[SPARK-25036][SQL] avoid match may not be exhaustive in Scala-2.12

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ScalaReflection.scala

@@ -709,7 +709,8 @@ object ScalaReflection extends ScalaReflection {
   def attributesFor[T: TypeTag]: Seq[Attribute] = schemaFor[T] match {
     case Schema(s: StructType, _) =>
       s.toAttributes
-    case _ => throw new RuntimeException(s"$schemaFor is not supported at attributesFor()")
+    case others =>
+      throw new UnsupportedOperationException(s"Attributes for type $others is not supported")
   }
 
   /** Returns a catalyst DataType and its nullability for the given Scala Type using reflection. */

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/ApproxCountDistinctForIntervals.scala

@@ -63,12 +63,11 @@ case class ApproxCountDistinctForIntervals(
   }
 
   // Mark as lazy so that endpointsExpression is not evaluated during tree transformation.
-  lazy val endpoints: Array[Double] =
-    (endpointsExpression.dataType, endpointsExpression.eval()) match {
-      case (ArrayType(elementType, _), arrayData: ArrayData) =>
-        arrayData.toObjectArray(elementType).map(_.toString.toDouble)
-      case _ => throw new RuntimeException("not found at endpoints")
-    }
+  lazy val endpoints: Array[Double] = {
+    val endpointsType = endpointsExpression.dataType.asInstanceOf[ArrayType]
+    val endpoints = endpointsExpression.eval().asInstanceOf[ArrayData]
+    endpoints.toObjectArray(endpointsType.elementType).map(_.toString.toDouble)
+  }
 
   override def checkInputDataTypes(): TypeCheckResult = {
     val defaultCheck = super.checkInputDataTypes()

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala

@@ -471,7 +471,8 @@ class CodegenContext {
       case NewFunctionSpec(functionName, None, None) => functionName
       case NewFunctionSpec(functionName, Some(_), Some(innerClassInstance)) =>
         innerClassInstance + "." + functionName
-      case _ => null // nothing to do since addNewFunctionInteral() must return one of them
+      case _ =>
+        throw new IllegalArgumentException(s"$funcName is not matched at addNewFunction")
     }
   }
 

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateUnsafeProjection.scala

@@ -87,7 +87,7 @@ object GenerateUnsafeProjection extends CodeGenerator[Seq[Expression], UnsafePro
       // For top level row writer, it always writes to the beginning of the global buffer holder,
       // which means its fixed-size region always in the same position, so we don't need to call
       // `reset` to set up its fixed-size region every time.
-      if (inputs.map(_.isNull).forall(_ == "false")) {
+      if (inputs.map(_.isNull).forall(_ == FalseLiteral)) {
         // If all fields are not nullable, which means the null bits never changes, then we don't
         // need to clear it out every time.
         ""

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

@@ -69,7 +69,8 @@ object ValueInterval {
       false
     case (n1: NumericValueInterval, n2: NumericValueInterval) =>
       n1.min.compareTo(n2.max) <= 0 && n1.max.compareTo(n2.min) >= 0
-    case _ => throw new RuntimeException(s"Not supported pair: $r1, $r2 at isIntersected()")
+    case _ =>
+      throw new UnsupportedOperationException(s"Not supported pair: $r1, $r2 at isIntersected()")
   }
 
   /**
@@ -87,7 +88,8 @@ object ValueInterval {
         val newMax = if (n1.max <= n2.max) n1.max else n2.max
         (Some(EstimationUtils.fromDouble(newMin, dt)),
           Some(EstimationUtils.fromDouble(newMax, dt)))
-      case _ => throw new RuntimeException(s"Not supported pair: $r1, $r2 at intersect()")
+      case _ =>
+        throw new UnsupportedOperationException(s"Not supported pair: $r1, $r2 at intersect()")
     }
   }
 }