Create an application using Apache Beam - Managed Service for Apache Flink
Create dependent resourcesWrite sample records to the input streamDownload and examine the application codeCompile the application codeUpload the Apache Flink streaming Java codeCreate and run the Managed Service for Apache Flink applicationClean UpNext steps

Amazon Managed Service for Apache Flink was previously known as Amazon Kinesis Data Analytics for Apache Flink.

Create an application using Apache Beam

In this exercise, you create a Managed Service for Apache Flink application that transforms data using Apache Beam. Apache Beam is a programming model for processing streaming data. For information about using Apache Beam with Managed Service for Apache Flink, see Use Apache Beam with Managed Service for Apache Flink applications.

Note

To set up required prerequisites for this exercise, first complete the Tutorial: Get started using the DataStream API in Managed Service for Apache Flink exercise.

Create dependent resources

Before you create a Managed Service for Apache Flink application for this exercise, you create the following dependent resources:

  • Two Kinesis data streams (ExampleInputStream and ExampleOutputStream)

  • An Amazon S3 bucket to store the application's code (ka-app-code-<username>)

You can create the Kinesis streams and Amazon S3 bucket using the console. For instructions for creating these resources, see the following topics:

  • Creating and Updating Data Streams in the Amazon Kinesis Data Streams Developer Guide. Name your data streams ExampleInputStream and ExampleOutputStream.

  • How Do I Create an S3 Bucket? in the Amazon Simple Storage Service User Guide. Give the Amazon S3 bucket a globally unique name by appending your login name, such as ka-app-code-<username>.

Write sample records to the input stream

In this section, you use a Python script to write random strings to the stream for the application to process.

Note

This section requires the AWS SDK for Python (Boto).

  1. Create a file named ping.py with the following contents:

    import json
import boto3
import random

kinesis = boto3.client('kinesis')

while True:
        data = random.choice(['ping', 'telnet', 'ftp', 'tracert', 'netstat'])
        print(data)
        kinesis.put_record(
                StreamName="ExampleInputStream",
                Data=data,
                PartitionKey="partitionkey")

  2. Run the ping.py script: 

    $ python ping.py

    Keep the script running while completing the rest of the tutorial.

Download and examine the application code

The Java application code for this example is available from GitHub. To download the application code, do the following:

  1. Install the Git client if you haven't already. For more information, see Installing Git.

  2. Clone the remote repository with the following command:

    git clone https://github.com/aws-samples/amazon-kinesis-data-analytics-examples.git

  3. Navigate to the amazon-kinesis-data-analytics-java-examples/Beam directory.

The application code is located in the BasicBeamStreamingJob.java file. Note the following about the application code:

  • The application uses the Apache Beam ParDo to process incoming records by invoking a custom transform function called PingPongFn.

    The code to invoke the PingPongFn function is as follows:

    .apply("Pong transform",
    ParDo.of(new PingPongFn())

  • Managed Service for Apache Flink applications that use Apache Beam require the following components. If you don't include these components and versions in your pom.xml, your application loads the incorrect versions from the environment dependencies, and since the versions do not match, your application crashes at runtime.

    <jackson.version>2.10.2</jackson.version>
...
<dependency>
    <groupId>com.fasterxml.jackson.module</groupId>
    <artifactId>jackson-module-jaxb-annotations</artifactId>
    <version>2.10.2</version>
</dependency>

  • The PingPongFn transform function passes the input data into the output stream, unless the input data is ping, in which case it emits the string pong\n to the output stream.

    The code of the transform function is as follows:

        private static class PingPongFn extends DoFn<KinesisRecord, byte[]> {
    private static final Logger LOG = LoggerFactory.getLogger(PingPongFn.class);
    
    @ProcessElement
    public void processElement(ProcessContext c) {
        String content = new String(c.element().getDataAsBytes(), StandardCharsets.UTF_8);
        if (content.trim().equalsIgnoreCase("ping")) {
            LOG.info("Ponged!");
            c.output("pong\n".getBytes(StandardCharsets.UTF_8));
        } else {
            LOG.info("No action for: " + content);
            c.output(c.element().getDataAsBytes());
        }
    }
}

Compile the application code

To compile the application, do the following:

  1. Install Java and Maven if you haven't already. For more information, see Complete the required prerequisites in the Tutorial: Get started using the DataStream API in Managed Service for Apache Flink tutorial.

  2. Compile the application with the following command: 

    mvn package -Dflink.version=1.15.2 -Dflink.version.minor=1.8
    Note

    The provided source code relies on libraries from Java 11.

Compiling the application creates the application JAR file (target/basic-beam-app-1.0.jar).

Upload the Apache Flink streaming Java code

In this section, you upload your application code to the Amazon S3 bucket you created in the Create dependent resources section.

  1. In the Amazon S3 console, choose the ka-app-code-<username> bucket, and choose Upload.

  2. In the Select files step, choose Add files. Navigate to the basic-beam-app-1.0.jar file that you created in the previous step.

  3. You don't need to change any of the settings for the object, so choose Upload.

Your application code is now stored in an Amazon S3 bucket where your application can access it.

Create and run the Managed Service for Apache Flink application

Follow these steps to create, configure, update, and run the application using the console.

Create the Application

  1. Open the Managed Service for Apache Flink console at https://console.aws.amazon.com/flink

  2. On the Managed Service for Apache Flink dashboard, choose Create analytics application.

  3. On the Managed Service for Apache Flink - Create application page, provide the application details as follows:

    • For Application name, enter MyApplication.

    • For Runtime, choose Apache Flink.

      Note

      Apache Beam is not presently compatible with Apache Flink version 1.19 or later.

    • Select Apache Flink version 1.15 from the version pulldown.

  4. For Access permissions, choose Create / update IAM role kinesis-analytics-MyApplication-us-west-2.

  5. Choose Create application.

Note

When you create a Managed Service for Apache Flink application using the console, you have the option of having an IAM role and policy created for your application. Your application uses this role and policy to access its dependent resources. These IAM resources are named using your application name and Region as follows:

  • Policy: kinesis-analytics-service-MyApplication-us-west-2

  • Role: kinesis-analytics-MyApplication-us-west-2

Edit the IAM policy

Edit the IAM policy to add permissions to access the Kinesis data streams.

  1. Open the IAM console at https://console.aws.amazon.com/iam/.

  2. Choose Policies. Choose the kinesis-analytics-service-MyApplication-us-west-2 policy that the console created for you in the previous section.

  3. On the Summary page, choose Edit policy. Choose the JSON tab.

  4. Add the highlighted section of the following policy example to the policy. Replace the sample account IDs (012345678901) with your account ID.

    {
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "ReadCode",
            "Effect": "Allow",
            "Action": [
                "s3:GetObject",
                "logs:DescribeLogGroups",
                "s3:GetObjectVersion"
            ],
            "Resource": [
                "arn:aws:logs:us-west-2:012345678901:log-group:*",
                "arn:aws:s3:::ka-app-code-<username>/basic-beam-app-1.0.jar"
            ]
        },
        {
            "Sid": "DescribeLogStreams",
            "Effect": "Allow",
            "Action": "logs:DescribeLogStreams",
            "Resource": "arn:aws:logs:us-west-2:012345678901:log-group:/aws/kinesis-analytics/MyApplication:log-stream:*"
        },
        {
            "Sid": "PutLogEvents",
            "Effect": "Allow",
            "Action": "logs:PutLogEvents",
            "Resource": "arn:aws:logs:us-west-2:012345678901:log-group:/aws/kinesis-analytics/MyApplication:log-stream:kinesis-analytics-log-stream"
        },
        {
            "Sid": "ListCloudwatchLogGroups",
            "Effect": "Allow",
            "Action": [
                "logs:DescribeLogGroups"
            ],
            "Resource": [
                "arn:aws:logs:us-west-2:012345678901:log-group:*"
            ]
        },
        {
            "Sid": "ReadInputStream",
            "Effect": "Allow",
            "Action": "kinesis:*",
            "Resource": "arn:aws:kinesis:us-west-2:012345678901:stream/ExampleInputStream"
        },
        {
            "Sid": "WriteOutputStream",
            "Effect": "Allow",
            "Action": "kinesis:*",
            "Resource": "arn:aws:kinesis:us-west-2:012345678901:stream/ExampleOutputStream"
        }
    ]
}

Configure the application

  1. On the MyApplication page, choose Configure.

  2. On the Configure application page, provide the Code location:

    • For Amazon S3 bucket, enter ka-app-code-<username>.

    • For Path to Amazon S3 object, enter basic-beam-app-1.0.jar.

  3. Under Access to application resources, for Access permissions, choose Create / update IAM role kinesis-analytics-MyApplication-us-west-2.

  4. Enter the following:

    Group ID Key Value
    BeamApplicationProperties InputStreamName ExampleInputStream
    BeamApplicationProperties OutputStreamName ExampleOutputStream
    BeamApplicationProperties AwsRegion us-west-2

  5. Under Monitoring, ensure that the Monitoring metrics level is set to Application.

  6. For CloudWatch logging, select the Enable check box.

  7. Choose Update.

Note

When you choose to enable CloudWatch logging, Managed Service for Apache Flink creates a log group and log stream for you. The names of these resources are as follows:

  • Log group: /aws/kinesis-analytics/MyApplication

  • Log stream: kinesis-analytics-log-stream

This log stream is used to monitor the application. This is not the same log stream that the application uses to send results.

Run the application

The Flink job graph can be viewed by running the application, opening the Apache Flink dashboard, and choosing the desired Flink job.

You can check the Managed Service for Apache Flink metrics on the CloudWatch console to verify that the application is working.

Clean up AWS resources

This section includes procedures for cleaning up AWS resources created in the Tumbling Window tutorial.

Delete your Managed Service for Apache Flink application

  1. Open the Managed Service for Apache Flink console at https://console.aws.amazon.com/flink

  2. in the Managed Service for Apache Flink panel, choose MyApplication.

  3. In the application's page, choose Delete and then confirm the deletion.

Delete your Kinesis data streams

  1. Open the Kinesis console at https://console.aws.amazon.com/kinesis.

  2. In the Kinesis Data Streams panel, choose ExampleInputStream.

  3. In the ExampleInputStream page, choose Delete Kinesis Stream and then confirm the deletion.

  4. In the Kinesis streams page, choose the ExampleOutputStream, choose Actions, choose Delete, and then confirm the deletion.

Delete your Amazon S3 object and bucket

  1. Open the Amazon S3 console at https://console.aws.amazon.com/s3/.

  2. Choose the ka-app-code-<username> bucket.

  3. Choose Delete and then enter the bucket name to confirm deletion.

Delete your IAM resources

  1. Open the IAM console at https://console.aws.amazon.com/iam/.

  2. In the navigation bar, choose Policies.

  3. In the filter control, enter kinesis.

  4. Choose the kinesis-analytics-service-MyApplication-us-west-2 policy.

  5. Choose Policy Actions and then choose Delete.

  6. In the navigation bar, choose Roles.

  7. Choose the kinesis-analytics-MyApplication-us-west-2 role.

  8. Choose Delete role and then confirm the deletion.

Delete your CloudWatch resources

  1. Open the CloudWatch console at https://console.aws.amazon.com/cloudwatch/.

  2. In the navigation bar, choose Logs.

  3. Choose the /aws/kinesis-analytics/MyApplication log group.

  4. Choose Delete Log Group and then confirm the deletion.

Next steps

Now that you've created and run a basic Managed Service for Apache Flink application that transforms data using Apache Beam, see the following application for an example of a more advanced Managed Service for Apache Flink solution.