Github user tdas commented on a diff in the pull request:
https://github.com/apache/spark/pull/9373#discussion_r44608862
--- Diff:
streaming/src/main/scala/org/apache/spark/streaming/util/FileBasedWriteAheadLog.scala
---
@@ -251,4 +261,23 @@ private[streaming] object FileBasedWriteAheadLog {
}
}.sortBy { _.startTime }
}
+
+ /**
+ * This creates an iterator from a parallel collection, by keeping at
most `n` objects in memory
+ * at any given time, where `n` is the size of the thread pool. This is
crucial for use cases
+ * where we create `FileBasedWriteAheadLogReader`s during parallel
recovery. We don't want to
+ * open up `k` streams altogether where `k` is the size of the Seq that
we want to parallelize.
+ */
+ def seqToParIterator[I, O](
+ tpool: ThreadPoolExecutor,
+ source: Seq[I],
+ handler: I => Iterator[O]): Iterator[O] = {
+ val taskSupport = new ThreadPoolTaskSupport(tpool)
+ val groupSize = math.max(math.max(tpool.getCorePoolSize,
tpool.getPoolSize), 8)
--- End diff --
Its not safe for the rest of the system to allow infinite number of thread.
I think there should be limits. The limit can be a sparkconf that will not be
exposed publicly.
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