fixed JavaLinearRegressionSuite.java Java sql api

nxwhite-str · Feb 5, 2015 · 9872424 · 9872424
1 parent f542997
commit 9872424
Showing 1 changed file with 6 additions and 15 deletions.
diff --git a/mllib/src/test/java/org/apache/spark/ml/classification/JavaLinearRegressionSuite.java b/mllib/src/test/java/org/apache/spark/ml/classification/JavaLinearRegressionSuite.java
@@ -17,8 +17,6 @@
 
 package org.apache.spark.ml.classification;
 
-import scala.Tuple2;
-
 import java.io.Serializable;
 import java.util.ArrayList;
 import java.util.List;
@@ -29,40 +27,33 @@
 
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.JavaSparkContext;
-import org.apache.spark.api.java.function.Function;
 import org.apache.spark.ml.regression.LinearRegression;
 import org.apache.spark.ml.regression.LinearRegressionModel;
 import static org.apache.spark.mllib.classification.LogisticRegressionSuite
     .generateLogisticInputAsList;
-import org.apache.spark.mllib.linalg.Vector;
 import org.apache.spark.mllib.regression.LabeledPoint;
-import org.apache.spark.sql.api.java.JavaSQLContext;
-import org.apache.spark.sql.api.java.JavaSchemaRDD;
-import org.apache.spark.sql.api.java.Row;
+import org.apache.spark.sql.SQLContext;
+import org.apache.spark.sql.SchemaRDD;
 
 
 public class JavaLinearRegressionSuite implements Serializable {
 
   private transient JavaSparkContext jsc;
-  private transient JavaSQLContext jsql;
-  private transient JavaSchemaRDD dataset;
+  private transient SQLContext jsql;
+  private transient SchemaRDD dataset;
   private transient JavaRDD<LabeledPoint> datasetRDD;
-  private transient JavaRDD<Vector> featuresRDD;
   private double eps = 1e-5;
 
   @Before
   public void setUp() {
     jsc = new JavaSparkContext("local", "JavaLinearRegressionSuite");
-    jsql = new JavaSQLContext(jsc);
+    jsql = new SQLContext(jsc);
     List<LabeledPoint> points = new ArrayList<LabeledPoint>();
     for (org.apache.spark.mllib.regression.LabeledPoint lp:
         generateLogisticInputAsList(1.0, 1.0, 100, 42)) {
       points.add(new LabeledPoint(lp.label(), lp.features()));
     }
     datasetRDD = jsc.parallelize(points, 2);
-    featuresRDD = datasetRDD.map(new Function<LabeledPoint, Vector>() {
-      @Override public Vector call(LabeledPoint lp) { return lp.features(); }
-    });
     dataset = jsql.applySchema(datasetRDD, LabeledPoint.class);
     dataset.registerTempTable("dataset");
   }
@@ -79,7 +70,7 @@ public void linearRegressionDefaultParams() {
     assert(lr.getLabelCol().equals("label"));
     LinearRegressionModel model = lr.fit(dataset);
     model.transform(dataset).registerTempTable("prediction");
-    JavaSchemaRDD predictions = jsql.sql("SELECT label, prediction FROM prediction");
+    SchemaRDD predictions = jsql.sql("SELECT label, prediction FROM prediction");
     predictions.collect();
     // Check defaults
     assert(model.getFeaturesCol().equals("features"));