Address comment.

Author: viirya

sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaPruning.scala

@@ -40,19 +40,11 @@ private[sql] object ParquetSchemaPruning extends Rule[LogicalPlan] {
       plan
     }
 
-  // `PhysicalOperation` pattern returns relation operator's outputs if there is no
-  // projects on it. In this case, we don't need to do schema pruning.
-  private def directOutput(projects: Seq[NamedExpression], plan: LogicalPlan): Boolean = {
-    projects.length == plan.output.length && projects.zip(plan.output).forall {
-      case (l, r) => l.name == r.name && l.dataType.sameType(r.dataType)
-    }
-  }
-
   private def apply0(plan: LogicalPlan): LogicalPlan =
     plan transformDown {
       case op @ PhysicalOperation(projects, filters,
           l @ LogicalRelation(hadoopFsRelation: HadoopFsRelation, _, _, _))
-        if canPruneRelation(hadoopFsRelation) && !directOutput(projects, l) =>
+        if canPruneRelation(hadoopFsRelation) =>
         val (normalizedProjects, normalizedFilters) =
           normalizeAttributeRefNames(l, projects, filters)
         val requestedRootFields = identifyRootFields(normalizedProjects, normalizedFilters)