Eliaaazzz opened a new pull request, #39825:
URL: https://github.com/apache/beam/pull/39825
`SparkTimerInternals.getNextProcessingTimer()` picked the eligible
processing-time timer with the latest timestamp, so when several timers for a
key were due in the same micro-batch their `@OnTimer` callbacks ran
latest-first: a callback scheduled for T2 observed state that the callback for
an earlier T1 had not written yet. `TimerUtils.getExpiredTimers` collected the
expired-timer sweep from an unordered set, so that path had no defined order
either.
Timers now fire earliest-first, matching `InMemoryTimerInternals` and the
other runners, and the timers fired by `triggerExpiredTimers` are sorted by
timestamp; the deletion-only sweep stays unsorted.
Earliest-first would also have surfaced superseded settings of a re-set
timer, which the old set-based store kept alongside the replacement. Timers are
therefore stored in a map keyed by namespace, id and family, so a later setting
replaces the prior one, per the `TimerInternals` contract. This also makes
`setTimer` constant-time where the interim replace-by-scan was linear per
insertion. Timers restored from state that predates this change collapse to the
setting with the latest target; a checkpoint written before it cannot be
recovered by an upgraded application anyway (Spark's DStream checkpoints do not
survive application upgrades), so the merge only normalizes bytes Spark already
declares unrecoverable.
`testProcessingTimersFireInTimestampOrder` fails on master with the later
timer drained first; `testSettingATimerAgainClearsThePriorSetting` and
`testAddTimersKeepsTheLatestSettingOfATimer` pin the replacement semantics.
Fixes #39824.
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