Related
Let's say I have a table with rows like number, image. But image is not mandatory, It can be null and when I'm selecting I want to prioritize the row with image over the one with null so i could get clean array with only one row per number.
SELECT DISTINCT number, image FROM table ORDER BY number ASC
What's now with SELECT DISTINCT:
[
{
"number": 1,
"image": null
},
{
"number": 1,
"image": "https://example.com/image1.png"
},
{
"number": 2,
"image": null
},
{
"number": 2,
"image": "https://example.com/image2.png"
},
{
"number": 3,
"image": "https://example.com/image3.png"
},
{
"number": 3,
"image": null
},
{
"number": 4,
"image": null
}
]
What I want to get:
[
{
"number": 1,
"image": "https://example.com/image1.png"
},
{
"number": 2,
"image": "https://example.com/image2.png"
},
{
"number": 3,
"image": "https://example.com/image3.png"
},
{
"number": 4,
"image": null
}
]
Try this:
SELECT number, image FROM table ORDER BY ISNULL(LEFT(image,0));
given the below data model:
{
"events": [
{
"customerId": "a",
"type": "credit" ,
"value": 10
},
{
"customerId": "a",
"type": "credit" ,
"value": 10
},
{
"customerId": "b",
"type": "credit" ,
"value": 5
},
{
"customerId": "b",
"type": "credit" ,
"value": 5
}
]
}
how can i query the sum of credits by customerId ? i.e:
{
{
"customerId": "a",
"total": "20
},
{
"customerId": "b",
"total": "10
}
}
Use SUBQUERY expression per document aggregation
SELECT d.*,
(SELECT e.customerId, SUM(e.`value`) AS total
FROM d.events AS e
WHERE ......
GROUP BY e.customerId) AS events
FROM default AS d
WHERE ...........;
For Whole Query
SELECT e.customerId, SUM(e.`value`) AS total
FROM default AS d
UNNEST d.events AS e
WHERE ......
GROUP BY e.customerId;
I have JSON stored in a SQL Server database table in the below format. I have been able to fudge a way to get the values I need but feel like there must be a better way to do it using T-SQL. The JSON is output from a report in the below format where the column names in "columns" correspond to the "rows"-"data" array values.
So column "Fiscal Month" corresponds to data value "11", "Fiscal Year" to "2019", etc.
{
"report": "Property ETL",
"id": 2648,
"columns": [
{
"name": "Fiscal Month",
"dataType": "int"
},
{
"name": "Fiscal Year",
"dataType": "int"
},
{
"name": "Portfolio",
"dataType": "varchar(50)"
},
{
"name": "Rent",
"dataType": "int"
}
],
"rows": [
{
"rowName": "1",
"type": "Detail",
"data": [
11,
2019,
"West Group",
10
]
},
{
"rowName": "2",
"type": "Detail",
"data": [
11,
2019,
"East Group",
10
]
},
{
"rowName": "3",
"type": "Detail",
"data": [
11,
2019,
"East Group",
10
]
},
{
"rowName": "Totals: ",
"type": "Total",
"data": [
null,
null,
null,
30
]
}
]
}
In order to get at the data in the 'data' array I currently have a 2 step process in T-SQL where I create a temp table, and insert the row key/values from '$.Rows' there. Then I can then select the individual columns for each row
CREATE TABLE #TempData
(
Id INT,
JsonData VARCHAR(MAX)
)
DECLARE #json VARCHAR(MAX);
DECLARE #LineageKey INT;
SET #json = (SELECT JsonString FROM Stage.Report);
SET #LineageKey = (SELECT LineageKey FROM Stage.Report);
INSERT INTO #TempData(Id, JsonData)
(SELECT [key], value FROM OPENJSON(#json, '$.rows'))
MERGE [dbo].[DestinationTable] TARGET
USING
(
SELECT
JSON_VALUE(JsonData, '$.data[0]') AS FiscalMonth,
JSON_VALUE(JsonData, '$.data[1]') AS FiscalYear,
JSON_VALUE(JsonData, '$.data[2]') AS Portfolio,
JSON_VALUE(JsonData, '$.data[3]') AS Rent
FROM #TempData
WHERE JSON_VALUE(JsonData, '$.data[0]') is not null
) AS SOURCE
...
etc., etc.
This works, but I want to know if there is a way to directly select the data values without the intermediate step of putting it into the temp table. The documentation and examples I've read seem to all require that the data have a name associated with it in order to access it. When I try and access the data directly at a position by index I just get Null.
I hope I understand your question correctly. If you know the columns names you need one OPENJSON() call with explicit schema, but if you want to read the JSON structure from $.columns, you need a dynamic statement.
JSON:
DECLARE #json nvarchar(max) = N'{
"report": "Property ETL",
"id": 2648,
"columns": [
{
"name": "Fiscal Month",
"dataType": "int"
},
{
"name": "Fiscal Year",
"dataType": "int"
},
{
"name": "Portfolio",
"dataType": "varchar(50)"
},
{
"name": "Rent",
"dataType": "int"
}
],
"rows": [
{
"rowName": "1",
"type": "Detail",
"data": [
11,
2019,
"West Group",
10
]
},
{
"rowName": "2",
"type": "Detail",
"data": [
11,
2019,
"East Group",
10
]
},
{
"rowName": "3",
"type": "Detail",
"data": [
11,
2019,
"East Group",
10
]
},
{
"rowName": "Totals: ",
"type": "Total",
"data": [
null,
null,
null,
30
]
}
]
}'
Statement for fixed structure:
SELECT *
FROM OPENJSON(#json, '$.rows') WITH (
[Fiscal Month] int '$.data[0]',
[Fiscal Year] int '$.data[1]',
[Portfolio] varchar(50) '$.data[2]',
[Rent] int '$.data[3]'
)
Dynamic statement:
DECLARE #stm nvarchar(max) = N''
SELECT #stm = CONCAT(
#stm,
N',',
QUOTENAME(j2.name),
N' ',
j2.dataType,
N' ''$.data[',
j1.[key],
N']'''
)
FROM OPENJSON(#json, '$.columns') j1
CROSS APPLY OPENJSON(j1.value) WITH (
name varchar(50) '$.name',
dataType varchar(50) '$.dataType'
) j2
SELECT #stm = CONCAT(
N'SELECT * FROM OPENJSON(#json, ''$.rows'') WITH (',
STUFF(#stm, 1, 1, N''),
N')'
)
PRINT #stm
EXEC sp_executesql #stm, N'#json nvarchar(max)', #json
Result:
--------------------------------------------
Fiscal Month Fiscal Year Portfolio Rent
--------------------------------------------
11 2019 West Group 10
11 2019 East Group 10
11 2019 East Group 10
30
Yes, it is possible without temporary table:
DECLARE #json NVARCHAR(MAX) =
N'
{
"report": "Property ETL",
"id": 2648,
"columns": [
{
"name": "Fiscal Month",
"dataType": "int"
},
{
"name": "Fiscal Year",
"dataType": "int"
},
{
"name": "Portfolio",
"dataType": "varchar(50)"
},
{
"name": "Rent",
"dataType": "int"
}
],
"rows": [
{
"rowName": "1",
"type": "Detail",
"data": [
11,
2019,
"West Group",
10
]
},
{
"rowName": "2",
"type": "Detail",
"data": [
11,
2019,
"East Group",
10
]
},
{
"rowName": "3",
"type": "Detail",
"data": [
11,
2019,
"East Group",
10
]
},
{
"rowName": "Totals: ",
"type": "Total",
"data": [
null,
null,
null,
30
]
}
]
}
}';
And query:
SELECT s.value,
rowName = JSON_VALUE(s.value, '$.rowName'),
[type] = JSON_VALUE(s.value, '$.type'),
s2.[key],
s2.value
FROM OPENJSON(JSON_QUERY(#json, '$.rows')) s
CROSS APPLY OPENJSON(JSON_QUERY(s.value, '$.data')) s2;
db<>fiddle demo
Or as a single row per detail:
SELECT s.value,
rowName = JSON_VALUE(s.value, '$.rowName'),
[type] = JSON_VALUE(s.value, '$.type'),
JSON_VALUE(s.value, '$.data[0]') AS FiscalMonth,
JSON_VALUE(s.value, '$.data[1]') AS FiscalYear,
JSON_VALUE(s.value, '$.data[2]') AS Portfolio,
JSON_VALUE(s.value, '$.data[3]') AS Rent
FROM OPENJSON(JSON_QUERY(#json, '$.rows')) s;
db<>fiddle demo 2
I am trying to update several rows in SQL with JSON.
I'd like to match a primary key on a table row to an index nested in an array of JS objects.
Sample data:
let json = [{
"header": object_data,
"items": [{
"id": {
"i": 0,
"name": "item_id"
},
"meta": {
"data": object_data,
"text": "some_text"
}
}, {
"id": {
"i": 4,
"name": "item_id4"
},
"meta": {
"data": object_data,
"text": "some_text"
}
}, {
"id": {
"i": 17,
"name": "item_id17"
},
"meta": {
"data": object_data,
"text": "some_text"
}}]
}]
Sample table:
i | json | item_id
---+---------------------------+---------
0 | entire_object_at_index_0 | item_id
4 | entire_object_at_index_4 | item_id4
17 | entire_object_at_index_17 | item_id17
entire_object_at_index, meaning appending the item data to the header to create a new object for each row.
"header" "some_data",
"items": [{
"id": {
"i": 0,
"name": "item_id1"
},
"meta": {
"data": "some_data",
"text": "some_text"
}
}]
SQL:
update someTable set
json = json_value(#jsons, '$') -- not sure how to join on index here
item_id = json_value(#jsons, '$.items[?].id.name' -- not sure how to select by index here
where [i] = json_query(#jsons, '$.items.id.i')
The requirement to repeat the other properties complicates this a bit, because we need to build a new object explicitly. Even so it's not too hard:
update someTable
set
[json] = (
select (
select
"header" = json_query(#json, '$.header'),
"items" = json_query(N'[' + items.item + N']')
for json path, without_array_wrapper
)
),
item_id = items.item_id
from openjson(#json, '$.items') with (
item nvarchar(max) '$' as json,
item_id varchar(50) '$.id.name',
i int '$.id.i'
) items
join someTable on [someTable].i = items.i
Here I'm assuming the #json has already been unwrapped from its array, as your query seems to assume. If it's not, substitute $.[0] for $ in the outer query.
Update:
It's an attempt to improve my answer (I missed the header part of the JSON content in the original answer). Of course, the #JeroenMostert's answer is an excellent solution, so this is just another possible approach. Note, that if header part of JSON content is scalar value, you should use JSON_VALUE().
Table and JSON:
-- Table
CREATE TABLE #Data (
i int,
[json] nvarchar(max),
item_id nvarchar(100)
)
INSERT INTO #Data
(i, [json], [item_id])
VALUES
(0 , N'entire_object_at_index_0', N'item_id'),
(4 , N'entire_object_at_index_4', N'item_id4'),
(17, N'entire_object_at_index_17', N'item_id17')
-- JSON
DECLARE #json nvarchar(max) = N'[{
"header": {"key": "some_data"},
"items": [{
"id": {
"i": 0,
"name": "item_id"
},
"meta": {
"data": "some_data",
"text": "some_text"
}
}, {
"id": {
"i": 4,
"name": "item_id4"
},
"meta": {
"data": "some_data",
"text": "some_text"
}
}, {
"id": {
"i": 17,
"name": "item_id17"
},
"meta": {
"data": "some_data",
"text": "some_text"
}}]
}]'
Statement:
UPDATE #Data
SET #Data.Json = j.Json
FROM #Data
CROSS APPLY (
SELECT
JSON_QUERY(#json, '$[0].header') AS header,
JSON_QUERY(j.[value], '$') AS items
FROM OPENJSON(#json, '$[0].items') j
WHERE JSON_VALUE(j.[value], '$.id.i') = #Data.[i]
FOR JSON PATH, WITHOUT_ARRAY_WRAPPER
) j ([Json])
Original answer:
One possible approach is to use OPENJSON and appropriate join:
Table and JSON:
-- Table
CREATE TABLE #Data (
i int,
[json] nvarchar(max),
item_id nvarchar(100)
)
INSERT INTO #Data
(i, [json], [item_id])
VALUES
(0 , N'entire_object_at_index_0', N'item_id'),
(4 , N'entire_object_at_index_4', N'item_id4'),
(17, N'entire_object_at_index_17', N'item_id17')
-- JSON
DECLARE #json nvarchar(max) = N'[{
"header": "some_data",
"items": [{
"id": {
"i": 0,
"name": "item_id"
},
"meta": {
"data": "some_data",
"text": "some_text"
}
}, {
"id": {
"i": 4,
"name": "item_id4"
},
"meta": {
"data": "some_data",
"text": "some_text"
}
}, {
"id": {
"i": 17,
"name": "item_id17"
},
"meta": {
"data": "some_data",
"text": "some_text"
}}]
}]'
Statement:
UPDATE #Data
SET [json] = j.[value]
FROM #Data
LEFT JOIN (
SELECT
[value],
JSON_VALUE([value], '$.id.i') AS [i]
FROM OPENJSON(#json, '$[0].items')
) j ON (#Data.[i] = j.[i])
How to index (N1QL query in Couchbase) above document to speed up searching by SerialNumber field in nested array (doc => groups => items => item.SerialNumber)?
Sample:
{
"Id": "0012ed6e-41af-4e45-b53f-bac3b2eb0b82",
"Machine": "Machine2",
"Groups": [
{
"Id": "0fed9b14-fa38-e511-893a-001125665867",
"Name": "Name",
"Items": [
{
"Id": "64e69b14-fa38-e511-893a-001125665867",
"SerialNumber": "1504H365",
"Position": 73
},
{
"Id": "7be69b14-fa38-e511-893a-001125665867",
"SerialNumber": "1504H364",
"Position": 72
}
]
},
{
"Id": "0fed9b14-fa38-e511-893a-001125665867",
"Name": "Name",
"Items": [
{
"Id": "64e69b14-fa38-e511-893a-001125665867",
"SerialNumber": "1504H365",
"Position": 73
},
{
"Id": "7be69b14-fa38-e511-893a-001125665867",
"SerialNumber": "1504H364",
"Position": 72
}
]
}
]
}
my query:
CREATE INDEX idx_serial ON `aplikomp-bucket`
(ALL ARRAY(ALL ARRAY i.SerialNumber FOR i IN g.Items END ) FOR g In Groups END);
CREATE INDEX idx_serial ON `aplikomp-bucket` (DISTINCT ARRAY(DISTINCT ARRAY i.SerialNumber FOR i IN g.Items END ) FOR g In Groups END);
SELECT META().id FROM `aplikomp-bucket` AS a
WHERE ANY g IN a.Groups SATISFIES (ANY i IN g.Items SATISFIES i.SerialNumber > 123 END) END;