Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/21190#discussion_r185750124
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercion.scala
---
@@ -102,22 +105,32 @@ object TypeCoercion {
case (_: TimestampType, _: DateType) | (_: DateType, _: TimestampType)
=>
Some(TimestampType)
- case (t1 @ StructType(fields1), t2 @ StructType(fields2)) if
t1.sameType(t2) =>
- Some(StructType(fields1.zip(fields2).map { case (f1, f2) =>
- // Since `t1.sameType(t2)` is true, two StructTypes have the same
DataType
- // except `name` (in case of `spark.sql.caseSensitive=false`) and
`nullable`.
- // - Different names: use f1.name
- // - Different nullabilities: `nullable` is true iff one of them
is nullable.
- val dataType = findTightestCommonType(f1.dataType, f2.dataType).get
- StructField(f1.name, dataType, nullable = f1.nullable ||
f2.nullable)
- }))
+ case (t1 @ StructType(fields1), t2 @ StructType(fields2)) =>
+ val isSameType = if (caseSensitive) {
+ t1.sameType(t2)
--- End diff --
Call `DataType.equalsIgnoreNullability` here for better show the difference
between the call of `DataType.equalsIgnoreCaseAndNullability` below?
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