I have the following sample data in a MS-SQL database: (Microsoft SQL Server Standard Version 13; Microsoft SQL Server Management Studio 18)
---------- ----------- ----- -------- --------- ---------
| LastName | Firstname | Age | Weight | Sallery | Married |
---------- ----------- ----- -------- --------- ---------
| Smith | Stan | 58 | 87 | 59.000 | true |
| Smith | Maria | 53 | 57 | 45.000 | true |
| Brown | Chris | 48 | 77 | 159.000 | true |
| Brown | Stepahnie | 39 | 67 | 95.000 | true |
| Brown | Angela | 12 | 37 | 0.0 | false |
---------- ----------- ----- -------- --------- ---------
I want to get a nested JSON array from it that looks like this:
[
{
"Smith": [
{
"Stan": [
{
"Age": 58,
"Weight": 87,
"Sallery": 59.000,
"Married": true
}
],
"Maria": [
{
"Age": 53,
"Weight": 57,
"Sallery": 45.000,
"Married": true
}
]
}
],
"Brown": [
{
"Chris": [
{
"Age": 48,
"Weight": 77,
"Sallery": 159.000,
"Married": true
}
],
"Stepahnie": [
{
"Age": 39,
"Weight": 67,
"Sallery": 95.000,
"Married": true
}
],
"Angela": [
{
"Age": 12,
"Weight": 37,
"Sallery": 0.0,
"Married": false
}
]
}
]
}
]
How do I have to build the SQL query?
I have tried different ways but I don't get to dynamize the root or the root keeps repeating itself....
For example, I tried the following query:
I get one Level with:
WITH cte AS
(
SELECT FirstName
js = json_query(
(
SELECT Age,
Weight,
Sallery,
Married
FOR json path,
without_array_wrapper ) )
FROM Table1)
SELECT '[' stuff(
(
SELECT '},{"' FirstName '":' '[' js ']'
FROM cte
FOR xml path ('')), 1, 2, '') '}]'
But I need one more nested level with LastName
Another try:
SELECT
LastName ,json
FROM Table1 as a
OUTER APPLY (
SELECT
FirstName
FROM Table1 as b
WHERE a.LastName = b.LastName
FOR JSON PATH
) child(json)
FOR JSON PATH
CodePudding user response：
It's certainly possible to get your desired JSON output but, as you can see below, the code is rather convoluted...
/*
* Data setup...
*/
create table dbo.Person (
LastName varchar(10),
FirstName varchar(10),
Age int,
Weight int,
Sallery int,
Married bit
);
insert dbo.Person (LastName, FirstName, Age, Weight, Sallery, Married)
values
('Smith', 'Stan', 58, 87, 59000, 1),
('Smith', 'Maria', 53, 57, 45000, 1),
('Brown', 'Chris', 48, 77, 159000, 1),
('Brown', 'Stepahnie', 39, 67, 95000, 1),
('Brown', 'Angela', 12, 37, 0, 0);
/*
* Example JSON query...
*/
with Persons as (
select LastName, Stan, Maria, Chris, Stepahnie, Angela
from (
select
LastName,
FirstName,
(
select Age, Weight, Sallery, Married
for json path
) as data
from dbo.Person
) src
pivot (max(data) for FirstName in (Stan, Maria, Chris, Stepahnie, Angela)) pvt
)
select
json_query((
select
json_query(Stan) as Stan,
json_query(Maria) as Maria
from Persons
where LastName = 'Smith'
for json path
)) as Smith,
json_query((
select
json_query(Chris) as Chris,
json_query(Stepahnie) as Stepahnie,
json_query(Angela) as Angela
from Persons
where LastName = 'Brown'
for json path
)) as Brown
for json path;
Which yields the output...
[
{
"Smith": [
{
"Stan": [
{
"Age": 58,
"Weight": 87,
"Sallery": 59000,
"Married": true
}
],
"Maria": [
{
"Age": 53,
"Weight": 57,
"Sallery": 45000,
"Married": true
}
]
}
],
"Brown": [
{
"Chris": [
{
"Age": 48,
"Weight": 77,
"Sallery": 159000,
"Married": true
}
],
"Stepahnie": [
{
"Age": 39,
"Weight": 67,
"Sallery": 95000,
"Married": true
}
],
"Angela": [
{
"Age": 12,
"Weight": 37,
"Sallery": 0,
"Married": false
}
]
}
]
}
]
CodePudding user response：
Unfortunately, SQL Server does not support JSON_AGG nor JSON_OBJECT_AGG, which would have helped here. But we can hack it with STRING_AGG and STRING_ESCAPE
WITH ByFirstName AS
(
SELECT
p.LastName,
p.FirstName,
json = STRING_AGG(j.json, ',')
FROM Person p
CROSS APPLY (
SELECT
p.Age,
p.Weight,
p.Sallery,
p.Married
FOR JSON PATH, WITHOUT_ARRAY_WRAPPER
) AS j(json)
GROUP BY
p.LastName,
p.FirstName
),
ByLastName AS
(
SELECT
p.LastName,
json = STRING_AGG(CONCAT(
'"',
STRING_ESCAPE(p.FirstName, 'json'),
'":[',
p.json,
']'
), ',')
FROM ByFirstName p
GROUP BY
p.LastName
)
SELECT '[{'
STRING_AGG(CONCAT(
'"',
STRING_ESCAPE(p.LastName, 'json'),
'":{',
p.json,
'}'
), ',') '}]'
FROM ByLastName p
This gets you
[
{
"Brown": {
"Angela": [
{
"Age": 12,
"Weight": 37,
"Sallery": 0,
"Married": false
}
],
"Chris": [
{
"Age": 48,
"Weight": 77,
"Sallery": 159000,
"Married": true
}
],
"Stepahnie": [
{
"Age": 39,
"Weight": 67,
"Sallery": 95000,
"Married": true
}
]
},
"Smith": {
"Maria": [
{
"Age": 53,
"Weight": 57,
"Sallery": 45000,
"Married": true
}
],
"Stan": [
{
"Age": 58,
"Weight": 87,
"Sallery": 59000,
"Married": true
}
]
}
}
]