[GitHub] [spark] srowen commented on a change in pull request #25998: [SPARK-29328][SQL] Fix calculation of mean seconds per month

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srowen commented on a change in pull request #25998: [SPARK-29328][SQL] Fix calculation of mean seconds per month
URL: https://github.com/apache/spark/pull/25998#discussion_r330876188
 
 

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 File path: python/pyspark/sql/functions.py
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 @@ -1122,9 +1122,9 @@ def months_between(date1, date2, roundOff=True):
 
     >>> df = spark.createDataFrame([('1997-02-28 10:30:00', '1996-10-30')], ['date1', 'date2'])
     >>> df.select(months_between(df.date1, df.date2).alias('months')).collect()
 
 Review comment:
   As an aside, I would have expected `months_between` returns an integer, like just the difference in months ignoring day, but that's not what other DBs do. However browsing some links like https://www.ibm.com/support/knowledgecenter/SSCRJT_5.0.1/com.ibm.swg.im.bigsql.commsql.doc/doc/r0053631.html and https://www.vertica.com/docs/9.2.x/HTML/Content/Authoring/SQLReferenceManual/Functions/Date-Time/MONTHS_BETWEEN.htm I see that some implementations just assume all months including Feb have 31 days (!?) .
   
   I agree that this is more accurate, but is it less consistent with Hive or other DBs? maybe it's already not consistent. 

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