Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/1083#discussion_r13779778
--- Diff: core/src/main/scala/org/apache/spark/CacheManager.scala ---
@@ -46,79 +46,27 @@ private[spark] class CacheManager(blockManager:
BlockManager) extends Logging {
new InterruptibleIterator(context,
values.asInstanceOf[Iterator[T]])
case None =>
- // Mark the split as loading (unless someone else marks it first)
- loading.synchronized {
- if (loading.contains(key)) {
- logInfo(s"Another thread is loading $key, waiting for it to
finish...")
- while (loading.contains(key)) {
- try {
- loading.wait()
- } catch {
- case e: Exception =>
- logWarning(s"Got an exception while waiting for another
thread to load $key", e)
- }
- }
- logInfo(s"Finished waiting for $key")
- /* See whether someone else has successfully loaded it. The
main way this would fail
- * is for the RDD-level cache eviction policy if someone else
has loaded the same RDD
- * partition but we didn't want to make space for it. However,
that case is unlikely
- * because it's unlikely that two threads would work on the
same RDD partition. One
- * downside of the current code is that threads wait serially
if this does happen. */
- blockManager.get(key) match {
- case Some(values) =>
- return new InterruptibleIterator(context,
values.asInstanceOf[Iterator[T]])
- case None =>
- logInfo(s"Whoever was loading $key failed; we'll try it
ourselves")
- loading.add(key)
- }
- } else {
- loading.add(key)
- }
+ // Acquire a lock for loading this partition
+ // If another thread already holds the lock, wait for it to finish
return its results
+ acquireLockForPartition(key).foreach { values =>
--- End diff --
Maybe better to avoid the foreach closure here because return within a
closure is implemented as a try-catch, and it is very error prone in the future
when we wrap this whole block with a try-catch that catches general Exception
... It has happened multiple times in Spark already, and those problems are
really hard to find/debug. Best to just avoid it.
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