Create nested JSON arrays using FOR JSON PATH - json

Question

I need to create a JSON output from a query that uses inner join between two tables with a one to many relationship.
I would like the values of the secondary table to be nested as array properties of the primary table.
Consider the following example:
DECLARE #Persons AS TABLE
(
person_id int primary key,
person_name varchar(20)
)
DECLARE #Pets AS TABLE
(
pet_owner int, -- in real tables, this would be a foreign key
pet_id int primary key,
pet_name varchar(10)
)
INSERT INTO #Persons (person_id, person_name) VALUES
(2, 'Jack'),
(3, 'Jill')
INSERT INTO #Pets (pet_owner, pet_id, pet_name) VALUES
(2, 4, 'Bug'),
(2, 5, 'Feature'),
(3, 6, 'Fiend')
And query:
DECLARE #Result as varchar(max)
SET #Result =
(
SELECT person_id as [person.id],
person_name as [person.name],
pet_id as [person.pet.id],
pet_name as [person.pet.name]
FROM #Persons
JOIN #Pets ON person_id = pet_owner
FOR JSON PATH, ROOT('pet owners')
)
PRINT #Result
This will print the following JSON:
{
"pet owners":
[
{"person":{"id":2,"name":"Jack","pet":{"id":4,"name":"Bug"}}},
{"person":{"id":2,"name":"Jack","pet":{"id":5,"name":"Feature"}}},
{"person":{"id":3,"name":"Jill","pet":{"id":6,"name":"Fiend"}}}
]
}
However, I would like to have the pets data as arrays inside the owners data:
{
"pet owners":
[
{
"person":
{
"id":2,"name":"Jack","pet":
[
{"id":4,"name":"Bug"},
{"id":5,"name":"Feature"}
]
}
},
{
"person":
{
"id":3,"name":"Jill","pet":
{"id":6,"name":"Fiend"}
}
}
]
}
How can I do this?

Answer 1

You can use the following query:
SELECT pr.person_id AS [person.id], pr.person_name AS [person.name],
(
SELECT pt.pet_id AS id, pt.pet_name AS name
FROM #Pets pt WHERE pt.pet_owner=pr.person_id
FOR JSON PATH
) AS [person.pet]
FROM #Persons pr
FOR JSON PATH, ROOT('pet owners')
For more information, see https://blogs.msdn.microsoft.com/sqlserverstorageengine/2015/10/09/returning-child-rows-formatted-as-json-in-sql-server-queries/

Answer 2

With deeply nested arrays the subqueries get unmanageable quickly:
select id,foo, (select id, bar, (select ... for json path) things,
(select...) more_things) yet_more, select(...) blarg
I create a relational (non-json) view that joins all my tables and has the json structure embedded in the column aliases, just like for json path does. But I also have [] to indicate that the json node is an array. Like this:
select p.id [id], p.foo [foo], c.name [children[].name], c.id [children[].id],
gp.name [grandparent.name], gc.name [children[].grandchildren[].name]
from parent p
join children c on c.parent_id = p.id .....
I wrote a stored procedure that creates a json view into the non-json view that parses the column names of the relational view and makes the json pretty. See below. Call it with the name of your relational view and it creates a view. It's not thoroughly tested but it works for me. Only caveat is that tables need to have id columns called id. It uses string_agg() and json_array() to the version of sql needs to be pretty new. It's also set up to return an array in the root. It will need tweaking to return an object.
create procedure create_json_from_view
#view_name varchar(max)
as
create table #doc_schema (
node_level int, -- nesting level starting with 0
node_name varchar(max), -- alias used for this nodes query
node_path varchar(max), -- full path to this node
parent_path varchar(max), -- full path to it's parents
is_array bit, -- is node marked as array by ending with []
select_columns varchar(max),-- comma separated path/alias pairs for selected columns on node
group_by_columns varchar(max), -- comma separated paths for selected columns on node. group by is necessary to prevent duplicates
node_parent_id varchar(max), -- the id column path to join subquery to parent. NOTE: ID COLUMN MUST BE CALLED ID
from_clause varchar(max), -- from clause built from above fields
node_query varchar(max) -- complete query built from above fields
)
/* get each node path from view schema
*/
INSERT INTO #doc_schema (node_path)
select distinct LEFT(COLUMN_NAME,CHARINDEX('.'+ VALUE + '.',COLUMN_NAME) + LEN(VALUE)) node_path
FROM INFORMATION_SCHEMA.COLUMNS
CROSS APPLY STRING_SPLIT(COLUMN_NAME, '.')
WHERE CHARINDEX('.',COLUMN_NAME) > 0
AND RIGHT(COLUMN_NAME,LEN(VALUE)) <> VALUE
and table_name = #view_name
/* node_name past rightmost period or the same as node_path if there is no period
also remove [] from arrays
*/
update #doc_schema set node_name =
case when charindex('.',node_path) = 0 then replace(node_path,'[]','')
else REPLACE(right(node_path,charindex('.',reverse(node_path)) - 1),'[]','') end
/* if path ends with [] node is array
escapes are necessary because [] have meaning for like
*/
update #doc_schema set is_array =
case when node_path like '%\[\]' escape '\' then 1 else 0 end --\
/* parent path is everything before last . in node path
except when the parent is the root, in which case parent is empty string
*/
update #doc_schema set parent_path =
case when charindex('.',node_path) = 0 then ''
else left(node_path,len(node_path) - charindex('.',reverse(node_path))) end
/* level is how many . in path. an ugly way to count.
*/
update #doc_schema set node_level = len(node_path) - len(replace(node_path,'.','')) + 1
/* set up root node
*/
insert into #doc_schema (node_path,node_name,parent_path,node_level,is_array)
select '','',null,0,1
/* I'm sorry this is so ugly. I just gave up on explaining
all paths need to be wrapped in [] and internal ] need to be escaped as ]]
*/
update #doc_schema set select_columns = sub2.select_columns, group_by_columns = sub2.group_by_columns
from (
select node_path,string_agg(column_path + ' ' + column_name,',') select_columns,
string_agg(column_path,',') group_by_columns
from (
select ds.node_path,'['+replace(c.COLUMN_NAME,']',']]')+']' column_path,replace(c.column_name,ds.node_path + '.','') column_name
from INFORMATION_SCHEMA.COLUMNS c
join #doc_schema ds
on (charindex(ds.node_path + '.', c.COLUMN_NAME) = 1
and charindex('.',replace(c.COLUMN_NAME,ds.node_path + '.','')) = 0)
or (ds.node_level = 0 and charindex('.',c.COLUMN_NAME) = 0)
where table_name = #view_name
) sub
group by node_path
) sub2
where #doc_schema.node_path = sub2.node_path
/* id paths for joining subqueries to parents
Again, the need to be wrapped in [] and and internal ] need to be escaped as ]]
*/
update #doc_schema set node_parent_id =
case when parent_path = '' then '[id]'
else '[' + replace(parent_path,']',']]')+'.id]'
end
/* table aliases for joining subqueries to parents need to be unique
just use L0 L1 etc based on nesting level
*/
update #doc_schema set from_clause =
case when node_level = 0 then ' from ' + #view_name + ' L'+cast(node_level as varchar(4)) + ' '
else ' from ' + #view_name + ' L'+cast(node_level as varchar(4))+' where L'+cast(node_level - 1 as varchar(4))+'.'+ node_parent_id +
' = L'+cast(node_level as varchar(4))+'.'+ node_parent_id
end
/* Assemble node query from all parts
###subqueries### is a place to put subqueries for node
*/
update #doc_schema set node_query =
' (select ' + select_columns + ', ###subqueries###' + from_clause
+ ' group by '+ group_by_columns
+' for json path) '
/* json path will treat all objects as arrays so select first explicitly
to prevent [] in json
*/
update #doc_schema set node_query =
case when is_array = 0
then '(select JSON_query(' + node_query + ',''$[0]'')) ' + node_name
else node_query + + node_name end
/* starting with highest nesting level substitute child subqueries ino
subquery hold in their parents
*/
declare #counter int = (select max(node_level) from #doc_schema)
while(#counter >= 0)
begin
update #doc_schema set node_query = replace(node_query,'###subqueries###', subs.subqueries)
from
(select parent_path, string_agg(node_query,',') subqueries, node_level from #doc_schema
group by parent_path, node_level ) subs
where subs.node_level = #counter and
#doc_schema.node_path = subs.parent_path
set #counter -= 1
end
/* objects and arrays with no subobjects or subarrays still have subquery holder so remove them
*/
update #doc_schema set node_query = replace(node_query,', ###subqueries###', '') where node_level = 0
declare #query nvarchar(max) = (select node_query from #doc_schema where node_level = 0)
/* add wrapper to query to specify column nave otherwise create view will fail
*/
set #query =
case when OBJECT_ID(#view_name + '_JSON', 'V') is NULL then 'create' else 'alter' end +
' view ' + #view_name + '_json as select' + #query + ' json'
exec sp_executesql #query

Answer 3

I have made below json format by following #Razvan Socol.
JSON
[
"domain_nm": "transactions",
"tables": [
{
"tableName": "transactions_details",
cols: [
{
"col_nm": "audit_transactions_details_guid",
"col_data_typ": "string"
}
]
}
]
]
SQL
select outer1.DOMAIN_NM as domain_nm,
(select inner2.TBL_NM as tableName,
(select inner1.COL_NM as col_nm, inner1.COL_DATA_TYP as col_data_typ
from ONBD_MTDT.CDM_TBL inner1
where inner1.TBL_NM=inner2.TBL_NM
FOR JSON PATH ) as cols
from ONBD_MTDT.CDM_TBL inner2
where inner2.DOMAIN_NM=outer1.DOMAIN_NM
group by inner2.DOMAIN_NM,inner2.TBL_NM
FOR JSON PATH ) as tables
from ONBD_MTDT.CDM_TBL outer1
group by outer1.DOMAIN_NM
FOR JSON PATH

Answer 4

It can be implemented like this
select OwnerFirstName, OwnerMiddleName , OwnerLastName, OwnerNumber,
ContactOwnerMailAddressUnit 'MailingAddress.UnitNumber',
ContactOwnerMailAddressUnitPrefix 'MailingAddress.UnitType',
case when ContactOwnerMailAddressHouseNumber='' then '' else ContactOwnerMailAddressHouseNumber + ' ' end+
ContactOwnerMailAddressStreetName +
case when ContactOwnerMailAddressStreetSuffix='' then '' else ' ' + ContactOwnerMailAddressStreetSuffix end 'MailingAddress.StreetAddress',
ContactOwnerMailAddressCity 'MailingAddress.City',
ContactOwnerMailAddressState 'MailingAddress.State',
ContactOwnerMailAddressZIP 'MailingAddress.ZipCode'
from T_Owners
join T_OwnersPropertiesMapping
on T_OwnersPropertiesMapping.OwnerID = T_Owners.OwnerID
where T_OwnersPropertiesMapping.PropertyID=#PropertyID
for json path
And here is result
[
{
"OwnerFirstName": "Bon 7360318",
"OwnerMiddleName": "Mr",
"OwnerLastName": "Jovi",
"OwnerNumber": 3,
"MailingAddress": {
"UnitNumber": "",
"UnitType": "",
"StreetAddress": "PO BOX 1736",
"City": "BOULDER CREEK",
"State": "CA",
"ZipCode": "95006"
}
},
{
"OwnerFirstName": "Bon 6717425",
"OwnerMiddleName": "Mr",
"OwnerLastName": "Jovi",
"OwnerNumber": 1,
"MailingAddress": {
"UnitNumber": "",
"UnitType": "",
"StreetAddress": "PO BOX 1736",
"City": "BOULDER CREEK",
"State": "CA",
"ZipCode": "95006"
}
}
]

Answer 5

Now, you’re flying completely blind. If the person who designed the API is sane, it is probably safe to assume that it will return an array of some kind of user objects — but what data each of the user objects actually carries can in no way be derived just from looking at this endpoint.