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From GitBox <...@apache.org>
Subject [GitHub] [flink] zhuzhurk commented on a change in pull request #16688: [FLINK-22773][coordination] Optimize the construction of pipelined regions
Date Tue, 10 Aug 2021 12:27:54 GMT

zhuzhurk commented on a change in pull request #16688:
URL: https://github.com/apache/flink/pull/16688#discussion_r685968287



##########
File path: flink-runtime/src/main/java/org/apache/flink/runtime/executiongraph/failover/flip1/SchedulingPipelinedRegionComputeUtil.java
##########
@@ -0,0 +1,186 @@
+/*
+ * 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.executiongraph.failover.flip1;
+
+import org.apache.flink.runtime.jobgraph.IntermediateResultPartitionID;
+import org.apache.flink.runtime.scheduler.strategy.ConsumedPartitionGroup;
+import org.apache.flink.runtime.scheduler.strategy.ConsumerVertexGroup;
+import org.apache.flink.runtime.scheduler.strategy.ExecutionVertexID;
+import org.apache.flink.runtime.scheduler.strategy.SchedulingExecutionVertex;
+import org.apache.flink.runtime.scheduler.strategy.SchedulingPipelinedRegion;
+import org.apache.flink.runtime.scheduler.strategy.SchedulingResultPartition;
+
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.HashSet;
+import java.util.IdentityHashMap;
+import java.util.Iterator;
+import java.util.List;
+import java.util.Map;
+import java.util.NoSuchElementException;
+import java.util.Set;
+import java.util.function.Function;
+
+import static org.apache.flink.runtime.executiongraph.failover.flip1.PipelinedRegionComputeUtil.buildRawRegions;
+import static org.apache.flink.runtime.executiongraph.failover.flip1.PipelinedRegionComputeUtil.mergeRegions;
+import static org.apache.flink.runtime.executiongraph.failover.flip1.PipelinedRegionComputeUtil.uniqueRegions;
+import static org.apache.flink.util.Preconditions.checkState;
+
+/** Utils for computing {@link SchedulingPipelinedRegion}s. */
+public final class SchedulingPipelinedRegionComputeUtil {
+
+    public static Set<Set<SchedulingExecutionVertex>> computePipelinedRegions(
+            final Iterable<? extends SchedulingExecutionVertex> topologicallySortedVertices,
+            final Function<ExecutionVertexID, ? extends SchedulingExecutionVertex>
+                    executionVertexRetriever,
+            final Function<IntermediateResultPartitionID, ? extends SchedulingResultPartition>
+                    resultPartitionRetriever) {
+
+        final Map<SchedulingExecutionVertex, Set<SchedulingExecutionVertex>>
vertexToRegion =
+                buildRawRegions(
+                        topologicallySortedVertices,
+                        (vertex) -> getReconnectableResults(vertex, resultPartitionRetriever));
+
+        return mergeRegionsOnCycles(vertexToRegion, executionVertexRetriever);
+    }
+
+    /**
+     * Merge the regions base on <a
+     * href="https://en.wikipedia.org/wiki/Tarjan%27s_strongly_connected_components_algorithm">
+     * Tarjan's strongly connected components algorithm</a>. For more details please
see <a
+     * href="https://issues.apache.org/jira/browse/FLINK-17330">FLINK-17330</a>.
+     */
+    private static Set<Set<SchedulingExecutionVertex>> mergeRegionsOnCycles(
+            final Map<SchedulingExecutionVertex, Set<SchedulingExecutionVertex>>
vertexToRegion,
+            final Function<ExecutionVertexID, ? extends SchedulingExecutionVertex>
+                    executionVertexRetriever) {
+
+        final List<Set<SchedulingExecutionVertex>> regionList =
+                new ArrayList<>(uniqueRegions(vertexToRegion));
+        final List<List<Integer>> outEdges =
+                buildOutEdgesDesc(vertexToRegion, regionList, executionVertexRetriever);
+        final Set<Set<Integer>> sccs =
+                StronglyConnectedComponentsComputeUtils.computeStronglyConnectedComponents(
+                        outEdges.size(), outEdges);
+
+        final Set<Set<SchedulingExecutionVertex>> mergedRegions =
+                Collections.newSetFromMap(new IdentityHashMap<>());
+        for (Set<Integer> scc : sccs) {
+            checkState(scc.size() > 0);
+
+            Set<SchedulingExecutionVertex> mergedRegion = new HashSet<>();
+            for (int regionIndex : scc) {
+                mergedRegion =
+                        mergeRegions(mergedRegion, regionList.get(regionIndex), vertexToRegion);
+            }
+            mergedRegions.add(mergedRegion);
+        }
+
+        return mergedRegions;
+    }
+
+    private static List<List<Integer>> buildOutEdgesDesc(
+            final Map<SchedulingExecutionVertex, Set<SchedulingExecutionVertex>>
vertexToRegion,
+            final List<Set<SchedulingExecutionVertex>> regionList,
+            final Function<ExecutionVertexID, ? extends SchedulingExecutionVertex>
+                    executionVertexRetriever) {
+
+        final Map<Set<SchedulingExecutionVertex>, Integer> regionIndices = new
IdentityHashMap<>();
+        for (int i = 0; i < regionList.size(); i++) {
+            regionIndices.put(regionList.get(i), i);
+        }
+
+        final List<List<Integer>> outEdges = new ArrayList<>(regionList.size());
+        for (Set<SchedulingExecutionVertex> currentRegion : regionList) {
+            final List<Integer> currentRegionOutEdges = new ArrayList<>();
+            for (SchedulingExecutionVertex vertex : currentRegion) {
+                for (SchedulingResultPartition producedResult : vertex.getProducedResults())
{
+                    if (producedResult.getResultType().isPipelined()) {
+                        continue;
+                    }
+                    for (ConsumerVertexGroup consumerVertexGroup :
+                            producedResult.getConsumerVertexGroups()) {
+                        for (ExecutionVertexID consumerVertexId : consumerVertexGroup) {
+                            SchedulingExecutionVertex consumerVertex =
+                                    executionVertexRetriever.apply(consumerVertexId);
+                            // Since we are merging SchedulingPipelinedRegions inside one
+                            // LogicalPipelinedRegion, if any vertex of the ConsumerVertexGroup
+                            // doesn't belong to this LogicalPipelinedRegion, we can just
skip the
+                            // remaining vertices in this group. This can decrease the computation
+                            // complexity.
+                            if (!vertexToRegion.containsKey(consumerVertex)) {
+                                break;
+                            }
+                            if (!currentRegion.contains(consumerVertex)) {
+                                currentRegionOutEdges.add(
+                                        regionIndices.get(vertexToRegion.get(consumerVertex)));
+                            }
+                        }
+                    }
+                }
+            }
+            outEdges.add(currentRegionOutEdges);
+        }
+
+        return outEdges;
+    }
+
+    private static Iterable<SchedulingResultPartition> getReconnectableResults(
+            SchedulingExecutionVertex vertex,
+            Function<IntermediateResultPartitionID, ? extends SchedulingResultPartition>
+                    resultPartitionRetriever) {
+        return () ->

Review comment:
       Ok. I did not expect this O(N) complexity operation to be that slow. It's then fine
to me to take the iterator way.




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