Access Live BigQuery Data in AWS Lambda (with IntelliJ IDEA)

AWS Lambda is a compute service that lets you build applications that respond quickly to new information and events. AWS Lambda functions can work with live BigQuery data when paired with the CData JDBC Driver for Google BigQuery. This article describes how to connect to and query BigQuery data from an AWS Lambda function built with Maven in IntelliJ.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live BigQuery data. When you issue complex SQL queries to BigQuery, the driver pushes supported SQL operations, like filters and aggregations, directly to BigQuery and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations). In addition, its built-in dynamic metadata querying allows you to work with and analyze BigQuery data using native data types.

Getting Started

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Step 1: Gather connection properties and build a connection string

Download the CData JDBC Driver for Google BigQuery installer, unzip the package, and run the JAR file to install the driver. Then gather the required connection properties.

Google uses the OAuth authentication standard. To access Google APIs on behalf of individual users, you can use the embedded credentials or you can register your own OAuth app.

OAuth also enables you to use a service account to connect on behalf of users in a Google Apps domain. To authenticate with a service account, register an application to obtain the OAuth JWT values.

In addition to the OAuth values, specify the DatasetId and ProjectId. See the "Getting Started" chapter of the help documentation for a guide to using OAuth.

NOTE: To use the JDBC driver in an AWS Lambda function, you will need a license (full or trial) and a Runtime Key (RTK). For more information on obtaining this license (or a trial), contact our sales team.

Built-in Connection String Designer

For assistance constructing the JDBC URL, use the connection string designer built into the BigQuery JDBC Driver. Double-click the JAR file or execute the jar file from the command line.

java -jar cdata.jdbc.googlebigquery.jar

👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)

Fill in the connection properties (including the RTK) and copy the connection string to the clipboard.

Step 2: Create a project in IntelliJ

1. In IntelliJ IDEA, click New Project.
2. Select "Maven Archetype" from the Generators
3. Name the project and select "maven.archetypes:maven-archetype-quickstart" Archetype.
4. Click "Create" 👁 Image
   

Install the CData JDBC Driver for Google BigQuery JAR File

Use the following Maven command from the project's root folder to install JAR file in the project.

mvn install:install-file -Dfile="PATH/TO/CData JDBC Driver for Google BigQuery 20XX/lib/cdata.jdbc.googlebigquery.jar" -DgroupId="org.cdata.connectors" -DartifactId="cdata-googlebigquery-connector" -Dversion="23" -Dpackaging=jar

Add Dependencies

Within the Maven project's pom.xml file, add AWS and the CData JDBC Driver for Google BigQuery] as dependencies (within the <dependencies> element) using the following XML.

• AWS

  <dependency>
   <groupId>com.amazonaws</groupId>
   <artifactId>aws-lambda-java-core</artifactId>
   <version>1.2.2</version> <!--Replace with the actual version-->
  </dependency>

• CData JDBC Driver for Google BigQuery

  <dependency>
   <groupId>org.cdata.connectors</groupId>
   <artifactId>cdata-googlebigquery-connector</artifactId>
   <version>25</version> <!--Replace with the actual version-->
  </dependency>

• Maven Shade Plugin to create a fat JAR

  <build>
   <plugins>
   <plugin>
   <groupId>org.apache.maven.plugins</groupId>
   <artifactId>maven-shade-plugin</artifactId>
   <version>3.4.1</version>
   <executions>
   <execution>
   <phase>package</phase>
   <goals>
   <goal>shade</goal>
   </goals>
   <configuration>
   <createDependencyReducedPom>false</createDependencyReducedPom>
   <transformers>
   <transformer implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">
   <mainClass>com.example.CDataLambda</mainClass>
   <!-- Change to your actual Lambda handler class -->
   </transformer>
   </transformers>
   </configuration>
   </execution>
   </executions>
   </plugin>
   </plugins>
  </build>

Create an AWS Lambda Function

For this sample project, we create two source files: CDataLambda.java and CDataLambdaTest.java.

Lambda Function Definition

1. Update CDataLambda to implement the RequestHandler interface from the AWS Lambda SDK. You will need to add the handleRequest method, which performs the following tasks when the Lambda function is triggered:
   1. Constructs a SQL query using the input
   2. Sets up AWS credentials and S3 configuration to store OAuth credentials.
   3. Registers the CData JDBC Driver for Google BigQuery
   4. Establishes a connection to BigQuery using JDBC
   5. Executes the SQL query on BigQuery
   6. Prints the results to the console
   7. Returns an output message

2. Use the complete Lambda class below, which includes the imports, class definition, and handleRequest method. Be sure to fill in your connection string values in the DriverManager.getConnection call.

   package com.example;
   
   import com.amazonaws.services.lambda.runtime.Context;
   import com.amazonaws.services.lambda.runtime.RequestHandler;
   
   import java.sql.Connection;
   import java.sql.DriverManager;
   import java.sql.ResultSet;
   import java.sql.ResultSetMetaData;
   import java.sql.SQLException;
   import java.sql.Statement;
   public class CDataLambda implements RequestHandler < Object, String > {
   
    @Override
    public String handleRequest(Object input, Context context) {
    String query = "SELECT * FROM " + input;
   
    String bucketName = "MY_AWS_BUCKET";
    String oauthSettings = "s3://" + bucketName + "/oauth/OAuthSettings.txt";
    String oauthConnection =
    "InitiateOAuth=REFRESH;" +
    "OAuthSettingsLocation=" + oauthSettings + ";";
    try {
    Class.forName("cdata.jdbc.googlebigquery.GoogleBigQueryDriver");
    cdata.jdbc.googlebigquery.GoogleBigQueryDriver driver = new cdata.jdbc.googlebigquery.GoogleBigQueryDriver();
    DriverManager.registerDriver(driver);
    } catch (SQLException ex) {
    // Registering the driver failed
    throw new RuntimeException("Failed to register JDBC driver", ex);
    } catch (ClassNotFoundException e) {
    // The driver class was not found in the classpath
    throw new RuntimeException("JDBC Driver class not found", e);
   
    }
    Connection connection = null;
    try {
    connection = DriverManager.getConnection("jdbc:cdata:googlebigquery:RTK=52465...;DataSetId=MyDataSetId;ProjectId=MyProjectId;InitiateOAuth=GETANDREFRESH;" + oauthConnection + "");
    } catch (SQLException ex) {
    context.getLogger().log("Error getting connection: " + ex.getMessage());
    } catch (Exception ex) {
    context.getLogger().log("Error: " + ex.getMessage());
    }
   
    if (connection != null) {
    context.getLogger().log("Connected Successfully!
   ");
    }
   
    ResultSet resultSet = null;
    try {
    //executing query
    Statement stmt = connection.createStatement();
    resultSet = stmt.executeQuery(query);
   
    ResultSetMetaData metaData = resultSet.getMetaData();
    int numCols = metaData.getColumnCount();
   
    //printing the results
    while (resultSet.next()) {
    for (int i = 1; i <= numCols; i++) {
    System.out.printf("%-25s", (resultSet.getObject(i) != null) ? resultSet.getObject(i).toString().replaceAll("
   ", "") : null);
    }
    System.out.print("
   ");
    }
    } catch (SQLException ex) {
    System.out.println("SQL Exception: " + ex.getMessage());
    } catch (Exception ex) {
    System.out.println("General exception: " + ex.getMessage());
    }
    return "v24 query: " + query + " complete";
    }
   }
   
   

Step 3: Deploy and run the lambda function

Once you build the function in Intellij, you are ready to deploy the entire Maven project as a single JAR file.

1. In IntelliJ, use the mvn install command to build the SNAPSHOT JAR file.

   Note: The Maven Shade Plugin generates two JARs in the target folder. Always upload the larger -shaded.jar file to AWS Lambda, as it contains all required dependencies.

2. Create a new function in AWS Lambda (or open an existing one).
3. Name the function, select an IAM role, and set the timeout value to a high enough value to ensure the function completes (depending on the result size of your query).
4. Click "Upload from" -> ".zip file" and select your SNAPSHOT JAR file. 👁 Uploading the SNAPSHOT JAR file.
   
5. In the "Runtime settings" section, click "Edit" and set Handler to your "handleRequest" method (e.g. package.class::handleRequest) 👁 Configuring the runtime handler.
   
6. You can now test the function. Set the "Event JSON" field to a table name and click, click "Test" 👁 Viewing the results.
   

Free Trial & More Information

Download a free 30-day trial of the CData JDBC Driver for Google BigQuery and start working with your live BigQuery data in AWS Lambda. Reach out to our Support Team if you have any questions.