ml/feature/JavaWord2VecSuite.java

0001 /*
0002  * Licensed to the Apache Software Foundation (ASF) under one or more
0003  * contributor license agreements.  See the NOTICE file distributed with
0004  * this work for additional information regarding copyright ownership.
0005  * The ASF licenses this file to You under the Apache License, Version 2.0
0006  * (the "License"); you may not use this file except in compliance with
0007  * the License.  You may obtain a copy of the License at
0008  *
0009  *    http://www.apache.org/licenses/LICENSE-2.0
0010  *
0011  * Unless required by applicable law or agreed to in writing, software
0012  * distributed under the License is distributed on an "AS IS" BASIS,
0013  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
0014  * See the License for the specific language governing permissions and
0015  * limitations under the License.
0016  */
0017
0018 package org.apache.spark.ml.feature;
0019
0020 import java.util.Arrays;
0021
0022 import org.junit.Assert;
0023 import org.junit.Test;
0024
0025 import org.apache.spark.SharedSparkSession;
0026 import org.apache.spark.ml.linalg.Vector;
0027 import org.apache.spark.sql.Dataset;
0028 import org.apache.spark.sql.Row;
0029 import org.apache.spark.sql.RowFactory;
0030 import org.apache.spark.sql.types.*;
0031
0032 public class JavaWord2VecSuite extends SharedSparkSession {
0033
0034   @Test
0035   public void testJavaWord2Vec() {
0036     StructType schema = new StructType(new StructField[]{
0037       new StructField("text", new ArrayType(DataTypes.StringType, true), false, Metadata.empty())
0038     });
0039     Dataset<Row> documentDF = spark.createDataFrame(
0040       Arrays.asList(
0041         RowFactory.create(Arrays.asList("Hi I heard about Spark".split(" "))),
0042         RowFactory.create(Arrays.asList("I wish Java could use case classes".split(" "))),
0043         RowFactory.create(Arrays.asList("Logistic regression models are neat".split(" ")))),
0044       schema);
0045
0046     Word2Vec word2Vec = new Word2Vec()
0047       .setInputCol("text")
0048       .setOutputCol("result")
0049       .setVectorSize(3)
0050       .setMinCount(0);
0051     Word2VecModel model = word2Vec.fit(documentDF);
0052     Dataset<Row> result = model.transform(documentDF);
0053
0054     for (Row r : result.select("result").collectAsList()) {
0055       double[] polyFeatures = ((Vector) r.get(0)).toArray();
0056       Assert.assertEquals(3, polyFeatures.length);
0057     }
0058   }
0059 }