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Posted to issues@spark.apache.org by "Dongjoon Hyun (Jira)" <ji...@apache.org> on 2020/03/16 22:51:06 UTC
[jira] [Updated] (SPARK-29832) Unnecessary persist on instances in
ml.regression.IsotonicRegression.fit
[ https://issues.apache.org/jira/browse/SPARK-29832?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Dongjoon Hyun updated SPARK-29832:
----------------------------------
Affects Version/s: (was: 3.0.0)
3.1.0
> Unnecessary persist on instances in ml.regression.IsotonicRegression.fit
> ------------------------------------------------------------------------
>
> Key: SPARK-29832
> URL: https://issues.apache.org/jira/browse/SPARK-29832
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 3.1.0
> Reporter: CacheCheck
> Priority: Major
>
> Persist on instances in ml.regression.IsotonicRegression.fit() is unnecessary, because it is only used once in run(instances).
> {code:scala}
> override def fit(dataset: Dataset[_]): IsotonicRegressionModel = instrumented { instr =>
> transformSchema(dataset.schema, logging = true)
> // Extract columns from data. If dataset is persisted, do not persist oldDataset.
> val instances = extractWeightedLabeledPoints(dataset)
> val handlePersistence = dataset.storageLevel == StorageLevel.NONE
> // Unnecessary persist
> if (handlePersistence) instances.persist(StorageLevel.MEMORY_AND_DISK)
> instr.logPipelineStage(this)
> instr.logDataset(dataset)
> instr.logParams(this, labelCol, featuresCol, weightCol, predictionCol, featureIndex, isotonic)
> instr.logNumFeatures(1)
> val isotonicRegression = new MLlibIsotonicRegression().setIsotonic($(isotonic))
> val oldModel = isotonicRegression.run(instances) // Only use once here
> if (handlePersistence) instances.unpersist()
> {code}
> This issue is reported by our tool CacheCheck, which is used to dynamically detecting persist()/unpersist() api misuses.
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