Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/14788
I took a look for MySQL and PostgreSQL. It seems they are not really
consistent for `NEXT_DAY`, `LAST_DAY` and `TRUNC` but it seems the return types
are fixed in general (whether it is `DateType` or `TimestampType` in terms of
Spark).
In more details, I skimmed through the function list here for MySQL
http://www.tutorialspoint.com/mysql/mysql-date-time-functions.htm and for
PostgreSQL https://www.postgresql.org/docs/9.1/static/functions-datetime.html,
and then tried to apply some equivalent as below:
- PostgreSQL
- `TRUNC` - Always returns `TimestampType` (in terms of Spark).
```sql
postgres=# SELECT DATE_TRUNC('day', CAST('2015-10-10' AS DATE));
date_trunc
------------------------
2015-10-10 00:00:00+02
(1 row)
```
```sql
postgres=# SELECT DATE_TRUNC('day', CAST('2015-10-10 12:00:00' AS
TIMESTAMP));
date_trunc
---------------------
2015-10-10 00:00:00
(1 row)
```
- MySQL
- `LASY_DAY` - Always returns `DateType` (in terms of Spark).
```sql
mysql> SELECT LAST_DAY(CAST("2015-10-10 12:00:00" AS DATETIME));
+---------------------------------------------------+
| LAST_DAY(CAST("2015-10-10 12:00:00" AS DATETIME)) |
+---------------------------------------------------+
| 2015-10-31 |
+---------------------------------------------------+
1 row in set (0.00 sec)
```
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