[SPARK-8075][SQL] apply type check interface to more expressions

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala

@@ -585,8 +585,8 @@ class Analyzer(
           failAnalysis(
             s"""Expect multiple names given for ${g.getClass.getName},
                |but only single name '${name}' specified""".stripMargin)
-        case Alias(g: Generator, name) => Some((g, name :: Nil))
-        case MultiAlias(g: Generator, names) => Some(g, names)
+        case Alias(g: Generator, name) if g.resolved => Some((g, name :: Nil))
+        case MultiAlias(g: Generator, names) if g.resolved => Some(g, names)
         case _ => None
       }
     }

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala

@@ -317,6 +317,7 @@ trait HiveTypeCoercion {
         i.makeCopy(Array(Cast(a, StringType), b.map(Cast(_, StringType))))
 
       case Sum(e @ StringType()) => Sum(Cast(e, DoubleType))
+      case SumDistinct(e @ StringType()) => Sum(Cast(e, DoubleType))
       case Average(e @ StringType()) => Average(Cast(e, DoubleType))
     }
   }
@@ -590,11 +591,12 @@ trait HiveTypeCoercion {
       // Skip nodes who's children have not been resolved yet.
       case e if !e.childrenResolved => e
 
-      case a @ CreateArray(children) if !a.resolved =>
-        val commonType = a.childTypes.reduce(
-          (a, b) => findTightestCommonTypeOfTwo(a, b).getOrElse(StringType))
-        CreateArray(
-          children.map(c => if (c.dataType == commonType) c else Cast(c, commonType)))
+      case a @ CreateArray(children) if children.map(_.dataType).distinct.size > 1 =>
+        val types = children.map(_.dataType)
+        findTightestCommonTypeAndPromoteToString(types) match {
+          case Some(finalDataType) => CreateArray(children.map(Cast(_, finalDataType)))
+          case None => a
+        }
 
       // Promote SUM, SUM DISTINCT and AVERAGE to largest types to prevent overflows.
       case s @ Sum(e @ DecimalType()) => s // Decimal is already the biggest.
@@ -620,12 +622,11 @@ trait HiveTypeCoercion {
       // Coalesce should return the first non-null value, which could be any column
       // from the list. So we need to make sure the return type is deterministic and
       // compatible with every child column.
-      case Coalesce(es) if es.map(_.dataType).distinct.size > 1 =>
+      case c @ Coalesce(es) if es.map(_.dataType).distinct.size > 1 =>
         val types = es.map(_.dataType)
         findTightestCommonTypeAndPromoteToString(types) match {
           case Some(finalDataType) => Coalesce(es.map(Cast(_, finalDataType)))
-          case None =>
-            sys.error(s"Could not determine return type of Coalesce for ${types.mkString(",")}")
+          case None => c
         }
     }
   }

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Cast.scala

@@ -22,7 +22,7 @@ import java.sql.{Date, Timestamp}
 import java.text.{DateFormat, SimpleDateFormat}
 
 import org.apache.spark.Logging
-import org.apache.spark.sql.catalyst
+import org.apache.spark.sql.catalyst.analysis.TypeCheckResult
 import org.apache.spark.sql.catalyst.expressions.codegen.{CodeGenContext, GeneratedExpressionCode}
 import org.apache.spark.sql.catalyst.util.DateTimeUtils
 import org.apache.spark.sql.types._
@@ -31,7 +31,14 @@ import org.apache.spark.unsafe.types.UTF8String
 /** Cast the child expression to the target data type. */
 case class Cast(child: Expression, dataType: DataType) extends UnaryExpression with Logging {
 
-  override lazy val resolved = childrenResolved && resolve(child.dataType, dataType)
+  override def checkInputDataTypes(): TypeCheckResult = {
+    if (resolve(child.dataType, dataType)) {
+      TypeCheckResult.TypeCheckSuccess
+    } else {
+      TypeCheckResult.TypeCheckFailure(
+        s"cannot cast ${child.dataType} to $dataType")
+    }
+  }
 
   override def foldable: Boolean = child.foldable
 

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Expression.scala

@@ -162,9 +162,7 @@ abstract class Expression extends TreeNode[Expression] {
   /**
    * Checks the input data types, returns `TypeCheckResult.success` if it's valid,
    * or returns a `TypeCheckResult` with an error message if invalid.
-   * Note: it's not valid to call this method until `childrenResolved == true`
-   * TODO: we should remove the default implementation and implement it for all
-   * expressions with proper error message.
+   * Note: it's not valid to call this method until `childrenResolved == true`.
    */
   def checkInputDataTypes(): TypeCheckResult = TypeCheckResult.TypeCheckSuccess
 }

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ExtractValue.scala

@@ -96,6 +96,11 @@ object ExtractValue {
   }
 }
 
+/**
+ * A common interface of all kinds of extract value expressions.
+ * Note: concrete extract value expressions are created only by `ExtractValue.apply`,
+ * we don't need to do type check for them.
+ */
 trait ExtractValue extends UnaryExpression {
   self: Product =>
 }
@@ -179,9 +184,6 @@ case class GetArrayItem(child: Expression, ordinal: Expression)
 
   override def dataType: DataType = child.dataType.asInstanceOf[ArrayType].elementType
 
-  override lazy val resolved = childrenResolved &&
-    child.dataType.isInstanceOf[ArrayType] && ordinal.dataType.isInstanceOf[IntegralType]
-
   protected def evalNotNull(value: Any, ordinal: Any) = {
     // TODO: consider using Array[_] for ArrayType child to avoid
     // boxing of primitives
@@ -203,8 +205,6 @@ case class GetMapValue(child: Expression, ordinal: Expression)
 
   override def dataType: DataType = child.dataType.asInstanceOf[MapType].valueType
 
-  override lazy val resolved = childrenResolved && child.dataType.isInstanceOf[MapType]
-
   protected def evalNotNull(value: Any, ordinal: Any) = {
     val baseValue = value.asInstanceOf[Map[Any, _]]
     baseValue.get(ordinal).orNull