[SPARK-29774][SQL][FOLLOWUP] Add a migration guide for date_add and date_sub

### What changes were proposed in this pull request?

add a migration guide for date_add and date_sub to indicates their behavior change. It a followup for #26412

### Why are the changes needed?
add a migration guide

### Does this PR introduce any user-facing change?

yes, doc change

### How was this patch tested?

no

Closes #26932 from yaooqinn/SPARK-29774-f.

Authored-by: Kent Yao <[email protected]>
Signed-off-by: Wenchen Fan <[email protected]>

Author: yaooqinn

docs/sql-migration-guide.md

@@ -256,6 +256,8 @@ license: |
 
   - Since Spark 3.0, day-time interval strings are converted to intervals with respect to the `from` and `to` bounds. If an input string does not match to the pattern defined by specified bounds, the `ParseException` exception is thrown. For example, `interval '2 10:20' hour to minute` raises the exception because the expected format is `[+|-]h[h]:[m]m`. In Spark version 2.4, the `from` bound was not taken into account, and the `to` bound was used to truncate the resulted interval. For instance, the day-time interval string from the showed example is converted to `interval 10 hours 20 minutes`. To restore the behavior before Spark 3.0, you can set `spark.sql.legacy.fromDayTimeString.enabled` to `true`.
 
+  - Since Spark 3.0, the `date_add` and `date_sub` functions only accepts int, smallint, tinyint as the 2nd argument, fractional and string types are not valid anymore, e.g. `date_add(cast('1964-05-23' as date), '12.34')` will cause `AnalysisException`. In Spark version 2.4 and earlier, if the 2nd argument is fractional or string value, it will be coerced to int value, and the result will be a date value of `1964-06-04`.
+
 ## Upgrading from Spark SQL 2.4 to 2.4.1
 
   - The value of `spark.executor.heartbeatInterval`, when specified without units like "30" rather than "30s", was