The Amazon Kinesis Client Library for Java (Amazon KCL) enables Java developers to easily consume and process data from Amazon Kinesis.

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• Provides an easy-to-use programming model for processing data using Amazon Kinesis
• Helps with scale-out and fault-tolerant processing

1. Sign up for AWS — Before you begin, you need an AWS account. For more information about creating an AWS account and retrieving your AWS credentials, see AWS Account and Credentials in the AWS SDK for Java Developer Guide.
2. Sign up for Amazon Kinesis — Go to the Amazon Kinesis console to sign up for the service and create an Amazon Kinesis stream. For more information, see Create an Amazon Kinesis Stream in the Amazon Kinesis Developer Guide.
3. Minimum requirements — To use the Amazon Kinesis Client Library, you'll need Java 1.8+. For more information about Amazon Kinesis Client Library requirements, see Before You Begin in the Amazon Kinesis Developer Guide.
4. Using the Amazon Kinesis Client Library — The best way to get familiar with the Amazon Kinesis Client Library is to read Developing Record Consumer Applications in the Amazon Kinesis Developer Guide.

After you've downloaded the code from GitHub, you can build it using Maven. To disable GPG signing in the build, use this command: mvn clean install -Dgpg.skip=true

For producer-side developers using the Kinesis Producer Library (KPL), the KCL integrates without additional effort. When the KCL retrieves an aggregated Amazon Kinesis record consisting of multiple KPL user records, it will automatically invoke the KPL to extract the individual user records before returning them to the user.

To make it easier for developers to write record processors in other languages, we have implemented a Java based daemon, called MultiLangDaemon that does all the heavy lifting. Our approach has the daemon spawn a sub-process, which in turn runs the record processor, which can be written in any language. The MultiLangDaemon process and the record processor sub-process communicate with each other over STDIN and STDOUT using a defined protocol. There will be a one to one correspondence amongst record processors, child processes, and shards. For Python developers specifically, we have abstracted these implementation details away and expose an interface that enables you to focus on writing record processing logic in Python. This approach enables KCL to be language agnostic, while providing identical features and similar parallel processing model across all languages.

• Added the ability to create a prepared checkpoint when at SHARD_END.
  • PR #301
• Added the ability to subscribe to worker state change events.
  • PR #291
• Added support for custom lease managers.
  A custom LeaseManager can be provided to Worker.Builder that will be used to provide lease services. This makes it possible to implement custom lease management systems in addition to the default DynamoDB system.
  • PR #297
• Updated the version of the AWS Java SDK to 1.11.219