MaxGekk commented on a change in pull request #33518:
URL: https://github.com/apache/spark/pull/33518#discussion_r677198955
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File path: docs/sql-ref-datatypes.md
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@@ -49,6 +49,44 @@ Spark SQL and DataFrames support the following data types:
absolute point in time.
- `DateType`: Represents values comprising values of fields year, month and
day, without a
time-zone.
+* Interval types
+ - `YearMonthIntervalType(startField, endField)`: Represents a year-month
interval which is made up of a contiguous subset of the following fields:
+ - MONTH, months within years `[0..11]`,
+ - YEAR, years in the range `[0..178956970]`.
+
+ Individual interval fields are non-negative, but an interval itself can
have a sign, and be negative.
+
+ `startField` is the leftmost field, and `endField` is the rightmost field
of the type. Valid values of `startField` and `endField` are 0(MONTH) and
1(YEAR). Supported year-month interval types are:
+
+ |Year-Month Interval Type|Short form|An instance of the type|
Review comment:
You are slightly late. I added the `SQL type` column instead. I think it
is more important.
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