[GitHub] [flink] zhuzhurk commented on a change in pull request #13009: [FLINK-18690][runtime] Implement LocalInputPreferredSlotSharingStrategy

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zhuzhurk commented on a change in pull request #13009:
URL: https://github.com/apache/flink/pull/13009#discussion_r461676413



##########
File path: flink-runtime/src/main/java/org/apache/flink/runtime/scheduler/LocalInputPreferredSlotSharingStrategy.java
##########
@@ -0,0 +1,297 @@
+/*
+ * 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;
+
+import org.apache.flink.runtime.instance.SlotSharingGroupId;
+import org.apache.flink.runtime.jobgraph.JobVertexID;
+import org.apache.flink.runtime.jobmanager.scheduler.CoLocationConstraintDesc;
+import org.apache.flink.runtime.jobmanager.scheduler.CoLocationGroupDesc;
+import org.apache.flink.runtime.jobmanager.scheduler.SlotSharingGroup;
+import org.apache.flink.runtime.scheduler.strategy.ExecutionVertexID;
+import org.apache.flink.runtime.scheduler.strategy.SchedulingExecutionVertex;
+import org.apache.flink.runtime.scheduler.strategy.SchedulingResultPartition;
+import org.apache.flink.runtime.scheduler.strategy.SchedulingTopology;
+
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.IdentityHashMap;
+import java.util.LinkedHashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.Set;
+
+import static org.apache.flink.util.Preconditions.checkNotNull;
+import static org.apache.flink.util.Preconditions.checkState;
+
+/**
+ * This strategy tries to reduce remote data exchanges. Execution vertices, which are connected
+ * and belong to the same SlotSharingGroup, tend to be put in the same ExecutionSlotSharingGroup.
+ * Co-location constraints will be respected.
+ */
+class LocalInputPreferredSlotSharingStrategy implements SlotSharingStrategy {
+
+	private final Map<ExecutionVertexID, ExecutionSlotSharingGroup> executionSlotSharingGroupMap;
+
+	LocalInputPreferredSlotSharingStrategy(
+			final SchedulingTopology topology,
+			final Set<SlotSharingGroup> logicalSlotSharingGroups,
+			final Set<CoLocationGroupDesc> coLocationGroups) {
+
+		this.executionSlotSharingGroupMap = new ExecutionSlotSharingGroupBuilder(
+			topology,
+			logicalSlotSharingGroups,
+			coLocationGroups).build();
+	}
+
+	@Override
+	public ExecutionSlotSharingGroup getExecutionSlotSharingGroup(final ExecutionVertexID executionVertexId) {
+		return executionSlotSharingGroupMap.get(executionVertexId);
+	}
+
+	@Override
+	public Set<ExecutionSlotSharingGroup> getExecutionSlotSharingGroups() {
+		return new HashSet<>(executionSlotSharingGroupMap.values());
+	}
+
+	static class Factory implements SlotSharingStrategy.Factory {
+
+		public LocalInputPreferredSlotSharingStrategy create(
+				final SchedulingTopology topology,
+				final Set<SlotSharingGroup> logicalSlotSharingGroups,
+				final Set<CoLocationGroupDesc> coLocationGroups) {
+
+			return new LocalInputPreferredSlotSharingStrategy(topology, logicalSlotSharingGroups, coLocationGroups);
+		}
+	}
+
+	private static class ExecutionSlotSharingGroupBuilder {
+		private final SchedulingTopology topology;
+
+		private final Map<JobVertexID, SlotSharingGroupId> slotSharingGroupMap;
+
+		private final Map<JobVertexID, CoLocationGroupDesc> coLocationGroupMap;
+
+		private final Map<ExecutionVertexID, ExecutionSlotSharingGroup> executionSlotSharingGroupMap;
+
+		final Map<CoLocationConstraintDesc, ExecutionSlotSharingGroup> constraintToExecutionSlotSharingGroupMap;
+
+		final Map<SlotSharingGroupId, List<ExecutionSlotSharingGroup>> executionSlotSharingGroups;
+
+		private final Map<ExecutionSlotSharingGroup, Set<JobVertexID>> assignedJobVerticesForGroups;
+
+		private ExecutionSlotSharingGroupBuilder(
+				final SchedulingTopology topology,
+				final Set<SlotSharingGroup> logicalSlotSharingGroups,
+				final Set<CoLocationGroupDesc> coLocationGroups) {
+
+			this.topology = checkNotNull(topology);
+
+			this.slotSharingGroupMap = new HashMap<>();
+			for (SlotSharingGroup slotSharingGroup : logicalSlotSharingGroups) {
+				for (JobVertexID jobVertexId : slotSharingGroup.getJobVertexIds()) {
+					slotSharingGroupMap.put(jobVertexId, slotSharingGroup.getSlotSharingGroupId());
+				}
+			}
+
+			this.coLocationGroupMap = new HashMap<>();
+			for (CoLocationGroupDesc coLocationGroup : coLocationGroups) {
+				for (JobVertexID jobVertexId : coLocationGroup.getVertices()) {
+					coLocationGroupMap.put(jobVertexId, coLocationGroup);
+				}
+			}
+
+			executionSlotSharingGroupMap = new HashMap<>();
+			constraintToExecutionSlotSharingGroupMap = new HashMap<>();
+			executionSlotSharingGroups = new HashMap<>();
+			assignedJobVerticesForGroups = new IdentityHashMap<>();
+		}
+
+		/**
+		 * Build ExecutionSlotSharingGroups for all vertices in the topology.
+		 * The ExecutionSlotSharingGroup of a vertex is determined in order below:

Review comment:
       One known defect is the grouping of execution vertices from brother job vertices are possible suboptimal because it does not take connections to consumers vertices into account.
   
   Example: A(parallelism=4) --forward--> C(parallelism=4), B(parallelism=2) --rescale--> C
   Execution edges are: A1->C1, A2->C2, A3->C3, A4->C4; B1->C1, B1->C2, B2->C3,B2->C4
   Optimal grouping: {A1,B1,C1}{A2,C2}{A3,B2,C3}{A4,C4}     ->   there would be 2 remote edges
   Current grouping result: {A1,B1,C1} {A2,B2,C2}  {A3,C3}  {A4,C4}     ->   there would be 3 remote edges




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