From b4856147e04c3d57f2bfc70c70e3f136f46fa873 Mon Sep 17 00:00:00 2001 From: Zheng RuiFeng Date: Tue, 12 Sep 2017 12:53:35 +0800 Subject: [PATCH] recreate pr --- .../apache/spark/ml/classification/LogisticRegression.scala | 2 +- .../scala/org/apache/spark/ml/classification/OneVsRest.scala | 4 ++-- .../main/scala/org/apache/spark/ml/clustering/KMeans.scala | 2 +- .../apache/spark/ml/regression/AFTSurvivalRegression.scala | 2 +- .../org/apache/spark/ml/regression/IsotonicRegression.scala | 2 +- .../org/apache/spark/ml/regression/LinearRegression.scala | 2 +- 6 files changed, 7 insertions(+), 7 deletions(-) diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala index f491a679b242..cbc8f4a2d8c2 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala @@ -484,7 +484,7 @@ class LogisticRegression @Since("1.2.0") ( } override protected[spark] def train(dataset: Dataset[_]): LogisticRegressionModel = { - val handlePersistence = dataset.rdd.getStorageLevel == StorageLevel.NONE + val handlePersistence = dataset.storageLevel == StorageLevel.NONE train(dataset, handlePersistence) } diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala index 05b8c3ab5456..f3aff4c44e70 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala @@ -164,7 +164,7 @@ final class OneVsRestModel private[ml] ( val newDataset = dataset.withColumn(accColName, initUDF()) // persist if underlying dataset is not persistent. - val handlePersistence = dataset.rdd.getStorageLevel == StorageLevel.NONE + val handlePersistence = dataset.storageLevel == StorageLevel.NONE if (handlePersistence) { newDataset.persist(StorageLevel.MEMORY_AND_DISK) } @@ -347,7 +347,7 @@ final class OneVsRest @Since("1.4.0") ( } // persist if underlying dataset is not persistent. - val handlePersistence = dataset.rdd.getStorageLevel == StorageLevel.NONE + val handlePersistence = dataset.storageLevel == StorageLevel.NONE if (handlePersistence) { multiclassLabeled.persist(StorageLevel.MEMORY_AND_DISK) } diff --git a/mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala b/mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala index e02b532ca8a9..f2af7fe082b4 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala @@ -304,7 +304,7 @@ class KMeans @Since("1.5.0") ( override def fit(dataset: Dataset[_]): KMeansModel = { transformSchema(dataset.schema, logging = true) - val handlePersistence = dataset.rdd.getStorageLevel == StorageLevel.NONE + val handlePersistence = dataset.storageLevel == StorageLevel.NONE val instances: RDD[OldVector] = dataset.select(col($(featuresCol))).rdd.map { case Row(point: Vector) => OldVectors.fromML(point) } diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/AFTSurvivalRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/AFTSurvivalRegression.scala index 16821f317760..4b46c3831d75 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/regression/AFTSurvivalRegression.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/regression/AFTSurvivalRegression.scala @@ -213,7 +213,7 @@ class AFTSurvivalRegression @Since("1.6.0") (@Since("1.6.0") override val uid: S override def fit(dataset: Dataset[_]): AFTSurvivalRegressionModel = { transformSchema(dataset.schema, logging = true) val instances = extractAFTPoints(dataset) - val handlePersistence = dataset.rdd.getStorageLevel == StorageLevel.NONE + val handlePersistence = dataset.storageLevel == StorageLevel.NONE if (handlePersistence) instances.persist(StorageLevel.MEMORY_AND_DISK) val featuresSummarizer = { diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/IsotonicRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/IsotonicRegression.scala index 529f66eadbcf..8faab52ea474 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/regression/IsotonicRegression.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/regression/IsotonicRegression.scala @@ -165,7 +165,7 @@ class IsotonicRegression @Since("1.5.0") (@Since("1.5.0") override val uid: Stri transformSchema(dataset.schema, logging = true) // Extract columns from data. If dataset is persisted, do not persist oldDataset. val instances = extractWeightedLabeledPoints(dataset) - val handlePersistence = dataset.rdd.getStorageLevel == StorageLevel.NONE + val handlePersistence = dataset.storageLevel == StorageLevel.NONE if (handlePersistence) instances.persist(StorageLevel.MEMORY_AND_DISK) val instr = Instrumentation.create(this, dataset) diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala index ed431f550817..b2a968118d1a 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala @@ -251,7 +251,7 @@ class LinearRegression @Since("1.3.0") (@Since("1.3.0") override val uid: String return lrModel } - val handlePersistence = dataset.rdd.getStorageLevel == StorageLevel.NONE + val handlePersistence = dataset.storageLevel == StorageLevel.NONE if (handlePersistence) instances.persist(StorageLevel.MEMORY_AND_DISK) val (featuresSummarizer, ySummarizer) = {