sadikovi commented on a change in pull request #34596:
URL: https://github.com/apache/spark/pull/34596#discussion_r759689089
##########
File path:
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVSuite.scala
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@@ -1012,6 +1012,196 @@ abstract class CSVSuite
}
}
+ test("SPARK-37326: Use different pattern to write and infer TIMESTAMP_NTZ
values") {
+ withTempDir { dir =>
+ val path = s"${dir.getCanonicalPath}/csv"
+
+ val exp = spark.sql("select timestamp_ntz'2020-12-12 12:12:12' as col0")
+ exp.write.format("csv").option("timestampNTZFormat", "yyyy-MM-dd
HH:mm:ss").save(path)
+
+ withSQLConf(SQLConf.TIMESTAMP_TYPE.key ->
SQLConf.TimestampTypes.TIMESTAMP_NTZ.toString) {
+ val res = spark.read
+ .format("csv")
+ .option("inferSchema", "true")
+ .option("timestampNTZFormat", "yyyy-MM-dd HH:mm:ss")
+ .load(path)
+
+ checkAnswer(res, exp)
Review comment:
Wouldn't that fail the answer since the values would be different? Yes,
I can check the type explicitly, thanks.
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