Dandandan commented on code in PR #3530:
URL: https://github.com/apache/arrow-datafusion/pull/3530#discussion_r974441046
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datafusion/core/src/physical_optimizer/parallel_sort.rs:
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@@ -55,31 +54,33 @@ impl PhysicalOptimizerRule for ParallelSort {
.map(|child| self.optimize(child.clone(), config))
.collect::<Result<Vec<_>>>()?;
let plan = with_new_children_if_necessary(plan, children)?;
- let children = plan.children();
let plan_any = plan.as_any();
- // GlobalLimitExec (SortExec preserve_partitioning=False)
- // -> GlobalLimitExec (SortExec preserve_partitioning=True)
- let parallel_sort =
plan_any.downcast_ref::<GlobalLimitExec>().is_some()
- && children.len() == 1
- && children[0].as_any().downcast_ref::<SortExec>().is_some()
- && !children[0]
- .as_any()
+ // SortExec preserve_partitioning=False, fetch=Some(n))
+ // -> SortPreservingMergeExec (SortExec
preserve_partitioning=True, fetch=Some(n))
+ let parallel_sort = plan_any.downcast_ref::<SortExec>().is_some()
Review Comment:
As we now have the pushdown - we can use `fetch`, and support more than just
a limit directly after sort.
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