BryanCutler commented on a change in pull request #25515: [SPARK-27659][PYTHON]
Allow PySpark to prefetch during toLocalIterator
URL: https://github.com/apache/spark/pull/25515#discussion_r317755713
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File path: core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala
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@@ -196,10 +204,15 @@ private[spark] object PythonRDD extends Logging {
// Read request for data, value of zero will stop iteration or
non-zero to continue
if (in.readInt() == 0) {
complete = true
- } else if (collectPartitionIter.hasNext) {
+ } else if (prefetchIter.hasNext) {
// Client requested more data, attempt to collect the next
partition
- val partitionArray = collectPartitionIter.next()
+ val partitionFuture = prefetchIter.next()
+ // Cause the next job to be submitted if prefecthPartitions is
enabled.
+ if (prefetchPartitions) {
+ prefetchIter.headOption
+ }
+ val partitionArray = ThreadUtils.awaitResult(partitionFuture,
Duration.Inf)
Review comment:
Ah yes, you are totally right. That would block while getting the prefetched
partition. This looks pretty good to me then.
One question though, when should the first job be triggered? I think the old
behavior used to start the first job as soon as `toLocalIterator()` was called.
From what I can tell, this will wait until the first iteration and then trigger
the first 2 jobs. Either way is probably fine, but you might get slightly
better performance by starting the first job immediately.
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