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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