Vsevolod Ostapenko created SPARK-37544:
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Summary: sequence over dates with month interval is producing
incorrect results
Key: SPARK-37544
URL: https://issues.apache.org/jira/browse/SPARK-37544
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 3.2.0, 3.1.1
Environment: Ubuntu 20, OSX 11.6
OpenJDK 11, Spark 3.2
Reporter: Vsevolod Ostapenko
Sequence function with dates and step interval in months producing unexpected
results.
Here is a sample using Spark 3.2 (though the behavior is the same in 3.1.1 and
presumably earlier):
{{scala> spark.sql("select sequence(date '2021-01-01', date '2022-01-01',
interval '3' month) x, date '2021-01-01' + interval '3' month y").collect()}}
{{res1: Array[org.apache.spark.sql.Row] = Array([WrappedArray(2021-01-01,
{color:#FF0000}*2021-03-31, 2021-06-30, 2021-09-30,*
{color}{color:#172b4d}2022-01-01{color}),2021-04-01])}}
Expected result of adding 3 months to the 2021-01-01 is 2021-04-01, while
sequence returns 2021-03-31.
At the same time sequence over timestamps works as expected:
{{scala> spark.sql("select sequence(timestamp '2021-01-01 00:00', timestamp
'2022-01-01 00:00', interval '3' month) x").collect()}}
{{res2: Array[org.apache.spark.sql.Row] = Array([WrappedArray(2021-01-01
00:00:00.0, *2021-04-01* 00:00:00.0, *2021-07-01* 00:00:00.0, *2021-10-01*
00:00:00.0, 2022-01-01 00:00:00.0)])}}
A similar issue was reported in the past - [SPARK-31654] sequence producing
inconsistent intervals for month step - ASF JIRA (apache.org)
It's marked resolved, but the problem is either resurfaced or was never
actually fixed.
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