| /* |
| * 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.function.Function; |
| import org.apache.wayang.basic.operators.LoopOperator; |
| import org.apache.wayang.core.api.Configuration; |
| import org.apache.wayang.core.api.exception.WayangException; |
| import org.apache.wayang.core.function.PredicateDescriptor; |
| 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.java.channels.CollectionChannel; |
| import org.apache.wayang.java.operators.JavaExecutionOperator; |
| import org.apache.wayang.spark.channels.RddChannel; |
| import org.apache.wayang.spark.execution.SparkExecutor; |
| |
| /** |
| * Spark implementation of the {@link LoopOperator}. |
| */ |
| public class SparkLoopOperator<InputType, ConvergenceType> |
| extends LoopOperator<InputType, ConvergenceType> |
| implements SparkExecutionOperator { |
| |
| |
| /** |
| * Creates a new instance. |
| */ |
| public SparkLoopOperator(DataSetType<InputType> inputType, |
| DataSetType<ConvergenceType> convergenceType, |
| PredicateDescriptor.SerializablePredicate<Collection<ConvergenceType>> criterionPredicate, |
| Integer numExpectedIterations) { |
| super(inputType, convergenceType, criterionPredicate, numExpectedIterations); |
| } |
| |
| public SparkLoopOperator(DataSetType<InputType> inputType, |
| DataSetType<ConvergenceType> convergenceType, |
| PredicateDescriptor<Collection<ConvergenceType>> criterionDescriptor, |
| Integer numExpectedIterations) { |
| super(inputType, convergenceType, criterionDescriptor, numExpectedIterations); |
| } |
| |
| /** |
| * Creates a copy of the given {@link LoopOperator}. |
| * |
| * @param that should be copied |
| */ |
| public SparkLoopOperator(LoopOperator<InputType, ConvergenceType> that) { |
| super(that); |
| } |
| |
| @Override |
| @SuppressWarnings("unchecked") |
| 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(); |
| |
| ExecutionLineageNode executionLineageNode = new ExecutionLineageNode(operatorContext); |
| executionLineageNode.addAtomicExecutionFromOperatorContext(); |
| |
| final Function<Collection<ConvergenceType>, Boolean> stoppingCondition = |
| sparkExecutor.getCompiler().compile(this.criterionDescriptor, this, operatorContext, inputs); |
| |
| boolean endloop = false; |
| final Collection<ConvergenceType> convergenceCollection; |
| final RddChannel.Instance input; |
| switch (this.getState()) { |
| case NOT_STARTED: |
| assert inputs[INITIAL_INPUT_INDEX] != null; |
| assert inputs[INITIAL_CONVERGENCE_INPUT_INDEX] != null; |
| |
| input = (RddChannel.Instance) inputs[INITIAL_INPUT_INDEX]; |
| JavaExecutionOperator.forward(inputs[INITIAL_CONVERGENCE_INPUT_INDEX], outputs[ITERATION_CONVERGENCE_OUTPUT_INDEX]); |
| break; |
| case RUNNING: |
| assert inputs[ITERATION_INPUT_INDEX] != null; |
| assert inputs[ITERATION_CONVERGENCE_INPUT_INDEX] != null; |
| |
| input = (RddChannel.Instance) inputs[ITERATION_INPUT_INDEX]; |
| convergenceCollection = ((CollectionChannel.Instance) inputs[ITERATION_CONVERGENCE_INPUT_INDEX]).provideCollection(); |
| executionLineageNode.addPredecessor(inputs[ITERATION_CONVERGENCE_INPUT_INDEX].getLineage()); |
| |
| try { |
| endloop = stoppingCondition.call(convergenceCollection); |
| } catch (Exception e) { |
| throw new WayangException(String.format("Executing %s's condition failed.", this), e); |
| } |
| JavaExecutionOperator.forward(inputs[ITERATION_CONVERGENCE_INPUT_INDEX], outputs[ITERATION_CONVERGENCE_OUTPUT_INDEX]); |
| break; |
| default: |
| throw new IllegalStateException(String.format("%s is finished, yet executed.", this)); |
| |
| } |
| |
| if (endloop) { |
| // final loop output |
| sparkExecutor.forward(input, outputs[FINAL_OUTPUT_INDEX]); |
| outputs[ITERATION_OUTPUT_INDEX] = null; |
| outputs[ITERATION_CONVERGENCE_OUTPUT_INDEX] = null; |
| this.setState(State.FINISHED); |
| } else { |
| outputs[FINAL_OUTPUT_INDEX] = null; |
| sparkExecutor.forward(input, outputs[ITERATION_OUTPUT_INDEX]); |
| this.setState(State.RUNNING); |
| } |
| |
| return executionLineageNode.collectAndMark(); |
| } |
| |
| @Override |
| protected ExecutionOperator createCopy() { |
| return new SparkLoopOperator<>( |
| this.getInputType(), |
| this.getConvergenceType(), |
| this.getCriterionDescriptor().getJavaImplementation(), |
| this.getNumExpectedIterations() |
| ); |
| } |
| |
| @Override |
| public String getLoadProfileEstimatorConfigurationKey() { |
| return "wayang.spark.loop.load"; |
| } |
| |
| @Override |
| public Optional<LoadProfileEstimator> createLoadProfileEstimator(Configuration configuration) { |
| final Optional<LoadProfileEstimator> optEstimator = |
| SparkExecutionOperator.super.createLoadProfileEstimator(configuration); |
| LoadProfileEstimators.nestUdfEstimator(optEstimator, this.criterionDescriptor, configuration); |
| return optEstimator; |
| } |
| |
| @Override |
| public List<ChannelDescriptor> getSupportedInputChannels(int index) { |
| assert index <= this.getNumInputs() || (index == 0 && this.getNumInputs() == 0); |
| switch (index) { |
| case INITIAL_INPUT_INDEX: |
| case ITERATION_INPUT_INDEX: |
| return Arrays.asList(RddChannel.UNCACHED_DESCRIPTOR, RddChannel.CACHED_DESCRIPTOR); |
| case INITIAL_CONVERGENCE_INPUT_INDEX: |
| case ITERATION_CONVERGENCE_INPUT_INDEX: |
| return Collections.singletonList(CollectionChannel.DESCRIPTOR); |
| default: |
| throw new IllegalStateException(String.format("%s has no %d-th input.", this, index)); |
| } |
| } |
| |
| @Override |
| public List<ChannelDescriptor> getSupportedOutputChannels(int index) { |
| assert index <= this.getNumOutputs() || (index == 0 && this.getNumOutputs() == 0); |
| switch (index) { |
| case ITERATION_OUTPUT_INDEX: |
| case FINAL_OUTPUT_INDEX: |
| // TODO: In this specific case, the actual output Channel is context-sensitive because we could forward Streams/Collections. |
| return Collections.singletonList(RddChannel.UNCACHED_DESCRIPTOR); |
| case INITIAL_CONVERGENCE_INPUT_INDEX: |
| case ITERATION_CONVERGENCE_INPUT_INDEX: |
| return Collections.singletonList(CollectionChannel.DESCRIPTOR); |
| default: |
| throw new IllegalStateException(String.format("%s has no %d-th input.", this, index)); |
| } |
| } |
| |
| @Override |
| public boolean containsAction() { |
| return false; |
| } |
| |
| } |