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https://issues.apache.org/jira/browse/SPARK-29815?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Aman Omer updated SPARK-29815:
------------------------------
Parent: SPARK-29818
Issue Type: Sub-task (was: Improvement)
> Missing persist in ml.tuning.CrossValidator.fit()
> -------------------------------------------------
>
> Key: SPARK-29815
> URL: https://issues.apache.org/jira/browse/SPARK-29815
> Project: Spark
> Issue Type: Sub-task
> Components: ML
> Affects Versions: 2.4.3
> Reporter: Dong Wang
> Priority: Major
>
> dataset.toDF.rdd in ml.tuning.CrossValidator.fit(dataset: Dataset[_]) will
> generate two rdds: training and validation. Some actions will be operated on
> these two rdds, but dataset.toDF.rdd is not persisted, which will cause
> recomputation.
> {code:scala}
> // Compute metrics for each model over each split
> val splits = MLUtils.kFold(dataset.toDF.rdd, $(numFolds), $(seed)) //
> dataset.toDF.rdd should be persisted
> val metrics = splits.zipWithIndex.map { case ((training, validation),
> splitIndex) =>
> val trainingDataset = sparkSession.createDataFrame(training,
> schema).cache()
> val validationDataset = sparkSession.createDataFrame(validation,
> schema).cache()
> {scala}
> This issue is reported by our tool CacheCheck, which is used to dynamically
> detecting persist()/unpersist() api misuses.
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