Github user ioana-delaney commented on a diff in the pull request:
https://github.com/apache/spark/pull/17546#discussion_r111194456
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/CostBasedJoinReorder.scala
---
@@ -327,3 +349,109 @@ object JoinReorderDP extends PredicateHelper with
Logging {
case class Cost(card: BigInt, size: BigInt) {
def +(other: Cost): Cost = Cost(this.card + other.card, this.size +
other.size)
}
+
+/**
+ * Implements optional filters to reduce the search space for join
enumeration.
+ *
+ * 1) Star-join filters: Plan star-joins together since they are assumed
+ * to have an optimal execution based on their RI relationship.
+ * 2) Cartesian products: Defer their planning later in the graph to avoid
+ * large intermediate results (expanding joins, in general).
+ * 3) Composite inners: Don't generate "bushy tree" plans to avoid
materializing
+ * intermediate results.
--- End diff --
@cloud-fan Left-deep trees are executed in a pipelined fashion. Given the
following join trees:
```
left-deep tree:
join
/ \
join t3
/ \
t1 t2
bushy-tree:
join
/ \
t1 join
/ \
t2 t3
```
The bushy-tree plan (right-deep in this case) requires the result of (t2
join t3) to be materialized before joining with t1. The left-deep tree
doesnât have this requirement.
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