What's the difference between Scala 2.12 and Scala 2.13 versions? Sent: Tuesday, August 02, 2022 at 1:45 AM From: "David Arthur" <davidart...@apache.org> To: annou...@apache.org, "dev" <d...@kafka.apache.org>, "users" <users@kafka.apache.org>, "kafka-clients" <kafka-clie...@googlegroups.com> Subject: [ANNOUNCE] Apache Kafka 3.2.1 The Apache Kafka community is pleased to announce the release for Apache Kafka 3.2.1
This is a bugfix release with several fixes since the release of 3.2.0. A few of the major issues include: * KAFKA-14062 OAuth client token refresh fails with SASL extensions * KAFKA-14079 Memory leak in connectors using errors.tolerance=all * KAFKA-14024 Cooperative rebalance regression causing clients to get stuck All of the changes in this release can be found in the release notes: https://www.apache.org/dist/kafka/3.2.1/RELEASE_NOTES.html You can download the source and binary release (Scala 2.12 and 2.13) from: https://kafka.apache.org/downloads#3.2.1[https://kafka.apache.org/downloads#3.2.1] --------------------------------------------------------------------------------------------------- Apache Kafka is a distributed streaming platform with four core APIs: ** The Producer API allows an application to publish a stream of records to one or more Kafka topics. ** The Consumer API allows an application to subscribe to one or more topics and process the stream of records produced to them. ** The Streams API allows an application to act as a stream processor, consuming an input stream from one or more topics and producing an output stream to one or more output topics, effectively transforming the input streams to output streams. ** The Connector API allows building and running reusable producers or consumers that connect Kafka topics to existing applications or data systems. For example, a connector to a relational database might capture every change to a table. With these APIs, Kafka can be used for two broad classes of application: ** Building real-time streaming data pipelines that reliably get data between systems or applications. ** Building real-time streaming applications that transform or react to the streams of data. Apache Kafka is in use at large and small companies worldwide, including Capital One, Goldman Sachs, ING, LinkedIn, Netflix, Pinterest, Rabobank, Target, The New York Times, Uber, Yelp, and Zalando, among others. A big thank you for the following 19 contributors to this release! Akhilesh Chaganti, Bruno Cadonna, Christopher L. Shannon, David Arthur, Divij Vaidya, Eugene Tolbakov, Guozhang Wang, Ismael Juma, James Hughes, Jason Gustafson, Kirk True, Lucas Bradstreet, Luke Chen, Nicolas Guyomar, Niket Goel, Okada Haruki, Shawn Wang, Viktor Somogyi-Vass, Walker Carlson We welcome your help and feedback. For more information on how to report problems, and to get involved, visit the project website at https://kafka.apache.org/[https://kafka.apache.org/] Thank you! Regards, David Arthur
