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### What changes were proposed in this pull request? Since 3.0.0, we make CalendarInterval public for input, it's better for it to be inferred to CalendarIntervalType. In the PR, we add a rule for CalendarInterval to be mapped to CalendarIntervalType in ScalaRelection, then records(e.g case class, tuples ...) contains interval fields are able to convert to a Dataframe. ### Why are the changes needed? CalendarInterval is public but can not be used as input for Datafame. ```scala scala> import org.apache.spark.unsafe.types.CalendarInterval import org.apache.spark.unsafe.types.CalendarInterval scala> Seq((1, new CalendarInterval(1, 2, 3))).toDF("a", "b") java.lang.UnsupportedOperationException: Schema for type org.apache.spark.unsafe.types.CalendarInterval is not supported at org.apache.spark.sql.catalyst.ScalaReflection$.$anonfun$schemaFor$1(ScalaReflection.scala:735) ``` this should be supported as well as ```scala scala> sql("select interval 2 month 1 day a") res2: org.apache.spark.sql.DataFrame = [a: interval] ``` ### Does this PR introduce any user-facing change? Yes, records(e.g case class, tuples ...) contains interval fields are able to convert to a Dataframe ### How was this patch tested? add uts Closes #28165 from yaooqinn/SPARK-31392. Authored-by: Kent Yao <yaooqinn@hotmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com> |
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