The Amazon DynamoDB Streams Adapter implements the Amazon Kinesis interface so that your application can use KCL to consume and process data from a DynamoDB stream.
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README.md

DynamoDB Streams Kinesis Adapter for Java

DynamoDB Streams Kinesis Adapter implements the Amazon Kinesis interface so that your application can use KCL to consume and process data from a DynamoDB stream. You can get started in minutes using Maven.

Features

  • The DynamoDB Streams Kinesis Adapter for Amazon Kinesis Client Library (KCL) is the best way to ingest and process data records from DynamoDB Streams.
  • The KCL is designed to process streams from Amazon Kinesis, but by adding the DynamoDB Streams Kinesis Adapter, your application can process DynamoDB Streams instead, seamlessly and efficiently.

Release Notes

Latest Release (v1.4.0)

  • This release fixes an issue of high propagation delay of streams records when processing streams on small tables. This issue occurs when KCL ShardSyncer is not discovering new shards due to server side delays in shard creation or in reporting new shard creation to internal services. The code is implemented in a new implementation of IKinesisProxy interface called DynamoDBStreamsProxy which is part of the latest release.
  • This release requires Kinesis Client Library version >= 1.8.10. It is however recommended to use Kinesis Client Library version 1.9.0. Versions >= 1.8.10 have changes to allow IKinesisProxy injection into the KCL Worker builder which is required by DynamoDB Streams Kinesis Adapter v1.4.0 for injection of DynamoDBStreamsProxy into the KCL worker during initialization. Please refer to Kinesis Client Library release notes for 1.8.10 for more information.
  • Suggested AWS Java SDK version >= 1.11.218
  • It is highly recommended to configure Kinesis Client Library with MaxRecords = 1000 and IdleTimeInMillis = 500 to optimize DynamoDB Streams costs.

Guidance for injecting DynamoDBStreamsProxy into KCL worker when using DynamoDB Streams Kinesis Adapter v1.4.0.

To fix high propagation delay problems, opt-into using DynamoDBStreamsProxy (instead of the default KinesisProxy) by using the StreamsWorkerFactory factory method (shown below). This injects an instance of DynamoDBStreamsProxy into the created KCL worker.

       final Worker worker = StreamsWorkerFactory
           .createDynamoDbStreamsWorker(
               recordProcessorFactory,
               workerConfig,
               adapterClient,
               amazonDynamoDB,
               amazonCloudWatchClient);

Getting Started

  1. Sign up for AWS - Before you begin, you need an AWS account. Please see the AWS Account and Credentials section of the developer guide for information about how to create an AWS account and retrieve your AWS credentials. You don’t need this if you’re using DynamoDB Local.
  2. Minimum requirements - To run the SDK you will need Java 1.8+. For more information about the requirements and optimum settings for the SDK, please see the Java Development Environment section of the developer guide.
  3. Install the DynamoDB Streams Kinesis Adapter - Using Maven is the recommended way to install the DynamoDB Streams Kinesis Adapter and its dependencies, including the AWS SDK for Java. To download the code from GitHub, simply clone the repository by typing: git clone https://github.com/awslabs/dynamodb-streams-kinesis-adapter.git, and run the Maven command described below in "Building From Source". You may also depend on the maven artifact com.amazonaws:dynamodb-streams-kinesis-adapter.
  4. Build your first application - There is a walkthrough to help you build first application using this adapter. Please see Using the DynamoDB Streams Kinesis Adapter to Process Stream Records.

Including as a Maven dependency

Add the following to your Maven pom file:

<dependency>
    <groupId>com.amazonaws</groupId>
    <artifactId>dynamodb-streams-kinesis-adapter</artifactId>
    <version>1.4.0</version>
</dependency>

Building From Source

Once you check out the code from GitHub, you can build it using Maven: mvn clean install