Github user fhueske commented on a diff in the pull request:
https://github.com/apache/flink/pull/1255#discussion_r43954837
--- Diff:
flink-optimizer/src/main/java/org/apache/flink/optimizer/traversals/RangePartitionRewriter.java
---
@@ -0,0 +1,188 @@
+/*
+ * 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.optimizer.traversals;
+
+import org.apache.flink.api.common.distributions.CommonRangeBoundaries;
+import org.apache.flink.api.common.operators.UnaryOperatorInformation;
+import org.apache.flink.api.common.operators.base.GroupReduceOperatorBase;
+import org.apache.flink.api.common.operators.base.MapOperatorBase;
+import org.apache.flink.api.common.operators.base.MapPartitionOperatorBase;
+import org.apache.flink.api.common.typeinfo.BasicTypeInfo;
+import org.apache.flink.api.common.typeinfo.TypeInformation;
+import org.apache.flink.api.common.typeutils.TypeComparatorFactory;
+import org.apache.flink.api.java.functions.AssignRangeIndex;
+import org.apache.flink.api.java.functions.PartitionIDRemoveWrapper;
+import org.apache.flink.api.java.functions.RangeBoundaryBuilder;
+import org.apache.flink.api.java.functions.SampleInCoordinator;
+import org.apache.flink.api.java.functions.SampleInPartition;
+import org.apache.flink.api.java.sampling.IntermediateSampleData;
+import org.apache.flink.api.java.tuple.Tuple2;
+import org.apache.flink.api.java.typeutils.TupleTypeInfo;
+import org.apache.flink.api.java.typeutils.TypeExtractor;
+import org.apache.flink.optimizer.dag.GroupReduceNode;
+import org.apache.flink.optimizer.dag.MapNode;
+import org.apache.flink.optimizer.dag.MapPartitionNode;
+import org.apache.flink.optimizer.dag.TempMode;
+import org.apache.flink.optimizer.plan.Channel;
+import org.apache.flink.optimizer.plan.NamedChannel;
+import org.apache.flink.optimizer.plan.OptimizedPlan;
+import org.apache.flink.optimizer.plan.PlanNode;
+import org.apache.flink.optimizer.plan.SingleInputPlanNode;
+import org.apache.flink.optimizer.util.Utils;
+import org.apache.flink.runtime.operators.DriverStrategy;
+import org.apache.flink.runtime.operators.shipping.ShipStrategyType;
+import org.apache.flink.util.Visitor;
+
+import java.util.ArrayList;
+import java.util.LinkedList;
+import java.util.List;
+
+public class RangePartitionRewriter implements Visitor<PlanNode> {
+
+ OptimizedPlan plan;
+
+ public RangePartitionRewriter(OptimizedPlan plan) {
+ this.plan = plan;
+ }
+
+ @Override
+ public boolean preVisit(PlanNode visitable) {
+ return true;
+ }
+
+ @Override
+ public void postVisit(PlanNode visitable) {
+ List<Channel> outgoingChannels =
visitable.getOutgoingChannels();
+ List<Channel> appendOutgoingChannels = new LinkedList<>();
+ List<Channel> removeOutgoingChannels = new LinkedList<>();
+ for (Channel channel : outgoingChannels) {
+ ShipStrategyType shipStrategy =
channel.getShipStrategy();
+ if (shipStrategy == ShipStrategyType.PARTITION_RANGE) {
+ if (channel.getDataDistribution() == null) {
+ removeOutgoingChannels.add(channel);
+
appendOutgoingChannels.addAll(rewriteRangePartitionChannel(channel));
+ }
+ }
+ }
+ outgoingChannels.addAll(appendOutgoingChannels);
+ for (Channel channel : removeOutgoingChannels) {
+ outgoingChannels.remove(channel);
+ }
+ }
+
+ private List<Channel> rewriteRangePartitionChannel(Channel channel) {
+ List<Channel> appendOutgoingChannels = new LinkedList<>();
+ PlanNode sourceNode = channel.getSource();
+ PlanNode targetNode = channel.getTarget();
+ int sourceParallelism = sourceNode.getParallelism();
+ int targetParallelism = targetNode.getParallelism();
+ TypeComparatorFactory<?> comparator =
Utils.getShipComparator(channel,
this.plan.getOriginalPlan().getExecutionConfig());
+ // 1. Fixed size sample in each partitions.
+ long seed = org.apache.flink.api.java.Utils.RNG.nextLong();
+ int sampleSize = 20 * targetParallelism;
+ SampleInPartition sampleInPartition = new
SampleInPartition(false, sampleSize, seed);
+ TypeInformation<?> sourceOutputType =
sourceNode.getOptimizerNode().getOperator().getOperatorInfo().getOutputType();
+ TypeInformation<IntermediateSampleData> isdTypeInformation =
TypeExtractor.getForClass(IntermediateSampleData.class);
+ UnaryOperatorInformation sipOperatorInformation = new
UnaryOperatorInformation(sourceOutputType, isdTypeInformation);
+ MapPartitionOperatorBase sipOperatorBase = new
MapPartitionOperatorBase(sampleInPartition, sipOperatorInformation, "Sample in
partitions");
+ MapPartitionNode sipNode = new
MapPartitionNode(sipOperatorBase);
+ Channel sipChannel = new Channel(sourceNode, TempMode.NONE);
+ sipChannel.setShipStrategy(ShipStrategyType.FORWARD,
channel.getDataExchangeMode());
+ SingleInputPlanNode sipPlanNode = new
SingleInputPlanNode(sipNode, "SampleInPartition PlanNode", sipChannel,
DriverStrategy.MAP_PARTITION);
+ sipPlanNode.setParallelism(sourceParallelism);
+ sipChannel.setTarget(sipPlanNode);
+ appendOutgoingChannels.add(sipChannel);
+ this.plan.getAllNodes().add(sipPlanNode);
+
+ // 2. Fixed size sample in a single coordinator.
+ SampleInCoordinator sampleInCoordinator = new
SampleInCoordinator(false, sampleSize, seed);
+ UnaryOperatorInformation sicOperatorInformation = new
UnaryOperatorInformation(isdTypeInformation, sourceOutputType);
+ GroupReduceOperatorBase sicOperatorBase = new
GroupReduceOperatorBase(sampleInCoordinator, sicOperatorInformation, "Sample in
coordinator");
+ GroupReduceNode sicNode = new GroupReduceNode(sicOperatorBase);
+ Channel sicChannel = new Channel(sipPlanNode, TempMode.NONE);
+ sicChannel.setShipStrategy(ShipStrategyType.PARTITION_HASH,
channel.getShipStrategyKeys(), channel.getShipStrategySortOrder(), null,
channel.getDataExchangeMode());
+ SingleInputPlanNode sicPlanNode = new
SingleInputPlanNode(sicNode, "SampleInCoordinator PlanNode", sicChannel,
DriverStrategy.ALL_GROUP_REDUCE);
+ sicPlanNode.setParallelism(1);
+ sicChannel.setTarget(sicPlanNode);
+ sipPlanNode.addOutgoingChannel(sicChannel);
+ this.plan.getAllNodes().add(sicPlanNode);
+
+ // 3. Use sampled data to build range boundaries.
+ RangeBoundaryBuilder rangeBoundaryBuilder = new
RangeBoundaryBuilder(comparator, targetParallelism);
+ TypeInformation<CommonRangeBoundaries> rbTypeInformation =
TypeExtractor.getForClass(CommonRangeBoundaries.class);
+ UnaryOperatorInformation rbOperatorInformation = new
UnaryOperatorInformation(sourceOutputType, rbTypeInformation);
+ MapPartitionOperatorBase rbOperatorBase = new
MapPartitionOperatorBase(rangeBoundaryBuilder, rbOperatorInformation,
"RangeBoundaryBuilder");
+ MapPartitionNode rbNode= new MapPartitionNode(rbOperatorBase);
+ Channel rbChannel = new Channel(sicPlanNode, TempMode.NONE);
+ rbChannel.setShipStrategy(ShipStrategyType.FORWARD,
channel.getDataExchangeMode());
+ SingleInputPlanNode rbPlanNode = new
SingleInputPlanNode(rbNode, "RangeBoundary PlanNode", rbChannel,
DriverStrategy.MAP_PARTITION);
+ rbPlanNode.setParallelism(1);
+ rbChannel.setTarget(rbPlanNode);
+ sicPlanNode.addOutgoingChannel(rbChannel);
+ this.plan.getAllNodes().add(rbPlanNode);
+
+ // 4. Take range boundaries as broadcast input and take the
tuple of partition id and record as output.
+ AssignRangeIndex assignRangeIndex = new
AssignRangeIndex(comparator);
+ TypeInformation<Tuple2> ariOutputTypeInformation = new
TupleTypeInfo<>(BasicTypeInfo.INT_TYPE_INFO, sourceOutputType);
+ UnaryOperatorInformation ariOperatorInformation = new
UnaryOperatorInformation(sourceOutputType, ariOutputTypeInformation);
+ MapPartitionOperatorBase ariOperatorBase = new
MapPartitionOperatorBase(assignRangeIndex, ariOperatorInformation, "Assign
Range Index");
+ MapPartitionNode ariNode= new MapPartitionNode(ariOperatorBase);
+ Channel ariChannel = new Channel(sourceNode, TempMode.NONE);
+ ariChannel.setShipStrategy(ShipStrategyType.FORWARD,
channel.getDataExchangeMode());
+ SingleInputPlanNode ariPlanNode = new
SingleInputPlanNode(ariNode, "AssignRangeIndex PlanNode", ariChannel,
DriverStrategy.MAP_PARTITION);
+ ariPlanNode.setParallelism(sourceParallelism);
+ ariChannel.setTarget(ariPlanNode);
+ appendOutgoingChannels.add(ariChannel);
+ this.plan.getAllNodes().add(ariPlanNode);
+
+ channel.setSource(ariPlanNode);
+ ariPlanNode.addOutgoingChannel(channel);
+
+ NamedChannel broadcastChannel = new
NamedChannel("RangeBoundaries", rbPlanNode);
+ broadcastChannel.setShipStrategy(ShipStrategyType.BROADCAST,
channel.getDataExchangeMode());
+ broadcastChannel.setTarget(ariPlanNode);
+ List<NamedChannel> broadcastChannels = new ArrayList<>(1);
+ broadcastChannels.add(broadcastChannel);
+ ariPlanNode.setBroadcastInputs(broadcastChannels);
+
+ // 5. Remove the partition id.
+ PartitionIDRemoveWrapper partitionIDRemoveWrapper = new
PartitionIDRemoveWrapper();
--- End diff --
The `PartitionIDRemoveWrapper` must be injected before the operator that
should receive the partitioned input because that operator does not expect the
`Tuple2`-wrapped input and will fail otherwise.
So we need to append the `PartitionIDRemoveWrapper` to the
`PartitionIDAssigner` with a Range-partition channel. The idAssigner has the
same DOP as the source and the idRemove has the same DOP as the target node.
Then the target node is appended to the idRemove node with a forward channel.
The range partitioning will happen between the idAssigner and idRemover but
will be preserved due to the forward channel and the equal DOP of idRemover and
target node.
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