yaooqinn opened a new pull request #28198: [SPARK-31392][SQL][3.0] Support CalendarInterval to be reflect to Ca… URL: https://github.com/apache/spark/pull/28198 <!-- Thanks for sending a pull request! Here are some tips for you: 1. If this is your first time, please read our contributor guidelines: https://spark.apache.org/contributing.html 2. Ensure you have added or run the appropriate tests for your PR: https://spark.apache.org/developer-tools.html 3. If the PR is unfinished, add '[WIP]' in your PR title, e.g., '[WIP][SPARK-XXXX] Your PR title ...'. 4. Be sure to keep the PR description updated to reflect all changes. 5. Please write your PR title to summarize what this PR proposes. 6. If possible, provide a concise example to reproduce the issue for a faster review. 7. If you want to add a new configuration, please read the guideline first for naming configurations in 'core/src/main/scala/org/apache/spark/internal/config/ConfigEntry.scala'. --> ### What changes were proposed in this pull request? This PR backport https://github.com/apache/spark/pull/28165 to 3.0.0, previous description shows as: 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? <!-- If yes, please clarify the previous behavior and the change this PR proposes - provide the console output, description and/or an example to show the behavior difference if possible. If no, write 'No'. --> Yes, records(e.g case class, tuples ...) contains interval fields are able to convert to a Dataframe ### How was this patch tested? <!-- If tests were added, say they were added here. Please make sure to add some test cases that check the changes thoroughly including negative and positive cases if possible. If it was tested in a way different from regular unit tests, please clarify how you tested step by step, ideally copy and paste-able, so that other reviewers can test and check, and descendants can verify in the future. If tests were not added, please describe why they were not added and/or why it was difficult to add. --> add uts
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