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/*
* 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.flink.operators;
import org.apache.flink.api.common.aggregators.ConvergenceCriterion;
import org.apache.flink.api.java.DataSet;
import org.apache.flink.api.java.operators.IterativeDataSet;
import org.apache.wayang.basic.operators.DoWhileOperator;
import org.apache.wayang.core.api.Configuration;
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.flink.channels.DataSetChannel;
import org.apache.wayang.flink.compiler.criterion.DummyFilter;
import org.apache.wayang.flink.compiler.criterion.DummyMap;
import org.apache.wayang.flink.compiler.criterion.WayangAggregator;
import org.apache.wayang.flink.compiler.criterion.WayangFilterCriterion;
import org.apache.wayang.flink.execution.FlinkExecutor;
import java.util.Collection;
import java.util.Collections;
import java.util.List;
import java.util.Optional;
/**
* Flink implementation of the {@link DoWhileOperator}.
*/
public class FlinkDoWhileOperator<InputType, ConvergenceType>
extends DoWhileOperator<InputType, ConvergenceType>
implements FlinkExecutionOperator {
private IterativeDataSet iterativeDataSet;
/**
* Creates a new instance.
*/
public FlinkDoWhileOperator(DataSetType<InputType> inputType,
DataSetType<ConvergenceType> convergenceType,
PredicateDescriptor.SerializablePredicate<Collection<ConvergenceType>> criterionPredicate,
Integer numExpectedIterations) {
super(inputType, convergenceType, criterionPredicate, numExpectedIterations);
}
public FlinkDoWhileOperator(DataSetType<InputType> inputType,
DataSetType<ConvergenceType> convergenceType,
PredicateDescriptor<Collection<ConvergenceType>> criterionDescriptor,
Integer numExpectedIterations) {
super(inputType, convergenceType, criterionDescriptor, numExpectedIterations);
}
/**
* Creates a new instance.
*/
public FlinkDoWhileOperator(DoWhileOperator<InputType, ConvergenceType> that) {
super(that);
}
@Override
@SuppressWarnings("unchecked")
public Tuple<Collection<ExecutionLineageNode>, Collection<ChannelInstance>> evaluate(
ChannelInstance[] inputs,
ChannelInstance[] outputs,
FlinkExecutor flinkExecutor,
OptimizationContext.OperatorContext operatorContext) {
assert inputs.length == this.getNumInputs();
assert outputs.length == this.getNumOutputs();
switch (this.getState()) {
case NOT_STARTED:
DataSet<InputType> input_initial = ((DataSetChannel.Instance) inputs[INITIAL_INPUT_INDEX]).provideDataSet();
DataSetChannel.Instance output_iteration = ((DataSetChannel.Instance) outputs[ITERATION_OUTPUT_INDEX]);
final ConvergenceCriterion wayangConvergeCriterion = flinkExecutor.getCompiler().compile(this.criterionDescriptor);
this.iterativeDataSet = input_initial
.iterate( 100000)
.registerAggregationConvergenceCriterion(
"Iteration_"+this.getName(),
new WayangAggregator(),
wayangConvergeCriterion
);
output_iteration.accept(this.iterativeDataSet, flinkExecutor);
outputs[FINAL_OUTPUT_INDEX] = null;
this.setState(State.RUNNING);
break;
case RUNNING:
assert this.iterativeDataSet != null;
DataSet<InputType> input_iteration = ((DataSetChannel.Instance) inputs[ITERATION_INPUT_INDEX]).provideDataSet();
DataSet<ConvergenceType> input_convergence = ((DataSetChannel.Instance) inputs[CONVERGENCE_INPUT_INDEX]).provideDataSet();
DataSetChannel.Instance final_output = ((DataSetChannel.Instance) outputs[FINAL_OUTPUT_INDEX]);
Class<InputType> input_class = this.getInputType().getDataUnitType().getTypeClass();
Class<ConvergenceType> convergence_class = this.getConvergenceType().getDataUnitType().getTypeClass();
DataSet<ConvergenceType> dummy_start = input_iteration
.map(
new DummyMap<InputType, ConvergenceType>(
input_class,
convergence_class
)
)
.filter(
new DummyFilter<ConvergenceType>(
convergence_class
)
);
DataSet<ConvergenceType> dummy_union = input_convergence.union(dummy_start);
DataSet<ConvergenceType> filter = dummy_union.filter(new WayangFilterCriterion<>("Iteration_"+this.getName()));
DataSet<InputType> dummy_finish = filter
.map(
new DummyMap<ConvergenceType, InputType>(
convergence_class,
input_class
)
)
.filter(
new DummyFilter<InputType>(
input_class
)
);
DataSet<InputType> final_union = input_iteration.union(dummy_finish);
final_output.accept(this.iterativeDataSet.closeWith(final_union), flinkExecutor);
outputs[ITERATION_OUTPUT_INDEX] = null;
this.setState(State.FINISHED);
break;
default:
throw new IllegalStateException(String.format("%s is finished, yet executed.", this));
}
return ExecutionOperator.modelLazyExecution(inputs, outputs, operatorContext);
}
@Override
public boolean containsAction() {
return false;
}
@Override
public String getLoadProfileEstimatorConfigurationKey() {
return "wayang.flink.while.load";
}
@Override
public Optional<LoadProfileEstimator> createLoadProfileEstimator(Configuration configuration) {
final Optional<LoadProfileEstimator> optEstimator =
FlinkExecutionOperator.super.createLoadProfileEstimator(configuration);
LoadProfileEstimators.nestUdfEstimator(optEstimator, this.criterionDescriptor, configuration);
return optEstimator;
}
@Override
protected ExecutionOperator createCopy() {
return new FlinkDoWhileOperator<>(this.getInputType(),
this.getConvergenceType(),
this.getCriterionDescriptor().getJavaImplementation(),
this.getNumExpectedIterations()
);
}
@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 Collections.singletonList(DataSetChannel.DESCRIPTOR);
case CONVERGENCE_INPUT_INDEX:
return Collections.singletonList(DataSetChannel.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);
return Collections.singletonList(DataSetChannel.DESCRIPTOR);
}
}