AngersZhuuuu commented on a change in pull request #33518:
URL: https://github.com/apache/spark/pull/33518#discussion_r677183164
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File path: docs/sql-ref-datatypes.md
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@@ -49,6 +49,37 @@ 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:
+ - `YearMonthIntervalType(YEAR, YEAR)` or `YearMonthIntervalType(YEAR)`.
For instance, a value of the type is `INTERVAL '2021' YEAR`.
+ - `YearMonthIntervalType(YEAR, MONTH)`. For instance, a value of the
type is `INTERVAL '2021-07' YEAR TO MONTH`.
+ - `YearMonthIntervalType(MONTH, MONTH)` or
`YearMonthIntervalType(MONTH)`. For example, `INTERVAL '10' MONTH` is a value
of the type.
Review comment:
> I think it would be better to convert the list to a table with table
title.
Looks better.
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