0001
0002
0003
0004
0005
0006
0007
0008
0009
0010
0011
0012
0013
0014
0015
0016
0017
0018 package org.apache.spark.examples.ml;
0019
0020 import org.apache.spark.sql.Dataset;
0021 import org.apache.spark.sql.SparkSession;
0022
0023
0024 import java.util.Arrays;
0025 import java.util.List;
0026
0027 import org.apache.spark.ml.feature.NGram;
0028 import org.apache.spark.sql.Row;
0029 import org.apache.spark.sql.RowFactory;
0030 import org.apache.spark.sql.types.DataTypes;
0031 import org.apache.spark.sql.types.Metadata;
0032 import org.apache.spark.sql.types.StructField;
0033 import org.apache.spark.sql.types.StructType;
0034
0035
0036 public class JavaNGramExample {
0037 public static void main(String[] args) {
0038 SparkSession spark = SparkSession
0039 .builder()
0040 .appName("JavaNGramExample")
0041 .getOrCreate();
0042
0043
0044 List<Row> data = Arrays.asList(
0045 RowFactory.create(0, Arrays.asList("Hi", "I", "heard", "about", "Spark")),
0046 RowFactory.create(1, Arrays.asList("I", "wish", "Java", "could", "use", "case", "classes")),
0047 RowFactory.create(2, Arrays.asList("Logistic", "regression", "models", "are", "neat"))
0048 );
0049
0050 StructType schema = new StructType(new StructField[]{
0051 new StructField("id", DataTypes.IntegerType, false, Metadata.empty()),
0052 new StructField(
0053 "words", DataTypes.createArrayType(DataTypes.StringType), false, Metadata.empty())
0054 });
0055
0056 Dataset<Row> wordDataFrame = spark.createDataFrame(data, schema);
0057
0058 NGram ngramTransformer = new NGram().setN(2).setInputCol("words").setOutputCol("ngrams");
0059
0060 Dataset<Row> ngramDataFrame = ngramTransformer.transform(wordDataFrame);
0061 ngramDataFrame.select("ngrams").show(false);
0062
0063
0064 spark.stop();
0065 }
0066 }