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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