JavaWord2VecExample.java Source code

Introduction

Here is the source code for JavaWord2VecExample.java

Source

/*
 * 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.
 */

// $example on$
import java.util.Arrays;

import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.ml.feature.Word2Vec;
import org.apache.spark.ml.feature.Word2VecModel;
import org.apache.spark.sql.DataFrame;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.RowFactory;
import org.apache.spark.sql.SQLContext;
import org.apache.spark.sql.types.*;
// $example off$

public class JavaWord2VecExample {
    public static void main(String[] args) {

        SparkConf conf = new SparkConf().setAppName("JavaWord2VecExample");
        JavaSparkContext jsc = new JavaSparkContext(conf);
        SQLContext sqlContext = new SQLContext(jsc);

        // $example on$
        // Input data: Each row is a bag of words from a sentence or document.
        JavaRDD<Row> jrdd = jsc
                .parallelize(Arrays.asList(RowFactory.create(Arrays.asList("Hi I heard about Spark".split(" "))),
                        RowFactory.create(Arrays.asList("I wish Java could use case classes".split(" "))),
                        RowFactory.create(Arrays.asList("Logistic regression models are neat".split(" ")))));
        StructType schema = new StructType(new StructField[] {
                new StructField("text", new ArrayType(DataTypes.StringType, true), false, Metadata.empty()) });
        DataFrame documentDF = sqlContext.createDataFrame(jrdd, schema);

        // Learn a mapping from words to Vectors.
        Word2Vec word2Vec = new Word2Vec().setInputCol("text").setOutputCol("result").setVectorSize(3)
                .setMinCount(0);
        Word2VecModel model = word2Vec.fit(documentDF);
        DataFrame result = model.transform(documentDF);
        for (Row r : result.select("result").take(3)) {
            System.out.println(r);
        }
        // $example off$
    }
}