bersprockets commented on a change in pull request #34984:
URL: https://github.com/apache/spark/pull/34984#discussion_r782613339
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File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcUtils.scala
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@@ -279,22 +275,40 @@ object OrcUtils extends Logging {
}
/**
- * Given a `StructType` object, this methods converts it to corresponding
string representation
- * in ORC.
+ * Given two `StructType` object, this methods converts it to corresponding
string representation
+ * in ORC. The second `StructType` used to change the `TimestampNTZType` as
LongType in result
+ * schema string when reading `TimestampNTZ` as `TimestampLTZ`.
*/
- def orcTypeDescriptionString(dt: DataType): String = dt match {
- case s: StructType =>
+ def getOrcSchemaString(
+ dt: DataType, orcDt: Option[DataType] = None): String = (dt, orcDt)
match {
+ case (s1: StructType, Some(s2: StructType)) =>
+ val fieldTypes = s1.fields.map { f =>
+ val idx = s2.fieldNames.indexWhere(caseSensitiveResolution(_, f.name))
Review comment:
Is this a potential O(n^2) issue? If I am reading correctly, it says
"for each field in s1, scan s2 to find the matching field".
Probably not a noticeable issue under most circumstances. But for wide
structs with many input files, it could add up.
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