| /* |
| * 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.ml; |
| |
| import org.apache.spark.api.java.JavaRDD; |
| import org.apache.spark.ml.clustering.KMeans; |
| import org.apache.spark.ml.clustering.KMeansModel; |
| import org.apache.spark.ml.linalg.Vector; |
| import org.apache.spark.ml.linalg.Vectors; |
| import org.apache.spark.sql.Dataset; |
| import org.apache.spark.sql.Row; |
| import org.apache.spark.sql.SparkSession; |
| import org.apache.wayang.basic.data.Tuple2; |
| import org.apache.wayang.basic.operators.KMeansOperatorV1; |
| import org.apache.wayang.core.optimizer.OptimizationContext; |
| 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.util.Tuple; |
| import org.apache.wayang.spark.channels.RddChannel; |
| import org.apache.wayang.spark.execution.SparkExecutor; |
| import org.apache.wayang.spark.operators.SparkExecutionOperator; |
| |
| import java.util.*; |
| |
| public class SparkKMeansOperatorV1 extends KMeansOperatorV1 implements SparkExecutionOperator { |
| |
| public SparkKMeansOperatorV1(int k) { |
| super(k); |
| } |
| |
| public SparkKMeansOperatorV1(KMeansOperatorV1 that) { |
| super(that); |
| } |
| |
| @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 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(); |
| |
| // TODO need DataFrameChannel? |
| final RddChannel.Instance input = (RddChannel.Instance) inputs[0]; |
| final RddChannel.Instance output = (RddChannel.Instance) outputs[0]; |
| |
| final JavaRDD<double[]> inputRdd = input.provideRdd(); |
| final JavaRDD<Data> dataRdd = inputRdd.map(Data::new); |
| final Dataset<Row> df = SparkSession.builder().getOrCreate().createDataFrame(dataRdd, Data.class); |
| final KMeansModel model = new KMeans() |
| .setK(this.k) |
| .fit(df); |
| |
| final Dataset<Row> transform = model.transform(df); |
| final JavaRDD<Tuple2<double[], Integer>> outputRdd = transform.toJavaRDD() |
| .map(row -> new Tuple2<>(((Vector) row.get(0)).toArray(), (Integer) row.get(1))); |
| |
| this.name(outputRdd); |
| output.accept(outputRdd, sparkExecutor); |
| |
| return ExecutionOperator.modelLazyExecution(inputs, outputs, operatorContext); |
| } |
| |
| // TODO support fit and transform |
| |
| @Override |
| public boolean containsAction() { |
| return false; |
| } |
| |
| public static class Data { |
| private final Vector features; |
| |
| |
| public Data(Vector features) { |
| this.features = features; |
| } |
| |
| public Data(double[] features) { |
| this.features = Vectors.dense(features); |
| } |
| |
| public Vector getFeatures() { |
| return features; |
| } |
| |
| @Override |
| public String toString() { |
| return "Data{" + |
| "features=" + features + |
| '}'; |
| } |
| |
| @Override |
| public boolean equals(Object o) { |
| if (this == o) return true; |
| if (!(o instanceof Data)) return false; |
| Data data = (Data) o; |
| return Objects.equals(features, data.features); |
| } |
| |
| @Override |
| public int hashCode() { |
| return Objects.hash(features); |
| } |
| } |
| } |