[SPARK-7528] [MLLIB] make RankingMetrics Java-friendly

`RankingMetrics` contains a ClassTag, which is hard to create in Java. This PR adds a factory method `of` for Java users. coderxiang

Author: Xiangrui Meng <meng@databricks.com>

Closes #6098 from mengxr/SPARK-7528 and squashes the following commits:

e5d57ae [Xiangrui Meng] make RankingMetrics Java-friendly

1 files changed, 64 insertions, 0 deletions

diff --git a/mllib/src/test/java/org/apache/spark/mllib/evaluation/JavaRankingMetricsSuite.java b/mllib/src/test/java/org/apache/spark/mllib/evaluation/JavaRankingMetricsSuite.java
new file mode 100644
index 0000000000..effc8a1a6d
--- /dev/null
+++ b/mllib/src/test/java/org/apache/spark/mllib/evaluation/JavaRankingMetricsSuite.java
@@ -0,0 +1,64 @@
+/*
+ * 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.mllib.evaluation;
+
+import java.io.Serializable;
+import java.util.ArrayList;
+
+import scala.Tuple2;
+import scala.Tuple2$;
+
+import com.google.common.collect.Lists;
+import org.junit.After;
+import org.junit.Assert;
+import org.junit.Before;
+import org.junit.Test;
+
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.JavaSparkContext;
+
+public class JavaRankingMetricsSuite implements Serializable {
+  private transient JavaSparkContext sc;
+  private transient JavaRDD<Tuple2<ArrayList<Integer>, ArrayList<Integer>>> predictionAndLabels;
+
+  @Before
+  public void setUp() {
+    sc = new JavaSparkContext("local", "JavaRankingMetricsSuite");
+    predictionAndLabels = sc.parallelize(Lists.newArrayList(
+      Tuple2$.MODULE$.apply(
+        Lists.newArrayList(1, 6, 2, 7, 8, 3, 9, 10, 4, 5), Lists.newArrayList(1, 2, 3, 4, 5)),
+      Tuple2$.MODULE$.apply(
+        Lists.newArrayList(4, 1, 5, 6, 2, 7, 3, 8, 9, 10), Lists.newArrayList(1, 2, 3)),
+      Tuple2$.MODULE$.apply(
+        Lists.newArrayList(1, 2, 3, 4, 5), Lists.<Integer>newArrayList())), 2);
+  }
+
+  @After
+  public void tearDown() {
+    sc.stop();
+    sc = null;
+  }
+
+  @Test
+  public void rankingMetrics() {
+    @SuppressWarnings("unchecked")
+    RankingMetrics<?> metrics = RankingMetrics.of(predictionAndLabels);
+    Assert.assertEquals(0.355026, metrics.meanAveragePrecision(), 1e-5);
+    Assert.assertEquals(0.75 / 3.0, metrics.precisionAt(4), 1e-5);
+  }
+}