Apache Flink 2.1.0: Ushers in a New Era of Unified Real-Time Data + AI with Comprehensive Upgrades
The Apache Flink PMC is proud to announce the release of Apache Flink 2.1.0. This marks a significant milestone in the evolution of the real-time data processing engine into a unified Data + AI platform. This release brings together 116 global contributors, implements 16 FLIPs (Flink Improvement Proposals), and resolves over 220 issues, with a strong focus on deepening the integration of real-time AI and intelligent stream processing:
Extends the ML_PREDICT Table-Valued Function (TVF), empowering real-time invocation of AI models within Flink SQL, laying the foundation for building end-to-end real-time AI workflows.
Process Table Functions (PTFs) open up the Flink SQL engine for more event-driven application. Giving access to Flink’s managed state, event-time and timer services, and underlying table changelogs.
Adds the VARIANT data type for efficient handling of semi-structured data like JSON. Combined with the PARSE_JSON function and lakehouse formats (e.g., Apache Paimon), it enables dynamic schema data analysis.
