Github user markhamstra commented on a diff in the pull request:
https://github.com/apache/spark/pull/3794#discussion_r22336168
--- Diff: core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala ---
@@ -203,9 +204,27 @@ class HadoopRDD[K, V](
for (i <- 0 until inputSplits.size) {
array(i) = new HadoopPartition(id, i, inputSplits(i))
}
+ logDebug("Get these partitions took %f s".format((System.nanoTime -
start) / 1e9))
array
}
+ @transient private var thesePartitions_ : Array[Partition] = {
+ try {
+ getThesePartitions()
+ } catch {
+ case e: Exception =>
+ logDebug("Error initializing HadoopRDD's partitions", e)
+ null
--- End diff --
> It seems like the fix in this patch is to force partitions to be
eagerly-computed in the driver thread that defines the RDD. This seems like a
good idea
How would this interact with the idea of @erikerlandson to defer partition
computation?
https://github.com/apache/spark/pull/3079
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at infrastruct...@apache.org or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org
