[GitHub] [spark] MaxGekk opened a new pull request #25998: [SPARK-29328][SQL] Fix calculation of mean seconds per month

[GitBox <gi...@apache.org>]

MaxGekk opened a new pull request #25998: [SPARK-29328][SQL] Fix calculation of mean seconds per month
URL: https://github.com/apache/spark/pull/25998
 
 
   ### What changes were proposed in this pull request?
   I introduced new constants `SECONDS_PER_MONTH` and `MILLIS_PER_MONTH`, and reused it in calculations of seconds/milliseconds per month. `SECONDS_PER_MONTH` is 2629746 because the average year of the Gregorian calendar is 365.2425 days long or 60 * 60 * 24 * 365.2425 = 31556952.0 = 12 * 2629746 seconds per year.
   
   ### Why are the changes needed?
   Spark uses the proleptic Gregorian calendar (see https://issues.apache.org/jira/browse/SPARK-26651) in which the average year is 365.2425 days (see https://en.wikipedia.org/wiki/Gregorian_calendar) but existing implementation assumes 31 days per months or 12 * 31 = 372 days. That's far away from the the truth.
   
   ### Does this PR introduce any user-facing change?
    Yes, the changes affect at least 3 methods in `GroupStateImpl`, `EventTimeWatermark` and `MonthsBetween`. For example, the `month_between()` function will return different result in some cases.
   
   Before:
   ```sql
   spark-sql> select months_between('2019-09-15', '1970-01-01');
   596.4516129
   ```
   After:
   ```sql
   spark-sql> select months_between('2019-09-15', '1970-01-01');
   596.45996838
   ```
   
   ### How was this patch tested?
   By existing test suite `DateTimeUtilsSuite`, `DateFunctionsSuite` and `DateExpressionsSuite`.
   

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