[SPARK-13383][SQL] Keep broadcast hint after column pruning

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala

@@ -332,6 +332,10 @@ case class Join(
  */
 case class BroadcastHint(child: LogicalPlan) extends UnaryNode {
   override def output: Seq[Attribute] = child.output
+
+  // We manually set statistics of BroadcastHint to smallest value to make sure
+  // the plan wrapped by BroadcastHint will be considered to broadcast later.
+  override def statistics: Statistics = Statistics(sizeInBytes = 1)
 }
 
 case class InsertIntoTable(

sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/JoinOrderSuite.scala → sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/JoinOptimizationSuite.scala

@@ -23,18 +23,18 @@ import org.apache.spark.sql.catalyst.dsl.expressions._
 import org.apache.spark.sql.catalyst.dsl.plans._
 import org.apache.spark.sql.catalyst.expressions.Expression
 import org.apache.spark.sql.catalyst.planning.ExtractFiltersAndInnerJoins
-import org.apache.spark.sql.catalyst.plans.PlanTest
-import org.apache.spark.sql.catalyst.plans.logical.{LocalRelation, LogicalPlan}
+import org.apache.spark.sql.catalyst.plans.{Inner, PlanTest}
+import org.apache.spark.sql.catalyst.plans.logical._
 import org.apache.spark.sql.catalyst.rules.RuleExecutor
 
 
-class JoinOrderSuite extends PlanTest {
+class JoinOptimizationSuite extends PlanTest {
 
   object Optimize extends RuleExecutor[LogicalPlan] {
     val batches =
       Batch("Subqueries", Once,
         EliminateSubqueryAliases) ::
-      Batch("Filter Pushdown", Once,
+      Batch("Filter Pushdown", FixedPoint(100),
         CombineFilters,
         PushPredicateThroughProject,
         BooleanSimplification,
@@ -92,4 +92,31 @@ class JoinOrderSuite extends PlanTest {
 
     comparePlans(optimized, analysis.EliminateSubqueryAliases(correctAnswer))
   }
+
+  test("broadcasthint sets relation statistics to smallest value") {
+    val input = LocalRelation('key.int, 'value.string)
+
+    val query =
+      Project(Seq($"x.key", $"y.key"),
+        Join(
+          SubqueryAlias("x", input),
+          BroadcastHint(SubqueryAlias("y", input)), Inner, None)).analyze
+
+    val optimized = Optimize.execute(query)
+
+    val expected =
+      Project(Seq($"x.key", $"y.key"),
+        Join(
+          Project(Seq($"x.key"), SubqueryAlias("x", input)),
+          BroadcastHint(
+            Project(Seq($"y.key"), SubqueryAlias("y", input))),
+          Inner, None)).analyze
+
+    comparePlans(optimized, expected)
+
+    val broadcastChildren = optimized.collect {
+      case Join(_, r, _, _) if r.statistics.sizeInBytes == 1 => r
+    }
+    assert(broadcastChildren.size == 1)
+  }
 }

sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala

@@ -81,11 +81,13 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] {
    * Matches a plan whose output should be small enough to be used in broadcast join.
    */
   object CanBroadcast {
-    def unapply(plan: LogicalPlan): Option[LogicalPlan] = plan match {
-      case BroadcastHint(p) => Some(p)
-      case p if sqlContext.conf.autoBroadcastJoinThreshold > 0 &&
-        p.statistics.sizeInBytes <= sqlContext.conf.autoBroadcastJoinThreshold => Some(p)
-      case _ => None
+    def unapply(plan: LogicalPlan): Option[LogicalPlan] = {
+      if (sqlContext.conf.autoBroadcastJoinThreshold > 0 &&
+          plan.statistics.sizeInBytes <= sqlContext.conf.autoBroadcastJoinThreshold) {
+        Some(plan)
+      } else {
+        None
+      }
     }
   }