From b6c435f5d55132d665afd23c84b2949eec5480fa Mon Sep 17 00:00:00 2001 From: Yanbo Liang Date: Fri, 18 Mar 2016 11:23:17 +0000 Subject: [PATCH] [MINOR][ML] When trainingSummary is None, it should throw RuntimeException. ## What changes were proposed in this pull request? When trainingSummary is None, it should throw ```RuntimeException```. cc mengxr ## How was this patch tested? Existing tests. Author: Yanbo Liang Closes #11784 from yanboliang/fix-summary. --- .../spark/ml/classification/LogisticRegression.scala | 8 ++------ .../scala/org/apache/spark/ml/clustering/KMeans.scala | 9 +++------ .../ml/regression/GeneralizedLinearRegression.scala | 3 +-- .../apache/spark/ml/regression/LinearRegression.scala | 8 ++------ 4 files changed, 8 insertions(+), 20 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 77e59d9188ef4..861b1d4b66f23 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 @@ -509,12 +509,8 @@ class LogisticRegressionModel private[spark] ( * thrown if `trainingSummary == None`. */ @Since("1.5.0") - def summary: LogisticRegressionTrainingSummary = trainingSummary match { - case Some(summ) => summ - case None => - throw new SparkException( - "No training summary available for this LogisticRegressionModel", - new NullPointerException()) + def summary: LogisticRegressionTrainingSummary = trainingSummary.getOrElse { + throw new SparkException("No training summary available for this LogisticRegressionModel") } /** 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 ab00127899edf..38428826a8a7d 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 @@ -148,12 +148,9 @@ class KMeansModel private[ml] ( * thrown if `trainingSummary == None`. */ @Since("2.0.0") - def summary: KMeansSummary = trainingSummary match { - case Some(summ) => summ - case None => - throw new SparkException( - s"No training summary available for the ${this.getClass.getSimpleName}", - new NullPointerException()) + def summary: KMeansSummary = trainingSummary.getOrElse { + throw new SparkException( + s"No training summary available for the ${this.getClass.getSimpleName}") } } diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala index 6e74cb54ad682..0e71e8d8e1339 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala @@ -681,8 +681,7 @@ class GeneralizedLinearRegressionModel private[ml] ( @Since("2.0.0") def summary: GeneralizedLinearRegressionSummary = trainingSummary.getOrElse { throw new SparkException( - "No training summary available for this GeneralizedLinearRegressionModel", - new RuntimeException()) + "No training summary available for this GeneralizedLinearRegressionModel") } private[regression] def setSummary(summary: GeneralizedLinearRegressionSummary): this.type = { 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 c8f3f70a9b446..b81c588e44fcc 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 @@ -398,12 +398,8 @@ class LinearRegressionModel private[ml] ( * thrown if `trainingSummary == None`. */ @Since("1.5.0") - def summary: LinearRegressionTrainingSummary = trainingSummary match { - case Some(summ) => summ - case None => - throw new SparkException( - "No training summary available for this LinearRegressionModel", - new NullPointerException()) + def summary: LinearRegressionTrainingSummary = trainingSummary.getOrElse { + throw new SparkException("No training summary available for this LinearRegressionModel") } private[regression] def setSummary(summary: LinearRegressionTrainingSummary): this.type = {