用于解析JSON文件的递归CTE
我正在使用SQL Server 2014解析JSON文件,为此我认为递归CTE很方便。用于解析JSON文件的递归CTE
的JSON文件是这样的:
{ "0": {
"SalesOrderNumber": "CSVSO67695",
"SalesOrderDetailID": 97971,
"OrderDate": "2014-03-05 00:00:00.000",
"ProductNumber": "WB-H098",
"Quantity": 1,
"LineTotal": 4.99,
"CustomerType": "Individual",
"TestData_1": "Sales extract OK!",
"TestData_2": 255
},
"1": {
"SalesOrderNumber": "CSVSO53485",
"SalesOrderDetailID": 47747,
"OrderDate": "2013-07-31 00:00:00.000",
"ProductNumber": "SJ-0194-L",
"Quantity": 10,
"LineTotal": 323.94,
"CustomerType": "Store",
"TestData_1": "Sales extract OK!",
"TestData_2": 255
},
"2": {
"SalesOrderNumber": "CSVSO52248",
"SalesOrderDetailID": 43809,
"OrderDate": "2013-07-07 00:00:00.000",
"ProductNumber": "TT-M928",
"Quantity": 1,
"LineTotal": 4.99,
"CustomerType": "Individual",
"TestData_1": "Sales extract OK!",
"TestData_2": 255
}
}
谁能帮助我?
回答:
你不需要为此递归。抢delimitedSplit8K副本,并做到这一点:
declare @json varchar(8000) = '{
"0": {
"SalesOrderNumber": "CSVSO67695",
"SalesOrderDetailID": 97971,
"OrderDate": "2014-03-05 00:00:00.000",
"ProductNumber": "WB-H098",
"Quantity": 1,
"LineTotal": 4.99,
"CustomerType": "Individual",
"TestData_1": "Sales extract OK!",
"TestData_2": 255
},
"1": {
"SalesOrderNumber": "CSVSO53485",
"SalesOrderDetailID": 47747,
"OrderDate": "2013-07-31 00:00:00.000",
"ProductNumber": "SJ-0194-L",
"Quantity": 10,
"LineTotal": 323.94,
"CustomerType": "Store",
"TestData_1": "Sales extract OK!",
"TestData_2": 255
},
"2": {
"SalesOrderNumber": "CSVSO52248",
"SalesOrderDetailID": 43809,
"OrderDate": "2013-07-07 00:00:00.000",
"ProductNumber": "TT-M928",
"Quantity": 1,
"LineTotal": 4.99,
"CustomerType": "Individual",
"TestData_1": "Sales extract OK!",
"TestData_2": 255
}
}';
select
jsonItemId,
item,
attrib,
attribValue
from
(
select
jsonItemId = sum(sign(jsonItemIdPrep)) over (order by itemnumber),
ItemNumber,
item,
attrib = ltrim(replace(substring(item, 1, sep.pos-1),'"','')),
attribValue = replace(ltrim(replace(substring(item, sep.pos+1, len(item)),'"','')),',',''),
jsonItemIdPrep
from
(
select ItemNumber, item, jsonItemIdPrep =
case
when item like '%"[0-9]": {%'
or item like '%"[0-9][0-9]": {%'
or item like '%"[0-9][0-9][0-9]": {%' -- 1,2 or 3 digits
then substring(item, v.ps, charindex('"', item, v.ps)- v.ps)
end
from dbo.DelimitedSplit8K(replace(@json,char(10),''), char(13))
cross apply (values (charindex('"',item)+1)) v(ps)
where ItemNumber > 1 and item not like '%}' and item not like '%},'
) x
cross apply (values (charindex(':', item))) sep(pos)
cross apply (values (replace(substring(item, 1, sep.pos-1),'"',''))) p(xxx)
) x
where jsonItemIdPrep is null;
结果
jsonItemId item attrib attribValue ----------- ----------------------------------------------------- ----------------------------- -----------------------------------
0 "SalesOrderNumber": "CSVSO67695", SalesOrderNumber CSVSO67695
0 "SalesOrderDetailID": 97971, SalesOrderDetailID 97971
0 "OrderDate": "2014-03-05 00:00:00.000", OrderDate 2014-03-05 00:00:00.000
0 "ProductNumber": "WB-H098", ProductNumber WB-H098
0 "Quantity": 1, Quantity 1
0 "LineTotal": 4.99, LineTotal 4.99
0 "CustomerType": "Individual", CustomerType Individual
0 "TestData_1": "Sales extract OK!", TestData_1 Sales extract OK!
0 "TestData_2": 255 TestData_2 255
1 "SalesOrderNumber": "CSVSO53485", SalesOrderNumber CSVSO53485
1 "SalesOrderDetailID": 47747, SalesOrderDetailID 47747
1 "OrderDate": "2013-07-31 00:00:00.000", OrderDate 2013-07-31 00:00:00.000
1 "ProductNumber": "SJ-0194-L", ProductNumber SJ-0194-L
1 "Quantity": 10, Quantity 10
1 "LineTotal": 323.94, LineTotal 323.94
1 "CustomerType": "Store", CustomerType Store
1 "TestData_1": "Sales extract OK!", TestData_1 Sales extract OK!
1 "TestData_2": 255 TestData_2 255
2 "SalesOrderNumber": "CSVSO52248", SalesOrderNumber CSVSO52248
2 "SalesOrderDetailID": 43809, SalesOrderDetailID 43809
2 "OrderDate": "2013-07-07 00:00:00.000", OrderDate 2013-07-07 00:00:00.000
2 "ProductNumber": "TT-M928", ProductNumber TT-M928
2 "Quantity": 1, Quantity 1
2 "LineTotal": 4.99, LineTotal 4.99
2 "CustomerType": "Individual", CustomerType Individual
2 "TestData_1": "Sales extract OK!", TestData_1 Sales extract OK!
2 "TestData_2": 255 TestData_2 255
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