Example: Read From a Kinesis Stream in a Different Account - Amazon Kinesis Data Analytics
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Example: Read From a Kinesis Stream in a Different Account

This example demonstrates how to create an Amazon Kinesis Data Analytics application that reads data from a Kinesis stream in a different account. In this example, you will use one account for the source Kinesis stream, and a second account for the Kinesis Data Analytics application and sink Kinesis stream.


  • In this tutorial, you modify the Getting Started example to read data from a Kinesis stream in a different account. Complete the Getting Started (DataStream API) tutorial before proceeding.

  • You need two Amazon accounts to complete this tutorial: one for the source stream, and one for the application and the sink stream. Use the Amazon account you used for the Getting Started tutorial for the application and sink stream. Use a different Amazon account for the source stream.


You will access your two Amazon accounts by using named profiles. Modify your Amazon credentials and configuration files to include two profiles that contain the region and connection information for your two accounts.

The following example credential file contains two named profiles, ka-source-stream-account-profile and ka-sink-stream-account-profile. Use the account you used for the Getting Started tutorial for the sink stream account.

[ka-source-stream-account-profile] aws_access_key_id=AKIAIOSFODNN7EXAMPLE aws_secret_access_key=wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY [ka-sink-stream-account-profile] aws_access_key_id=AKIAI44QH8DHBEXAMPLE aws_secret_access_key=je7MtGbClwBF/2Zp9Utk/h3yCo8nvbEXAMPLEKEY

The following example configuration file contains the same named profiles with region and output format information.

[profile ka-source-stream-account-profile] region=us-west-2 output=json [profile ka-sink-stream-account-profile] region=us-west-2 output=json

This tutorial does not use the ka-sink-stream-account-profile. It is included as an example of how to access two different Amazon accounts using profiles.

For more information on using named profiles with the Amazon CLI, see Named Profiles in the Amazon Command Line Interface documentation.

Create Source Kinesis Stream

In this section, you will create the Kinesis stream in the source account.

Enter the following command to create the Kinesis stream that the application will use for input. Note that the --profile parameter specifies which account profile to use.

$ aws kinesis create-stream \ --stream-name SourceAccountExampleInputStream \ --shard-count 1 \ --profile ka-source-stream-account-profile

Create and Update IAM Roles and Policies

To allow object access across Amazon accounts, you create an IAM role and policy in the source account. Then, you modify the IAM policy in the sink account. For information about creating IAM roles and policies, see the following topics in the Amazon Identity and Access Management User Guide:

Sink Account Roles and Policies

  1. Edit the kinesis-analytics-service-MyApplication-us-west-2 policy from the Getting Started tutorial. This policy allows the role in the source account to be assumed in order to read the source stream.


    When you use the console to create your application, the console creates a policy called kinesis-analytics-service-<application name>-<application region>, and a role called kinesis-analytics-<application name>-<application region>.

    Add the highlighted section below to the policy. Replace the sample account ID (SOURCE01234567) with the ID of the account you will use for the source stream.

    { "Version": "2012-10-17", "Statement": [ { "Sid": "AssumeRoleInSourceAccount", "Effect": "Allow", "Action": "sts:AssumeRole", "Resource": "arn:aws:iam::SOURCE01234567:role/KA-Source-Stream-Role" }, { "Sid": "ReadCode", "Effect": "Allow", "Action": [ "s3:GetObject", "s3:GetObjectVersion" ], "Resource": [ "arn:aws:s3:::ka-app-code-username/aws-kinesis-analytics-java-apps-1.0.jar" ] }, { "Sid": "ListCloudwatchLogGroups", "Effect": "Allow", "Action": [ "logs:DescribeLogGroups" ], "Resource": [ "arn:aws:logs:us-west-2:SINK012345678:log-group:*" ] }, { "Sid": "ListCloudwatchLogStreams", "Effect": "Allow", "Action": [ "logs:DescribeLogStreams" ], "Resource": [ "arn:aws:logs:us-west-2:SINK012345678:log-group:/aws/kinesis-analytics/MyApplication:log-stream:*" ] }, { "Sid": "PutCloudwatchLogs", "Effect": "Allow", "Action": [ "logs:PutLogEvents" ], "Resource": [ "arn:aws:logs:us-west-2:SINK012345678:log-group:/aws/kinesis-analytics/MyApplication:log-stream:kinesis-analytics-log-stream" ] } ] }
  2. Open the kinesis-analytics-MyApplication-us-west-2 role, and make a note of its Amazon Resource Name (ARN). You will need it in the next section. The role ARN looks like the following.


Source Account Roles and Policies

  1. Create a policy in the source account called KA-Source-Stream-Policy. Use the following JSON for the policy. Replace the sample account number with the account number of the source account.

    { "Version": "2012-10-17", "Statement": [ { "Sid": "ReadInputStream", "Effect": "Allow", "Action": [ "kinesis:DescribeStream", "kinesis:GetRecords", "kinesis:GetShardIterator", "kinesis:ListShards" ], "Resource": "arn:aws:kinesis:us-west-2:SOURCE123456784:stream/SourceAccountExampleInputStream" } ] }
  2. Create a role in the source account called KA-Source-Stream-Role. Do the following to create the role using the Kinesis Analytics use case:

    1. In the IAM Management Console, choose Create Role.

    2. On the Create Role page, choose Amazon Service. In the service list, choose Kinesis.

    3. In the Select your use case section, choose Kinesis Analytics.

    4. Choose Next: Permissions.

    5. Add the KA-Source-Stream-Policy permissions policy you created in the previous step. Choose Next:Tags.

    6. Choose Next: Review.

    7. Name the role KA-Source-Stream-Role. Your application will use this role to access the source stream.

  3. Add the kinesis-analytics-MyApplication-us-west-2 ARN from the sink account to the trust relationship of the KA-Source-Stream-Role role in the source account:

    1. Open the KA-Source-Stream-Role in the IAM console.

    2. Choose the Trust Relationships tab.

    3. Choose Edit trust relationship.

    4. Use the following code for the trust relationship. Replace the sample account ID (SINK012345678) with your sink account ID.

      { "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Principal": { "AWS": "arn:aws:iam::SINK012345678:role/service-role/kinesis-analytics-MyApplication-us-west-2" }, "Action": "sts:AssumeRole" } ] }

Update the Python Script

In this section, you update the Python script that generates sample data to use the source account profile.

Update the stock.py script with the following highlighted changes.

import json import boto3 import random import datetime import os os.environ['AWS_PROFILE'] ='ka-source-stream-account-profile' os.environ['AWS_DEFAULT_REGION'] = 'us-west-2' kinesis = boto3.client('kinesis') def getReferrer(): data = {} now = datetime.datetime.now() str_now = now.isoformat() data['event_time'] = str_now data['ticker'] = random.choice(['AAPL', 'AMZN', 'MSFT', 'INTC', 'TBV']) price = random.random() * 100 data['price'] = round(price, 2) return data while True: data = json.dumps(getReferrer()) print(data) kinesis.put_record( StreamName="SourceAccountExampleInputStream", Data=data, PartitionKey="partitionkey")

Update the Java Application

In this section, you update the Java application code to assume the source account role when reading from the source stream.

Make the following changes to the BasicStreamingJob.java file. Replace the example source account number (SOURCE01234567) with your source account number.

package com.amazonaws.services.kinesisanalytics; import com.amazonaws.services.kinesisanalytics.runtime.KinesisAnalyticsRuntime; import org.apache.flink.api.common.serialization.SimpleStringSchema; import org.apache.flink.streaming.api.datastream.DataStream; import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment; import org.apache.flink.streaming.connectors.kinesis.FlinkKinesisConsumer; import org.apache.flink.streaming.connectors.kinesis.FlinkKinesisProducer; import org.apache.flink.streaming.connectors.kinesis.config.ConsumerConfigConstants; import org.apache.flink.streaming.connectors.kinesis.config.AWSConfigConstants; import java.io.IOException; import java.util.Map; import java.util.Properties; /** * A basic Kinesis Data Analytics for Java application with Kinesis data streams * as source and sink. */ public class BasicStreamingJob { private static final String region = "us-west-2"; private static final String inputStreamName = "SourceAccountExampleInputStream"; private static final String outputStreamName = ExampleOutputStream; private static final String roleArn = "arn:aws:iam::SOURCE01234567:role/KA-Source-Stream-Role"; private static final String roleSessionName = "ksassumedrolesession"; private static DataStream<String> createSourceFromStaticConfig(StreamExecutionEnvironment env) { Properties inputProperties = new Properties(); inputProperties.setProperty(AWSConfigConstants.AWS_CREDENTIALS_PROVIDER, "ASSUME_ROLE"); inputProperties.setProperty(AWSConfigConstants.AWS_ROLE_ARN, roleArn); inputProperties.setProperty(AWSConfigConstants.AWS_ROLE_SESSION_NAME, roleSessionName); inputProperties.setProperty(ConsumerConfigConstants.AWS_REGION, region); inputProperties.setProperty(ConsumerConfigConstants.STREAM_INITIAL_POSITION, "LATEST"); return env.addSource(new FlinkKinesisConsumer<>(inputStreamName, new SimpleStringSchema(), inputProperties)); } private static KinesisStreamsSink<String> createSinkFromStaticConfig() { Properties outputProperties = new Properties(); outputProperties.setProperty(AWSConfigConstants.AWS_REGION, region); return KinesisStreamsSink.<String>builder() .setKinesisClientProperties(outputProperties) .setSerializationSchema(new SimpleStringSchema()) .setStreamName(outputProperties.getProperty("OUTPUT_STREAM", "ExampleOutputStream")) .setPartitionKeyGenerator(element -> String.valueOf(element.hashCode())) .build(); } public static void main(String[] args) throws Exception { // set up the streaming execution environment final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment(); DataStream<String> input = createSourceFromStaticConfig(env); input.addSink(createSinkFromStaticConfig()); env.execute("Flink Streaming Java API Skeleton"); } }

Build, Upload, and Run the Application

Do the following to update and run the application:

  1. Build the application again by running the following command in the directory with the pom.xml file.

    mvn package -Dflink.version=1.15.3
  2. Delete the previous JAR file from your Amazon Simple Storage Service (Amazon S3) bucket, and then upload the new aws-kinesis-analytics-java-apps-1.0.jar file to the S3 bucket.

  3. In the application's page in the Kinesis Data Analytics console, choose Configure, Update to reload the application JAR file.

  4. Run the stock.py script to send data to the source stream.

    python stock.py

The application now reads data from the Kinesis stream in the other account.

You can verify that the application is working by checking the PutRecords.Bytes metric of the ExampleOutputStream stream. If there is activity in the output stream, the application is functioning properly.