Reputation: 315
Example of initial data:
| ID | ParentID |
|------|------------|
| 1 | NULL |
| 2 | 1 |
| 3 | 1 |
| 4 | 2 |
| 5 | NULL |
| 6 | 2 |
| 7 | 3 |
In my initial data I have ID of element and his parent ID. Some elements has parent, some has not, some has a parent and his parent has a parent.
The maximum number of levels in this hierarchy is 3.
I need to get this hierarchy by levels.
Lvl 1
- elements without parents
Lvl 2
- elements with parent which doesn't have parent
Lvl 3
- elements with parent which has a parent too.
Expected result looks like:
| Lvl1 | Lvl2 | Lvl3 |
|-------|----------|----------|
| 1 | NULL | NULL |
| 1 | 2 | NULL |
| 1 | 3 | NULL |
| 1 | 2 | 4 |
| 5 | NULL | NULL |
| 1 | 2 | 6 |
| 1 | 3 | 7 |
How I can do it?
Upvotes: 2
Views: 555
Reputation: 86745
For a fixed dept of three, you can use CROSS APPLY
.
It can be used like a JOIN
, but also return extra records to give you the NULL
s.
SELECT
Lvl1.ID AS lvl1,
Lvl2.ID AS lvl2,
Lvl3.ID AS lvl3
FROM
initial_data AS Lvl1
CROSS APPLY
(
SELECT ID FROM initial_data WHERE ParentID = Lvl1.ID
UNION ALL
SELECT NULL AS ID
)
AS Lvl2
CROSS APPLY
(
SELECT ID FROM initial_data WHERE ParentID = Lvl2.ID
UNION ALL
SELECT NULL AS ID
)
AS Lvl3
WHERE
Lvl1.ParentID IS NULL
ORDER BY
Lvl1.ID,
Lvl2.ID,
Lvl3.ID
But, as per my comment, this is often a sign that you're headed down a non-sql route. It might feel easier to start with, but later it turns and bites you, because SQL benefits tremendously from normalised structures (your starting data).
Upvotes: 3