Added JavaLabeledPointSuite.java for spark.ml, and added constructor …

…to LabeledPoint which defaults weight to 1.0

mllib/src/main/scala/org/apache/spark/ml/LabeledPoint.scala

@@ -34,6 +34,9 @@ import org.apache.spark.mllib.linalg.Vector
 @BeanInfo
 case class LabeledPoint(label: Double, features: Vector, weight: Double) {
 
+  /** Constructor which sets instance weight to 1.0 */
+  def this(label: Double, features: Vector) = this(label, features, 1.0)
+
   override def toString: String = {
     "(%s,%s,%s)".format(label, features, weight)
   }

mllib/src/test/java/org/apache/spark/ml/JavaLabeledPointSuite.java

@@ -0,0 +1,61 @@
+package org.apache.spark.ml;
+
+import java.util.List;
+
+import org.junit.After;
+import org.junit.Before;
+import org.junit.Test;
+
+import com.google.common.collect.Lists;
+
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.mllib.linalg.Vector;
+import org.apache.spark.mllib.linalg.Vectors;
+import org.apache.spark.sql.api.java.JavaSQLContext;
+import org.apache.spark.sql.api.java.JavaSchemaRDD;
+import org.apache.spark.sql.api.java.Row;
+
+/**
+ * Test {@link LabeledPoint} in Java
+ */
+public class JavaLabeledPointSuite {
+
+  private transient JavaSparkContext jsc;
+  private transient JavaSQLContext jsql;
+
+  @Before
+  public void setUp() {
+    jsc = new JavaSparkContext("local", "JavaLabeledPointSuite");
+    jsql = new JavaSQLContext(jsc);
+  }
+
+  @After
+  public void tearDown() {
+    jsc.stop();
+    jsc = null;
+  }
+
+  @Test
+  public void labeledPointDefaultWeight() {
+    double label = 1.0;
+    Vector features = Vectors.dense(1.0, 2.0, 3.0);
+    LabeledPoint lp1 = new LabeledPoint(label, features);
+    LabeledPoint lp2 = new LabeledPoint(label, features, 1.0);
+    assert(lp1.equals(lp2));
+  }
+
+  @Test
+  public void labeledPointSchemaRDD() {
+    List<LabeledPoint> arr = Lists.newArrayList(
+        new LabeledPoint(0.0, Vectors.dense(1.0, 2.0, 3.0)),
+        new LabeledPoint(1.0, Vectors.dense(1.1, 2.1, 3.1)),
+        new LabeledPoint(0.0, Vectors.dense(1.2, 2.2, 3.2)),
+        new LabeledPoint(1.0, Vectors.dense(1.3, 2.3, 3.3)));
+    JavaRDD<LabeledPoint> rdd = jsc.parallelize(arr);
+    JavaSchemaRDD schemaRDD = jsql.applySchema(rdd, LabeledPoint.class);
+    schemaRDD.registerTempTable("points");
+    List<Row> points = jsql.sql("SELECT label, features FROM points").collect();
+    assert (points.size() == arr.size());
+  }
+}

mllib/src/test/scala/org/apache/spark/ml/LabeledPointSuite.scala

@@ -19,11 +19,13 @@ package org.apache.spark.ml
 
 import org.scalatest.FunSuite
 
-import org.apache.spark.mllib.classification.LogisticRegressionSuite.generateLogisticInput
 import org.apache.spark.mllib.linalg.Vectors
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.sql.{SQLContext, SchemaRDD}
+import org.apache.spark.sql.SQLContext
 
+/**
+ * Test [[LabeledPoint]]
+ */
 class LabeledPointSuite extends FunSuite with MLlibTestSparkContext {
 
   @transient var sqlContext: SQLContext = _