MaxGekk commented on a change in pull request #25981: [SPARK-28420][SQL]
Support the `INTERVAL` type in `date_part()`
URL: https://github.com/apache/spark/pull/25981#discussion_r332218582
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File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/datetimeExpressions.scala
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@@ -2067,6 +2082,10 @@ object DatePart {
224
> SELECT _FUNC_('SECONDS', timestamp'2019-10-01 00:00:01.000001');
1.000001
+ > SELECT _FUNC_('days', interval 1 year 10 months 5 days);
Review comment:
> But it does seem like this proposal doesn't match PostgreSQL in the
`SELECT date_part('hour', INTERVAL '4 hours 3 minutes')`;
It does. In PostgreSQL:
```sql
maxim=# SELECT date_part('hour', INTERVAL '4 hours 3 minutes');
date_part
-----------
4
```
In SparkSQL:
```sql
spark-sql> SELECT date_part('hour', interval 4 hours 3 minutes);
4
```
> SELECT date_part('hour', INTERVAL '1 month 1 day'); gives 24, right?
because the days are separable from the months.
No, it is 0 because the range of hours is `[0, 23]`:
In PostgreSQL:
```sql
maxim=# SELECT date_part('hour', INTERVAL '1 month 1 day');
date_part
-----------
0
```
In SparkSQL:
```sql
spark-sql> SELECT date_part('hour', INTERVAL 1 month 1 day);
0
```
> SELECT date_part('month', INTERVAL '1 year 1 month'); gives 13, not 1,
right? because the month part isn't separable.
No, it gives 1.
In PostgreSQL:
```sql
maxim=# SELECT date_part('month', INTERVAL '1 year 1 month');
date_part
-----------
1
```
In SparkSQL:
```sql
spark-sql> SELECT date_part('month', INTERVAL 1 year 1 month);
1
```
> This feels inconsistent.
I cannot agree with you so far.
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