holdenk commented on a change in pull request #24070: [SPARK-23961][PYTHON] Fix
error when toLocalIterator goes out of scope
URL: https://github.com/apache/spark/pull/24070#discussion_r270946373
##########
File path: core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala
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@@ -168,7 +168,32 @@ private[spark] object PythonRDD extends Logging {
}
def toLocalIteratorAndServe[T](rdd: RDD[T]): Array[Any] = {
- serveIterator(rdd.toLocalIterator, s"serve toLocalIterator")
+ val (port, secret) = SocketAuthServer.setupOneConnectionServer(
+ authHelper, "serve toLocalIterator") { s =>
+ val out = new DataOutputStream(s.getOutputStream)
+ val in = new DataInputStream(s.getInputStream)
+ Utils.tryWithSafeFinally {
+
+ // Collects a partition on each iteration
+ val collectPartitionIter = rdd.partitions.indices.iterator.map { i =>
+ rdd.sparkContext.runJob(rdd, (iter: Iterator[Any]) => iter.toArray,
Seq(i)).head
Review comment:
For performance, as mentioned in my questions, would it make sense to use
something like a iterator with look ahead of say 1 partition (or X% of
partitions) so we decrease the blocking time.
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