Support for aggregate functions on intervals

### Is your feature request related to a problem or challenge?

In postgres you can have the following query:
```sql
with test_values as (
select * from (values (interval '1 second'), (interval '1 year'), (interval '1 month')) as t(value)
)
select avg(value) from test_values;

>> 0 years 4 mons 10 days 0 hours 0 mins 0.333333 secs

with test_values as (
select * from (values (interval '1 second'), (interval '1 year'), (interval '1 month')) as t(value)
)
select sum(value) from test_values;

>> 1 years 1 mons 0 days 0 hours 0 mins 1.0 secs
```

It would be nice if Datafusion also had support for it. Datafusion current output:
```sql
> with test_values as (
select * from (values (interval '1 second'), (interval '1 year'), (interval '1 month')) as t(value)
)
select avg(value) from test_values;
Error during planning: Internal error: Function 'avg' failed to match any signature, errors: Error during planning: Function 'avg' requires Decimal, but received Interval(MonthDayNano) (DataType: Interval(MonthDayNano)).,Error during planning: Function 'avg' requires Duration, but received Interval(MonthDayNano) (DataType: Interval(MonthDayNano)).,Error during planning: Function 'avg' requires Float64, but received Interval(MonthDayNano) (DataType: Interval(MonthDayNano))..
This issue was likely caused by a bug in DataFusion's code. Please help us to resolve this by filing a bug report in our issue tracker: https://github.com/apache/datafusion/issues. No function matches the given name and argument types 'avg(Interval(MonthDayNano))'. You might need to add explicit type casts.
Candidate functions:
avg(Decimal)
avg(Duration)
avg(Float64)

> with test_values as (
select * from (values (interval '1 second'), (interval '1 year'), (interval '1 month')) as t(value)
)
select sum(value) from test_values;
Error during planning: Internal error: Function 'sum' failed to match any signature, errors: Error during planning: Function 'sum' requires Decimal, but received Interval(MonthDayNano) (DataType: Interval(MonthDayNano)).,Error during planning: Function 'sum' requires UInt64, but received Interval(MonthDayNano) (DataType: Interval(MonthDayNano)).,Error during planning: Function 'sum' requires Int64, but received Interval(MonthDayNano) (DataType: Interval(MonthDayNano)).,Error during planning: Function 'sum' requires Float64, but received Interval(MonthDayNano) (DataType: Interval(MonthDayNano)).,Error during planning: Function 'sum' requires Duration, but received Interval(MonthDayNano) (DataType: Interval(MonthDayNano))..
This issue was likely caused by a bug in DataFusion's code. Please help us to resolve this by filing a bug report in our issue tracker: https://github.com/apache/datafusion/issues. No function matches the given name and argument types 'sum(Interval(MonthDayNano))'. You might need to add explicit type casts.
Candidate functions:
sum(Decimal)
sum(UInt64)
sum(Int64)
sum(Float64)
sum(Duration)
```

### Describe the solution you'd like

_No response_

### Describe alternatives you've considered

aggregating epoch
```sql
with test_values as (
select * from (values (interval '1 second'), (interval '1 year'), (interval '1 month')) as t(value)
)
select sum(extract(epoch from value)) from test_values;
````

it works but it wont be a duration/interval anymore

### Additional context

Very nice for time series operations. for example if you would like to know the total duration of present gaps of a time series

No files or tests are named. Start by reproducing the PostgreSQL comparison queries and tracing how DataFusion resolves avg and sum signatures for Interval(MonthDayNano); done means both aggregates accept intervals and return interval/duration results consistent with the requested behavior, with coverage for the supplied values.

Written by the indexing model from the issue text.