Github user chhao01 commented on a diff in the pull request:
https://github.com/apache/spark/pull/1238#discussion_r14581617
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala ---
@@ -61,8 +61,6 @@ private[sql] abstract class SparkStrategies extends
QueryPlanner[SparkPlan] {
condition.map(Filter(_,
broadcastHashJoin)).getOrElse(broadcastHashJoin) :: Nil
}
- def broadcastTables: Seq[String] =
sqlContext.joinBroadcastTables.split(",").toBuffer
-
def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match {
--- End diff --
I agree. I'd like to add 2 more concerns :)
* zero maybe means the zero record of an input table, we probably need to
take some other default value, or like Hive does, to add an new option like
"set hive.auto.convert.join=false;"
* size estimates interface is very helpful for cost based join optimization
(join reordering), besides the BroadcastNestedLoopJoin, we can also use that
for equi-inner-join(we always prefer the bigger table as streaming table and
the smaller one as build table). just make sure you didn't misunderstanding
what I suggested in the top comment of this thread.
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