Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/10451#discussion_r48579121
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala
---
@@ -69,6 +73,33 @@ object DefaultOptimizer extends Optimizer {
}
/**
+ * Pushes down Limit for reducing the amount of returned data.
+ *
+ * 1. Adding Extra Limit beneath the operations, including Union All.
+ * 2. Project is pushed through Limit in the rule ColumnPruning
+ *
+ * Any operator that a Limit can be pushed passed should override the
maxRows function.
+ *
+ * Note: This rule has to be done when the logical plan is stable;
+ * Otherwise, it could impact the other rules.
--- End diff --
For example, if we push `Limit` through `Filter`, `Aggregate` and
`Distinct`, the results will be wrong. For example, `df.aggregate().limit(1)`
and `df.limit(1).aggregate()`will generate the different results.
This is true iff we can push `Limit` through some operators. So far, we did
not find any eligible operators except ` outer/left-outer/right-outer Join` and
`Union`. Thus, let me revert them back. Thanks!
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