16e8404dc4
* Fix a race condition between ShardConsumer shutdown and initialization When Kinesis shards have no data, there can be a race condition where the shard-end record processing from RecordProcessorThread interleaves with Scheduler performing initialization. This leads to ShardConsumer making incorrect state transition during initialization (moves from PROCESSING -> SHUTTING_DOWN) state and during shutdown handling it moves from SHUTTING_DOWN -> SHUTDOWN_COMPLETE without running the ShutdownTask. This can cause the ShardConsumer to not perform proper shutdown processing that is required for a child shard processing to be unblocked. So the child shard could be blocked forever unless the lease for the parent shard moves to a new worker and that worker does not run into the race condition. This patch fixes the race condition as follows: The intializationComplete invocation is not needed after needsInitialization has been set to false. Because initializationComplete is mean to perform initialization in an async manner, but once its done, the async task is a no-op in happy-path, but it can perform incorrect state transition during a race condition. |
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Amazon Kinesis Client Library for Java
The Amazon Kinesis Client Library for Java (Amazon KCL) enables Java developers to easily consume and process data from Amazon Kinesis.
Recommended Upgrade for All Users of the 1.x Amazon Kinesis Client
⚠️ We recommend customers to migrate to 1.14.1 or newer to avoid known bugs in 1.14.0 version
Recommended Upgrade for All Users of the 2.x Amazon Kinesis Client
⚠️ It's highly recommended for users of version 2.0 of the Amazon Kinesis Client to upgrade to version 2.0.3 or later. A bug has been identified in versions prior to 2.0.3 that could cause records to be delivered to the wrong record processor.
ℹ️ Amazon Kinesis Client versions 1.x are not impacted.
Please open an issue if you have any questions.
Features
- Provides an easy-to-use programming model for processing data using Amazon Kinesis
- Helps with scale-out and fault-tolerant processing
Getting Started
- 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.
- 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.
- 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.
- 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.
Building from Source
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.
Note: This command does not run integration tests.
To disable running unit tests in the build, add the property -Dskip.ut=true.
Running Integration Tests
Note that running integration tests creates AWS resources.
Integration tests require valid AWS credentials.
This will look for a default AWS profile specified in your local .aws/credentials.
To run all integration tests: mvn verify -DskipITs=false.
To run one integration tests, specify the integration test class: mvn -Dit.test="BasicStreamConsumerIntegrationTest" -DskipITs=false verify
Optionally, you can provide the name of an IAM user/role to run tests with as a string using this command: mvn -DskipITs=false -DawsProfile="<PROFILE_NAME>" verify.
Integration with the Kinesis Producer Library
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.
Amazon KCL support for other languages
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.
Using the KCL
The recommended way to use the KCL for Java is to consume it from Maven.
Version 2.x
<dependency>
<groupId>software.amazon.kinesis</groupId>
<artifactId>amazon-kinesis-client</artifactId>
<version>2.6.0</version>
</dependency>
Version 1.x
<dependency>
<groupId>com.amazonaws</groupId>
<artifactId>amazon-kinesis-client</artifactId>
<version>1.14.1</version>
</dependency>
Release Notes
| KCL Version | Changelog |
|---|---|
| 2.x | master/CHANGELOG.md |
| 1.x | v1.x/CHANGELOG.md |