[SPARK-23908][SQL][FOLLOW-UP] Rename inputs to arguments, and add argument type check.

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

@@ -90,6 +90,19 @@ trait CheckAnalysis extends PredicateHelper {
         u.failAnalysis(s"Table or view not found: ${u.tableIdentifier}")
 
       case operator: LogicalPlan =>
+        // Check argument data types of higher-order functions downwards first because function
+        // arguments of the higher-order functions might be unresolved due to the unresolved
+        // argument data types, otherwise always claims the function arguments are unresolved.
+        operator transformExpressionsDown {
+          case hof: HigherOrderFunction
+              if hof.argumentsResolved && hof.checkArgumentDataTypes().isFailure =>
+            hof.checkArgumentDataTypes() match {
+              case TypeCheckResult.TypeCheckFailure(message) =>
+                hof.failAnalysis(
+                  s"cannot resolve '${hof.sql}' due to argument data type mismatch: $message")
+            }
+        }
+
         operator transformExpressionsUp {
           case a: Attribute if !a.resolved =>
             val from = operator.inputSet.map(_.qualifiedName).mkString(", ")

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

@@ -95,23 +95,23 @@ case class ResolveLambdaVariables(conf: SQLConf) extends Rule[LogicalPlan] {
    */
   private def createLambda(
       e: Expression,
-      partialArguments: Seq[(DataType, Boolean)]): LambdaFunction = e match {
+      argInfo: Seq[(DataType, Boolean)]): LambdaFunction = e match {
     case f: LambdaFunction if f.bound => f
 
     case LambdaFunction(function, names, _) =>
-      if (names.size != partialArguments.size) {
+      if (names.size != argInfo.size) {
         e.failAnalysis(
           s"The number of lambda function arguments '${names.size}' does not " +
             "match the number of arguments expected by the higher order function " +
-            s"'${partialArguments.size}'.")
+            s"'${argInfo.size}'.")
       }
 
       if (names.map(a => canonicalizer(a.name)).distinct.size < names.size) {
         e.failAnalysis(
           "Lambda function arguments should not have names that are semantically the same.")
       }
 
-      val arguments = partialArguments.zip(names).map {
+      val arguments = argInfo.zip(names).map {
         case ((dataType, nullable), ne) =>
           NamedLambdaVariable(ne.name, dataType, nullable)
       }
@@ -122,7 +122,7 @@ case class ResolveLambdaVariables(conf: SQLConf) extends Rule[LogicalPlan] {
       // create a lambda function with default parameters because this is expected by the higher
       // order function. Note that we hide the lambda variables produced by this function in order
       // to prevent accidental naming collisions.
-      val arguments = partialArguments.zipWithIndex.map {
+      val arguments = argInfo.zipWithIndex.map {
         case ((dataType, nullable), i) =>
           NamedLambdaVariable(s"col$i", dataType, nullable)
       }
@@ -135,7 +135,7 @@ case class ResolveLambdaVariables(conf: SQLConf) extends Rule[LogicalPlan] {
   private def resolve(e: Expression, parentLambdaMap: LambdaVariableMap): Expression = e match {
     case _ if e.resolved => e
 
-    case h: HigherOrderFunction if h.inputResolved =>
+    case h: HigherOrderFunction if h.argumentsResolved && h.checkArgumentDataTypes().isSuccess =>
       h.bind(createLambda).mapChildren(resolve(_, parentLambdaMap))
 
     case l: LambdaFunction if !l.bound =>

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

@@ -41,10 +41,19 @@ trait ExpectsInputTypes extends Expression {
   def inputTypes: Seq[AbstractDataType]
 
   override def checkInputDataTypes(): TypeCheckResult = {
-    val mismatches = children.zip(inputTypes).zipWithIndex.collect {
-      case ((child, expected), idx) if !expected.acceptsType(child.dataType) =>
+    ExpectsInputTypes.checkInputDataTypes(children, inputTypes)
+  }
+}
+
+object ExpectsInputTypes {
+
+  def checkInputDataTypes(
+      inputs: Seq[Expression],
+      inputTypes: Seq[AbstractDataType]): TypeCheckResult = {
+    val mismatches = inputs.zip(inputTypes).zipWithIndex.collect {
+      case ((input, expected), idx) if !expected.acceptsType(input.dataType) =>
         s"argument ${idx + 1} requires ${expected.simpleString} type, " +
-          s"however, '${child.sql}' is of ${child.dataType.catalogString} type."
+          s"however, '${input.sql}' is of ${input.dataType.catalogString} type."
     }
 
     if (mismatches.isEmpty) {
@@ -55,7 +64,6 @@ trait ExpectsInputTypes extends Expression {
   }
 }
 
-
 /**
  * A mixin for the analyzer to perform implicit type casting using
  * [[org.apache.spark.sql.catalyst.analysis.TypeCoercion.ImplicitTypeCasts]].