Copilot commented on code in PR #3035:
URL: https://github.com/apache/pekko/pull/3035#discussion_r3345632116
##########
stream/src/main/scala/org/apache/pekko/stream/stage/GraphStage.scala:
##########
@@ -275,6 +308,123 @@ object GraphStageLogic {
type Receive = ((ActorRef, Any)) => Unit
}
+ private object StageActor {
+ def localCell(ref: ActorRef, description: String): ActorCell =
+ ref match {
+ case ref: LocalActorRef => ref.underlying
+ case ref: RepointableActorRef =>
+ ref.underlying match {
+ case cell: ActorCell => cell
+ case unknown =>
+ throw new IllegalStateException(s"$description must be a local
actor, was [${unknown.getClass.getName}]")
+ }
+ case unknown =>
+ throw new IllegalStateException(s"$description must be a local
actor, was [${unknown.getClass.getName}]")
+ }
+
+ /**
+ * Reads `pekko.stream.materializer.stage-actor-drain-batch` from the
materializer's ActorSystem config.
+ * Called once per lazy StageActor construction (never on the hot path).
Bounded to `>= 1`.
+ */
+ def drainBatchSize(materializer: Materializer): Int =
+ Math.max(1,
materializer.system.settings.config.getInt("pekko.stream.materializer.stage-actor-drain-batch"))
+
+ private final val SchedStateIdle: Int = 0
+ private final val SchedStateScheduled: Int = 1
+
+ /**
+ * Lazy-path dispatch: producers enqueue into a Vyukov MPSC queue and
elect a single drain via
+ * IDLE -> SCHEDULED CAS; only the elected producer pays a mailbox
enqueue. The drain runs on the
+ * interpreter thread, polls in a tight loop bounded by `drainBatchSize`,
then either publishes IDLE
+ * (with a recheck for the publish-window race) or re-schedules another
envelope to yield to other
+ * BoundaryEvents.
+ *
+ * JIT/GC notes:
+ * - `final class` + monomorphic per-StageActor instance → JIT
devirtualizes the apply at the
+ * FunctionRef call site.
+ * - Extends `AbstractNodeQueue` directly so the queue head atomic and
the dispatch function share one
+ * object (one allocation per StageActor, one fewer field deref on the
producer hot path).
+ * - All hot-path state is `private[this]` → direct field access, no
accessor methods.
+ * - `drainBatchSize` is read once into a stack-local at the top of
`drain` so the JIT can treat the loop
+ * bound as a constant.
+ * - Per-tell allocation = 1 Node (`AbstractNodeQueue.Node`, ~24 bytes) +
1 Tuple2 (~24 bytes). The
+ * Tuple2 is forced by the public `StageActorRef.Receive` type. No
AsyncInput / Envelope per tell —
+ * those are amortized across the batch.
+ */
+ // Not marked `private` so that `class StageActor`'s aux constructor
(compiled outside of the companion
+ // object on Scala 3) can reference it; the enclosing `object StageActor`
is itself private.
+ final class LazyDispatch(
+ interpreter: GraphInterpreter,
+ logic: GraphStageLogic,
+ handler: Any => Unit,
+ drainBatchSize: Int)
+ extends AbstractNodeQueue[(ActorRef, Any)]
+ with (((ActorRef, Any)) => Unit) {
+
+ // IDLE/SCHEDULED election state. AtomicInteger gives us volatile read +
CAS without the cross-Scala
+ // VarHandle / field-updater access fuss; the wrapper costs one extra
reference per StageActor, which
+ // is negligible against the per-tell mailbox traffic we are saving.
+ private[this] val state = new AtomicInteger(SchedStateIdle)
Review Comment:
The PR description claims the lazy dispatch election state is implemented as
a `@volatile var Int` driven by a `VarHandle` (to avoid per-instance wrapper
allocations), but the implementation here uses `new AtomicInteger(...)`. Please
either update the PR description to match the code, or switch the
implementation to the described `VarHandle` pattern if that is still the
intended design goal.
##########
stream/src/main/scala/org/apache/pekko/stream/stage/GraphStage.scala:
##########
@@ -275,6 +308,123 @@ object GraphStageLogic {
type Receive = ((ActorRef, Any)) => Unit
}
+ private object StageActor {
+ def localCell(ref: ActorRef, description: String): ActorCell =
+ ref match {
+ case ref: LocalActorRef => ref.underlying
+ case ref: RepointableActorRef =>
+ ref.underlying match {
+ case cell: ActorCell => cell
+ case unknown =>
+ throw new IllegalStateException(s"$description must be a local
actor, was [${unknown.getClass.getName}]")
+ }
+ case unknown =>
+ throw new IllegalStateException(s"$description must be a local
actor, was [${unknown.getClass.getName}]")
+ }
+
+ /**
+ * Reads `pekko.stream.materializer.stage-actor-drain-batch` from the
materializer's ActorSystem config.
+ * Called once per lazy StageActor construction (never on the hot path).
Bounded to `>= 1`.
+ */
+ def drainBatchSize(materializer: Materializer): Int =
+ Math.max(1,
materializer.system.settings.config.getInt("pekko.stream.materializer.stage-actor-drain-batch"))
+
+ private final val SchedStateIdle: Int = 0
+ private final val SchedStateScheduled: Int = 1
+
+ /**
+ * Lazy-path dispatch: producers enqueue into a Vyukov MPSC queue and
elect a single drain via
+ * IDLE -> SCHEDULED CAS; only the elected producer pays a mailbox
enqueue. The drain runs on the
+ * interpreter thread, polls in a tight loop bounded by `drainBatchSize`,
then either publishes IDLE
+ * (with a recheck for the publish-window race) or re-schedules another
envelope to yield to other
+ * BoundaryEvents.
+ *
+ * JIT/GC notes:
+ * - `final class` + monomorphic per-StageActor instance → JIT
devirtualizes the apply at the
+ * FunctionRef call site.
+ * - Extends `AbstractNodeQueue` directly so the queue head atomic and
the dispatch function share one
+ * object (one allocation per StageActor, one fewer field deref on the
producer hot path).
+ * - All hot-path state is `private[this]` → direct field access, no
accessor methods.
+ * - `drainBatchSize` is read once into a stack-local at the top of
`drain` so the JIT can treat the loop
+ * bound as a constant.
+ * - Per-tell allocation = 1 Node (`AbstractNodeQueue.Node`, ~24 bytes) +
1 Tuple2 (~24 bytes). The
+ * Tuple2 is forced by the public `StageActorRef.Receive` type. No
AsyncInput / Envelope per tell —
+ * those are amortized across the batch.
+ */
+ // Not marked `private` so that `class StageActor`'s aux constructor
(compiled outside of the companion
+ // object on Scala 3) can reference it; the enclosing `object StageActor`
is itself private.
+ final class LazyDispatch(
+ interpreter: GraphInterpreter,
+ logic: GraphStageLogic,
+ handler: Any => Unit,
+ drainBatchSize: Int)
+ extends AbstractNodeQueue[(ActorRef, Any)]
+ with (((ActorRef, Any)) => Unit) {
+
+ // IDLE/SCHEDULED election state. AtomicInteger gives us volatile read +
CAS without the cross-Scala
+ // VarHandle / field-updater access fuss; the wrapper costs one extra
reference per StageActor, which
+ // is negligible against the per-tell mailbox traffic we are saving.
+ private[this] val state = new AtomicInteger(SchedStateIdle)
+
+ // Reused across all drain batches; allocated once at construction.
+ private[this] val drainCallback: Any => Unit = (_: Any) => drain()
+
+ override def apply(pair: (ActorRef, Any)): Unit = {
+ // Producer-side completion guard. `runAsyncInput` short-circuits the
drain handler when the stage
+ // is completed, so without this check a CAS-winning producer would
leave state=SCHEDULED forever
+ // and subsequent producers would skip the mailbox push, growing the
queue unbounded. Dropping
+ // post-completion sends here matches the original per-tell behaviour
where `runAsyncInput`
+ // silently ignored them. The read is racy against the interpreter
thread that flips
+ // `shutdownCounter`, but eventually visible — enough to bound the
leak to messages enqueued
+ // before completion becomes visible to this thread.
+ if (interpreter.isStageCompleted(logic)) return
+ add(pair) // Vyukov producer path: getAndSet + release-store, no CAS
spin
+ // Double-checked CAS: uncontended fast path is one volatile read;
only the IDLE->SCHEDULED winner
+ // pays a CAS + mailbox push.
+ if (state.get() == SchedStateIdle &&
state.compareAndSet(SchedStateIdle, SchedStateScheduled)) {
+ // Re-check after winning election: if completion landed between the
initial guard and the CAS,
+ // `scheduleDrain` would post an envelope that `runAsyncInput`
skips, leaving state=SCHEDULED.
+ // Reset to IDLE and skip the schedule.
+ if (interpreter.isStageCompleted(logic)) state.set(SchedStateIdle)
+ else scheduleDrain()
+ }
+ }
+
+ private def scheduleDrain(): Unit =
+ // 1 AsyncInput + 1 Envelope per drain batch (amortized across up to
drainBatchSize tells).
+ interpreter.onAsyncInput(logic, null, NoPromise, drainCallback)
+
+ private def drain(): Unit = {
+ val limit = drainBatchSize // hoisted to a local so JIT treats it as a
loop-invariant constant
+ var processed = 0
+ while (processed < limit) {
+ if (interpreter.isStageCompleted(logic)) {
+ // Stage completed mid-drain; drop the remainder (matches the
original per-tell behaviour where
+ // runAsyncInput silently skipped completed stages). Don't
reschedule — no future drain will run.
+ while (poll() ne null) ()
+ state.set(SchedStateIdle)
+ return
+ }
+ val item = poll()
+ if (item eq null) {
+ state.set(SchedStateIdle)
+ // Recheck race: a producer may have added between `poll == null`
and the IDLE publish above.
+ // That producer saw state=SCHEDULED and skipped the mailbox send,
so we must re-elect.
+ if (!isEmpty && state.compareAndSet(SchedStateIdle,
SchedStateScheduled))
+ scheduleDrain()
+ return
+ }
+ handler(item)
+ processed += 1
+ }
+ // Hit batch cap with items potentially still queued. Re-schedule
another envelope so other
+ // BoundaryEvents (pull/push/complete) can interleave via the actor
mailbox. `scheduledState` stays
+ // SCHEDULED: concurrent producers correctly observe SCHEDULED and
skip; the new envelope will drain.
+ scheduleDrain()
Review Comment:
`LazyDispatch.drain()` always schedules another drain envelope after hitting
the batch limit, even if the last processed item completed the stage. In that
case `GraphInterpreter.runAsyncInput` will skip the scheduled drain (because
the stage is already completed), leaving `state` stuck at SCHEDULED and
retaining any already-enqueued items until the FunctionRef is stopped. Add a
completion check before re-scheduling and drop any remaining queued items when
completed (matching the existing mid-drain completion branch).
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