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author | Josh Rosen <joshrosen@databricks.com> | 2015-12-05 08:15:30 +0800 |
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committer | Reynold Xin <rxin@databricks.com> | 2015-12-05 08:15:30 +0800 |
commit | b7204e1d41271d2e8443484371770936664350b1 (patch) | |
tree | 3b09d003dce3b482282e3ae21b893fe57e607128 /mllib/src | |
parent | d64806b37373c5cc4fd158a9f5005743bd00bf28 (diff) | |
download | spark-b7204e1d41271d2e8443484371770936664350b1.tar.gz spark-b7204e1d41271d2e8443484371770936664350b1.tar.bz2 spark-b7204e1d41271d2e8443484371770936664350b1.zip |
[SPARK-12112][BUILD] Upgrade to SBT 0.13.9
We should upgrade to SBT 0.13.9, since this is a requirement in order to use SBT's new Maven-style resolution features (which will be done in a separate patch, because it's blocked by some binary compatibility issues in the POM reader plugin).
I also upgraded Scalastyle to version 0.8.0, which was necessary in order to fix a Scala 2.10.5 compatibility issue (see https://github.com/scalastyle/scalastyle/issues/156). The newer Scalastyle is slightly stricter about whitespace surrounding tokens, so I fixed the new style violations.
Author: Josh Rosen <joshrosen@databricks.com>
Closes #10112 from JoshRosen/upgrade-to-sbt-0.13.9.
Diffstat (limited to 'mllib/src')
5 files changed, 16 insertions, 14 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/ml/param/params.scala b/mllib/src/main/scala/org/apache/spark/ml/param/params.scala index d182b0a988..ee7e89edd8 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/param/params.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/param/params.scala @@ -82,7 +82,9 @@ class Param[T](val parent: String, val name: String, val doc: String, val isVali def w(value: T): ParamPair[T] = this -> value /** Creates a param pair with the given value (for Scala). */ + // scalastyle:off def ->(value: T): ParamPair[T] = ParamPair(this, value) + // scalastyle:on /** Encodes a param value into JSON, which can be decoded by [[jsonDecode()]]. */ def jsonEncode(value: T): String = { diff --git a/mllib/src/main/scala/org/apache/spark/mllib/stat/test/StreamingTestMethod.scala b/mllib/src/main/scala/org/apache/spark/mllib/stat/test/StreamingTestMethod.scala index a7eaed51b4..911b4b9237 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/stat/test/StreamingTestMethod.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/stat/test/StreamingTestMethod.scala @@ -152,8 +152,8 @@ private[stat] object StudentTTest extends StreamingTestMethod with Logging { private[stat] object StreamingTestMethod { // Note: after new `StreamingTestMethod`s are implemented, please update this map. private final val TEST_NAME_TO_OBJECT: Map[String, StreamingTestMethod] = Map( - "welch"->WelchTTest, - "student"->StudentTTest) + "welch" -> WelchTTest, + "student" -> StudentTTest) def getTestMethodFromName(method: String): StreamingTestMethod = TEST_NAME_TO_OBJECT.get(method) match { diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/DecisionTreeClassifierSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/DecisionTreeClassifierSuite.scala index 92b8f84144..fda2711fed 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/classification/DecisionTreeClassifierSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/classification/DecisionTreeClassifierSuite.scala @@ -73,7 +73,7 @@ class DecisionTreeClassifierSuite extends SparkFunSuite with MLlibTestSparkConte .setMaxDepth(2) .setMaxBins(100) .setSeed(1) - val categoricalFeatures = Map(0 -> 3, 1-> 3) + val categoricalFeatures = Map(0 -> 3, 1 -> 3) val numClasses = 2 compareAPIs(categoricalDataPointsRDD, dt, categoricalFeatures, numClasses) } @@ -214,7 +214,7 @@ class DecisionTreeClassifierSuite extends SparkFunSuite with MLlibTestSparkConte .setMaxBins(2) .setMaxDepth(2) .setMinInstancesPerNode(2) - val categoricalFeatures = Map(0 -> 2, 1-> 2) + val categoricalFeatures = Map(0 -> 2, 1 -> 2) val numClasses = 2 compareAPIs(rdd, dt, categoricalFeatures, numClasses) } diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/DecisionTreeRegressorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/DecisionTreeRegressorSuite.scala index e0d5afa7a7..6999a910c3 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/regression/DecisionTreeRegressorSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/regression/DecisionTreeRegressorSuite.scala @@ -50,7 +50,7 @@ class DecisionTreeRegressorSuite extends SparkFunSuite with MLlibTestSparkContex .setMaxDepth(2) .setMaxBins(100) .setSeed(1) - val categoricalFeatures = Map(0 -> 3, 1-> 3) + val categoricalFeatures = Map(0 -> 3, 1 -> 3) compareAPIs(categoricalDataPointsRDD, dt, categoricalFeatures) } @@ -59,12 +59,12 @@ class DecisionTreeRegressorSuite extends SparkFunSuite with MLlibTestSparkContex .setImpurity("variance") .setMaxDepth(2) .setMaxBins(100) - val categoricalFeatures = Map(0 -> 2, 1-> 2) + val categoricalFeatures = Map(0 -> 2, 1 -> 2) compareAPIs(categoricalDataPointsRDD, dt, categoricalFeatures) } test("copied model must have the same parent") { - val categoricalFeatures = Map(0 -> 2, 1-> 2) + val categoricalFeatures = Map(0 -> 2, 1 -> 2) val df = TreeTests.setMetadata(categoricalDataPointsRDD, categoricalFeatures, numClasses = 0) val model = new DecisionTreeRegressor() .setImpurity("variance") diff --git a/mllib/src/test/scala/org/apache/spark/mllib/tree/DecisionTreeSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/tree/DecisionTreeSuite.scala index 1a4299db4e..bf8fe1acac 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/tree/DecisionTreeSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/tree/DecisionTreeSuite.scala @@ -64,7 +64,7 @@ class DecisionTreeSuite extends SparkFunSuite with MLlibTestSparkContext { maxDepth = 2, numClasses = 2, maxBins = 100, - categoricalFeaturesInfo = Map(0 -> 2, 1-> 2)) + categoricalFeaturesInfo = Map(0 -> 2, 1 -> 2)) val metadata = DecisionTreeMetadata.buildMetadata(rdd, strategy) val (splits, bins) = DecisionTree.findSplitsBins(rdd, metadata) @@ -178,7 +178,7 @@ class DecisionTreeSuite extends SparkFunSuite with MLlibTestSparkContext { maxDepth = 2, numClasses = 100, maxBins = 100, - categoricalFeaturesInfo = Map(0 -> 3, 1-> 3)) + categoricalFeaturesInfo = Map(0 -> 3, 1 -> 3)) val metadata = DecisionTreeMetadata.buildMetadata(rdd, strategy) assert(metadata.isUnordered(featureIndex = 0)) @@ -237,7 +237,7 @@ class DecisionTreeSuite extends SparkFunSuite with MLlibTestSparkContext { maxDepth = 2, numClasses = 100, maxBins = 100, - categoricalFeaturesInfo = Map(0 -> 10, 1-> 10)) + categoricalFeaturesInfo = Map(0 -> 10, 1 -> 10)) // 2^(10-1) - 1 > 100, so categorical features will be ordered val metadata = DecisionTreeMetadata.buildMetadata(rdd, strategy) @@ -421,7 +421,7 @@ class DecisionTreeSuite extends SparkFunSuite with MLlibTestSparkContext { numClasses = 2, maxDepth = 2, maxBins = 100, - categoricalFeaturesInfo = Map(0 -> 3, 1-> 3)) + categoricalFeaturesInfo = Map(0 -> 3, 1 -> 3)) val metadata = DecisionTreeMetadata.buildMetadata(rdd, strategy) assert(!metadata.isUnordered(featureIndex = 0)) @@ -455,7 +455,7 @@ class DecisionTreeSuite extends SparkFunSuite with MLlibTestSparkContext { Variance, maxDepth = 2, maxBins = 100, - categoricalFeaturesInfo = Map(0 -> 3, 1-> 3)) + categoricalFeaturesInfo = Map(0 -> 3, 1 -> 3)) val metadata = DecisionTreeMetadata.buildMetadata(rdd, strategy) assert(!metadata.isUnordered(featureIndex = 0)) @@ -484,7 +484,7 @@ class DecisionTreeSuite extends SparkFunSuite with MLlibTestSparkContext { Variance, maxDepth = 2, maxBins = 100, - categoricalFeaturesInfo = Map(0 -> 2, 1-> 2)) + categoricalFeaturesInfo = Map(0 -> 2, 1 -> 2)) val metadata = DecisionTreeMetadata.buildMetadata(rdd, strategy) assert(!metadata.isUnordered(featureIndex = 0)) assert(!metadata.isUnordered(featureIndex = 1)) @@ -788,7 +788,7 @@ class DecisionTreeSuite extends SparkFunSuite with MLlibTestSparkContext { val rdd = sc.parallelize(arr) val strategy = new Strategy(algo = Classification, impurity = Gini, - maxBins = 2, maxDepth = 2, categoricalFeaturesInfo = Map(0 -> 2, 1-> 2), + maxBins = 2, maxDepth = 2, categoricalFeaturesInfo = Map(0 -> 2, 1 -> 2), numClasses = 2, minInstancesPerNode = 2) val rootNode = DecisionTree.train(rdd, strategy).topNode |