diff options
Diffstat (limited to 'mllib')
3 files changed, 15 insertions, 15 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala index e47c4db629..ca11ede4cc 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala @@ -20,7 +20,7 @@ package org.apache.spark.mllib.clustering import scala.collection.mutable.ArrayBuffer import org.apache.spark.Logging -import org.apache.spark.annotation.{Experimental, Since} +import org.apache.spark.annotation.Since import org.apache.spark.mllib.linalg.{Vector, Vectors} import org.apache.spark.mllib.linalg.BLAS.{axpy, scal} import org.apache.spark.mllib.util.MLUtils @@ -107,7 +107,7 @@ class KMeans private ( * Number of runs of the algorithm to execute in parallel. */ @Since("1.4.0") - @deprecated("Support for runs is deprecated. This param will have no effect in 1.7.0.", "1.6.0") + @deprecated("Support for runs is deprecated. This param will have no effect in 2.0.0.", "1.6.0") def getRuns: Int = runs /** @@ -117,7 +117,7 @@ class KMeans private ( * return the best clustering found over any run. Default: 1. */ @Since("0.8.0") - @deprecated("Support for runs is deprecated. This param will have no effect in 1.7.0.", "1.6.0") + @deprecated("Support for runs is deprecated. This param will have no effect in 2.0.0.", "1.6.0") def setRuns(runs: Int): this.type = { if (runs <= 0) { throw new IllegalArgumentException("Number of runs must be positive") @@ -431,7 +431,7 @@ class KMeans private ( val rs = (0 until runs).filter { r => rand.nextDouble() < 2.0 * c(r) * k / sumCosts(r) } - if (rs.length > 0) Some(p, rs) else None + if (rs.length > 0) Some((p, rs)) else None } }.collect() mergeNewCenters() diff --git a/mllib/src/test/java/org/apache/spark/mllib/recommendation/JavaALSSuite.java b/mllib/src/test/java/org/apache/spark/mllib/recommendation/JavaALSSuite.java index 271dda4662..a6631ed7eb 100644 --- a/mllib/src/test/java/org/apache/spark/mllib/recommendation/JavaALSSuite.java +++ b/mllib/src/test/java/org/apache/spark/mllib/recommendation/JavaALSSuite.java @@ -56,10 +56,10 @@ public class JavaALSSuite implements Serializable { double matchThreshold, boolean implicitPrefs, DoubleMatrix truePrefs) { - List<Tuple2<Integer, Integer>> localUsersProducts = new ArrayList(users * products); + List<Tuple2<Integer, Integer>> localUsersProducts = new ArrayList<>(users * products); for (int u=0; u < users; ++u) { for (int p=0; p < products; ++p) { - localUsersProducts.add(new Tuple2<Integer, Integer>(u, p)); + localUsersProducts.add(new Tuple2<>(u, p)); } } JavaPairRDD<Integer, Integer> usersProducts = sc.parallelizePairs(localUsersProducts); diff --git a/mllib/src/test/java/org/apache/spark/mllib/regression/JavaIsotonicRegressionSuite.java b/mllib/src/test/java/org/apache/spark/mllib/regression/JavaIsotonicRegressionSuite.java index 32c2f4f339..3db9b39e74 100644 --- a/mllib/src/test/java/org/apache/spark/mllib/regression/JavaIsotonicRegressionSuite.java +++ b/mllib/src/test/java/org/apache/spark/mllib/regression/JavaIsotonicRegressionSuite.java @@ -36,11 +36,11 @@ import org.apache.spark.api.java.JavaSparkContext; public class JavaIsotonicRegressionSuite implements Serializable { private transient JavaSparkContext sc; - private List<Tuple3<Double, Double, Double>> generateIsotonicInput(double[] labels) { - ArrayList<Tuple3<Double, Double, Double>> input = new ArrayList(labels.length); + private static List<Tuple3<Double, Double, Double>> generateIsotonicInput(double[] labels) { + List<Tuple3<Double, Double, Double>> input = new ArrayList<>(labels.length); for (int i = 1; i <= labels.length; i++) { - input.add(new Tuple3<Double, Double, Double>(labels[i-1], (double) i, 1d)); + input.add(new Tuple3<>(labels[i-1], (double) i, 1.0)); } return input; @@ -70,7 +70,7 @@ public class JavaIsotonicRegressionSuite implements Serializable { runIsotonicRegression(new double[]{1, 2, 3, 3, 1, 6, 7, 8, 11, 9, 10, 12}); Assert.assertArrayEquals( - new double[] {1, 2, 7d/3, 7d/3, 6, 7, 8, 10, 10, 12}, model.predictions(), 1e-14); + new double[] {1, 2, 7.0/3, 7.0/3, 6, 7, 8, 10, 10, 12}, model.predictions(), 1.0e-14); } @Test @@ -81,10 +81,10 @@ public class JavaIsotonicRegressionSuite implements Serializable { JavaDoubleRDD testRDD = sc.parallelizeDoubles(Arrays.asList(0.0, 1.0, 9.5, 12.0, 13.0)); List<Double> predictions = model.predict(testRDD).collect(); - Assert.assertTrue(predictions.get(0) == 1d); - Assert.assertTrue(predictions.get(1) == 1d); - Assert.assertTrue(predictions.get(2) == 10d); - Assert.assertTrue(predictions.get(3) == 12d); - Assert.assertTrue(predictions.get(4) == 12d); + Assert.assertEquals(1.0, predictions.get(0).doubleValue(), 1.0e-14); + Assert.assertEquals(1.0, predictions.get(1).doubleValue(), 1.0e-14); + Assert.assertEquals(10.0, predictions.get(2).doubleValue(), 1.0e-14); + Assert.assertEquals(12.0, predictions.get(3).doubleValue(), 1.0e-14); + Assert.assertEquals(12.0, predictions.get(4).doubleValue(), 1.0e-14); } } |