junaiddshaukat opened a new issue, #38955:
URL: https://github.com/apache/beam/issues/38955
Tracking issue: #18479
Follows: #38843 (Redistribute + type-agnostic ExecutableStage edge, merged)
## Summary
First slice of the WatermarkManager. The runner needs a watermark before any
stateful transform (GroupByKey etc.) can land, so this goes in next per the
plan agreed with @je-ik. WatermarkManager is too large for one PR, so it's
split; this part is the in-memory core, decoupled from Kafka wiring so it can
be unit-tested in isolation.
## Design (agreed with @je-ik on Slack)
A stage's input watermark is min() over its upstream source partitions'
committed watermarks. Tracking is keyed on *source partitions*, not producer
instances:
- the total source-partition count travels in-band with every report, so the
reader always knows how many it's waiting for;
- a partition is owned by exactly one live instance, and on failure its
partitions are reassigned and the new owner keeps reporting — so a killed
instance never leaves the reader stuck (no instance liveness tracking, no
describeConsumerGroups, no generationId needed).
This was validated in a standalone Kafka Streams PoC before implementation.
## Scope (this PR)
- WatermarkManager: observe(sourcePartition, committedWatermarkMillis,
totalSourcePartitions); holds at BoundedWindow.TIMESTAMP_MIN_VALUE until
every source partition has reported; then emits min(); output is clamped
non-decreasing; a change in totalSourcePartitions re-opens the hold (the
"revert" case, without an explicit epoch).
- Unit tests for hold/emit, monotonicity, partition-count change, validation.
## Out of scope (later parts)
- Part 2: wire it into ExecutableStageProcessor — flush
(sourcePartition, committedWatermark, totalSourcePartitions) atomically
with
the offset commit (EOS), fan out to all downstream partitions, consume +
feed the manager, replace the provisional "flush on every watermark"
behavior; real-Kafka integration tests over the 5 scenarios (steady,
scale-out, clean scale-in, SIGKILL, partition reassignment).
- Part 3: persistence / watermark holds and downstream timer firing once
state + timers land.
## Testing
9 unit tests; ./gradlew :runners:kafka-streams:check green.
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