jerrypeng commented on code in PR #59523:
URL: https://github.com/apache/spark/pull/59523#discussion_r4429427544


##########
core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala:
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@@ -1520,13 +1519,39 @@ private[spark] class DAGScheduler(
     checkPipelinedStageCreation(finalRDD, partitions, jobId)
   }
 
+  /** Reject persistence that could bypass a native pipelined shuffle reader. 
*/
+  private def checkPipelinedCacheSupported(finalRDD: RDD[_]): Unit = {
+    val persisted = new HashSet[RDD[_]]
+    traverseRDDGraph(finalRDD) { (rdd, enqueue) =>
+      if (rdd.getStorageLevel != StorageLevel.NONE || 
rdd.isLocallyCheckpointed) {
+        persisted += rdd
+      }
+      rdd.dependencies.foreach {
+        case pd: PipelinedShuffleDependency[_, _, _] => enqueue(pd.rdd)
+        case _: ShuffleDependency[_, _, _] =>
+          // Shape validation excludes pipelined readers below a regular 
boundary.
+        case dep => enqueue(dep.rdd)
+      }
+    }
+    // Cache locations cannot establish a stable cut: eviction can revive an 
upstream producer,
+    // and a partial cache hit skips a reader whose producer still needs its 
termination ACK.
+    // Check storage intent instead, including pending local checkpoints and 
narrow descendants.
+    val visited = new HashSet[RDD[_]]
+    persisted.find(rdd => rddChainReadsPipelinedShuffle(rdd, visited)).foreach 
{ rdd =>

Review Comment:
   Changed `persisted` to `ListBuffer`, since `traverseRDDGraph` already visits 
each RDD once. This preserves traversal order while retaining the shared 
visited set and short-circuiting `find`.
   
   The regression uses a cached consumer and cached descendant with swapped 
fixed hashes: it names the descendant first, then the consumer when the 
descendant is unpersisted and resubmitted. The regression fails with the old 
collector in both scheduler variants and passes with the fix.



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