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Posted to dev@flink.apache.org by "Guowei Ma (Jira)" <ji...@apache.org> on 2026/06/01 03:28:00 UTC

[jira] [Created] (FLINK-39807) [umbrella] FLIP-577: AI-Native Flink — Umbrella for Multimodal Data Processing

Guowei Ma created FLINK-39807:
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             Summary: [umbrella] FLIP-577: AI-Native Flink — Umbrella for Multimodal Data Processing
                 Key: FLINK-39807
                 URL: https://issues.apache.org/jira/browse/FLINK-39807
             Project: Flink
          Issue Type: New Feature
            Reporter: Guowei Ma


This is the umbrella issue tracking FLIP-577: AI-Native Flink — An Umbrella Proposal for Multimodal Data Processing.

_FLIP:_ [FLIP-577|[https://cwiki.apache.org/confluence/pages/viewpage.action?pageId=421957275]] _Discussion thread:_ [dev@ thread|[https://lists.apache.org/thread/l5obwo4kvjblqnx24btsv4rwjwoflb6d]]

User workloads are shifting from BI analytics to multimodal data processing centered on model inference — data expands from structured records to images/video/audio/embeddings, resources move from CPU to mixed CPU/GPU, and execution moves from row-oriented to vectorized batch. This umbrella proposes evolving Flink from a unified stream-batch compute engine into one that natively supports AI workloads (AI-Native), decomposed into 11 sub-FLIPs across three layers:
 * _Layer 1 — Core Runtime Primitives:_ RpcOperator; multimodal type system and OBJECT_REF.
 * _Layer 2 — Workload Expression and Execution:_ Python DataFrame API; multimodal Source/Sink connector API; GPU resource declaration and independent deployment; built-in multimodal operators and AI functions; Arrow columnar transport.
 * _Layer 3 — Production-Grade Operational Guarantees:_ non-disruptive scaling for CPU and GPU operators; Unaligned Checkpoint enhancements; Pipeline-Region-based independent checkpoints.

Most sub-FLIPs have no hard dependencies and can be advanced in parallel. This umbrella seeks consensus on the overall direction only; detailed design and APIs are deferred to each sub-FLIP. All changes are incremental. Sub-FLIPs will be tracked as separate issues and linked here.



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