Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/19891#discussion_r154967811
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Cast.scala
---
@@ -1024,37 +1024,33 @@ case class Cast(child: Expression, dataType:
DataType, timeZoneId: Option[String
val toFieldNull = ctx.freshName("tfn")
val fromType = ctx.javaType(from.fields(i).dataType)
s"""
- boolean $fromFieldNull = $tmpRow.isNullAt($i);
+ boolean $fromFieldNull = $tmpInput.isNullAt($i);
if ($fromFieldNull) {
- $result.setNullAt($i);
+ $tmpResult.setNullAt($i);
} else {
$fromType $fromFieldPrim =
- ${ctx.getValue(tmpRow, from.fields(i).dataType, i.toString)};
+ ${ctx.getValue(tmpInput, from.fields(i).dataType, i.toString)};
${castCode(ctx, fromFieldPrim,
fromFieldNull, toFieldPrim, toFieldNull,
to.fields(i).dataType, cast)}
if ($toFieldNull) {
- $result.setNullAt($i);
+ $tmpResult.setNullAt($i);
} else {
- ${ctx.setColumn(result, to.fields(i).dataType, i,
toFieldPrim)};
+ ${ctx.setColumn(tmpResult, to.fields(i).dataType, i,
toFieldPrim)};
}
}
"""
}
- val fieldsEvalCodes = if (ctx.currentVars == null) {
- ctx.splitExpressions(
- expressions = fieldsEvalCode,
- funcName = "castStruct",
- arguments = ("InternalRow", tmpRow) :: (rowClass, result) :: Nil)
- } else {
- fieldsEvalCode.mkString("\n")
- }
+ val fieldsEvalCodes = ctx.splitExpressions(
+ expressions = fieldsEvalCode,
+ funcName = "castStruct",
+ arguments = ("InternalRow", tmpInput) :: (rowClass, tmpResult) ::
Nil)
- (c, evPrim, evNull) =>
+ (input, result, resultIsNull) =>
s"""
- final $rowClass $result = new $rowClass(${fieldsCasts.length});
- final InternalRow $tmpRow = $c;
+ final $rowClass $tmpResult = new $rowClass(${fieldsCasts.length});
+ final InternalRow $tmpInput = $input;
--- End diff --
in another word, the code to cast a struct is always row-based, the input
is a variable of type `InternalRow`. We don't care about `ctx.INPUT_ROW` and
`ctx.currentVars` here.
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