blob: 076fd1bc98b87a858464159adda12141d550e765 [file] [log] [blame]
/*
* 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 org.apache.spark.api.java.JavaRDD;
import org.apache.wayang.basic.channels.FileChannel;
import org.apache.wayang.basic.data.Tuple2;
import org.apache.wayang.core.optimizer.OptimizationContext;
import org.apache.wayang.core.plan.wayangplan.ExecutionOperator;
import org.apache.wayang.core.plan.wayangplan.Operator;
import org.apache.wayang.core.plan.wayangplan.UnarySink;
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 org.apache.wayang.spark.platform.SparkPlatform;
import java.util.Arrays;
import java.util.Collection;
import java.util.Collections;
import java.util.List;
/**
* {@link Operator} for the {@link SparkPlatform} that creates a TSV file.
* Only applicable to tuples with standard datatypes.
*
* @see SparkObjectFileSource
*/
public class SparkTsvFileSink<T extends Tuple2<?, ?>> extends UnarySink<T> implements SparkExecutionOperator {
private final String targetPath;
public SparkTsvFileSink(DataSetType<T> type) {
this(null, type);
}
public SparkTsvFileSink(String targetPath, DataSetType<T> type) {
super(type);
assert type.equals(DataSetType.createDefault(Tuple2.class)) :
String.format("Illegal type for %s: %s", this, type);
this.targetPath = targetPath;
}
@Override
public Tuple<Collection<ExecutionLineageNode>, Collection<ChannelInstance>> evaluate(
ChannelInstance[] inputs,
ChannelInstance[] outputs,
SparkExecutor sparkExecutor,
OptimizationContext.OperatorContext operatorContext) {
assert inputs.length == this.getNumInputs();
final FileChannel.Instance output = (FileChannel.Instance) outputs[0];
final String targetPath = output.addGivenOrTempPath(this.targetPath, sparkExecutor.getConfiguration());
final RddChannel.Instance input = (RddChannel.Instance) inputs[0];
final JavaRDD<Object> rdd = input.provideRdd();
final JavaRDD<String> serializedRdd = rdd
.map(dataQuantum -> {
// TODO: Once there are more tuple types, make this generic.
@SuppressWarnings("unchecked")
Tuple2<Object, Object> tuple2 = (Tuple2<Object, Object>) dataQuantum;
return String.valueOf(tuple2.field0) + '\t' + String.valueOf(tuple2.field1);
});
this.name(serializedRdd);
serializedRdd
.coalesce(1) // TODO: Allow more than one TSV file?
.saveAsTextFile(targetPath);
return ExecutionOperator.modelEagerExecution(inputs, outputs, operatorContext);
}
@Override
protected ExecutionOperator createCopy() {
return new SparkTsvFileSink<>(this.targetPath, this.getType());
}
@Override
public String getLoadProfileEstimatorConfigurationKey() {
return "wayang.spark.tsvfilesink.load";
}
@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(FileChannel.HDFS_TSV_DESCRIPTOR);
}
@Override
public boolean containsAction() {
return true;
}
}