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
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