Github user andrewor14 commented on a diff in the pull request:
https://github.com/apache/spark/pull/9428#discussion_r44321308
--- Diff: core/src/main/scala/org/apache/spark/rdd/RDD.scala ---
@@ -258,11 +258,14 @@ abstract class RDD[T: ClassTag](
* subclasses of RDD.
*/
final def iterator(split: Partition, context: TaskContext): Iterator[T]
= {
- if (storageLevel != StorageLevel.NONE) {
+ val iter = if (storageLevel != StorageLevel.NONE) {
SparkEnv.get.cacheManager.getOrCompute(this, split, context,
storageLevel)
} else {
computeOrReadCheckpoint(split, context)
}
+ checkpointData.collect { case data: ReliableRDDCheckpointData[T] =>
+ data.getCheckpointIterator(this, iter, context, split.index)
--- End diff --
if you make `getCheckpointIterator` a method in the abstract
`RDDCheckpointData` then you can just do
```
checkpointData
.map(_.getCheckpointIterator(this, iter, context, split.index))
.getOrElse(iter)
```
We can address local checkpointing separately and for now just have it
return the iterator
```
def getCheckpointIterator(...): Iterator[T] = iter
```
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