github-actions[bot] opened a new issue, #362: URL: https://github.com/apache/incubator-wayang/issues/362
need DataFrameChannel? https://github.com/apache/incubator-wayang/blob/897797899866f373f93e5672b36d5e34611faece/wayang-platforms/wayang-spark/code/main/java/org/apache/wayang/spark/operators/ml/SparkKMeansOperator.java#L55 ```java /* * 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.KMeansOperator; 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 SparkKMeansOperator extends KMeansOperator implements SparkExecutionOperator { public SparkKMeansOperator(int k) { super(k); } public SparkKMeansOperator(KMeansOperator that) { super(that); } @Override public List<ChannelDescriptor> getSupportedInputChannels(int index) { // TODO need DataFrameChannel? return Arrays.asList(RddChannel.UNCACHED_DESCRIPTOR, RddChannel.CACHED_DESCRIPTOR); } @Override public List<ChannelDescriptor> getSupportedOutputChannels(int index) { // TODO need DataFrameChannel? 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.getNumInputs(); 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); } } } ``` bf0ae8055e229f8ccd3f6550b68ee2be4bde3acc -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
