[GitHub] [spark] xiaonanyang-db commented on a diff in pull request #37933: [SPARK-40474][SQL] Infer columns with mixed date and timestamp as String in CSV schema inference

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xiaonanyang-db commented on code in PR #37933:
URL: https://github.com/apache/spark/pull/37933#discussion_r975634588


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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVOptions.scala:
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@@ -183,7 +180,9 @@ class CSVOptions(
       Some(parameters.getOrElse("timestampFormat",
         s"${DateFormatter.defaultPattern}'T'HH:mm:ss.SSSXXX"))
     } else {
-      parameters.get("timestampFormat")
+      // Use Iso8601TimestampFormatter (with strict timestamp parsing) to
+      // avoid parsing dates in timestamp columns as timestamp type

Review Comment:
   Totally agree with your concerns @cloud-fan @sadikovi.
   
   After some quick discussion within my team, we agreed on not changing these 
lines to avoid unnecessary regressions and any other behavior changes. Thus, 
the behavior after this PR become:
   - If user provides a `timestampFormat/timestampNTZFormat`, we will strictly 
parse fields as timestamp according to the format. Thus, columns with mixing 
dates and timestamps will always be inferred as `StringType`.
   - If no `timestampFormat/timestampNTZFormat` specified by user, for a column 
with mixing dates and timestamps
     - If date values are before timestamp values
       - If `prefersDate=true`, the column will be inferred as `StringType`
       - otherwise
         - If the date format is supported by `Iso8601TimestampFormatter `, the 
column will be inferred as `timestampFormat/timestampNTZFormat`
         - otherwise, the column will be inferred as `StringType`
     - If timestamp values are before date values
       - If the date format is supported by `Iso8601TimestampFormatter `, the 
column will be inferred as `timestampFormat/timestampNTZFormat`
       - otherwise the column will be inferred as `StringType`
   
   Does this make sense to you? @sadikovi @cloud-fan 
   
   cc @brkyvz @Yaohua628 



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