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   * 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.ml.classification;
  
  import java.util.HashMap;
  import java.util.Map;
  
  import org.junit.Test;
  
  import org.apache.spark.SharedSparkSession;
  import org.apache.spark.api.java.JavaRDD;
  import org.apache.spark.ml.feature.LabeledPoint;
  import org.apache.spark.ml.tree.impl.TreeTests;
  import org.apache.spark.sql.Dataset;
  import org.apache.spark.sql.Row;
  
  public class JavaDecisionTreeClassifierSuite extends SharedSparkSession {
  
    @Test
    public void runDT() {
      int nPoints = 20;
      double A = 2.0;
      double B = -1.5;
  
      JavaRDD<LabeledPoint> data = jsc.parallelize(
        LogisticRegressionSuite.generateLogisticInputAsList(A, B, nPoints, 42), 2).cache();
      Map<Integer, Integer> categoricalFeatures = new HashMap<>();
      Dataset<Row> dataFrame = TreeTests.setMetadata(data, categoricalFeatures, 2);
  
      // This tests setters. Training with various options is tested in Scala.
      DecisionTreeClassifier dt = new DecisionTreeClassifier()
        .setMaxDepth(2)
        .setMaxBins(10)
        .setMinInstancesPerNode(5)
        .setMinInfoGain(0.0)
        .setMaxMemoryInMB(256)
        .setCacheNodeIds(false)
        .setCheckpointInterval(10)
        .setMaxDepth(2); // duplicate setMaxDepth to check builder pattern
      for (String impurity : DecisionTreeClassifier.supportedImpurities()) {
        dt.setImpurity(impurity);
      }
      DecisionTreeClassificationModel model = dt.fit(dataFrame);
  
      model.transform(dataFrame);
      model.numNodes();
      model.depth();
      model.toDebugString();
  
      /*
      // TODO: Add test once save/load are implemented.  SPARK-6725
      File tempDir = Utils.createTempDir(System.getProperty("java.io.tmpdir"), "spark");
      String path = tempDir.toURI().toString();
      try {
        model3.save(sc.sc(), path);
        DecisionTreeClassificationModel sameModel =
          DecisionTreeClassificationModel.load(sc.sc(), path);
        TreeTests.checkEqual(model3, sameModel);
      } finally {
        Utils.deleteRecursively(tempDir);
      }
      */
    }
  }
  