Access Live Bitbucket 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 Bitbucket data when paired with the CData JDBC Driver for Bitbucket. This article describes how to connect to and query Bitbucket 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 Bitbucket data. When you issue complex SQL queries to Bitbucket, the driver pushes supported SQL operations, like filters and aggregations, directly to Bitbucket 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 Bitbucket data using native data types.

Step 1: Gather connection properties and build a connection string

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

For most queries, you must set the Workspace. The only exception to this is the Workspaces table, which does not require this property to be set, as querying it provides a list of workspace slugs that can be used to set Workspace. To query this table, you must set Schema to 'Information' and execute the query SELECT * FROM Workspaces>.

Setting Schema to 'Information' displays general information. To connect to Bitbucket, set these parameters:

• Schema: To show general information about a workspace, such as its users, repositories, and projects, set this to Information. Otherwise, set this to the schema of the repository or project you are querying. To get a full set of available schemas, query the sys_schemas table.
• Workspace: Required if you are not querying the Workspaces table. This property is not required for querying the Workspaces table, as that query only returns a list of workspace slugs that can be used to set Workspace.

Authenticating to Bitbucket

Bitbucket supports OAuth authentication only. To enable this authentication from all OAuth flows, you must create a custom OAuth application, and set AuthScheme to OAuth.

Be sure to review the Help documentation for the required connection properties for you specific authentication needs (desktop applications, web applications, and headless machines).

Creating a custom OAuth application

From your Bitbucket account:

1. Go to Settings (the gear icon) and select Workspace Settings.
2. In the Apps and Features section, select OAuth Consumers.
3. Click Add Consumer.
4. Enter a name and description for your custom application.
5. Set the callback URL:
   • For desktop applications and headless machines, use http://localhost:33333 or another port number of your choice. The URI you set here becomes the CallbackURL property.
   • For web applications, set the callback URL to a trusted redirect URL. This URL is the web location the user returns to with the token that verifies that your application has been granted access.
6. If you plan to use client credentials to authenticate, you must select This is a private consumer. In the driver, you must set AuthScheme to client.
7. Select which permissions to give your OAuth application. These determine what data you can read and write with it.
8. To save the new custom application, click Save.
9. After the application has been saved, you can select it to view its settings. The application's Key and Secret are displayed. Record these for future use. You will use the Key to set the OAuthClientId and the Secret to set the OAuthClientSecret.

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 Bitbucket JDBC Driver. Double-click the JAR file or execute the jar file from the command line.

java -jar cdata.jdbc.bitbucket.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 Bitbucket 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 Bitbucket 20XX/lib/cdata.jdbc.bitbucket.jar" -DgroupId="org.cdata.connectors" -DartifactId="cdata-bitbucket-connector" -Dversion="23" -Dpackaging=jar

Add Dependencies

Within the Maven project's pom.xml file, add AWS and the CData JDBC Driver for Bitbucket] 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 Bitbucket

  <dependency>
   <groupId>org.cdata.connectors</groupId>
   <artifactId>cdata-bitbucket-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 Bitbucket
   4. Establishes a connection to Bitbucket using JDBC
   5. Executes the SQL query on Bitbucket
   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.bitbucket.BitbucketDriver");
    cdata.jdbc.bitbucket.BitbucketDriver driver = new cdata.jdbc.bitbucket.BitbucketDriver();
    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:bitbucket:RTK=52465...;Workspace=myworkspaceslug;Schema=Information;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 Bitbucket and start working with your live Bitbucket data in AWS Lambda. Reach out to our Support Team if you have any questions.