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[SPARK-28699][Core] Cache an indeterminate RDD could lead to incorrect result while stage rerun #25420

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xuanyuanking wants to merge 2 commits into from
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[SPARK-28699][Core] Cache an indeterminate RDD could lead to incorrect result while stage rerun #25420

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99457d8
Rerun the indeterminate stage for cache operation
xuanyuanking Aug 12, 2019
b3ea90f
Abort indeterminate stage
xuanyuanking Aug 12, 2019
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Rerun the indeterminate stage for cache operation 
(cherry picked from commit b543fab)
Signed-off-by: Yuanjian Li <[email protected]>
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@xuanyuanking
xuanyuanking committed Aug 12, 2019
commit 99457d8dafeb8be7e1dfee02fb6d4598fc4b07d7
4 changes: 2 additions & 2 deletions sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/InMemoryRelation.scala
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Expand Up @@ -86,7 +86,7 @@ case class CachedRDDBuilder(

private def buildBuffers(): RDD[CachedBatch] = {
val output = cachedPlan.output
val cached = cachedPlan.execute().mapPartitionsInternal { rowIterator =>
val cached = cachedPlan.execute().mapPartitionsWithIndexInternal({ (_, rowIterator) =>
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@viirya viirya Aug 12, 2019

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I think we only run cached plan once. I think it should be determinate? If so, this map should not be order sensitive effectively?

new Iterator[CachedBatch] {
def next(): CachedBatch = {
val columnBuilders = output.map { attribute =>
Expand Down Expand Up @@ -131,7 +131,7 @@ case class CachedRDDBuilder(

def hasNext: Boolean = rowIterator.hasNext
}
}.persist(storageLevel)
}, isOrderSensitive = true).persist(storageLevel)
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@cloud-fan cloud-fan Aug 12, 2019

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I don't quite get it. The isOrderSensitive flag is used to describe the map function. Why the map function is order sensitive?


cached.setName(cachedName)
cached
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