Github user junegunn commented on the issue:
https://github.com/apache/spark/pull/16347
@cloud-fan Unfortunately, yes.
```scala
sc.parallelize(1 to 10000000).toDS.withColumn("part", 'value.mod(2))
.repartition(1, 'part).sortWithinPartitions("value")
.write.mode("overwrite").format("orc").partitionBy("part")
.saveAsTable("test_sort_within")
```
For the above case, `requiredOrdering` is `part` and `actualOrdering` is
`value`, so SortExec runs anyway and the ordering within the partition is not
respected if spill occurs.
However, we now have a workaround; prepend partition columns to
`sortWithinPartitions` call or `SORT BY` clause, i.e.
`.sortWithinPartitions("part", "value")`, to bypass SortExec.
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