At-Most-Once Semantics

At-Most-Once Semantics is a processing guarantee in distributed systems ensuring that each message or event will be delivered or processed at most one time, meaning it could be processed either zero times or exactly one time.

This guarantee prioritizes avoiding duplicate processing over preventing data loss. If a failure occurs during processing or delivery, the system might 'lose' the message rather than risk sending or processing it again upon recovery. It's often considered the 'weakest' of the common processing guarantees (At-Most-Once, At-Least-Once, Exactly-Once).

Context: Processing Guarantees

In distributed systems, managing message delivery amidst failures requires trade-offs:

1. At-Most-Once: Process zero or one time. Avoids duplicates but risks data loss. Often called 'best-effort' delivery.
2. At-Least-Once: Process one or more times. Prevents data loss but risks duplicates.
3. Exactly-Once Semantics (EOS): Process exactly one time. Prevents both data loss and duplicates, but is the most complex to implement.

At-Most-Once is typically simpler to implement but is often unsuitable for applications where data loss cannot be tolerated.

How At-Most-Once Works (Example Scenario)

Consider a simple pipeline: Producer -> Message Queue -> Consumer

Scenario 1: Failure before processing

1. Producer sends Message M1: Queue receives M1.
2. Queue delivers M1 to Consumer: Consumer receives M1.
3. Queue marks M1 as delivered (or Consumer acknowledges receipt immediately): The queue considers its job done for M1.
4. Failure! The consumer crashes before it finishes processing M1.
5. Recovery: The consumer restarts, but since the queue already marked M1 as delivered (or received an early acknowledgment), M1 is not redelivered.
6. Result: M1 is lost; it was delivered but never fully processed.

Scenario 2: Acknowledgment after processing (less common for pure At-Most-Once, often leans towards At-Least-Once if acknowledgment fails)

If acknowledgment happens after processing, a failure during acknowledgment could lead to redelivery, breaking the 'at most once' guarantee. Pure At-Most-Once often involves acknowledging delivery early or simply not retrying on failure, accepting potential loss.

Implications and Trade-offs

• Pro: No Duplicates: Ensures that downstream operations are never performed more than once for a given message.
• Pro: Simpler Implementation: Often easier for systems to provide this guarantee as it doesn't require complex state management for retries or acknowledgments in the same way as At-Least-Once or Exactly-Once.
• Con: Potential Data Loss: This is the major drawback. Failures can lead to messages being skipped entirely, which is unacceptable for many critical data pipelines (e.g., financial transactions, vital sensor readings).

When is At-Most-Once Acceptable?

This guarantee might be acceptable for use cases where:

• Occasional data loss is tolerable (e.g., non-critical metrics sampling, some types of logging where volume is high and individual events aren't crucial).
• The cost or complexity of implementing stronger guarantees outweighs the value of processing every single event.
• Downstream systems cannot handle duplicates at all, and data loss is preferred.

At-Most-Once in Stream Processing (RisingWave Context)

Modern stream processing systems like RisingWave generally prioritize avoiding data loss and aim for stronger guarantees like At-Least-Once or, ideally, Exactly-Once Semantics (EOS) for their internal state management.

Providing only At-Most-Once semantics is typically not the goal for RisingWave's core processing or state. However, understanding the concept is important:

• Sources/Sinks: It's possible (though less common for robust systems) for an external source or sink connected to RisingWave to only offer At-Most-Once guarantees. If a source provides At-Most-Once, RisingWave might miss input events permanently. If a sink provides At-Most-Once, RisingWave might successfully process data internally, but the final output could be lost if the sink fails to persist it and doesn't retry.
• Configuration: In some systems, certain configurations (e.g., disabling acknowledgments or retries) might implicitly result in At-Most-Once behavior, often trading reliability for potentially lower latency or simpler operation, but this is usually not recommended for critical pipelines.

For reliable stream processing, especially involving stateful operations where every event matters for correctness (like in RisingWave's materialized views), At-Most-Once semantics are generally insufficient.

Related Glossary Terms

• Exactly-Once Semantics (EOS)
• At-Least-Once Semantics
• Idempotency
• Fault Tolerance
• Message Queue (MQ)
• Event Streaming Platform (ESP)