| /* |
| * 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.wayang.spark.operators; |
| |
| import java.util.Arrays; |
| import java.util.Collection; |
| import java.util.Collections; |
| import java.util.List; |
| import java.util.Optional; |
| import org.apache.spark.api.java.JavaPairRDD; |
| import org.apache.spark.api.java.JavaRDD; |
| import org.apache.spark.api.java.function.Function; |
| import org.apache.wayang.basic.operators.MaterializedGroupByOperator; |
| import org.apache.wayang.core.api.Configuration; |
| import org.apache.wayang.core.function.TransformationDescriptor; |
| import org.apache.wayang.core.optimizer.OptimizationContext; |
| import org.apache.wayang.core.optimizer.costs.LoadProfileEstimator; |
| import org.apache.wayang.core.optimizer.costs.LoadProfileEstimators; |
| import org.apache.wayang.core.plan.wayangplan.ExecutionOperator; |
| import org.apache.wayang.core.platform.ChannelDescriptor; |
| import org.apache.wayang.core.platform.ChannelInstance; |
| import org.apache.wayang.core.platform.lineage.ExecutionLineageNode; |
| import org.apache.wayang.core.types.DataSetType; |
| import org.apache.wayang.core.util.Tuple; |
| import org.apache.wayang.spark.channels.RddChannel; |
| import org.apache.wayang.spark.execution.SparkExecutor; |
| import scala.Tuple2; |
| |
| |
| /** |
| * Spark implementation of the {@link MaterializedGroupByOperator}. |
| */ |
| public class SparkMaterializedGroupByOperator<Type, KeyType> |
| extends MaterializedGroupByOperator<Type, KeyType> |
| implements SparkExecutionOperator { |
| |
| |
| public SparkMaterializedGroupByOperator(TransformationDescriptor<Type, KeyType> keyDescriptor, |
| DataSetType<Type> inputType, |
| DataSetType<Iterable<Type>> outputType) { |
| super(keyDescriptor, inputType, outputType); |
| } |
| |
| /** |
| * Copies an instance (exclusive of broadcasts). |
| * |
| * @param that that should be copied |
| */ |
| public SparkMaterializedGroupByOperator(MaterializedGroupByOperator<Type, KeyType> that) { |
| super(that); |
| } |
| |
| @Override |
| public Tuple<Collection<ExecutionLineageNode>, Collection<ChannelInstance>> evaluate( |
| ChannelInstance[] inputs, |
| ChannelInstance[] outputs, |
| SparkExecutor sparkExecutor, |
| OptimizationContext.OperatorContext operatorContext) { |
| assert inputs.length == this.getNumInputs(); |
| assert outputs.length == this.getNumOutputs(); |
| |
| RddChannel.Instance input = (RddChannel.Instance) inputs[0]; |
| RddChannel.Instance output = (RddChannel.Instance) outputs[0]; |
| |
| final JavaRDD<Type> inputRdd = input.provideRdd(); |
| final Function<Type, KeyType> keyExtractor = |
| sparkExecutor.getCompiler().compile(this.keyDescriptor, this, operatorContext, inputs); |
| final Function<scala.Tuple2<KeyType, Iterable<Type>>, Iterable<Type>> projector = new GroupProjector<>(); |
| final JavaPairRDD<KeyType, Iterable<Type>> groupedKeyRdd = inputRdd.groupBy(keyExtractor, sparkExecutor.getNumDefaultPartitions()); |
| this.name(groupedKeyRdd); |
| final JavaRDD<Iterable<Type>> outputRdd = groupedKeyRdd.map(projector); |
| this.name(outputRdd); |
| |
| output.accept(outputRdd, sparkExecutor); |
| |
| return ExecutionOperator.modelLazyExecution(inputs, outputs, operatorContext); |
| } |
| |
| @Override |
| protected ExecutionOperator createCopy() { |
| return new SparkMaterializedGroupByOperator<>(this.getKeyDescriptor(), this.getInputType(), this.getOutputType()); |
| } |
| |
| private static class GroupProjector<Key, Type> implements Function<scala.Tuple2<Key, Iterable<Type>>, Iterable<Type>> { |
| |
| @Override |
| public Iterable<Type> call(Tuple2<Key, Iterable<Type>> groupWithKey) throws Exception { |
| return groupWithKey._2; |
| } |
| |
| } |
| |
| @Override |
| public String getLoadProfileEstimatorConfigurationKey() { |
| return "wayang.spark.groupby.load"; |
| } |
| |
| @Override |
| public Optional<LoadProfileEstimator> createLoadProfileEstimator(Configuration configuration) { |
| final Optional<LoadProfileEstimator> optEstimator = |
| SparkExecutionOperator.super.createLoadProfileEstimator(configuration); |
| LoadProfileEstimators.nestUdfEstimator(optEstimator, this.keyDescriptor, configuration); |
| return optEstimator; |
| } |
| |
| @Override |
| public List<ChannelDescriptor> getSupportedInputChannels(int index) { |
| return Arrays.asList(RddChannel.UNCACHED_DESCRIPTOR, RddChannel.CACHED_DESCRIPTOR); |
| } |
| |
| @Override |
| public List<ChannelDescriptor> getSupportedOutputChannels(int index) { |
| return Collections.singletonList(RddChannel.UNCACHED_DESCRIPTOR); |
| } |
| |
| @Override |
| public boolean containsAction() { |
| return false; |
| } |
| |
| } |