ConeyLiu commented on code in PR #7714:
URL: https://github.com/apache/iceberg/pull/7714#discussion_r1284032956
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spark/v3.4/spark/src/main/java/org/apache/iceberg/spark/source/SparkPartitioningAwareScan.java:
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@@ -232,6 +232,16 @@ protected synchronized List<ScanTaskGroup<T>> taskGroups()
{
return taskGroups;
}
+ private long targetSplitSize() {
+ if (readConf().adaptiveSplitSizeEnabled()) {
+ long scanSize = tasks().stream().mapToLong(ScanTask::sizeBytes).sum();
+ int parallelism = sparkContext().defaultParallelism();
Review Comment:
> I feel we should use the current core count if dynamic allocation is
disabled (which we can check).
I agree with this. This should be easy to check and get the parallelism.
> When dynamic allocation is enabled, we can rely on the number of shuffle
partitions or check the dynamic allocation config (e.g. we know the core count
per each executor and the max number of executors). It seems the dynamic
allocation config would give us a more precise estimate.
From my option. I would be more likely to calculate the parallelism from the
max number of executors. Because the number of shuffle partitions seems more
like a parameter for the shuffle stage or reduce stage parallelism.
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