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Posted to notifications@pekko.apache.org by "pjfanning (via GitHub)" <gi...@apache.org> on 2023/08/11 20:29:40 UTC
[GitHub] [incubator-pekko] pjfanning opened a new pull request, #561: [DRAFT] MapAsyncPartition
pjfanning opened a new pull request, #561:
URL: https://github.com/apache/incubator-pekko/pull/561
* very early days
* lots more work to do
* code based on https://github.com/jaceksokol/akka-stream-map-async-partition
* relates to #553
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[GitHub] [incubator-pekko] pjfanning commented on a diff in pull request #561: [DRAFT] MapAsyncPartition
Posted by "pjfanning (via GitHub)" <gi...@apache.org>.
pjfanning commented on code in PR #561:
URL: https://github.com/apache/incubator-pekko/pull/561#discussion_r1294888466
##########
legal/pekko-stream-jar-license.txt:
##########
@@ -0,0 +1,231 @@
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+---------------
+
+pekko-stream contains code derived from jaceksokol/akka-stream-map-async-partition
+<https://github.com/jaceksokol/akka-stream-map-async-partition>
+wich is licensed under an MIT License.
+
+ - stream/src/main/scala/org/apache/pekko/stream/MapAsyncPartition.scala
+
+MIT License
+
+Copyright (c) 2021 Jacek Sokol
Review Comment:
This is a copy of the license in https://github.com/jaceksokol/akka-stream-map-async-partition
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[GitHub] [incubator-pekko] He-Pin commented on pull request #561: mapAsyncPartitioned / mapAsyncPartitionedUnordered
Posted by "He-Pin (via GitHub)" <gi...@apache.org>.
He-Pin commented on PR #561:
URL: https://github.com/apache/incubator-pekko/pull/561#issuecomment-1729994197
@pjfanning I think we can merge this, and tweak can comes later.
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[GitHub] [incubator-pekko] He-Pin commented on a diff in pull request #561: mapAsyncPartitioned / mapAsyncPartitionedUnordered
Posted by "He-Pin (via GitHub)" <gi...@apache.org>.
He-Pin commented on code in PR #561:
URL: https://github.com/apache/incubator-pekko/pull/561#discussion_r1320933234
##########
stream/src/main/scala/org/apache/pekko/stream/MapAsyncPartitioned.scala:
##########
@@ -0,0 +1,346 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.pekko.stream
+
+import scala.collection.mutable
+import scala.concurrent.Future
+import scala.util.control.{ NoStackTrace, NonFatal }
+import scala.util.{ Failure, Success, Try }
+
+import org.apache.pekko
+import pekko.dispatch.ExecutionContexts
+import pekko.stream.ActorAttributes.SupervisionStrategy
+import pekko.stream.Attributes.{ Name, SourceLocation }
+import pekko.stream.MapAsyncPartitioned._
+import pekko.stream.scaladsl.{ Flow, FlowWithContext, Source, SourceWithContext }
+import pekko.stream.stage._
+
+private[stream] object MapAsyncPartitioned {
+
+ private def extractPartitionWithCtx[In, Ctx, Partition](extract: In => Partition)(tuple: (In, Ctx)): Partition =
+ extract(tuple._1)
+
+ private def fWithCtx[In, Out, Ctx, Partition](f: (In, Partition) => Future[Out])(tuple: (In, Ctx),
+ partition: Partition): Future[(Out, Ctx)] =
+ f(tuple._1, partition).map(_ -> tuple._2)(ExecutionContexts.parasitic)
+
+ def mapSourceOrdered[In, Out, Partition, Mat](source: Source[In, Mat], parallelism: Int)(
+ extractPartition: In => Partition)(
+ f: (In, Partition) => Future[Out]): Source[Out, Mat] =
+ source.via(new MapAsyncPartitioned[In, Out, Partition](orderedOutput = true, parallelism, extractPartition, f))
+
+ def mapSourceUnordered[In, Out, Partition, Mat](source: Source[In, Mat], parallelism: Int)(
+ extractPartition: In => Partition)(
+ f: (In, Partition) => Future[Out]): Source[Out, Mat] =
+ source.via(new MapAsyncPartitioned[In, Out, Partition](orderedOutput = false, parallelism, extractPartition, f))
+
+ def mapSourceWithContextOrdered[In, Ctx, T, Partition, Mat](flow: SourceWithContext[In, Ctx, Mat], parallelism: Int)(
+ extractPartition: In => Partition)(
+ f: (In, Partition) => Future[T]): SourceWithContext[T, Ctx, Mat] =
+ flow.via(
+ new MapAsyncPartitioned[(In, Ctx), (T, Ctx), Partition](
+ orderedOutput = true,
+ parallelism,
+ extractPartitionWithCtx(extractPartition),
+ fWithCtx[In, T, Ctx, Partition](f)))
+
+ def mapSourceWithContextUnordered[In, Ctx, T, Partition, Mat](flow: SourceWithContext[In, Ctx, Mat],
+ parallelism: Int)(extractPartition: In => Partition)(
+ f: (In, Partition) => Future[T]): SourceWithContext[T, Ctx, Mat] =
+ flow.via(
+ new MapAsyncPartitioned[(In, Ctx), (T, Ctx), Partition](
+ orderedOutput = false,
+ parallelism,
+ extractPartitionWithCtx(extractPartition),
+ fWithCtx[In, T, Ctx, Partition](f)))
+
+ def mapFlowOrdered[In, Out, T, Partition, Mat](flow: Flow[In, Out, Mat], parallelism: Int)(
+ extractPartition: Out => Partition)(
+ f: (Out, Partition) => Future[T]): Flow[In, T, Mat] =
+ flow.via(new MapAsyncPartitioned[Out, T, Partition](orderedOutput = true, parallelism, extractPartition,
+ f))
+
+ def mapFlowUnordered[In, Out, T, Partition, Mat](flow: Flow[In, Out, Mat], parallelism: Int)(
+ extractPartition: Out => Partition)(
+ f: (Out, Partition) => Future[T]): Flow[In, T, Mat] =
+ flow.via(new MapAsyncPartitioned[Out, T, Partition](orderedOutput = false, parallelism,
+ extractPartition, f))
+
+ def mapFlowWithContextOrdered[In, Out, CtxIn, CtxOut, T, Partition, Mat](
+ flow: FlowWithContext[In, CtxIn, Out, CtxOut, Mat], parallelism: Int)(
+ extractPartition: Out => Partition)(
+ f: (Out, Partition) => Future[T]): FlowWithContext[In, CtxIn, T, CtxOut, Mat] =
+ flow.via(
+ new MapAsyncPartitioned[(Out, CtxOut), (T, CtxOut), Partition](
+ orderedOutput = true,
+ parallelism,
+ extractPartitionWithCtx(extractPartition),
+ fWithCtx[Out, T, CtxOut, Partition](f)))
+
+ def mapFlowWithContextUnordered[In, Out, CtxIn, CtxOut, T, Partition, Mat](
+ flow: FlowWithContext[In, CtxIn, Out, CtxOut, Mat], parallelism: Int)(extractPartition: Out => Partition)(
+ f: (Out, Partition) => Future[T]): FlowWithContext[In, CtxIn, T, CtxOut, Mat] =
+ flow.via(
+ new MapAsyncPartitioned[(Out, CtxOut), (T, CtxOut), Partition](
+ orderedOutput = false,
+ parallelism,
+ extractPartitionWithCtx(extractPartition),
+ fWithCtx[Out, T, CtxOut, Partition](f)))
+
+ private[stream] val NotYetThere: Failure[Nothing] = Failure(new Exception with NoStackTrace)
+
+ private[stream] final class Holder[In, Out](
+ val in: In,
+ var out: Try[Out],
+ callback: AsyncCallback[Holder[In, Out]]) extends (Try[Out] => Unit) {
+
+ // To support both fail-fast when the supervision directive is Stop
+ // and not calling the decider multiple times (#23888) we need to cache the decider result and re-use that
+ private var cachedSupervisionDirective: Option[Supervision.Directive] = None
+
+ def supervisionDirectiveFor(decider: Supervision.Decider, ex: Throwable): Supervision.Directive = {
+ cachedSupervisionDirective match {
+ case Some(d) => d
+ case _ =>
+ val d = decider(ex)
+ cachedSupervisionDirective = Some(d)
+ d
+ }
+ }
+
+ def setOut(t: Try[Out]): Unit =
+ out = t
+
+ override def apply(t: Try[Out]): Unit = {
+ setOut(t)
+ callback.invoke(this)
+ }
+ }
+}
+
+private[stream] class MapAsyncPartitioned[In, Out, Partition](
+ orderedOutput: Boolean,
+ parallelism: Int,
+ extractPartition: In => Partition,
+ f: (In, Partition) => Future[Out]) extends GraphStage[FlowShape[In, Out]] {
+
+ if (parallelism < 1) throw new IllegalArgumentException("parallelism must be at least 1")
Review Comment:
Use `require`?
##########
stream/src/main/scala/org/apache/pekko/stream/MapAsyncPartitioned.scala:
##########
@@ -0,0 +1,346 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.pekko.stream
+
+import scala.collection.mutable
+import scala.concurrent.Future
+import scala.util.control.{ NoStackTrace, NonFatal }
+import scala.util.{ Failure, Success, Try }
+
+import org.apache.pekko
+import pekko.dispatch.ExecutionContexts
+import pekko.stream.ActorAttributes.SupervisionStrategy
+import pekko.stream.Attributes.{ Name, SourceLocation }
+import pekko.stream.MapAsyncPartitioned._
+import pekko.stream.scaladsl.{ Flow, FlowWithContext, Source, SourceWithContext }
+import pekko.stream.stage._
+
+private[stream] object MapAsyncPartitioned {
+
+ private def extractPartitionWithCtx[In, Ctx, Partition](extract: In => Partition)(tuple: (In, Ctx)): Partition =
+ extract(tuple._1)
+
+ private def fWithCtx[In, Out, Ctx, Partition](f: (In, Partition) => Future[Out])(tuple: (In, Ctx),
+ partition: Partition): Future[(Out, Ctx)] =
+ f(tuple._1, partition).map(_ -> tuple._2)(ExecutionContexts.parasitic)
+
+ def mapSourceOrdered[In, Out, Partition, Mat](source: Source[In, Mat], parallelism: Int)(
+ extractPartition: In => Partition)(
+ f: (In, Partition) => Future[Out]): Source[Out, Mat] =
+ source.via(new MapAsyncPartitioned[In, Out, Partition](orderedOutput = true, parallelism, extractPartition, f))
+
+ def mapSourceUnordered[In, Out, Partition, Mat](source: Source[In, Mat], parallelism: Int)(
+ extractPartition: In => Partition)(
+ f: (In, Partition) => Future[Out]): Source[Out, Mat] =
+ source.via(new MapAsyncPartitioned[In, Out, Partition](orderedOutput = false, parallelism, extractPartition, f))
+
+ def mapSourceWithContextOrdered[In, Ctx, T, Partition, Mat](flow: SourceWithContext[In, Ctx, Mat], parallelism: Int)(
+ extractPartition: In => Partition)(
+ f: (In, Partition) => Future[T]): SourceWithContext[T, Ctx, Mat] =
+ flow.via(
+ new MapAsyncPartitioned[(In, Ctx), (T, Ctx), Partition](
+ orderedOutput = true,
+ parallelism,
+ extractPartitionWithCtx(extractPartition),
+ fWithCtx[In, T, Ctx, Partition](f)))
+
+ def mapSourceWithContextUnordered[In, Ctx, T, Partition, Mat](flow: SourceWithContext[In, Ctx, Mat],
+ parallelism: Int)(extractPartition: In => Partition)(
+ f: (In, Partition) => Future[T]): SourceWithContext[T, Ctx, Mat] =
+ flow.via(
+ new MapAsyncPartitioned[(In, Ctx), (T, Ctx), Partition](
+ orderedOutput = false,
+ parallelism,
+ extractPartitionWithCtx(extractPartition),
+ fWithCtx[In, T, Ctx, Partition](f)))
+
+ def mapFlowOrdered[In, Out, T, Partition, Mat](flow: Flow[In, Out, Mat], parallelism: Int)(
+ extractPartition: Out => Partition)(
+ f: (Out, Partition) => Future[T]): Flow[In, T, Mat] =
+ flow.via(new MapAsyncPartitioned[Out, T, Partition](orderedOutput = true, parallelism, extractPartition,
+ f))
+
+ def mapFlowUnordered[In, Out, T, Partition, Mat](flow: Flow[In, Out, Mat], parallelism: Int)(
+ extractPartition: Out => Partition)(
+ f: (Out, Partition) => Future[T]): Flow[In, T, Mat] =
+ flow.via(new MapAsyncPartitioned[Out, T, Partition](orderedOutput = false, parallelism,
+ extractPartition, f))
+
+ def mapFlowWithContextOrdered[In, Out, CtxIn, CtxOut, T, Partition, Mat](
+ flow: FlowWithContext[In, CtxIn, Out, CtxOut, Mat], parallelism: Int)(
+ extractPartition: Out => Partition)(
+ f: (Out, Partition) => Future[T]): FlowWithContext[In, CtxIn, T, CtxOut, Mat] =
+ flow.via(
+ new MapAsyncPartitioned[(Out, CtxOut), (T, CtxOut), Partition](
+ orderedOutput = true,
+ parallelism,
+ extractPartitionWithCtx(extractPartition),
+ fWithCtx[Out, T, CtxOut, Partition](f)))
+
+ def mapFlowWithContextUnordered[In, Out, CtxIn, CtxOut, T, Partition, Mat](
+ flow: FlowWithContext[In, CtxIn, Out, CtxOut, Mat], parallelism: Int)(extractPartition: Out => Partition)(
+ f: (Out, Partition) => Future[T]): FlowWithContext[In, CtxIn, T, CtxOut, Mat] =
+ flow.via(
+ new MapAsyncPartitioned[(Out, CtxOut), (T, CtxOut), Partition](
+ orderedOutput = false,
+ parallelism,
+ extractPartitionWithCtx(extractPartition),
+ fWithCtx[Out, T, CtxOut, Partition](f)))
+
+ private[stream] val NotYetThere: Failure[Nothing] = Failure(new Exception with NoStackTrace)
+
+ private[stream] final class Holder[In, Out](
+ val in: In,
+ var out: Try[Out],
+ callback: AsyncCallback[Holder[In, Out]]) extends (Try[Out] => Unit) {
+
+ // To support both fail-fast when the supervision directive is Stop
+ // and not calling the decider multiple times (#23888) we need to cache the decider result and re-use that
+ private var cachedSupervisionDirective: Option[Supervision.Directive] = None
+
+ def supervisionDirectiveFor(decider: Supervision.Decider, ex: Throwable): Supervision.Directive = {
+ cachedSupervisionDirective match {
+ case Some(d) => d
+ case _ =>
+ val d = decider(ex)
+ cachedSupervisionDirective = Some(d)
+ d
+ }
+ }
+
+ def setOut(t: Try[Out]): Unit =
+ out = t
+
+ override def apply(t: Try[Out]): Unit = {
+ setOut(t)
+ callback.invoke(this)
+ }
+ }
+}
+
+private[stream] class MapAsyncPartitioned[In, Out, Partition](
+ orderedOutput: Boolean,
+ parallelism: Int,
+ extractPartition: In => Partition,
+ f: (In, Partition) => Future[Out]) extends GraphStage[FlowShape[In, Out]] {
+
+ if (parallelism < 1) throw new IllegalArgumentException("parallelism must be at least 1")
+
+ private val in = Inlet[In]("MapAsyncPartitionOrdered.in")
+ private val out = Outlet[Out]("MapAsyncPartitionOrdered.out")
+
+ override val shape: FlowShape[In, Out] = FlowShape(in, out)
+
+ override def initialAttributes: Attributes =
+ Attributes(Name("MapAsyncPartitionOrdered")) and SourceLocation.forLambda(f)
Review Comment:
Move this to `DefaultAttributes`
##########
stream/src/main/scala/org/apache/pekko/stream/MapAsyncPartitioned.scala:
##########
@@ -0,0 +1,346 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.pekko.stream
+
+import scala.collection.mutable
+import scala.concurrent.Future
+import scala.util.control.{ NoStackTrace, NonFatal }
+import scala.util.{ Failure, Success, Try }
+
+import org.apache.pekko
+import pekko.dispatch.ExecutionContexts
+import pekko.stream.ActorAttributes.SupervisionStrategy
+import pekko.stream.Attributes.{ Name, SourceLocation }
+import pekko.stream.MapAsyncPartitioned._
+import pekko.stream.scaladsl.{ Flow, FlowWithContext, Source, SourceWithContext }
+import pekko.stream.stage._
+
+private[stream] object MapAsyncPartitioned {
+
+ private def extractPartitionWithCtx[In, Ctx, Partition](extract: In => Partition)(tuple: (In, Ctx)): Partition =
+ extract(tuple._1)
+
+ private def fWithCtx[In, Out, Ctx, Partition](f: (In, Partition) => Future[Out])(tuple: (In, Ctx),
+ partition: Partition): Future[(Out, Ctx)] =
+ f(tuple._1, partition).map(_ -> tuple._2)(ExecutionContexts.parasitic)
+
+ def mapSourceOrdered[In, Out, Partition, Mat](source: Source[In, Mat], parallelism: Int)(
+ extractPartition: In => Partition)(
+ f: (In, Partition) => Future[Out]): Source[Out, Mat] =
+ source.via(new MapAsyncPartitioned[In, Out, Partition](orderedOutput = true, parallelism, extractPartition, f))
+
+ def mapSourceUnordered[In, Out, Partition, Mat](source: Source[In, Mat], parallelism: Int)(
+ extractPartition: In => Partition)(
+ f: (In, Partition) => Future[Out]): Source[Out, Mat] =
+ source.via(new MapAsyncPartitioned[In, Out, Partition](orderedOutput = false, parallelism, extractPartition, f))
+
+ def mapSourceWithContextOrdered[In, Ctx, T, Partition, Mat](flow: SourceWithContext[In, Ctx, Mat], parallelism: Int)(
+ extractPartition: In => Partition)(
+ f: (In, Partition) => Future[T]): SourceWithContext[T, Ctx, Mat] =
+ flow.via(
+ new MapAsyncPartitioned[(In, Ctx), (T, Ctx), Partition](
+ orderedOutput = true,
+ parallelism,
+ extractPartitionWithCtx(extractPartition),
+ fWithCtx[In, T, Ctx, Partition](f)))
+
+ def mapSourceWithContextUnordered[In, Ctx, T, Partition, Mat](flow: SourceWithContext[In, Ctx, Mat],
+ parallelism: Int)(extractPartition: In => Partition)(
+ f: (In, Partition) => Future[T]): SourceWithContext[T, Ctx, Mat] =
+ flow.via(
+ new MapAsyncPartitioned[(In, Ctx), (T, Ctx), Partition](
+ orderedOutput = false,
+ parallelism,
+ extractPartitionWithCtx(extractPartition),
+ fWithCtx[In, T, Ctx, Partition](f)))
+
+ def mapFlowOrdered[In, Out, T, Partition, Mat](flow: Flow[In, Out, Mat], parallelism: Int)(
+ extractPartition: Out => Partition)(
+ f: (Out, Partition) => Future[T]): Flow[In, T, Mat] =
+ flow.via(new MapAsyncPartitioned[Out, T, Partition](orderedOutput = true, parallelism, extractPartition,
+ f))
+
+ def mapFlowUnordered[In, Out, T, Partition, Mat](flow: Flow[In, Out, Mat], parallelism: Int)(
+ extractPartition: Out => Partition)(
+ f: (Out, Partition) => Future[T]): Flow[In, T, Mat] =
+ flow.via(new MapAsyncPartitioned[Out, T, Partition](orderedOutput = false, parallelism,
+ extractPartition, f))
+
+ def mapFlowWithContextOrdered[In, Out, CtxIn, CtxOut, T, Partition, Mat](
+ flow: FlowWithContext[In, CtxIn, Out, CtxOut, Mat], parallelism: Int)(
+ extractPartition: Out => Partition)(
+ f: (Out, Partition) => Future[T]): FlowWithContext[In, CtxIn, T, CtxOut, Mat] =
+ flow.via(
+ new MapAsyncPartitioned[(Out, CtxOut), (T, CtxOut), Partition](
+ orderedOutput = true,
+ parallelism,
+ extractPartitionWithCtx(extractPartition),
+ fWithCtx[Out, T, CtxOut, Partition](f)))
+
+ def mapFlowWithContextUnordered[In, Out, CtxIn, CtxOut, T, Partition, Mat](
+ flow: FlowWithContext[In, CtxIn, Out, CtxOut, Mat], parallelism: Int)(extractPartition: Out => Partition)(
+ f: (Out, Partition) => Future[T]): FlowWithContext[In, CtxIn, T, CtxOut, Mat] =
+ flow.via(
+ new MapAsyncPartitioned[(Out, CtxOut), (T, CtxOut), Partition](
+ orderedOutput = false,
+ parallelism,
+ extractPartitionWithCtx(extractPartition),
+ fWithCtx[Out, T, CtxOut, Partition](f)))
+
+ private[stream] val NotYetThere: Failure[Nothing] = Failure(new Exception with NoStackTrace)
+
+ private[stream] final class Holder[In, Out](
+ val in: In,
+ var out: Try[Out],
+ callback: AsyncCallback[Holder[In, Out]]) extends (Try[Out] => Unit) {
+
+ // To support both fail-fast when the supervision directive is Stop
+ // and not calling the decider multiple times (#23888) we need to cache the decider result and re-use that
+ private var cachedSupervisionDirective: Option[Supervision.Directive] = None
+
+ def supervisionDirectiveFor(decider: Supervision.Decider, ex: Throwable): Supervision.Directive = {
+ cachedSupervisionDirective match {
+ case Some(d) => d
+ case _ =>
+ val d = decider(ex)
+ cachedSupervisionDirective = Some(d)
+ d
+ }
+ }
+
+ def setOut(t: Try[Out]): Unit =
+ out = t
+
+ override def apply(t: Try[Out]): Unit = {
+ setOut(t)
+ callback.invoke(this)
+ }
+ }
+}
+
+private[stream] class MapAsyncPartitioned[In, Out, Partition](
+ orderedOutput: Boolean,
+ parallelism: Int,
+ extractPartition: In => Partition,
+ f: (In, Partition) => Future[Out]) extends GraphStage[FlowShape[In, Out]] {
+
+ if (parallelism < 1) throw new IllegalArgumentException("parallelism must be at least 1")
+
+ private val in = Inlet[In]("MapAsyncPartitionOrdered.in")
+ private val out = Outlet[Out]("MapAsyncPartitionOrdered.out")
+
+ override val shape: FlowShape[In, Out] = FlowShape(in, out)
+
+ override def initialAttributes: Attributes =
+ Attributes(Name("MapAsyncPartitionOrdered")) and SourceLocation.forLambda(f)
+
+ override def createLogic(inheritedAttributes: Attributes): GraphStageLogic =
+ new GraphStageLogic(shape) with InHandler with OutHandler {
+ private val contextPropagation = pekko.stream.impl.ContextPropagation()
+
+ private final class Contextual[T](context: AnyRef, val element: T) {
+ private var suspended = false
+
+ def suspend(): Unit =
+ if (!suspended) {
+ suspended = true
+ contextPropagation.suspendContext()
+ }
+
+ def resume(): Unit =
+ if (suspended) {
+ suspended = false
+ contextPropagation.resumeContext(context)
+ }
+
+ }
+
+ private lazy val decider = inheritedAttributes.mandatoryAttribute[SupervisionStrategy].decider
+
+ private var partitionsInProgress: mutable.Set[Partition] = _
+ private var buffer: mutable.Queue[(Partition, Contextual[Holder[In, Out]])] = _
Review Comment:
use `org.apache.pekko.stream.impl.Buffer` like mapAsync?
##########
stream/src/main/scala/org/apache/pekko/stream/scaladsl/Flow.scala:
##########
@@ -163,6 +163,36 @@ final class Flow[-In, +Out, +Mat](
override def mapMaterializedValue[Mat2](f: Mat => Mat2): ReprMat[Out, Mat2] =
new Flow(traversalBuilder.transformMat(f), shape)
+ /**
+ * Transforms this stream. Works very similarly to [[#mapAsync]] but with an additional
+ * partition step before the transform step. The transform function receives the an individual
+ * stream entry and the calculated partition value for that entry.
+ *
+ * @since 1.1.0
+ * @see [[#mapAsync]]
+ * @see [[#mapAsyncPartitionedUnordered]]
+ */
Review Comment:
This scala doc meed explain the behavior in more detail with the backpressure sementic.
##########
stream/src/main/scala/org/apache/pekko/stream/MapAsyncPartitioned.scala:
##########
@@ -0,0 +1,346 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.pekko.stream
+
+import scala.collection.mutable
+import scala.concurrent.Future
+import scala.util.control.{ NoStackTrace, NonFatal }
+import scala.util.{ Failure, Success, Try }
+
+import org.apache.pekko
+import pekko.dispatch.ExecutionContexts
+import pekko.stream.ActorAttributes.SupervisionStrategy
+import pekko.stream.Attributes.{ Name, SourceLocation }
+import pekko.stream.MapAsyncPartitioned._
+import pekko.stream.scaladsl.{ Flow, FlowWithContext, Source, SourceWithContext }
+import pekko.stream.stage._
+
+private[stream] object MapAsyncPartitioned {
+
+ private def extractPartitionWithCtx[In, Ctx, Partition](extract: In => Partition)(tuple: (In, Ctx)): Partition =
+ extract(tuple._1)
+
+ private def fWithCtx[In, Out, Ctx, Partition](f: (In, Partition) => Future[Out])(tuple: (In, Ctx),
+ partition: Partition): Future[(Out, Ctx)] =
+ f(tuple._1, partition).map(_ -> tuple._2)(ExecutionContexts.parasitic)
Review Comment:
a better name than `fwithCtx`
##########
stream/src/main/scala/org/apache/pekko/stream/MapAsyncPartitioned.scala:
##########
@@ -0,0 +1,346 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.pekko.stream
+
+import scala.collection.mutable
+import scala.concurrent.Future
+import scala.util.control.{ NoStackTrace, NonFatal }
+import scala.util.{ Failure, Success, Try }
+
+import org.apache.pekko
+import pekko.dispatch.ExecutionContexts
+import pekko.stream.ActorAttributes.SupervisionStrategy
+import pekko.stream.Attributes.{ Name, SourceLocation }
+import pekko.stream.MapAsyncPartitioned._
+import pekko.stream.scaladsl.{ Flow, FlowWithContext, Source, SourceWithContext }
+import pekko.stream.stage._
+
+private[stream] object MapAsyncPartitioned {
+
+ private def extractPartitionWithCtx[In, Ctx, Partition](extract: In => Partition)(tuple: (In, Ctx)): Partition =
+ extract(tuple._1)
Review Comment:
tuple is not a good name, use `indexWithCtx`?
##########
stream/src/main/scala/org/apache/pekko/stream/MapAsyncPartitioned.scala:
##########
@@ -0,0 +1,346 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.pekko.stream
+
+import scala.collection.mutable
+import scala.concurrent.Future
+import scala.util.control.{ NoStackTrace, NonFatal }
+import scala.util.{ Failure, Success, Try }
+
+import org.apache.pekko
+import pekko.dispatch.ExecutionContexts
+import pekko.stream.ActorAttributes.SupervisionStrategy
+import pekko.stream.Attributes.{ Name, SourceLocation }
+import pekko.stream.MapAsyncPartitioned._
+import pekko.stream.scaladsl.{ Flow, FlowWithContext, Source, SourceWithContext }
+import pekko.stream.stage._
+
+private[stream] object MapAsyncPartitioned {
+
+ private def extractPartitionWithCtx[In, Ctx, Partition](extract: In => Partition)(tuple: (In, Ctx)): Partition =
+ extract(tuple._1)
+
+ private def fWithCtx[In, Out, Ctx, Partition](f: (In, Partition) => Future[Out])(tuple: (In, Ctx),
+ partition: Partition): Future[(Out, Ctx)] =
+ f(tuple._1, partition).map(_ -> tuple._2)(ExecutionContexts.parasitic)
+
+ def mapSourceOrdered[In, Out, Partition, Mat](source: Source[In, Mat], parallelism: Int)(
+ extractPartition: In => Partition)(
+ f: (In, Partition) => Future[Out]): Source[Out, Mat] =
+ source.via(new MapAsyncPartitioned[In, Out, Partition](orderedOutput = true, parallelism, extractPartition, f))
+
+ def mapSourceUnordered[In, Out, Partition, Mat](source: Source[In, Mat], parallelism: Int)(
+ extractPartition: In => Partition)(
+ f: (In, Partition) => Future[Out]): Source[Out, Mat] =
+ source.via(new MapAsyncPartitioned[In, Out, Partition](orderedOutput = false, parallelism, extractPartition, f))
+
+ def mapSourceWithContextOrdered[In, Ctx, T, Partition, Mat](flow: SourceWithContext[In, Ctx, Mat], parallelism: Int)(
+ extractPartition: In => Partition)(
+ f: (In, Partition) => Future[T]): SourceWithContext[T, Ctx, Mat] =
+ flow.via(
+ new MapAsyncPartitioned[(In, Ctx), (T, Ctx), Partition](
+ orderedOutput = true,
+ parallelism,
+ extractPartitionWithCtx(extractPartition),
+ fWithCtx[In, T, Ctx, Partition](f)))
+
+ def mapSourceWithContextUnordered[In, Ctx, T, Partition, Mat](flow: SourceWithContext[In, Ctx, Mat],
+ parallelism: Int)(extractPartition: In => Partition)(
+ f: (In, Partition) => Future[T]): SourceWithContext[T, Ctx, Mat] =
+ flow.via(
+ new MapAsyncPartitioned[(In, Ctx), (T, Ctx), Partition](
+ orderedOutput = false,
+ parallelism,
+ extractPartitionWithCtx(extractPartition),
+ fWithCtx[In, T, Ctx, Partition](f)))
+
+ def mapFlowOrdered[In, Out, T, Partition, Mat](flow: Flow[In, Out, Mat], parallelism: Int)(
+ extractPartition: Out => Partition)(
+ f: (Out, Partition) => Future[T]): Flow[In, T, Mat] =
+ flow.via(new MapAsyncPartitioned[Out, T, Partition](orderedOutput = true, parallelism, extractPartition,
+ f))
+
+ def mapFlowUnordered[In, Out, T, Partition, Mat](flow: Flow[In, Out, Mat], parallelism: Int)(
+ extractPartition: Out => Partition)(
+ f: (Out, Partition) => Future[T]): Flow[In, T, Mat] =
+ flow.via(new MapAsyncPartitioned[Out, T, Partition](orderedOutput = false, parallelism,
+ extractPartition, f))
+
+ def mapFlowWithContextOrdered[In, Out, CtxIn, CtxOut, T, Partition, Mat](
+ flow: FlowWithContext[In, CtxIn, Out, CtxOut, Mat], parallelism: Int)(
+ extractPartition: Out => Partition)(
+ f: (Out, Partition) => Future[T]): FlowWithContext[In, CtxIn, T, CtxOut, Mat] =
+ flow.via(
+ new MapAsyncPartitioned[(Out, CtxOut), (T, CtxOut), Partition](
+ orderedOutput = true,
+ parallelism,
+ extractPartitionWithCtx(extractPartition),
+ fWithCtx[Out, T, CtxOut, Partition](f)))
+
+ def mapFlowWithContextUnordered[In, Out, CtxIn, CtxOut, T, Partition, Mat](
+ flow: FlowWithContext[In, CtxIn, Out, CtxOut, Mat], parallelism: Int)(extractPartition: Out => Partition)(
+ f: (Out, Partition) => Future[T]): FlowWithContext[In, CtxIn, T, CtxOut, Mat] =
+ flow.via(
+ new MapAsyncPartitioned[(Out, CtxOut), (T, CtxOut), Partition](
+ orderedOutput = false,
+ parallelism,
+ extractPartitionWithCtx(extractPartition),
+ fWithCtx[Out, T, CtxOut, Partition](f)))
+
+ private[stream] val NotYetThere: Failure[Nothing] = Failure(new Exception with NoStackTrace)
+
+ private[stream] final class Holder[In, Out](
+ val in: In,
+ var out: Try[Out],
+ callback: AsyncCallback[Holder[In, Out]]) extends (Try[Out] => Unit) {
+
+ // To support both fail-fast when the supervision directive is Stop
+ // and not calling the decider multiple times (#23888) we need to cache the decider result and re-use that
+ private var cachedSupervisionDirective: Option[Supervision.Directive] = None
+
+ def supervisionDirectiveFor(decider: Supervision.Decider, ex: Throwable): Supervision.Directive = {
+ cachedSupervisionDirective match {
+ case Some(d) => d
+ case _ =>
+ val d = decider(ex)
+ cachedSupervisionDirective = Some(d)
+ d
+ }
+ }
+
+ def setOut(t: Try[Out]): Unit =
Review Comment:
set `elem` as the `MapAsync`?
##########
stream/src/main/scala/org/apache/pekko/stream/MapAsyncPartitioned.scala:
##########
@@ -0,0 +1,346 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.pekko.stream
+
+import scala.collection.mutable
+import scala.concurrent.Future
+import scala.util.control.{ NoStackTrace, NonFatal }
+import scala.util.{ Failure, Success, Try }
+
+import org.apache.pekko
+import pekko.dispatch.ExecutionContexts
+import pekko.stream.ActorAttributes.SupervisionStrategy
+import pekko.stream.Attributes.{ Name, SourceLocation }
+import pekko.stream.MapAsyncPartitioned._
+import pekko.stream.scaladsl.{ Flow, FlowWithContext, Source, SourceWithContext }
+import pekko.stream.stage._
+
+private[stream] object MapAsyncPartitioned {
+
+ private def extractPartitionWithCtx[In, Ctx, Partition](extract: In => Partition)(tuple: (In, Ctx)): Partition =
+ extract(tuple._1)
+
+ private def fWithCtx[In, Out, Ctx, Partition](f: (In, Partition) => Future[Out])(tuple: (In, Ctx),
+ partition: Partition): Future[(Out, Ctx)] =
+ f(tuple._1, partition).map(_ -> tuple._2)(ExecutionContexts.parasitic)
+
+ def mapSourceOrdered[In, Out, Partition, Mat](source: Source[In, Mat], parallelism: Int)(
+ extractPartition: In => Partition)(
+ f: (In, Partition) => Future[Out]): Source[Out, Mat] =
+ source.via(new MapAsyncPartitioned[In, Out, Partition](orderedOutput = true, parallelism, extractPartition, f))
+
+ def mapSourceUnordered[In, Out, Partition, Mat](source: Source[In, Mat], parallelism: Int)(
+ extractPartition: In => Partition)(
+ f: (In, Partition) => Future[Out]): Source[Out, Mat] =
+ source.via(new MapAsyncPartitioned[In, Out, Partition](orderedOutput = false, parallelism, extractPartition, f))
+
+ def mapSourceWithContextOrdered[In, Ctx, T, Partition, Mat](flow: SourceWithContext[In, Ctx, Mat], parallelism: Int)(
+ extractPartition: In => Partition)(
+ f: (In, Partition) => Future[T]): SourceWithContext[T, Ctx, Mat] =
+ flow.via(
+ new MapAsyncPartitioned[(In, Ctx), (T, Ctx), Partition](
+ orderedOutput = true,
+ parallelism,
+ extractPartitionWithCtx(extractPartition),
+ fWithCtx[In, T, Ctx, Partition](f)))
+
+ def mapSourceWithContextUnordered[In, Ctx, T, Partition, Mat](flow: SourceWithContext[In, Ctx, Mat],
+ parallelism: Int)(extractPartition: In => Partition)(
+ f: (In, Partition) => Future[T]): SourceWithContext[T, Ctx, Mat] =
+ flow.via(
+ new MapAsyncPartitioned[(In, Ctx), (T, Ctx), Partition](
+ orderedOutput = false,
+ parallelism,
+ extractPartitionWithCtx(extractPartition),
+ fWithCtx[In, T, Ctx, Partition](f)))
+
+ def mapFlowOrdered[In, Out, T, Partition, Mat](flow: Flow[In, Out, Mat], parallelism: Int)(
+ extractPartition: Out => Partition)(
+ f: (Out, Partition) => Future[T]): Flow[In, T, Mat] =
+ flow.via(new MapAsyncPartitioned[Out, T, Partition](orderedOutput = true, parallelism, extractPartition,
+ f))
+
+ def mapFlowUnordered[In, Out, T, Partition, Mat](flow: Flow[In, Out, Mat], parallelism: Int)(
+ extractPartition: Out => Partition)(
+ f: (Out, Partition) => Future[T]): Flow[In, T, Mat] =
+ flow.via(new MapAsyncPartitioned[Out, T, Partition](orderedOutput = false, parallelism,
+ extractPartition, f))
+
+ def mapFlowWithContextOrdered[In, Out, CtxIn, CtxOut, T, Partition, Mat](
+ flow: FlowWithContext[In, CtxIn, Out, CtxOut, Mat], parallelism: Int)(
+ extractPartition: Out => Partition)(
+ f: (Out, Partition) => Future[T]): FlowWithContext[In, CtxIn, T, CtxOut, Mat] =
+ flow.via(
+ new MapAsyncPartitioned[(Out, CtxOut), (T, CtxOut), Partition](
+ orderedOutput = true,
+ parallelism,
+ extractPartitionWithCtx(extractPartition),
+ fWithCtx[Out, T, CtxOut, Partition](f)))
+
+ def mapFlowWithContextUnordered[In, Out, CtxIn, CtxOut, T, Partition, Mat](
+ flow: FlowWithContext[In, CtxIn, Out, CtxOut, Mat], parallelism: Int)(extractPartition: Out => Partition)(
+ f: (Out, Partition) => Future[T]): FlowWithContext[In, CtxIn, T, CtxOut, Mat] =
+ flow.via(
+ new MapAsyncPartitioned[(Out, CtxOut), (T, CtxOut), Partition](
+ orderedOutput = false,
+ parallelism,
+ extractPartitionWithCtx(extractPartition),
+ fWithCtx[Out, T, CtxOut, Partition](f)))
+
+ private[stream] val NotYetThere: Failure[Nothing] = Failure(new Exception with NoStackTrace)
+
+ private[stream] final class Holder[In, Out](
+ val in: In,
+ var out: Try[Out],
+ callback: AsyncCallback[Holder[In, Out]]) extends (Try[Out] => Unit) {
+
+ // To support both fail-fast when the supervision directive is Stop
+ // and not calling the decider multiple times (#23888) we need to cache the decider result and re-use that
+ private var cachedSupervisionDirective: Option[Supervision.Directive] = None
+
+ def supervisionDirectiveFor(decider: Supervision.Decider, ex: Throwable): Supervision.Directive = {
+ cachedSupervisionDirective match {
+ case Some(d) => d
+ case _ =>
+ val d = decider(ex)
+ cachedSupervisionDirective = Some(d)
+ d
+ }
+ }
+
+ def setOut(t: Try[Out]): Unit =
+ out = t
+
+ override def apply(t: Try[Out]): Unit = {
+ setOut(t)
+ callback.invoke(this)
+ }
+ }
+}
+
+private[stream] class MapAsyncPartitioned[In, Out, Partition](
+ orderedOutput: Boolean,
+ parallelism: Int,
+ extractPartition: In => Partition,
+ f: (In, Partition) => Future[Out]) extends GraphStage[FlowShape[In, Out]] {
+
+ if (parallelism < 1) throw new IllegalArgumentException("parallelism must be at least 1")
+
+ private val in = Inlet[In]("MapAsyncPartitionOrdered.in")
+ private val out = Outlet[Out]("MapAsyncPartitionOrdered.out")
+
+ override val shape: FlowShape[In, Out] = FlowShape(in, out)
+
+ override def initialAttributes: Attributes =
+ Attributes(Name("MapAsyncPartitionOrdered")) and SourceLocation.forLambda(f)
+
+ override def createLogic(inheritedAttributes: Attributes): GraphStageLogic =
+ new GraphStageLogic(shape) with InHandler with OutHandler {
+ private val contextPropagation = pekko.stream.impl.ContextPropagation()
+
+ private final class Contextual[T](context: AnyRef, val element: T) {
+ private var suspended = false
+
+ def suspend(): Unit =
+ if (!suspended) {
+ suspended = true
+ contextPropagation.suspendContext()
+ }
+
+ def resume(): Unit =
+ if (suspended) {
+ suspended = false
+ contextPropagation.resumeContext(context)
+ }
+
+ }
+
+ private lazy val decider = inheritedAttributes.mandatoryAttribute[SupervisionStrategy].decider
+
+ private var partitionsInProgress: mutable.Set[Partition] = _
+ private var buffer: mutable.Queue[(Partition, Contextual[Holder[In, Out]])] = _
+
+ private val futureCB = getAsyncCallback[Holder[In, Out]](holder =>
+ holder.out match {
+ case Success(_) => pushNextIfPossible()
+ case Failure(ex) =>
+ holder.supervisionDirectiveFor(decider, ex) match {
+ // fail fast as if supervision says so
+ case Supervision.Stop => failStage(ex)
+ case _ => pushNextIfPossible()
+ }
+ })
+
+ override def preStart(): Unit = {
+ partitionsInProgress = mutable.Set()
+ buffer = mutable.Queue()
+ }
+
+ override def onPull(): Unit =
+ pushNextIfPossible()
+
+ override def onPush(): Unit = {
+ try {
+ val element = grab(in)
+ val partition = extractPartition(element)
+
+ val wrappedInput = new Contextual(
+ contextPropagation.currentContext(),
+ new Holder[In, Out](element, NotYetThere, futureCB))
+
+ buffer.enqueue(partition -> wrappedInput)
+
+ if (canStartNextElement(partition)) {
+ processElement(partition, wrappedInput)
+ } else {
+ wrappedInput.suspend()
+ }
+ } catch {
+ case NonFatal(ex) => if (decider(ex) == Supervision.Stop) failStage(ex)
+ }
+
+ pullIfNeeded()
+ }
+
+ override def onUpstreamFinish(): Unit =
+ if (idle()) completeStage()
+
+ private def processElement(partition: Partition, wrappedInput: Contextual[Holder[In, Out]]): Unit = {
+ import wrappedInput.{ element => holder }
+ val future = f(holder.in, partition)
+
+ partitionsInProgress += partition
+
+ future.value match {
+ case None => future.onComplete(holder)(ExecutionContexts.parasitic)
+ case Some(v) =>
+ // #20217 the future is already here, optimization: avoid scheduling it on the dispatcher and
Review Comment:
There is no `#20217` in this repo
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[GitHub] [incubator-pekko] jaceksokol commented on pull request #561: mapAsyncPartitioned / mapAsyncPartitionedUnordered
Posted by "jaceksokol (via GitHub)" <gi...@apache.org>.
jaceksokol commented on PR #561:
URL: https://github.com/apache/incubator-pekko/pull/561#issuecomment-1715078452
Yes, this operator may help mitigate the head-of-line problem. The main performance optimisation is related to the fact that values for different keys can be usually processed independently (in parallel in this case).
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[GitHub] [incubator-pekko] pjfanning merged pull request #561: mapAsyncPartitioned / mapAsyncPartitionedUnordered
Posted by "pjfanning (via GitHub)" <gi...@apache.org>.
pjfanning merged PR #561:
URL: https://github.com/apache/incubator-pekko/pull/561
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[GitHub] [incubator-pekko] pjfanning commented on a diff in pull request #561: [DRAFT] MapAsyncPartitioned
Posted by "pjfanning (via GitHub)" <gi...@apache.org>.
pjfanning commented on code in PR #561:
URL: https://github.com/apache/incubator-pekko/pull/561#discussion_r1297219660
##########
legal/pekko-stream-jar-license.txt:
##########
@@ -0,0 +1,231 @@
+ Apache License
+ Version 2.0, January 2004
+ http://www.apache.org/licenses/
+
+ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+ 1. Definitions.
+
+ "License" shall mean the terms and conditions for use, reproduction,
+ and distribution as defined by Sections 1 through 9 of this document.
+
+ "Licensor" shall mean the copyright owner or entity authorized by
+ the copyright owner that is granting the License.
+
+ "Legal Entity" shall mean the union of the acting entity and all
+ other entities that control, are controlled by, or are under common
+ control with that entity. For the purposes of this definition,
+ "control" means (i) the power, direct or indirect, to cause the
+ direction or management of such entity, whether by contract or
+ otherwise, or (ii) ownership of fifty percent (50%) or more of the
+ outstanding shares, or (iii) beneficial ownership of such entity.
+
+ "You" (or "Your") shall mean an individual or Legal Entity
+ exercising permissions granted by this License.
+
+ "Source" form shall mean the preferred form for making modifications,
+ including but not limited to software source code, documentation
+ source, and configuration files.
+
+ "Object" form shall mean any form resulting from mechanical
+ transformation or translation of a Source form, including but
+ not limited to compiled object code, generated documentation,
+ and conversions to other media types.
+
+ "Work" shall mean the work of authorship, whether in Source or
+ Object form, made available under the License, as indicated by a
+ copyright notice that is included in or attached to the work
+ (an example is provided in the Appendix below).
+
+ "Derivative Works" shall mean any work, whether in Source or Object
+ form, that is based on (or derived from) the Work and for which the
+ editorial revisions, annotations, elaborations, or other modifications
+ represent, as a whole, an original work of authorship. For the purposes
+ of this License, Derivative Works shall not include works that remain
+ separable from, or merely link (or bind by name) to the interfaces of,
+ the Work and Derivative Works thereof.
+
+ "Contribution" shall mean any work of authorship, including
+ the original version of the Work and any modifications or additions
+ to that Work or Derivative Works thereof, that is intentionally
+ submitted to Licensor for inclusion in the Work by the copyright owner
+ or by an individual or Legal Entity authorized to submit on behalf of
+ the copyright owner. For the purposes of this definition, "submitted"
+ means any form of electronic, verbal, or written communication sent
+ to the Licensor or its representatives, including but not limited to
+ communication on electronic mailing lists, source code control systems,
+ and issue tracking systems that are managed by, or on behalf of, the
+ Licensor for the purpose of discussing and improving the Work, but
+ excluding communication that is conspicuously marked or otherwise
+ designated in writing by the copyright owner as "Not a Contribution."
+
+ "Contributor" shall mean Licensor and any individual or Legal Entity
+ on behalf of whom a Contribution has been received by Licensor and
+ subsequently incorporated within the Work.
+
+ 2. Grant of Copyright License. Subject to the terms and conditions of
+ this License, each Contributor hereby grants to You a perpetual,
+ worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+ copyright license to reproduce, prepare Derivative Works of,
+ publicly display, publicly perform, sublicense, and distribute the
+ Work and such Derivative Works in Source or Object form.
+
+ 3. Grant of Patent License. Subject to the terms and conditions of
+ this License, each Contributor hereby grants to You a perpetual,
+ worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+ (except as stated in this section) patent license to make, have made,
+ use, offer to sell, sell, import, and otherwise transfer the Work,
+ where such license applies only to those patent claims licensable
+ by such Contributor that are necessarily infringed by their
+ Contribution(s) alone or by combination of their Contribution(s)
+ with the Work to which such Contribution(s) was submitted. If You
+ institute patent litigation against any entity (including a
+ cross-claim or counterclaim in a lawsuit) alleging that the Work
+ or a Contribution incorporated within the Work constitutes direct
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+ granted to You under this License for that Work shall terminate
+ as of the date such litigation is filed.
+
+ 4. Redistribution. You may reproduce and distribute copies of the
+ Work or Derivative Works thereof in any medium, with or without
+ modifications, and in Source or Object form, provided that You
+ meet the following conditions:
+
+ (a) You must give any other recipients of the Work or
+ Derivative Works a copy of this License; and
+
+ (b) You must cause any modified files to carry prominent notices
+ stating that You changed the files; and
+
+ (c) You must retain, in the Source form of any Derivative Works
+ that You distribute, all copyright, patent, trademark, and
+ attribution notices from the Source form of the Work,
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+ (d) If the Work includes a "NOTICE" text file as part of its
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+ wherever such third-party notices normally appear. The contents
+ of the NOTICE file are for informational purposes only and
+ do not modify the License. You may add Your own attribution
+ notices within Derivative Works that You distribute, alongside
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+ that such additional attribution notices cannot be construed
+ as modifying the License.
+
+ You may add Your own copyright statement to Your modifications and
+ may provide additional or different license terms and conditions
+ for use, reproduction, or distribution of Your modifications, or
+ for any such Derivative Works as a whole, provided Your use,
+ reproduction, and distribution of the Work otherwise complies with
+ the conditions stated in this License.
+
+ 5. Submission of Contributions. Unless You explicitly state otherwise,
+ any Contribution intentionally submitted for inclusion in the Work
+ by You to the Licensor shall be under the terms and conditions of
+ this License, without any additional terms or conditions.
+ Notwithstanding the above, nothing herein shall supersede or modify
+ the terms of any separate license agreement you may have executed
+ with Licensor regarding such Contributions.
+
+ 6. Trademarks. This License does not grant permission to use the trade
+ names, trademarks, service marks, or product names of the Licensor,
+ except as required for reasonable and customary use in describing the
+ origin of the Work and reproducing the content of the NOTICE file.
+
+ 7. Disclaimer of Warranty. Unless required by applicable law or
+ agreed to in writing, Licensor provides the Work (and each
+ Contributor provides its Contributions) on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
+ implied, including, without limitation, any warranties or conditions
+ of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
+ PARTICULAR PURPOSE. You are solely responsible for determining the
+ appropriateness of using or redistributing the Work and assume any
+ risks associated with Your exercise of permissions under this License.
+
+ 8. Limitation of Liability. In no event and under no legal theory,
+ whether in tort (including negligence), contract, or otherwise,
+ unless required by applicable law (such as deliberate and grossly
+ negligent acts) or agreed to in writing, shall any Contributor be
+ liable to You for damages, including any direct, indirect, special,
+ incidental, or consequential damages of any character arising as a
+ result of this License or out of the use or inability to use the
+ Work (including but not limited to damages for loss of goodwill,
+ work stoppage, computer failure or malfunction, or any and all
+ other commercial damages or losses), even if such Contributor
+ has been advised of the possibility of such damages.
+
+ 9. Accepting Warranty or Additional Liability. While redistributing
+ the Work or Derivative Works thereof, You may choose to offer,
+ and charge a fee for, acceptance of support, warranty, indemnity,
+ or other liability obligations and/or rights consistent with this
+ License. However, in accepting such obligations, You may act only
+ on Your own behalf and on Your sole responsibility, not on behalf
+ of any other Contributor, and only if You agree to indemnify,
+ defend, and hold each Contributor harmless for any liability
+ incurred by, or claims asserted against, such Contributor by reason
+ of your accepting any such warranty or additional liability.
+
+ END OF TERMS AND CONDITIONS
+
+ APPENDIX: How to apply the Apache License to your work.
+
+ To apply the Apache License to your work, attach the following
+ boilerplate notice, with the fields enclosed by brackets "[]"
+ replaced with your own identifying information. (Don't include
+ the brackets!) The text should be enclosed in the appropriate
+ comment syntax for the file format. We also recommend that a
+ file or class name and description of purpose be included on the
+ same "printed page" as the copyright notice for easier
+ identification within third-party archives.
+
+ Copyright [yyyy] [name of copyright owner]
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+
+---------------
+
+pekko-stream contains code derived from jaceksokol/akka-stream-map-async-partition
+<https://github.com/jaceksokol/akka-stream-map-async-partition>
+wich is licensed under an MIT License.
+
+ - stream/src/main/scala/org/apache/pekko/stream/MapAsyncPartition.scala
+
+MIT License
+
+Copyright (c) 2021 Jacek Sokol
Review Comment:
I think we can support both.
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[GitHub] [incubator-pekko] He-Pin commented on pull request #561: mapAsyncPartitioned / mapAsyncPartitionedUnordered
Posted by "He-Pin (via GitHub)" <gi...@apache.org>.
He-Pin commented on PR #561:
URL: https://github.com/apache/incubator-pekko/pull/561#issuecomment-1714400269
> > @pjfanning It would be nice to compare the performance boost with `mapAsync`.
>
> This is a new set of functions - so I don't think a perf test is necessary. @jaceksokol would you have a sample scenario where the mapAsyncPartitioned was better for you than mapAsync?
I think when the a head of line problem occurs ？
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[GitHub] [incubator-pekko] He-Pin commented on pull request #561: mapAsyncPartitioned / mapAsyncPartitionedUnordered
Posted by "He-Pin (via GitHub)" <gi...@apache.org>.
He-Pin commented on PR #561:
URL: https://github.com/apache/incubator-pekko/pull/561#issuecomment-1713073207
@pjfanning @mdedetrich I will need more time to review this, I will try to after work today, overall ,looking very good.
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[GitHub] [incubator-pekko] jaceksokol commented on a diff in pull request #561: [DRAFT] MapAsyncPartition
Posted by "jaceksokol (via GitHub)" <gi...@apache.org>.
jaceksokol commented on code in PR #561:
URL: https://github.com/apache/incubator-pekko/pull/561#discussion_r1296930741
##########
legal/pekko-stream-jar-license.txt:
##########
@@ -0,0 +1,231 @@
+ Apache License
+ Version 2.0, January 2004
+ http://www.apache.org/licenses/
+
+ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+ 1. Definitions.
+
+ "License" shall mean the terms and conditions for use, reproduction,
+ and distribution as defined by Sections 1 through 9 of this document.
+
+ "Licensor" shall mean the copyright owner or entity authorized by
+ the copyright owner that is granting the License.
+
+ "Legal Entity" shall mean the union of the acting entity and all
+ other entities that control, are controlled by, or are under common
+ control with that entity. For the purposes of this definition,
+ "control" means (i) the power, direct or indirect, to cause the
+ direction or management of such entity, whether by contract or
+ otherwise, or (ii) ownership of fifty percent (50%) or more of the
+ outstanding shares, or (iii) beneficial ownership of such entity.
+
+ "You" (or "Your") shall mean an individual or Legal Entity
+ exercising permissions granted by this License.
+
+ "Source" form shall mean the preferred form for making modifications,
+ including but not limited to software source code, documentation
+ source, and configuration files.
+
+ "Object" form shall mean any form resulting from mechanical
+ transformation or translation of a Source form, including but
+ not limited to compiled object code, generated documentation,
+ and conversions to other media types.
+
+ "Work" shall mean the work of authorship, whether in Source or
+ Object form, made available under the License, as indicated by a
+ copyright notice that is included in or attached to the work
+ (an example is provided in the Appendix below).
+
+ "Derivative Works" shall mean any work, whether in Source or Object
+ form, that is based on (or derived from) the Work and for which the
+ editorial revisions, annotations, elaborations, or other modifications
+ represent, as a whole, an original work of authorship. For the purposes
+ of this License, Derivative Works shall not include works that remain
+ separable from, or merely link (or bind by name) to the interfaces of,
+ the Work and Derivative Works thereof.
+
+ "Contribution" shall mean any work of authorship, including
+ the original version of the Work and any modifications or additions
+ to that Work or Derivative Works thereof, that is intentionally
+ submitted to Licensor for inclusion in the Work by the copyright owner
+ or by an individual or Legal Entity authorized to submit on behalf of
+ the copyright owner. For the purposes of this definition, "submitted"
+ means any form of electronic, verbal, or written communication sent
+ to the Licensor or its representatives, including but not limited to
+ communication on electronic mailing lists, source code control systems,
+ and issue tracking systems that are managed by, or on behalf of, the
+ Licensor for the purpose of discussing and improving the Work, but
+ excluding communication that is conspicuously marked or otherwise
+ designated in writing by the copyright owner as "Not a Contribution."
+
+ "Contributor" shall mean Licensor and any individual or Legal Entity
+ on behalf of whom a Contribution has been received by Licensor and
+ subsequently incorporated within the Work.
+
+ 2. Grant of Copyright License. Subject to the terms and conditions of
+ this License, each Contributor hereby grants to You a perpetual,
+ worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+ copyright license to reproduce, prepare Derivative Works of,
+ publicly display, publicly perform, sublicense, and distribute the
+ Work and such Derivative Works in Source or Object form.
+
+ 3. Grant of Patent License. Subject to the terms and conditions of
+ this License, each Contributor hereby grants to You a perpetual,
+ worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+ (except as stated in this section) patent license to make, have made,
+ use, offer to sell, sell, import, and otherwise transfer the Work,
+ where such license applies only to those patent claims licensable
+ by such Contributor that are necessarily infringed by their
+ Contribution(s) alone or by combination of their Contribution(s)
+ with the Work to which such Contribution(s) was submitted. If You
+ institute patent litigation against any entity (including a
+ cross-claim or counterclaim in a lawsuit) alleging that the Work
+ or a Contribution incorporated within the Work constitutes direct
+ or contributory patent infringement, then any patent licenses
+ granted to You under this License for that Work shall terminate
+ as of the date such litigation is filed.
+
+ 4. Redistribution. You may reproduce and distribute copies of the
+ Work or Derivative Works thereof in any medium, with or without
+ modifications, and in Source or Object form, provided that You
+ meet the following conditions:
+
+ (a) You must give any other recipients of the Work or
+ Derivative Works a copy of this License; and
+
+ (b) You must cause any modified files to carry prominent notices
+ stating that You changed the files; and
+
+ (c) You must retain, in the Source form of any Derivative Works
+ that You distribute, all copyright, patent, trademark, and
+ attribution notices from the Source form of the Work,
+ excluding those notices that do not pertain to any part of
+ the Derivative Works; and
+
+ (d) If the Work includes a "NOTICE" text file as part of its
+ distribution, then any Derivative Works that You distribute must
+ include a readable copy of the attribution notices contained
+ within such NOTICE file, excluding those notices that do not
+ pertain to any part of the Derivative Works, in at least one
+ of the following places: within a NOTICE text file distributed
+ as part of the Derivative Works; within the Source form or
+ documentation, if provided along with the Derivative Works; or,
+ within a display generated by the Derivative Works, if and
+ wherever such third-party notices normally appear. The contents
+ of the NOTICE file are for informational purposes only and
+ do not modify the License. You may add Your own attribution
+ notices within Derivative Works that You distribute, alongside
+ or as an addendum to the NOTICE text from the Work, provided
+ that such additional attribution notices cannot be construed
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+
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+ may provide additional or different license terms and conditions
+ for use, reproduction, or distribution of Your modifications, or
+ for any such Derivative Works as a whole, provided Your use,
+ reproduction, and distribution of the Work otherwise complies with
+ the conditions stated in this License.
+
+ 5. Submission of Contributions. Unless You explicitly state otherwise,
+ any Contribution intentionally submitted for inclusion in the Work
+ by You to the Licensor shall be under the terms and conditions of
+ this License, without any additional terms or conditions.
+ Notwithstanding the above, nothing herein shall supersede or modify
+ the terms of any separate license agreement you may have executed
+ with Licensor regarding such Contributions.
+
+ 6. Trademarks. This License does not grant permission to use the trade
+ names, trademarks, service marks, or product names of the Licensor,
+ except as required for reasonable and customary use in describing the
+ origin of the Work and reproducing the content of the NOTICE file.
+
+ 7. Disclaimer of Warranty. Unless required by applicable law or
+ agreed to in writing, Licensor provides the Work (and each
+ Contributor provides its Contributions) on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
+ implied, including, without limitation, any warranties or conditions
+ of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
+ PARTICULAR PURPOSE. You are solely responsible for determining the
+ appropriateness of using or redistributing the Work and assume any
+ risks associated with Your exercise of permissions under this License.
+
+ 8. Limitation of Liability. In no event and under no legal theory,
+ whether in tort (including negligence), contract, or otherwise,
+ unless required by applicable law (such as deliberate and grossly
+ negligent acts) or agreed to in writing, shall any Contributor be
+ liable to You for damages, including any direct, indirect, special,
+ incidental, or consequential damages of any character arising as a
+ result of this License or out of the use or inability to use the
+ Work (including but not limited to damages for loss of goodwill,
+ work stoppage, computer failure or malfunction, or any and all
+ other commercial damages or losses), even if such Contributor
+ has been advised of the possibility of such damages.
+
+ 9. Accepting Warranty or Additional Liability. While redistributing
+ the Work or Derivative Works thereof, You may choose to offer,
+ and charge a fee for, acceptance of support, warranty, indemnity,
+ or other liability obligations and/or rights consistent with this
+ License. However, in accepting such obligations, You may act only
+ on Your own behalf and on Your sole responsibility, not on behalf
+ of any other Contributor, and only if You agree to indemnify,
+ defend, and hold each Contributor harmless for any liability
+ incurred by, or claims asserted against, such Contributor by reason
+ of your accepting any such warranty or additional liability.
+
+ END OF TERMS AND CONDITIONS
+
+ APPENDIX: How to apply the Apache License to your work.
+
+ To apply the Apache License to your work, attach the following
+ boilerplate notice, with the fields enclosed by brackets "[]"
+ replaced with your own identifying information. (Don't include
+ the brackets!) The text should be enclosed in the appropriate
+ comment syntax for the file format. We also recommend that a
+ file or class name and description of purpose be included on the
+ same "printed page" as the copyright notice for easier
+ identification within third-party archives.
+
+ Copyright [yyyy] [name of copyright owner]
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+
+---------------
+
+pekko-stream contains code derived from jaceksokol/akka-stream-map-async-partition
+<https://github.com/jaceksokol/akka-stream-map-async-partition>
+wich is licensed under an MIT License.
+
+ - stream/src/main/scala/org/apache/pekko/stream/MapAsyncPartition.scala
+
+MIT License
+
+Copyright (c) 2021 Jacek Sokol
Review Comment:
I added an ordered version of the operator, please check this out: https://github.com/pjfanning/incubator-pekko/pull/1. I'm not sure if we need both versions. When I was developing the operator a couple of years ago, the use case I had did not require the order of the output elements to be the same as in the input.
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[GitHub] [incubator-pekko] He-Pin commented on pull request #561: mapAsyncPartitioned / mapAsyncPartitionedUnordered
Posted by "He-Pin (via GitHub)" <gi...@apache.org>.
He-Pin commented on PR #561:
URL: https://github.com/apache/incubator-pekko/pull/561#issuecomment-1729951868
@pjfanning Do you have more to update on this, I will go through it this weekend.
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[GitHub] [incubator-pekko] gmethvin commented on a diff in pull request #561: [DRAFT] MapAsyncPartition
Posted by "gmethvin (via GitHub)" <gi...@apache.org>.
gmethvin commented on code in PR #561:
URL: https://github.com/apache/incubator-pekko/pull/561#discussion_r1295426708
##########
legal/pekko-stream-jar-license.txt:
##########
@@ -0,0 +1,231 @@
+ Apache License
+ Version 2.0, January 2004
+ http://www.apache.org/licenses/
+
+ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+ 1. Definitions.
+
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+
+ To apply the Apache License to your work, attach the following
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+ replaced with your own identifying information. (Don't include
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+ same "printed page" as the copyright notice for easier
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+
+ Copyright [yyyy] [name of copyright owner]
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
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+
+---------------
+
+pekko-stream contains code derived from jaceksokol/akka-stream-map-async-partition
+<https://github.com/jaceksokol/akka-stream-map-async-partition>
+wich is licensed under an MIT License.
+
+ - stream/src/main/scala/org/apache/pekko/stream/MapAsyncPartition.scala
+
+MIT License
+
+Copyright (c) 2021 Jacek Sokol
Review Comment:
@jaceksokol it's up to you whether we include this. If you don't mind, you can choose to contribute this work under Pekko's standard Apache license, without your copyright notice. This would make things a bit simpler for us but it's ultimately your call.
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[GitHub] [incubator-pekko] pjfanning commented on pull request #561: mapAsyncPartitioned / mapAsyncPartitionedUnordered
Posted by "pjfanning (via GitHub)" <gi...@apache.org>.
pjfanning commented on PR #561:
URL: https://github.com/apache/incubator-pekko/pull/561#issuecomment-1714028802
> @pjfanning It would be nice to compare the performance boost with `mapAsync`.
This is a new set of functions - so I don't think a perf test is necessary. @jaceksokol would you have a sample scenario where the mapAsyncPartitioned was better for you than mapAsync?
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[GitHub] [incubator-pekko] jaceksokol commented on a diff in pull request #561: [DRAFT] MapAsyncPartition
Posted by "jaceksokol (via GitHub)" <gi...@apache.org>.
jaceksokol commented on code in PR #561:
URL: https://github.com/apache/incubator-pekko/pull/561#discussion_r1294291763
##########
legal/pekko-stream-jar-license.txt:
##########
@@ -0,0 +1,231 @@
+ Apache License
+ Version 2.0, January 2004
+ http://www.apache.org/licenses/
+
+ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+ 1. Definitions.
+
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+
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+
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+
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+
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+
+ To apply the Apache License to your work, attach the following
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+ replaced with your own identifying information. (Don't include
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+ same "printed page" as the copyright notice for easier
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+
+ Copyright [yyyy] [name of copyright owner]
+
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+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
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+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+
+---------------
+
+pekko-stream contains code derived from jaceksokol/akka-stream-map-async-partition
+<https://github.com/jaceksokol/akka-stream-map-async-partition>
+wich is licensed under an MIT License.
+
+ - stream/src/main/scala/org/apache/pekko/stream/MapAsyncPartition.scala
+
+MIT License
+
+Copyright (c) 2021 Jacek Sokol
Review Comment:
I guess you don't want my name here 😉
##########
legal/pekko-stream-jar-license.txt:
##########
@@ -0,0 +1,231 @@
+ Apache License
+ Version 2.0, January 2004
+ http://www.apache.org/licenses/
+
+ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+ 1. Definitions.
+
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+ form, that is based on (or derived from) the Work and for which the
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+ submitted to Licensor for inclusion in the Work by the copyright owner
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+ the copyright owner. For the purposes of this definition, "submitted"
+ means any form of electronic, verbal, or written communication sent
+ to the Licensor or its representatives, including but not limited to
+ communication on electronic mailing lists, source code control systems,
+ and issue tracking systems that are managed by, or on behalf of, the
+ Licensor for the purpose of discussing and improving the Work, but
+ excluding communication that is conspicuously marked or otherwise
+ designated in writing by the copyright owner as "Not a Contribution."
+
+ "Contributor" shall mean Licensor and any individual or Legal Entity
+ on behalf of whom a Contribution has been received by Licensor and
+ subsequently incorporated within the Work.
+
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+ this License, each Contributor hereby grants to You a perpetual,
+ worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+ copyright license to reproduce, prepare Derivative Works of,
+ publicly display, publicly perform, sublicense, and distribute the
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+ worldwide, non-exclusive, no-charge, royalty-free, irrevocable
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+ or contributory patent infringement, then any patent licenses
+ granted to You under this License for that Work shall terminate
+ as of the date such litigation is filed.
+
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+ Work or Derivative Works thereof in any medium, with or without
+ modifications, and in Source or Object form, provided that You
+ meet the following conditions:
+
+ (a) You must give any other recipients of the Work or
+ Derivative Works a copy of this License; and
+
+ (b) You must cause any modified files to carry prominent notices
+ stating that You changed the files; and
+
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+---------------
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+pekko-stream contains code derived from jaceksokol/akka-stream-map-async-partition
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+ - stream/src/main/scala/org/apache/pekko/stream/MapAsyncPartition.scala
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+MIT License
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+Copyright (c) 2021 Jacek Sokol
Review Comment:
I guess you don't want my name here 😉
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[GitHub] [incubator-pekko] jaceksokol commented on pull request #561: [DRAFT] MapAsyncPartition
Posted by "jaceksokol (via GitHub)" <gi...@apache.org>.
jaceksokol commented on PR #561:
URL: https://github.com/apache/incubator-pekko/pull/561#issuecomment-1678548067
LGTM
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[GitHub] [incubator-pekko] pjfanning commented on pull request #561: mapAsyncPartitioned / mapAsyncPartitionedUnordered
Posted by "pjfanning (via GitHub)" <gi...@apache.org>.
pjfanning commented on PR #561:
URL: https://github.com/apache/incubator-pekko/pull/561#issuecomment-1729960705
@He-Pin I'm not planning anything more on this, My view is it is big enough already. The impl can be tweaked in follow up PRs. If there is anything fundamentally wrong with the code then of course, the PR will not be merged until that issue is addressed,
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[GitHub] [incubator-pekko] He-Pin commented on pull request #561: mapAsyncPartitioned / mapAsyncPartitionedUnordered
Posted by "He-Pin (via GitHub)" <gi...@apache.org>.
He-Pin commented on PR #561:
URL: https://github.com/apache/incubator-pekko/pull/561#issuecomment-1713134033
@pjfanning It would be nice to compare the performance boost with `mapAsync`.
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