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Revert "Incorrectly merged AFTAggregator with zero total count" for branch-1.6 #13630

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Revert "Incorrectly merged AFTAggregator with zero total count" for branch-1.6 #13630

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5555022
Change spark to sqlContext for 1.6
HyukjinKwon Jun 13, 2016
4e344cb
Revert "SPARK-15892: Incorrectly merged AFTAggregator with zero total…
HyukjinKwon Jun 14, 2016
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2 changes: 1 addition & 1 deletion mllib/src/main/scala/org/apache/spark/ml/regression/AFTSurvivalRegression.scala
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Expand Up @@ -496,7 +496,7 @@ private class AFTAggregator(parameters: BDV[Double], fitIntercept: Boolean)
* @return This AFTAggregator object.
*/
def merge(other: AFTAggregator): this.type = {
if (other.count != 0) {
if (totalCnt != 0) {
totalCnt += other.totalCnt
lossSum += other.lossSum

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12 changes: 0 additions & 12 deletions mllib/src/test/scala/org/apache/spark/ml/regression/AFTSurvivalRegressionSuite.scala
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Expand Up @@ -346,18 +346,6 @@ class AFTSurvivalRegressionSuite
testEstimatorAndModelReadWrite(aft, datasetMultivariate,
AFTSurvivalRegressionSuite.allParamSettings, checkModelData)
}

test("SPARK-15892: Incorrectly merged AFTAggregator with zero total count") {
// This `dataset` will contain an empty partition because it has two rows but
// the parallelism is bigger than that. Because the issue was about `AFTAggregator`s
// being merged incorrectly when it has an empty partition, running the codes below
// should not throw an exception.
val dataset = spark.createDataFrame(
sc.parallelize(generateAFTInput(
1, Array(5.5), Array(0.8), 2, 42, 1.0, 2.0, 2.0), numSlices = 3))
val trainer = new AFTSurvivalRegression()
trainer.fit(dataset)
}
}

object AFTSurvivalRegressionSuite {
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