[jira] [Created] (SPARK-29815) Missing persist in ml.tuning.CrossValidator.fit()

["Dong Wang (Jira)" <ji...@apache.org>]

Dong Wang created SPARK-29815:
---------------------------------

             Summary: Missing persist in ml.tuning.CrossValidator.fit()
                 Key: SPARK-29815
                 URL: https://issues.apache.org/jira/browse/SPARK-29815
             Project: Spark
          Issue Type: Improvement
          Components: ML
    Affects Versions: 2.4.3
            Reporter: Dong Wang


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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