Github user mengxr commented on a diff in the pull request: https://github.com/apache/spark/pull/11919#discussion_r61764855 --- Diff: mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala --- @@ -1355,4 +1359,28 @@ object ALS extends DefaultParamsReadable[ALS] with Logging { * satisfies this requirement, we simply use a type alias here. */ private[recommendation] type ALSPartitioner = org.apache.spark.HashPartitioner + + /** + * Private function to clean up all of the shuffles files from the dependencies and their parents. + */ + private[spark] def cleanShuffleDependencies[T](sc: SparkContext, deps: Seq[Dependency[_]], + blocking: Boolean = false): Unit = { + // If there is no reference tracking we skip clean up. + sc.cleaner.foreach{ cleaner => + /** + * Clean the shuffles & all of its parents. + */ + def cleanEagerly(dep: Dependency[_]): Unit = { + if (dep.isInstanceOf[ShuffleDependency[_, _, _]]) { + val shuffleId = dep.asInstanceOf[ShuffleDependency[_, _, _]].shuffleId + cleaner.doCleanupShuffle(shuffleId, blocking) --- End diff -- I don't know the behavior when the shuffle files are deleted but we still need to recover the RDDs that depend on them. The safest approach would be cleaning up to the cache RDDs, but it is still valuable to figure out the current behavior.
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