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Question: Does RisingWave plan to support pattern recognition in materialized views similar to Flink's CEP?
Context:
Apache Flink's Complex Event Processing (CEP) library enables pattern detection in event streams using declarative patterns (e.g., BEGIN.where(...).followedBy(...).within()). This is particularly useful for scenarios like fraud detection or failure sequence analysis [1].
Current State in RisingWave:
RisingWave's materialized views excel at continuous SQL-based aggregations and window operations, but lack native syntax for temporal pattern matching on event sequences [2][3].
Ask:
Is there a roadmap to support Flink-style CEP expressions (e.g., MATCH_RECOGNIZE or custom pattern operators) in materialized views?
If planned, what would be the expected implementation approach (e.g., leveraging existing SQL:2016 standards vs. custom syntax)?
For use cases requiring multi-event pattern detection (e.g., "3 failed logins within 5 minutes followed by a success"), what are the current recommended workarounds?
Community Engagement:
Should this be tracked via a specific GitHub issue? (e.g., similar to Issue #12435 on watermark propagation) [4]
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Question: Does RisingWave plan to support pattern recognition in materialized views similar to Flink's CEP?
Context:
Apache Flink's Complex Event Processing (CEP) library enables pattern detection in event streams using declarative patterns (e.g.,
BEGIN.where(...).followedBy(...).within()
). This is particularly useful for scenarios like fraud detection or failure sequence analysis [1].Current State in RisingWave:
RisingWave's materialized views excel at continuous SQL-based aggregations and window operations, but lack native syntax for temporal pattern matching on event sequences [2] [3].
Ask:
MATCH_RECOGNIZE
or custom pattern operators) in materialized views?Community Engagement:
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