[enhancement] Direct dispatch with parallel.

### Cloudberry Database version

_No response_

### What happened

Direct dispatch in parallel mode may have no improvement compared to a non-parallel direct dispatch.
non-parallel direct dispatch:
```sql
gpadmin=# explain select a, count(*) from dd_part_singlecol where a=1 group by a;
QUERY PLAN
----------------------------------------------------------------------------------------------------------------------
Gather Motion 1:1 (slice1; segments: 1) (cost=0.00..2160.85 rows=467 width=12)
-> GroupAggregate (cost=0.00..2154.62 rows=156 width=12)
Group Key: dd_part_singlecol.a
-> Append (cost=0.00..2152.28 rows=156 width=4)
-> Seq Scan on dd_part_singlecol_1_prt_2 dd_part_singlecol_1 (cost=0.00..358.58 rows=26 width=4)
Filter: (a = 1)
-> Seq Scan on dd_part_singlecol_1_prt_3 dd_part_singlecol_2 (cost=0.00..358.58 rows=26 width=4)
Filter: (a = 1)
-> Seq Scan on dd_part_singlecol_1_prt_4 dd_part_singlecol_3 (cost=0.00..358.58 rows=26 width=4)
Filter: (a = 1)
-> Seq Scan on dd_part_singlecol_1_prt_5 dd_part_singlecol_4 (cost=0.00..358.58 rows=26 width=4)
Filter: (a = 1)
-> Seq Scan on dd_part_singlecol_1_prt_6 dd_part_singlecol_5 (cost=0.00..358.58 rows=26 width=4)
Filter: (a = 1)
-> Seq Scan on dd_part_singlecol_1_prt_extra dd_part_singlecol_6 (cost=0.00..358.58 rows=26 width=4)
Filter: (a = 1)
Optimizer: Postgres query optimizer
(17 rows)

gpadmin=# select a, count(*) from dd_part_singlecol where a=1 group by a;
a | count
---+-------
1 | 1
(1 row)

Time: 3.517 ms
```
parallel direct dispatch:
```sql
gpadmin=# explain select a, count(*) from dd_part_singlecol where a=1 group by a;
QUERY PLAN
----------------------------------------------------------------------------------------------------------------------------------
Gather Motion 6:1 (slice1; segments: 6) (cost=1079.26..1091.72 rows=935 width=12)
-> Finalize HashAggregate (cost=1079.26..1080.81 rows=156 width=12)
Group Key: dd_part_singlecol.a
-> Redistribute Motion 2:6 (slice2; segments: 2) (cost=0.00..1078.87 rows=78 width=12)
Hash Key: dd_part_singlecol.a
Hash Module: 3
-> Partial GroupAggregate (cost=0.00..1077.31 rows=78 width=12)
Group Key: dd_part_singlecol.a
-> Parallel Append (cost=0.00..1076.14 rows=78 width=4)
-> Seq Scan on dd_part_singlecol_1_prt_2 dd_part_singlecol_1 (cost=0.00..358.58 rows=26 width=4)
Filter: (a = 1)
-> Seq Scan on dd_part_singlecol_1_prt_3 dd_part_singlecol_2 (cost=0.00..358.58 rows=26 width=4)
Filter: (a = 1)
-> Seq Scan on dd_part_singlecol_1_prt_4 dd_part_singlecol_3 (cost=0.00..358.58 rows=26 width=4)
Filter: (a = 1)
-> Seq Scan on dd_part_singlecol_1_prt_5 dd_part_singlecol_4 (cost=0.00..358.58 rows=26 width=4)
Filter: (a = 1)
-> Seq Scan on dd_part_singlecol_1_prt_6 dd_part_singlecol_5 (cost=0.00..358.58 rows=26 width=4)
Filter: (a = 1)
-> Seq Scan on dd_part_singlecol_1_prt_extra dd_part_singlecol_6 (cost=0.00..358.58 rows=26 width=4)
Filter: (a = 1)
Optimizer: Postgres query optimizer
(22 rows)

gpadmin=# select a, count(*) from dd_part_singlecol where a=1 group by a;
a | count
---+-------
1 | 1
(1 row)

Time: 4.156 ms

```
Slice2 's origin Motion(6:6) is reduced to Motion(2:6) due to direct_dispatch.

And it have to Gather(6:1) as we will use a parallel plan.

We should reconsider a direct-dispatch able plan in parallel mode.

### What you think should happen instead

We should reconsider direct dispatch in parallel mode, it may not be better than a Single process.

### How to reproduce

dd_part_singlecol in regression.

### Operating System

Ubuntu

### Anything else

_No response_

### Are you willing to submit PR?

- [ ] Yes, I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://cloudberrydb.org/community/coc).

Riprodurre il problema utilizzando la tabella di regressione dd_part_singlecol e le due query EXPLAIN fornite, in modalità non parallela e parallela. Confrontare i piani e i tempi di direct-dispatch, quindi determinare quale comportamento del piano debba essere considerato completato per il direct dispatch parallelo; nell’issue non sono identificati alcun file sorgente né alcun punto di ingresso dei test.

Scritto dal modello di indicizzazione a partire dal testo della issue.