[SPARK-12441][SQL] Fixing missingInput in Generate/MapPartitions/AppendColumns/MapGroups/CoGroup

When explain any plan with Generate, we will see an exclamation mark in the plan. Normally, when we see this mark, it means the plan has an error. This PR is to correct the `missingInput` in `Generate`.

For example,
```scala
val df = Seq((1, "a b c"), (2, "a b"), (3, "a")).toDF("number", "letters")
val df2 =
  df.explode('letters) {
    case Row(letters: String) => letters.split(" ").map(Tuple1(_)).toSeq
  }

df2.explain(true)
```
Before the fix, the plan is like
```
== Parsed Logical Plan ==
'Generate UserDefinedGenerator('letters), true, false, None
+- Project [_1#0 AS number#2,_2#1 AS letters#3]
   +- LocalRelation [_1#0,_2#1], [[1,a b c],[2,a b],[3,a]]

== Analyzed Logical Plan ==
number: int, letters: string, _1: string
Generate UserDefinedGenerator(letters#3), true, false, None, [_1#8]
+- Project [_1#0 AS number#2,_2#1 AS letters#3]
   +- LocalRelation [_1#0,_2#1], [[1,a b c],[2,a b],[3,a]]

== Optimized Logical Plan ==
Generate UserDefinedGenerator(letters#3), true, false, None, [_1#8]
+- LocalRelation [number#2,letters#3], [[1,a b c],[2,a b],[3,a]]

== Physical Plan ==
!Generate UserDefinedGenerator(letters#3), true, false, [number#2,letters#3,_1#8]
+- LocalTableScan [number#2,letters#3], [[1,a b c],[2,a b],[3,a]]
```

**Updates**: The same issues are also found in the other four Dataset operators: `MapPartitions`/`AppendColumns`/`MapGroups`/`CoGroup`. Fixed all these four.

Author: gatorsmile <gatorsmile@gmail.com>
Author: xiaoli <lixiao1983@gmail.com>
Author: Xiao Li <xiaoli@Xiaos-MacBook-Pro.local>

Closes #10393 from gatorsmile/generateExplain.

2 files changed, 5 insertions, 0 deletions

diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScan.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScan.scala
index 806d2b9b0b..8141136de5 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScan.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScan.scala
@@ -51,6 +51,9 @@ case class HiveTableScan(
   require(partitionPruningPred.isEmpty || relation.hiveQlTable.isPartitioned,
     "Partition pruning predicates only supported for partitioned tables.")
 
+  override def producedAttributes: AttributeSet = outputSet ++
+    AttributeSet(partitionPruningPred.flatMap(_.references))
+
   // Retrieve the original attributes based on expression ID so that capitalization matches.
   val attributes = requestedAttributes.map(relation.attributeMap)
 
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/ScriptTransformation.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/ScriptTransformation.scala
index d9b9ba4bfd..a61e162f48 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/ScriptTransformation.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/ScriptTransformation.scala
@@ -60,6 +60,8 @@ case class ScriptTransformation(
 
   override protected def otherCopyArgs: Seq[HiveContext] = sc :: Nil
 
+  override def producedAttributes: AttributeSet = outputSet -- inputSet
+
   private val serializedHiveConf = new SerializableConfiguration(sc.hiveconf)
 
   protected override def doExecute(): RDD[InternalRow] = {