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https://issues.apache.org/jira/browse/FLINK-4576?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15635986#comment-15635986
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Aljoscha Krettek commented on FLINK-4576:
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Yes, that was my thinking as well.
The {{OperatorChain}} code is a bit of a mess. But yes, essentially
{{ChainingOutput}} directly forwards elements/watermarks/etc to the next
operator in the chain.
The logic with the idle watermarks will be somewhat tricky to get right:
normally, the watermark is the minimum of the input watermarks. Assume that an
operator has three inputs, one is idle, the others have watermark 10 and 15,
respectively. Now, the idle operator starts emitting again and the watermark
that it emits is 5. Our operator now has to ignore those watermarks until they
catch up to the current minimum watermark (which was 10 but could increase in
the meantime) because the watermark is not allowed to go backwards.
> Low Watermark Service in JobManager for Streaming Sources
> ---------------------------------------------------------
>
> Key: FLINK-4576
> URL: https://issues.apache.org/jira/browse/FLINK-4576
> Project: Flink
> Issue Type: New Feature
> Components: JobManager, Streaming, TaskManager
> Reporter: Tzu-Li (Gordon) Tai
> Assignee: Tzu-Li (Gordon) Tai
> Priority: Blocker
> Fix For: 1.2.0
>
>
> As per discussion in FLINK-4341 by [~aljoscha] and [~StephanEwen], we need a
> low watermark service in the JobManager to support transparent resharding /
> partition discovery for our Kafka and Kinesis consumers (and any future
> streaming connectors in general for which the external system may elastically
> scale up and down independently of the parallelism of sources in Flink). The
> main idea is to let source subtasks that don't emit their own watermarks
> (because they currently don't have data partitions to consume) emit the low
> watermark across all subtasks, instead of simply emitting a Long.MAX_VALUE
> watermark and forbidding them to be assigned partitions in the future.
> The proposed implementation, from a high-level: a {{LowWatermarkCoordinator}}
> will be added to execution graphs, periodically triggering only the source
> vertices with a {{RetrieveLowWatermark}} message. The tasks reply to the
> JobManager through the actor gateway (or a new interface after FLINK-4456
> gets merged) with a {{ReplyLowWatermark}} message. When the coordinator
> collects all low watermarks for a particular source vertex and determines the
> aggregated low watermark for this round (accounting only values that are
> larger than the aggregated low watermark of the last round), it sends a
> {{NotifyNewLowWatermark}} message to the source vertex's tasks.
> The messages will only be relevant to tasks that implement an internal
> {{LowWatermarkCooperatingTask}} interface. For now, only {{SourceStreamTask}}
> should implement {{LowWatermarkCooperatingTask}}.
> Source functions should implement a public {{LowWatermarkListener}} interface
> if they wish to get notified of the aggregated low watermarks across
> subtasks. Connectors like the Kinesis consumer can choose to emit this
> watermark if the subtask currently does not have any shards, so that
> downstream operators may still properly advance time windows (implementation
> for this is tracked as a separate issue).
> Overall, the service will include -
> New messages between JobManager <-> TaskManager:
> {{RetrieveLowWatermark(jobId, jobVertexId, taskId, timestamp)}}
> {{ReplyLowWatermark(jobId, jobVertexId, taskId, currentLowWatermark)}}
> {{NotifyNewLowWatermark(jobId, jobVertexId, taskId, newLowWatermark,
> timestamp)}}
> New internal task interface {{LowWatermarkCooperatingTask}} in flink-runtime
> New public interface {{LowWatermarkListener}} in flink-streaming-java
> Might also need to extend {{SourceFunction.SourceContext}} to support
> retrieving the current low watermark of sources.
> Any feedback for this is appreciated!
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