Github user wzhfy commented on a diff in the pull request:
https://github.com/apache/spark/pull/15363#discussion_r105856838
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/CostBasedJoinReorder.scala
---
@@ -51,6 +51,11 @@ case class CostBasedJoinReorder(conf: CatalystConf)
extends Rule[LogicalPlan] wi
def reorder(plan: LogicalPlan, output: AttributeSet): LogicalPlan = {
val (items, conditions) = extractInnerJoins(plan)
+ // Find the star schema joins. Currently, it returns the star join
with the largest
+ // fact table. In the future, it can return more than one star join
(e.g. F1-D1-D2
+ // and F2-D3-D4).
+ val starJoinPlans = StarSchemaDetection(conf).findStarJoins(items,
conditions.toSeq)
--- End diff --
The method splitting is good, let's remove this `val starJoinPlans` since
it's not used.
In fact I think we could first do something like this in
`CostBasedJoinReorder`:
```
if (conf.cboEnabled && conf.joinReorderEnabled) {
do join reordering
} else if (conf.starSchemaJoinReorder) {
use star schema
} else {
plan
}
```
But since the current algorithm is in the `Operator Optimizations` batch,
the tree structure is different from that in `CostBasedJoinReorder`, will
moving into `CostBasedJoinReorder` break some logic in the algorithm?
Other than that I'm fine with the current structure.
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