shell and agree to the terms, click Authorize.

   node app.js
   

   The result is similar to the following:

   Query Results:
   url: https://stackoverflow.com/questions/35159967, 170023 views
   url: https://stackoverflow.com/questions/22879669, 142581 views
   url: https://stackoverflow.com/questions/10604135, 132406 views
   url: https://stackoverflow.com/questions/44564887, 128781 views
   url: https://stackoverflow.com/questions/27060396, 127008 views
   url: https://stackoverflow.com/questions/12482637, 120766 views
   url: https://stackoverflow.com/questions/20673986, 115720 views
   url: https://stackoverflow.com/questions/39109817, 108368 views
   url: https://stackoverflow.com/questions/11057219, 105175 views
   url: https://stackoverflow.com/questions/43195143, 101878 views
   

You have successfully queried a public dataset with the BigQuery Node.js client library.

PHP

1. In Cloud Shell, create a new PHP project and file:

   mkdir bigquery-php-quickstart \
       && touch \
       bigquery-php-quickstart/app.php
   

   This command creates a PHP project that's named bigquery-php-quickstart and a file that's named app.php.

2. Open the Cloud Shell Editor:

   cloudshell workspace bigquery-php-quickstart
   

3. To open a terminal in the Cloud Shell Editor, click the icon, and then click Terminal > New Terminal:

   

4. Install the BigQuery client library for PHP:

   composer require google/cloud-bigquery
   

   The output is similar to the following. Several lines are omitted to simplify the output.

   Running composer update google/cloud-bigquery
   Loading composer repositories with package information
   Updating dependencies
   ...
   No security vulnerability advisories found
   Using version ^1.24 for google/cloud-bigquery
   

5. In the Explorer pane, locate your BIGQUERY-PHP-QUICKSTART project.

6. Click the app.php file to open it.

7. To create a query against the bigquery-public-data.stackoverflow dataset that returns the top 10 most viewed Stack Overflow pages and their view counts, copy the following code into the app.php file:

   <?php
   # ...
   
   require __DIR__ . '/vendor/autoload.php';
   
   use Google\Cloud\BigQuery\BigQueryClient;
   
   
   $bigQuery = new BigQueryClient();
   $query = <<<ENDSQL
   SELECT
     CONCAT(
       'https://stackoverflow.com/questions/',
       CAST(id as STRING)) as url,
     view_count
   FROM `bigquery-public-data.stackoverflow.posts_questions`
   WHERE tags like '%google-bigquery%'
   ORDER BY view_count DESC
   LIMIT 10;
   ENDSQL;
   $queryJobConfig = $bigQuery->query($query);
   $queryResults = $bigQuery->runQuery($queryJobConfig);
   
   if ($queryResults->isComplete()) {
       $i = 0;
       $rows = $queryResults->rows();
       foreach ($rows as $row) {
           printf('--- Row %s ---' . PHP_EOL, ++$i);
           printf('url: %s, %s views' . PHP_EOL, $row['url'], $row['view_count']);
       }
       printf('Found %s row(s)' . PHP_EOL, $i);
   } else {
       throw new Exception('The query failed to complete');
   }

8. In the terminal, run the app.php script. If you are prompted to authorize Cloud Shell and agree to the terms, click Authorize.

   php app.php
   

   The result is similar to the following:

   --- Row 1 ---
   url: https://stackoverflow.com/questions/35159967, 170023 views
   --- Row 2 ---
   url: https://stackoverflow.com/questions/22879669, 142581 views
   --- Row 3 ---
   url: https://stackoverflow.com/questions/10604135, 132406 views
   --- Row 4 ---
   url: https://stackoverflow.com/questions/44564887, 128781 views
   --- Row 5 ---
   url: https://stackoverflow.com/questions/27060396, 127008 views
   --- Row 6 ---
   url: https://stackoverflow.com/questions/12482637, 120766 views
   --- Row 7 ---
   url: https://stackoverflow.com/questions/20673986, 115720 views
   --- Row 8 ---
   url: https://stackoverflow.com/questions/39109817, 108368 views
   --- Row 9 ---
   url: https://stackoverflow.com/questions/11057219, 105175 views
   --- Row 10 ---
   url: https://stackoverflow.com/questions/43195143, 101878 views
   Found 10 row(s)
   

You have successfully queried a public dataset with the BigQuery PHP client library.

Python

1. In Cloud Shell, create a new Python project and file:

   mkdir bigquery-python-quickstart \
       && touch \
       bigquery-python-quickstart/app.py
   

   This command creates a Python project that's named bigquery-python-quickstart and a file that's named app.py.

2. Open the Cloud Shell Editor:

   cloudshell workspace bigquery-python-quickstart
   

3. To open a terminal in the Cloud Shell Editor, click the icon, and then click Terminal > New Terminal:

   

4. Install the BigQuery client library for Python:

   pip install --upgrade google-cloud-bigquery
   

   The output is similar to the following. Several lines are omitted to simplify the output.

   Installing collected packages: google-cloud-bigquery
   ...
   Successfully installed google-cloud-bigquery-3.9.0
   ...
   

5. In the Explorer pane, locate your BIGQUERY-PYTHON-QUICKSTART project.

6. Click the app.py file to open it.

7. To create a query against the bigquery-public-data.stackoverflow dataset that returns the top 10 most viewed Stack Overflow pages and their view counts, copy the following code into the app.py file:

   from google.cloud import bigquery
   
   
   
   def query_stackoverflow():
       client = bigquery.Client()
       query_job = client.query(
           """
           SELECT
             CONCAT(
               'https://stackoverflow.com/questions/',
               CAST(id as STRING)) as url,
             view_count
           FROM `bigquery-public-data.stackoverflow.posts_questions`
           WHERE tags like '%google-bigquery%'
           ORDER BY view_count DESC
           LIMIT 10"""
       )
   
       results = query_job.result()  # Waits for job to complete.
   
       for row in results:
           print("{} : {} views".format(row.url, row.view_count))
   
   
   if __name__ == "__main__":
       query_stackoverflow()

8. In the terminal, run the app.py script. If you are prompted to authorize Cloud Shell and agree to the terms, click Authorize.

   python app.py
   

   The result is similar to the following:

   https://stackoverflow.com/questions/35159967 : 170023 views
   https://stackoverflow.com/questions/22879669 : 142581 views
   https://stackoverflow.com/questions/10604135 : 132406 views
   https://stackoverflow.com/questions/44564887 : 128781 views
   https://stackoverflow.com/questions/27060396 : 127008 views
   https://stackoverflow.com/questions/12482637 : 120766 views
   https://stackoverflow.com/questions/20673986 : 115720 views
   https://stackoverflow.com/questions/39109817 : 108368 views
   https://stackoverflow.com/questions/11057219 : 105175 views
   https://stackoverflow.com/questions/43195143 : 101878 views
   

You have successfully queried a public dataset with the BigQuery Python client library.

Ruby

1. In Cloud Shell, create a new Ruby project and file:

   mkdir bigquery-ruby-quickstart \
       && touch \
       bigquery-ruby-quickstart/app.rb
   

   This command creates a Ruby project that's named bigquery-ruby-quickstart and a file that's named app.rb.

2. Open the Cloud Shell Editor:

   cloudshell workspace bigquery-ruby-quickstart
   

3. To open a terminal in the Cloud Shell Editor, click the icon, and then click Terminal > New Terminal:

   

4. Install the BigQuery client library for Ruby:

   gem install google-cloud-bigquery
   

   The output is similar to the following. Several lines are omitted to simplify the output.

   23 gems installed
   

5. In the Explorer pane, locate your BIGQUERY-RUBY-QUICKSTART project.

6. Click the app.rb file to open it.

7. To create a query against the bigquery-public-data.stackoverflow dataset that returns the top 10 most viewed Stack Overflow pages and their view counts, copy the following code into the app.rb file:

   require "google/cloud/bigquery"
   
   # This uses Application Default Credentials to authenticate.
   # @see https://cloud.google.com/bigquery/docs/authentication/getting-started
   bigquery = Google::Cloud::Bigquery.new
   
   sql     = "SELECT " \
             "CONCAT('https://stackoverflow.com/questions/', CAST(id as STRING)) as url, view_count " \
             "FROM `bigquery-public-data.stackoverflow.posts_questions` " \
             "WHERE tags like '%google-bigquery%' " \
             "ORDER BY view_count DESC LIMIT 10"
   results = bigquery.query sql
   
   results.each do |row|
     puts "#{row[:url]}: #{row[:view_count]} views"
   end

8. In the terminal, run the app.rb script. If you are prompted to authorize Cloud Shell and agree to the terms, click Authorize.

   ruby app.rb
   

   The result is similar to the following:

   https://stackoverflow.com/questions/35159967: 170023 views
   https://stackoverflow.com/questions/22879669: 142581 views
   https://stackoverflow.com/questions/10604135: 132406 views
   https://stackoverflow.com/questions/44564887: 128781 views
   https://stackoverflow.com/questions/27060396: 127008 views
   https://stackoverflow.com/questions/12482637: 120766 views
   https://stackoverflow.com/questions/20673986: 115720 views
   https://stackoverflow.com/questions/39109817: 108368 views
   https://stackoverflow.com/questions/11057219: 105175 views
   https://stackoverflow.com/questions/43195143: 101878 views
   

You have successfully queried a public dataset with the BigQuery Ruby client library.

Clean up

To avoid incurring charges to your Google Cloud account, either delete your Google Cloud project, or delete the resources that you created in this walkthrough.

Delete the project

The easiest way to eliminate billing is to delete the project that you created for the tutorial.

To delete the project:

Caution: Deleting a project has the following effects:

• Everything in the project is deleted. If you used an existing project for the tasks in this document, when you delete it, you also delete any other work you've done in the project.
• Custom project IDs are lost. When you created this project, you might have created a custom project ID that you want to use in the future. To preserve the URLs that use the project ID, such as an appspot.com URL, delete selected resources inside the project instead of deleting the whole project.

If you plan to explore multiple architectures, tutorials, or quickstarts, reusing projects can help you avoid exceeding project quota limits.

1. In the Google Cloud console, go to the Manage resources page.

   Go to Manage resources

2. In the project list, select the project that you want to delete, and then click Delete.
3. In the dialog, type the project ID, and then click Shut down to delete the project.

Delete the resources

If you used an existing project, delete the resources that you created:

C#

1. In Cloud Shell, move up a directory:

   cd ..
   

2. Delete the BigQueryCsharpDemo folder that you created:

   rm -R BigQueryCsharpDemo
   

   The -R flag deletes all assets in a folder.

Go

1. In Cloud Shell, move up a directory:

   cd ..
   

2. Delete the bigquery-go-quickstart folder that you created:

   rm -R bigquery-go-quickstart
   

   The -R flag deletes all assets in a folder.

Java

1. In Cloud Shell, move up a directory:

   cd ..
   

2. Delete the bigquery-java-quickstart folder that you created:

   rm -R bigquery-java-quickstart
   

   The -R flag deletes all assets in a folder.

Node.js

1. In Cloud Shell, move up a directory:

   cd ..
   

2. Delete the bigquery-node-quickstart folder that you created:

   rm -R bigquery-node-quickstart
   

   The -R flag deletes all assets in a folder.

PHP

1. In Cloud Shell, move up a directory:

   cd ..
   

2. Delete the bigquery-php-quickstart folder that you created:

   rm -R bigquery-php-quickstart
   

   The -R flag deletes all assets in a folder.

Python

1. In Cloud Shell, move up a directory:

   cd ..
   

2. Delete the bigquery-python-quickstart folder that you created:

   rm -R bigquery-python-quickstart
   

   The -R flag deletes all assets in a folder.

Ruby

1. In Cloud Shell, move up a directory:

   cd ..
   

2. Delete the bigquery-ruby-quickstart folder that you created:

   rm -R bigquery-ruby-quickstart
   

   The -R flag deletes all assets in a folder.

What's next

• Learn more about using the BigQuery client libraries.
• Learn more about BigQuery public datasets.
• Learn how to load data into BigQuery.
• Learn more about querying data in BigQuery.
• Get updates about BigQuery.
• Learn about BigQuery pricing.
• Learn about BigQuery quotas and limits.