zentol commented on code in PR #21981:
URL: https://github.com/apache/flink/pull/21981#discussion_r1112826336
##########
flink-runtime/src/main/java/org/apache/flink/runtime/scheduler/adaptive/StateTransitions.java:
##########
@@ -163,7 +165,12 @@ CompletableFuture<String> goToStopWithSavepoint(
/** Interface covering transition to the {@link WaitingForResources}
state. */
interface ToWaitingForResources extends StateTransitions {
- /** Transitions into the {@link WaitingForResources} state. */
+ /**
+ * Transitions into the {@link WaitingForResources} state without
{@link ExecutionGraph}
+ * (e.g. after creation).
+ */
void goToWaitingForResources();
+ /** Transitions into the {@link WaitingForResources} state (e.g. after
restarting). */
+ void goToWaitingForResources(ExecutionGraph executionGraph);
Review Comment:
It's not great to have a second method. It implies that these 2 states are
somehow different.
##########
flink-runtime/src/main/java/org/apache/flink/runtime/scheduler/adaptive/allocator/DefaultSlotAssigner.java:
##########
@@ -0,0 +1,45 @@
+/*
+ * 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.flink.runtime.scheduler.adaptive.allocator;
+
+import org.apache.flink.runtime.jobmaster.SlotInfo;
+
+import java.util.ArrayList;
+import java.util.Collection;
+import java.util.Iterator;
+import java.util.List;
+
+/** Simple {@link SlotAssigner} that threats all slots and slot sharing groups
equally. */
Review Comment:
```suggestion
/** Simple {@link SlotAssigner} that treats all slots and slot sharing
groups equally. */
```
##########
flink-runtime/src/main/java/org/apache/flink/runtime/scheduler/adaptive/allocator/StateLocalitySlotAssigner.java:
##########
@@ -0,0 +1,209 @@
+/*
+ * 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.flink.runtime.scheduler.adaptive.allocator;
+
+import org.apache.flink.annotation.Internal;
+import org.apache.flink.runtime.clusterframework.types.AllocationID;
+import org.apache.flink.runtime.executiongraph.ExecutionGraph;
+import org.apache.flink.runtime.executiongraph.ExecutionJobVertex;
+import org.apache.flink.runtime.executiongraph.ExecutionVertex;
+import org.apache.flink.runtime.jobgraph.JobVertexID;
+import org.apache.flink.runtime.jobmaster.SlotInfo;
+import
org.apache.flink.runtime.scheduler.adaptive.allocator.SlotSharingSlotAllocator.ExecutionSlotSharingGroup;
+import
org.apache.flink.runtime.scheduler.adaptive.allocator.SlotSharingSlotAllocator.ExecutionSlotSharingGroupAndSlot;
+import org.apache.flink.runtime.scheduler.strategy.ExecutionVertexID;
+import org.apache.flink.runtime.state.KeyGroupRange;
+import org.apache.flink.runtime.state.KeyGroupRangeAssignment;
+import org.apache.flink.util.Preconditions;
+
+import java.util.ArrayList;
+import java.util.Collection;
+import java.util.Comparator;
+import java.util.HashMap;
+import java.util.Iterator;
+import java.util.List;
+import java.util.Map;
+import java.util.PriorityQueue;
+import java.util.stream.StreamSupport;
+
+import static java.util.function.Function.identity;
+import static java.util.stream.Collectors.toMap;
+
+/** A {@link SlotAssigner} that assigns slots based on the number of local key
groups. */
+@Internal
+public class StateLocalitySlotAssigner implements SlotAssigner {
+
+ private static class AllocationScore implements
Comparable<AllocationScore> {
+
+ private final String group;
+ private final AllocationID allocationId;
+
+ public AllocationScore(String group, AllocationID allocationId, int
score) {
+ this.group = group;
+ this.allocationId = allocationId;
+ this.score = score;
+ }
+
+ private final int score;
+
+ public String getGroup() {
+ return group;
+ }
+
+ public AllocationID getAllocationId() {
+ return allocationId;
+ }
+
+ public int getScore() {
+ return score;
+ }
+
+ @Override
+ public int compareTo(StateLocalitySlotAssigner.AllocationScore other) {
+ int result = Integer.compare(score, other.score);
+ if (result != 0) {
+ return result;
+ }
+ result = other.allocationId.compareTo(allocationId);
+ if (result != 0) {
+ return result;
+ }
+ return other.group.compareTo(group);
+ }
+ }
+
+ private final Map<AllocationID, Map<JobVertexID, KeyGroupRange>> locality;
+ private final Map<JobVertexID, Integer> maxParallelism;
+
+ public StateLocalitySlotAssigner(ExecutionGraph archivedExecutionGraph) {
+ this(
+ calculateLocalKeyGroups(archivedExecutionGraph),
+ StreamSupport.stream(
+
archivedExecutionGraph.getVerticesTopologically().spliterator(),
+ false)
+ .collect(
+ toMap(
+ ExecutionJobVertex::getJobVertexId,
+
ExecutionJobVertex::getMaxParallelism)));
+ }
+
+ public StateLocalitySlotAssigner(
+ Map<AllocationID, Map<JobVertexID, KeyGroupRange>> locality,
+ Map<JobVertexID, Integer> maxParallelism) {
+ this.locality = locality;
+ this.maxParallelism = maxParallelism;
+ }
+
+ @Override
+ public AssignmentResult assignSlots(
+ Collection<? extends SlotInfo> slots,
Collection<ExecutionSlotSharingGroup> groups) {
+
+ final Map<JobVertexID, Integer> parallelism = new HashMap<>();
+ groups.forEach(
+ group ->
+ group.getContainedExecutionVertices()
+ .forEach(
+ evi ->
+ parallelism.merge(
+ evi.getJobVertexId(),
1, Integer::sum)));
Review Comment:
I feel forEach here doesn't actually make the code more readable (the
opposite actually due to indentation).
##########
flink-runtime/src/main/java/org/apache/flink/runtime/scheduler/adaptive/allocator/SlotSharingSlotAllocator.java:
##########
@@ -121,16 +133,13 @@ public Optional<VertexParallelismWithSlotSharing>
determineParallelism(
slotSharingGroupParallelism.get(
slotSharingGroup.getSlotSharingGroupId()));
- final Iterable<ExecutionSlotSharingGroup>
sharedSlotToVertexAssignment =
+ final List<ExecutionSlotSharingGroup> sharedSlotToVertexAssignment
=
createExecutionSlotSharingGroups(vertexParallelism);
- for (ExecutionSlotSharingGroup executionSlotSharingGroup :
- sharedSlotToVertexAssignment) {
- final SlotInfo slotInfo = slotIterator.next();
-
- assignments.add(
- new
ExecutionSlotSharingGroupAndSlot(executionSlotSharingGroup, slotInfo));
- }
+ SlotAssigner.AssignmentResult result =
+ slotAssigner.assignSlots(freeSlots,
sharedSlotToVertexAssignment);
+ assignments.addAll(result.assignments);
+ freeSlots = result.remainingSlots;
Review Comment:
I have some concerns over the implementation.
As I understood it with this PR we only wanted to cover the case where the
parallelism is identical to the previous run; not a rescale case. In that case
I'd like to see us short-cutting the entire `determineParallelism` and
`determineParallelismAndCalculateAssignment` logic to make this obvious.
If this PR intends to go further and handle the rescaling case, then the
interface imo doesn't quite fit, because local recovery is not accounted for in
the distribution of slots across groups.
##########
flink-runtime/src/main/java/org/apache/flink/runtime/scheduler/adaptive/AdaptiveScheduler.java:
##########
@@ -794,7 +802,23 @@ public void goToWaitingForResources() {
LOG,
desiredResources,
this.initialResourceAllocationTimeout,
- this.resourceStabilizationTimeout));
+ this.resourceStabilizationTimeout,
+ null));
+ }
+
+ @Override
+ public void goToWaitingForResources(ExecutionGraph executionGraph) {
Review Comment:
We could, but I'm not sure if we really should sneakily extract state from a
previous state and pass it on to the next one.
##########
flink-runtime/src/main/java/org/apache/flink/runtime/scheduler/adaptive/allocator/StateLocalitySlotAssigner.java:
##########
@@ -0,0 +1,209 @@
+/*
+ * 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.flink.runtime.scheduler.adaptive.allocator;
+
+import org.apache.flink.annotation.Internal;
+import org.apache.flink.runtime.clusterframework.types.AllocationID;
+import org.apache.flink.runtime.executiongraph.ExecutionGraph;
+import org.apache.flink.runtime.executiongraph.ExecutionJobVertex;
+import org.apache.flink.runtime.executiongraph.ExecutionVertex;
+import org.apache.flink.runtime.jobgraph.JobVertexID;
+import org.apache.flink.runtime.jobmaster.SlotInfo;
+import
org.apache.flink.runtime.scheduler.adaptive.allocator.SlotSharingSlotAllocator.ExecutionSlotSharingGroup;
+import
org.apache.flink.runtime.scheduler.adaptive.allocator.SlotSharingSlotAllocator.ExecutionSlotSharingGroupAndSlot;
+import org.apache.flink.runtime.scheduler.strategy.ExecutionVertexID;
+import org.apache.flink.runtime.state.KeyGroupRange;
+import org.apache.flink.runtime.state.KeyGroupRangeAssignment;
+import org.apache.flink.util.Preconditions;
+
+import java.util.ArrayList;
+import java.util.Collection;
+import java.util.Comparator;
+import java.util.HashMap;
+import java.util.Iterator;
+import java.util.List;
+import java.util.Map;
+import java.util.PriorityQueue;
+import java.util.stream.StreamSupport;
+
+import static java.util.function.Function.identity;
+import static java.util.stream.Collectors.toMap;
+
+/** A {@link SlotAssigner} that assigns slots based on the number of local key
groups. */
+@Internal
+public class StateLocalitySlotAssigner implements SlotAssigner {
+
+ private static class AllocationScore implements
Comparable<AllocationScore> {
+
+ private final String group;
+ private final AllocationID allocationId;
+
+ public AllocationScore(String group, AllocationID allocationId, int
score) {
+ this.group = group;
+ this.allocationId = allocationId;
+ this.score = score;
+ }
+
+ private final int score;
+
+ public String getGroup() {
+ return group;
+ }
+
+ public AllocationID getAllocationId() {
+ return allocationId;
+ }
+
+ public int getScore() {
+ return score;
+ }
+
+ @Override
+ public int compareTo(StateLocalitySlotAssigner.AllocationScore other) {
+ int result = Integer.compare(score, other.score);
+ if (result != 0) {
+ return result;
+ }
+ result = other.allocationId.compareTo(allocationId);
+ if (result != 0) {
+ return result;
+ }
+ return other.group.compareTo(group);
+ }
+ }
+
+ private final Map<AllocationID, Map<JobVertexID, KeyGroupRange>> locality;
+ private final Map<JobVertexID, Integer> maxParallelism;
+
+ public StateLocalitySlotAssigner(ExecutionGraph archivedExecutionGraph) {
+ this(
+ calculateLocalKeyGroups(archivedExecutionGraph),
+ StreamSupport.stream(
+
archivedExecutionGraph.getVerticesTopologically().spliterator(),
+ false)
+ .collect(
+ toMap(
+ ExecutionJobVertex::getJobVertexId,
+
ExecutionJobVertex::getMaxParallelism)));
+ }
+
+ public StateLocalitySlotAssigner(
+ Map<AllocationID, Map<JobVertexID, KeyGroupRange>> locality,
+ Map<JobVertexID, Integer> maxParallelism) {
+ this.locality = locality;
+ this.maxParallelism = maxParallelism;
+ }
+
+ @Override
+ public AssignmentResult assignSlots(
+ Collection<? extends SlotInfo> slots,
Collection<ExecutionSlotSharingGroup> groups) {
+
+ final Map<JobVertexID, Integer> parallelism = new HashMap<>();
+ groups.forEach(
+ group ->
+ group.getContainedExecutionVertices()
+ .forEach(
+ evi ->
+ parallelism.merge(
+ evi.getJobVertexId(),
1, Integer::sum)));
+
+ PriorityQueue<AllocationScore> scores = new
PriorityQueue<>(Comparator.reverseOrder());
+ for (ExecutionSlotSharingGroup group : groups) {
+ calculateScore(group, parallelism)
+ .forEach(
+ (allocationId, score) ->
+ scores.add(
+ new AllocationScore(
+ group.getId(),
allocationId, score)));
+ }
+ Map<String, ExecutionSlotSharingGroup> groupsById =
+
groups.stream().collect(toMap(ExecutionSlotSharingGroup::getId, identity()));
+ Map<AllocationID, SlotInfo> slotsById =
+ slots.stream().collect(toMap(SlotInfo::getAllocationId,
identity()));
+ List<ExecutionSlotSharingGroupAndSlot> result = new ArrayList<>();
+ AllocationScore score;
+ while ((score = scores.poll()) != null) {
+ SlotInfo slot = slotsById.remove(score.getAllocationId());
+ if (slot != null) {
+ ExecutionSlotSharingGroup group =
groupsById.remove(score.getGroup());
+ if (group != null) {
+ result.add(new ExecutionSlotSharingGroupAndSlot(group,
slot));
+ }
+ }
+ }
+
+ // Distribute the remaining slots with no score
+ Iterator<? extends SlotInfo> remainingSlots =
slotsById.values().iterator();
+ for (ExecutionSlotSharingGroup group : groupsById.values()) {
+ result.add(new ExecutionSlotSharingGroupAndSlot(group,
remainingSlots.next()));
+ remainingSlots.remove();
+ }
+
+ return AssignmentResult.of(result, remainingSlots);
+ }
+
+ public Map<AllocationID, Integer> calculateScore(
+ ExecutionSlotSharingGroup group, Map<JobVertexID, Integer>
parallelism) {
+ final Map<AllocationID, Integer> score = new HashMap<>();
+ for (ExecutionVertexID evi : group.getContainedExecutionVertices()) {
+ if (maxParallelism.containsKey(evi.getJobVertexId())) {
+ final KeyGroupRange kgr =
+
KeyGroupRangeAssignment.computeKeyGroupRangeForOperatorIndex(
+ maxParallelism.get(evi.getJobVertexId()),
+ parallelism.get(evi.getJobVertexId()),
+ evi.getSubtaskIndex());
+ locality.forEach(
+ (allocationId, potentials) -> {
+ KeyGroupRange prev =
potentials.get(evi.getJobVertexId());
+ if (prev != null) {
+ int intersection =
prev.getIntersection(kgr).getNumberOfKeyGroups();
Review Comment:
Have there been thoughts on also making use of the state size?
Right now it seems easy to construct scenarios where the result would be
sub-optimal.
(for an extreme example, an operator with barely any state and maxP=1
basically beats everything else)
##########
flink-runtime/src/main/java/org/apache/flink/runtime/scheduler/adaptive/allocator/StateLocalitySlotAssigner.java:
##########
@@ -0,0 +1,209 @@
+/*
+ * 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.flink.runtime.scheduler.adaptive.allocator;
+
+import org.apache.flink.annotation.Internal;
+import org.apache.flink.runtime.clusterframework.types.AllocationID;
+import org.apache.flink.runtime.executiongraph.ExecutionGraph;
+import org.apache.flink.runtime.executiongraph.ExecutionJobVertex;
+import org.apache.flink.runtime.executiongraph.ExecutionVertex;
+import org.apache.flink.runtime.jobgraph.JobVertexID;
+import org.apache.flink.runtime.jobmaster.SlotInfo;
+import
org.apache.flink.runtime.scheduler.adaptive.allocator.SlotSharingSlotAllocator.ExecutionSlotSharingGroup;
+import
org.apache.flink.runtime.scheduler.adaptive.allocator.SlotSharingSlotAllocator.ExecutionSlotSharingGroupAndSlot;
+import org.apache.flink.runtime.scheduler.strategy.ExecutionVertexID;
+import org.apache.flink.runtime.state.KeyGroupRange;
+import org.apache.flink.runtime.state.KeyGroupRangeAssignment;
+import org.apache.flink.util.Preconditions;
+
+import java.util.ArrayList;
+import java.util.Collection;
+import java.util.Comparator;
+import java.util.HashMap;
+import java.util.Iterator;
+import java.util.List;
+import java.util.Map;
+import java.util.PriorityQueue;
+import java.util.stream.StreamSupport;
+
+import static java.util.function.Function.identity;
+import static java.util.stream.Collectors.toMap;
+
+/** A {@link SlotAssigner} that assigns slots based on the number of local key
groups. */
+@Internal
+public class StateLocalitySlotAssigner implements SlotAssigner {
+
+ private static class AllocationScore implements
Comparable<AllocationScore> {
+
+ private final String group;
+ private final AllocationID allocationId;
+
+ public AllocationScore(String group, AllocationID allocationId, int
score) {
+ this.group = group;
+ this.allocationId = allocationId;
+ this.score = score;
+ }
+
+ private final int score;
+
+ public String getGroup() {
+ return group;
+ }
+
+ public AllocationID getAllocationId() {
+ return allocationId;
+ }
+
+ public int getScore() {
+ return score;
+ }
+
+ @Override
+ public int compareTo(StateLocalitySlotAssigner.AllocationScore other) {
+ int result = Integer.compare(score, other.score);
+ if (result != 0) {
+ return result;
+ }
+ result = other.allocationId.compareTo(allocationId);
+ if (result != 0) {
+ return result;
+ }
+ return other.group.compareTo(group);
+ }
+ }
+
+ private final Map<AllocationID, Map<JobVertexID, KeyGroupRange>> locality;
+ private final Map<JobVertexID, Integer> maxParallelism;
+
+ public StateLocalitySlotAssigner(ExecutionGraph archivedExecutionGraph) {
+ this(
+ calculateLocalKeyGroups(archivedExecutionGraph),
+ StreamSupport.stream(
+
archivedExecutionGraph.getVerticesTopologically().spliterator(),
+ false)
+ .collect(
+ toMap(
+ ExecutionJobVertex::getJobVertexId,
+
ExecutionJobVertex::getMaxParallelism)));
+ }
+
+ public StateLocalitySlotAssigner(
+ Map<AllocationID, Map<JobVertexID, KeyGroupRange>> locality,
+ Map<JobVertexID, Integer> maxParallelism) {
+ this.locality = locality;
+ this.maxParallelism = maxParallelism;
+ }
+
+ @Override
+ public AssignmentResult assignSlots(
+ Collection<? extends SlotInfo> slots,
Collection<ExecutionSlotSharingGroup> groups) {
+
+ final Map<JobVertexID, Integer> parallelism = new HashMap<>();
+ groups.forEach(
+ group ->
+ group.getContainedExecutionVertices()
+ .forEach(
+ evi ->
+ parallelism.merge(
+ evi.getJobVertexId(),
1, Integer::sum)));
+
+ PriorityQueue<AllocationScore> scores = new
PriorityQueue<>(Comparator.reverseOrder());
Review Comment:
It would be nice to add a short comment as to what this will contain (like,
"a score for every group <-> slot pair where the score (keygroup intersection
size) is > 0").
##########
flink-runtime/src/main/java/org/apache/flink/runtime/scheduler/adaptive/allocator/StateLocalitySlotAssigner.java:
##########
@@ -0,0 +1,209 @@
+/*
+ * 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.flink.runtime.scheduler.adaptive.allocator;
+
+import org.apache.flink.annotation.Internal;
+import org.apache.flink.runtime.clusterframework.types.AllocationID;
+import org.apache.flink.runtime.executiongraph.ExecutionGraph;
+import org.apache.flink.runtime.executiongraph.ExecutionJobVertex;
+import org.apache.flink.runtime.executiongraph.ExecutionVertex;
+import org.apache.flink.runtime.jobgraph.JobVertexID;
+import org.apache.flink.runtime.jobmaster.SlotInfo;
+import
org.apache.flink.runtime.scheduler.adaptive.allocator.SlotSharingSlotAllocator.ExecutionSlotSharingGroup;
+import
org.apache.flink.runtime.scheduler.adaptive.allocator.SlotSharingSlotAllocator.ExecutionSlotSharingGroupAndSlot;
+import org.apache.flink.runtime.scheduler.strategy.ExecutionVertexID;
+import org.apache.flink.runtime.state.KeyGroupRange;
+import org.apache.flink.runtime.state.KeyGroupRangeAssignment;
+import org.apache.flink.util.Preconditions;
+
+import java.util.ArrayList;
+import java.util.Collection;
+import java.util.Comparator;
+import java.util.HashMap;
+import java.util.Iterator;
+import java.util.List;
+import java.util.Map;
+import java.util.PriorityQueue;
+import java.util.stream.StreamSupport;
+
+import static java.util.function.Function.identity;
+import static java.util.stream.Collectors.toMap;
+
+/** A {@link SlotAssigner} that assigns slots based on the number of local key
groups. */
+@Internal
+public class StateLocalitySlotAssigner implements SlotAssigner {
+
+ private static class AllocationScore implements
Comparable<AllocationScore> {
+
+ private final String group;
+ private final AllocationID allocationId;
+
+ public AllocationScore(String group, AllocationID allocationId, int
score) {
+ this.group = group;
+ this.allocationId = allocationId;
+ this.score = score;
+ }
+
+ private final int score;
+
+ public String getGroup() {
+ return group;
+ }
+
+ public AllocationID getAllocationId() {
+ return allocationId;
+ }
+
+ public int getScore() {
+ return score;
+ }
+
+ @Override
+ public int compareTo(StateLocalitySlotAssigner.AllocationScore other) {
+ int result = Integer.compare(score, other.score);
+ if (result != 0) {
+ return result;
+ }
+ result = other.allocationId.compareTo(allocationId);
+ if (result != 0) {
+ return result;
+ }
+ return other.group.compareTo(group);
+ }
+ }
+
+ private final Map<AllocationID, Map<JobVertexID, KeyGroupRange>> locality;
+ private final Map<JobVertexID, Integer> maxParallelism;
+
+ public StateLocalitySlotAssigner(ExecutionGraph archivedExecutionGraph) {
+ this(
+ calculateLocalKeyGroups(archivedExecutionGraph),
+ StreamSupport.stream(
+
archivedExecutionGraph.getVerticesTopologically().spliterator(),
+ false)
+ .collect(
+ toMap(
+ ExecutionJobVertex::getJobVertexId,
+
ExecutionJobVertex::getMaxParallelism)));
Review Comment:
We shouldn't recompute this map again and again. This information is static
from the get-go and will never change. (You don't even need an execution graph
to compute it; the job graph would suffice)
##########
flink-runtime/src/main/java/org/apache/flink/runtime/scheduler/adaptive/allocator/StateLocalitySlotAssigner.java:
##########
@@ -0,0 +1,209 @@
+/*
+ * 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.flink.runtime.scheduler.adaptive.allocator;
+
+import org.apache.flink.annotation.Internal;
+import org.apache.flink.runtime.clusterframework.types.AllocationID;
+import org.apache.flink.runtime.executiongraph.ExecutionGraph;
+import org.apache.flink.runtime.executiongraph.ExecutionJobVertex;
+import org.apache.flink.runtime.executiongraph.ExecutionVertex;
+import org.apache.flink.runtime.jobgraph.JobVertexID;
+import org.apache.flink.runtime.jobmaster.SlotInfo;
+import
org.apache.flink.runtime.scheduler.adaptive.allocator.SlotSharingSlotAllocator.ExecutionSlotSharingGroup;
+import
org.apache.flink.runtime.scheduler.adaptive.allocator.SlotSharingSlotAllocator.ExecutionSlotSharingGroupAndSlot;
+import org.apache.flink.runtime.scheduler.strategy.ExecutionVertexID;
+import org.apache.flink.runtime.state.KeyGroupRange;
+import org.apache.flink.runtime.state.KeyGroupRangeAssignment;
+import org.apache.flink.util.Preconditions;
+
+import java.util.ArrayList;
+import java.util.Collection;
+import java.util.Comparator;
+import java.util.HashMap;
+import java.util.Iterator;
+import java.util.List;
+import java.util.Map;
+import java.util.PriorityQueue;
+import java.util.stream.StreamSupport;
+
+import static java.util.function.Function.identity;
+import static java.util.stream.Collectors.toMap;
+
+/** A {@link SlotAssigner} that assigns slots based on the number of local key
groups. */
+@Internal
+public class StateLocalitySlotAssigner implements SlotAssigner {
+
+ private static class AllocationScore implements
Comparable<AllocationScore> {
+
+ private final String group;
+ private final AllocationID allocationId;
+
+ public AllocationScore(String group, AllocationID allocationId, int
score) {
+ this.group = group;
+ this.allocationId = allocationId;
+ this.score = score;
+ }
+
+ private final int score;
+
+ public String getGroup() {
+ return group;
+ }
+
+ public AllocationID getAllocationId() {
+ return allocationId;
+ }
+
+ public int getScore() {
+ return score;
+ }
+
+ @Override
+ public int compareTo(StateLocalitySlotAssigner.AllocationScore other) {
+ int result = Integer.compare(score, other.score);
+ if (result != 0) {
+ return result;
+ }
+ result = other.allocationId.compareTo(allocationId);
+ if (result != 0) {
+ return result;
+ }
+ return other.group.compareTo(group);
+ }
+ }
+
+ private final Map<AllocationID, Map<JobVertexID, KeyGroupRange>> locality;
+ private final Map<JobVertexID, Integer> maxParallelism;
+
+ public StateLocalitySlotAssigner(ExecutionGraph archivedExecutionGraph) {
+ this(
+ calculateLocalKeyGroups(archivedExecutionGraph),
+ StreamSupport.stream(
+
archivedExecutionGraph.getVerticesTopologically().spliterator(),
+ false)
+ .collect(
+ toMap(
+ ExecutionJobVertex::getJobVertexId,
+
ExecutionJobVertex::getMaxParallelism)));
+ }
+
+ public StateLocalitySlotAssigner(
+ Map<AllocationID, Map<JobVertexID, KeyGroupRange>> locality,
+ Map<JobVertexID, Integer> maxParallelism) {
+ this.locality = locality;
+ this.maxParallelism = maxParallelism;
+ }
+
+ @Override
+ public AssignmentResult assignSlots(
+ Collection<? extends SlotInfo> slots,
Collection<ExecutionSlotSharingGroup> groups) {
+
+ final Map<JobVertexID, Integer> parallelism = new HashMap<>();
+ groups.forEach(
+ group ->
+ group.getContainedExecutionVertices()
+ .forEach(
+ evi ->
+ parallelism.merge(
+ evi.getJobVertexId(),
1, Integer::sum)));
+
+ PriorityQueue<AllocationScore> scores = new
PriorityQueue<>(Comparator.reverseOrder());
+ for (ExecutionSlotSharingGroup group : groups) {
+ calculateScore(group, parallelism)
+ .forEach(
+ (allocationId, score) ->
+ scores.add(
+ new AllocationScore(
+ group.getId(),
allocationId, score)));
+ }
+ Map<String, ExecutionSlotSharingGroup> groupsById =
+
groups.stream().collect(toMap(ExecutionSlotSharingGroup::getId, identity()));
+ Map<AllocationID, SlotInfo> slotsById =
+ slots.stream().collect(toMap(SlotInfo::getAllocationId,
identity()));
+ List<ExecutionSlotSharingGroupAndSlot> result = new ArrayList<>();
+ AllocationScore score;
+ while ((score = scores.poll()) != null) {
+ SlotInfo slot = slotsById.remove(score.getAllocationId());
+ if (slot != null) {
+ ExecutionSlotSharingGroup group =
groupsById.remove(score.getGroup());
+ if (group != null) {
+ result.add(new ExecutionSlotSharingGroupAndSlot(group,
slot));
+ }
+ }
+ }
+
+ // Distribute the remaining slots with no score
+ Iterator<? extends SlotInfo> remainingSlots =
slotsById.values().iterator();
+ for (ExecutionSlotSharingGroup group : groupsById.values()) {
+ result.add(new ExecutionSlotSharingGroupAndSlot(group,
remainingSlots.next()));
+ remainingSlots.remove();
+ }
+
+ return AssignmentResult.of(result, remainingSlots);
+ }
+
+ public Map<AllocationID, Integer> calculateScore(
+ ExecutionSlotSharingGroup group, Map<JobVertexID, Integer>
parallelism) {
+ final Map<AllocationID, Integer> score = new HashMap<>();
+ for (ExecutionVertexID evi : group.getContainedExecutionVertices()) {
+ if (maxParallelism.containsKey(evi.getJobVertexId())) {
+ final KeyGroupRange kgr =
+
KeyGroupRangeAssignment.computeKeyGroupRangeForOperatorIndex(
+ maxParallelism.get(evi.getJobVertexId()),
Review Comment:
Since the max parallelism doesn't change you could extract it from the
execution job vertex. This would also remove the need for the map and the
condition above.
##########
flink-runtime/src/main/java/org/apache/flink/runtime/scheduler/adaptive/allocator/StateLocalitySlotAssigner.java:
##########
@@ -0,0 +1,209 @@
+/*
+ * 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.flink.runtime.scheduler.adaptive.allocator;
+
+import org.apache.flink.annotation.Internal;
+import org.apache.flink.runtime.clusterframework.types.AllocationID;
+import org.apache.flink.runtime.executiongraph.ExecutionGraph;
+import org.apache.flink.runtime.executiongraph.ExecutionJobVertex;
+import org.apache.flink.runtime.executiongraph.ExecutionVertex;
+import org.apache.flink.runtime.jobgraph.JobVertexID;
+import org.apache.flink.runtime.jobmaster.SlotInfo;
+import
org.apache.flink.runtime.scheduler.adaptive.allocator.SlotSharingSlotAllocator.ExecutionSlotSharingGroup;
+import
org.apache.flink.runtime.scheduler.adaptive.allocator.SlotSharingSlotAllocator.ExecutionSlotSharingGroupAndSlot;
+import org.apache.flink.runtime.scheduler.strategy.ExecutionVertexID;
+import org.apache.flink.runtime.state.KeyGroupRange;
+import org.apache.flink.runtime.state.KeyGroupRangeAssignment;
+import org.apache.flink.util.Preconditions;
+
+import java.util.ArrayList;
+import java.util.Collection;
+import java.util.Comparator;
+import java.util.HashMap;
+import java.util.Iterator;
+import java.util.List;
+import java.util.Map;
+import java.util.PriorityQueue;
+import java.util.stream.StreamSupport;
+
+import static java.util.function.Function.identity;
+import static java.util.stream.Collectors.toMap;
+
+/** A {@link SlotAssigner} that assigns slots based on the number of local key
groups. */
+@Internal
+public class StateLocalitySlotAssigner implements SlotAssigner {
+
+ private static class AllocationScore implements
Comparable<AllocationScore> {
+
+ private final String group;
+ private final AllocationID allocationId;
+
+ public AllocationScore(String group, AllocationID allocationId, int
score) {
+ this.group = group;
+ this.allocationId = allocationId;
+ this.score = score;
+ }
+
+ private final int score;
+
+ public String getGroup() {
+ return group;
+ }
+
+ public AllocationID getAllocationId() {
+ return allocationId;
+ }
+
+ public int getScore() {
+ return score;
+ }
+
+ @Override
+ public int compareTo(StateLocalitySlotAssigner.AllocationScore other) {
+ int result = Integer.compare(score, other.score);
+ if (result != 0) {
+ return result;
+ }
+ result = other.allocationId.compareTo(allocationId);
+ if (result != 0) {
+ return result;
+ }
+ return other.group.compareTo(group);
+ }
+ }
+
+ private final Map<AllocationID, Map<JobVertexID, KeyGroupRange>> locality;
+ private final Map<JobVertexID, Integer> maxParallelism;
+
+ public StateLocalitySlotAssigner(ExecutionGraph archivedExecutionGraph) {
+ this(
+ calculateLocalKeyGroups(archivedExecutionGraph),
+ StreamSupport.stream(
+
archivedExecutionGraph.getVerticesTopologically().spliterator(),
+ false)
+ .collect(
+ toMap(
+ ExecutionJobVertex::getJobVertexId,
+
ExecutionJobVertex::getMaxParallelism)));
+ }
+
+ public StateLocalitySlotAssigner(
+ Map<AllocationID, Map<JobVertexID, KeyGroupRange>> locality,
+ Map<JobVertexID, Integer> maxParallelism) {
+ this.locality = locality;
+ this.maxParallelism = maxParallelism;
+ }
+
+ @Override
+ public AssignmentResult assignSlots(
+ Collection<? extends SlotInfo> slots,
Collection<ExecutionSlotSharingGroup> groups) {
+
+ final Map<JobVertexID, Integer> parallelism = new HashMap<>();
+ groups.forEach(
+ group ->
+ group.getContainedExecutionVertices()
+ .forEach(
+ evi ->
+ parallelism.merge(
+ evi.getJobVertexId(),
1, Integer::sum)));
+
+ PriorityQueue<AllocationScore> scores = new
PriorityQueue<>(Comparator.reverseOrder());
+ for (ExecutionSlotSharingGroup group : groups) {
+ calculateScore(group, parallelism)
+ .forEach(
+ (allocationId, score) ->
+ scores.add(
+ new AllocationScore(
+ group.getId(),
allocationId, score)));
+ }
+ Map<String, ExecutionSlotSharingGroup> groupsById =
+
groups.stream().collect(toMap(ExecutionSlotSharingGroup::getId, identity()));
+ Map<AllocationID, SlotInfo> slotsById =
+ slots.stream().collect(toMap(SlotInfo::getAllocationId,
identity()));
+ List<ExecutionSlotSharingGroupAndSlot> result = new ArrayList<>();
+ AllocationScore score;
+ while ((score = scores.poll()) != null) {
+ SlotInfo slot = slotsById.remove(score.getAllocationId());
+ if (slot != null) {
+ ExecutionSlotSharingGroup group =
groupsById.remove(score.getGroup());
+ if (group != null) {
+ result.add(new ExecutionSlotSharingGroupAndSlot(group,
slot));
+ }
+ }
+ }
+
+ // Distribute the remaining slots with no score
+ Iterator<? extends SlotInfo> remainingSlots =
slotsById.values().iterator();
+ for (ExecutionSlotSharingGroup group : groupsById.values()) {
+ result.add(new ExecutionSlotSharingGroupAndSlot(group,
remainingSlots.next()));
+ remainingSlots.remove();
+ }
+
+ return AssignmentResult.of(result, remainingSlots);
+ }
+
+ public Map<AllocationID, Integer> calculateScore(
+ ExecutionSlotSharingGroup group, Map<JobVertexID, Integer>
parallelism) {
+ final Map<AllocationID, Integer> score = new HashMap<>();
+ for (ExecutionVertexID evi : group.getContainedExecutionVertices()) {
+ if (maxParallelism.containsKey(evi.getJobVertexId())) {
Review Comment:
Isn't this always true? If it isn't we should fail hard here because
something's broken.
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