content: /*
   * 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.spark.examples.ml;
  
  // $example on$
  import java.util.Arrays;
  import java.util.List;
  
  import org.apache.spark.ml.feature.MaxAbsScaler;
  import org.apache.spark.ml.feature.MaxAbsScalerModel;
  import org.apache.spark.ml.linalg.Vectors;
  import org.apache.spark.ml.linalg.VectorUDT;
  import org.apache.spark.sql.Dataset;
  import org.apache.spark.sql.Row;
  import org.apache.spark.sql.RowFactory;
  import org.apache.spark.sql.types.DataTypes;
  import org.apache.spark.sql.types.Metadata;
  import org.apache.spark.sql.types.StructField;
  import org.apache.spark.sql.types.StructType;
  // $example off$
  import org.apache.spark.sql.SparkSession;
  
  public class JavaMaxAbsScalerExample {
  
    public static void main(String[] args) {
      SparkSession spark = SparkSession
        .builder()
        .appName("JavaMaxAbsScalerExample")
        .getOrCreate();
  
      // $example on$
      List<Row> data = Arrays.asList(
          RowFactory.create(0, Vectors.dense(1.0, 0.1, -8.0)),
          RowFactory.create(1, Vectors.dense(2.0, 1.0, -4.0)),
          RowFactory.create(2, Vectors.dense(4.0, 10.0, 8.0))
      );
      StructType schema = new StructType(new StructField[]{
          new StructField("id", DataTypes.IntegerType, false, Metadata.empty()),
          new StructField("features", new VectorUDT(), false, Metadata.empty())
      });
      Dataset<Row> dataFrame = spark.createDataFrame(data, schema);
  
      MaxAbsScaler scaler = new MaxAbsScaler()
        .setInputCol("features")
        .setOutputCol("scaledFeatures");
  
      // Compute summary statistics and generate MaxAbsScalerModel
      MaxAbsScalerModel scalerModel = scaler.fit(dataFrame);
  
      // rescale each feature to range [-1, 1].
      Dataset<Row> scaledData = scalerModel.transform(dataFrame);
      scaledData.select("features", "scaledFeatures").show();
      // $example off$
  
      spark.stop();
    }
  
  }
  