我有一个要求，我在数据库中有nvarchar列，我需要从数据库中以行和列的形式提取。
我的nvarchar就像
{
"notifications": [
{
"apMacAddress": "20:50:7a:09:5t:30",
"associated": false,
"band": "IEEE_802_11_A",
"confidenceFactor": 192,
"deviceId": "34:f4:23:23:f4:wr",
"entity": "Wired",
"eventId": 2343434,
"floorId": 3244234234234,
"floorRefId": 234235465234,
"geoCoordinate": {
"latitude": -999.0,
"longitude": -999.0,
"unit": "DEGREES"
},
"ipAddress": [
"23.423.23.234"
],
"lastSeen": "2018-02-09T12:24:53.512+0000",
"locationCoordinate": {
"x": 423.2342,
"y": 23.423,
"z": 0.0,
"unit": "FEET"
},
"locationMapHierarchy": "North Campus>North SIde>F4>F4 Academies ",
"manufacturer": "Sony Corporate",
"maxDetectedRssi": {
"antennaIndex": 0,
"apMacAddress": "234:23:56d:45d:5f:20",
"band": "IEEE_802_11_B",
"lastHeardInSeconds": 23,
"rssi": -54,
"slot": 2
},
"notificationType": "locationupdate",
"rawLocation": {
"RawX": 0.0,
"RawY": 0.0,
"Unit": null
},
"ssid": "aide",
"subscriptionName": " Lab Location",
"tagVendorData": null,
"timestamp": 2343657436,
"username": "abc.gmail.com"
}
]
}
我希望数据像单独的列一样被提取
以下是列名列表
- apMacAddress
- associated
- band
- confidenceFactor
- deviceId
- entity
- eventId
- floorId
- floorRefId
- latitude
- longitude
- unit
- ipAddress
- lastSeen
- X
- Y
- Z
- Unit
- locationMapHierarchy
- manufacturer
- antennaIndex
- apMacAddress
- band
- lastHeardInSeconds
- rssi
- slot
- notificationType
- RawX
- RawY
- Unit
- ssid
- subscriptionName
- tagVendorData
- timestamp
- username
有没有办法在SQL中执行此操作？
答案 0 :(得分：3)
这不是非结构化数据，即JSON数据，一种结构化格式。您无法通过字符串拆分来解析JSON。 SQL Server 2016添加了JSON支持，如Work with JSON data in SQL Server
所示您可以使用OPENJSON函数解析数据并通过指定其路径来提取属性，例如：
DECLARE @json NVARCHAR(MAX)
SET @json =
N'{"notifications":[{"apMacAddress":"20:50:7a:09:5t:30","associated":false,"band":"IEEE_802_11_A","confidenceFactor":192,"deviceId":"34:f4:23:23:f4:wr","entity":"Wired","eventId":2343434,"floorId":3244234234234,"floorRefId":234235465234,"geoCoordinate":{"latitude":-999.0,"longitude":-999.0,"unit":"DEGREES"},"ipAddress":["23.423.23.234"],"lastSeen":"2018-02-09T12:24:53.512+0000","locationCoordinate":{"x":423.2342,"y":23.423,"z":0.0,"unit":"FEET"},"locationMapHierarchy":"North Campus>North SIde>F4>F4 Academies ","manufacturer":"Sony Corporate","maxDetectedRssi":{"antennaIndex":0,"apMacAddress":"234:23:56d:45d:5f:20","band":"IEEE_802_11_B","lastHeardInSeconds":23,"rssi":-54,"slot":2},"notificationType":"locationupdate","rawLocation":{"RawX":0.0,"RawY":0.0,"Unit":null},"ssid":"aide","subscriptionName":" Lab Location","tagVendorData":null,"timestamp":2343657436,"username":"abc.gmail.com"}]}'
SELECT *
FROM OPENJSON(@json, '$.notifications')
with (
apMacAddress nvarchar(500) '$.apMacAddress',
associated bit '$.associated',
band nvarchar(50) '$.band'
)
这将返回：
apMacAddress associated band
20:50:7a:09:5t:30 0 IEEE_802_11_A
要解析嵌套结构，您需要使用AS JSON子句提取结构，并使用CROSS APPLY再次对其应用OPENJSON，例如：
SELECT apMacAddress,associated,band,latitude,longitude
FROM OPENJSON(@json, '$.notifications')
with (
apMacAddress nvarchar(500) '$.apMacAddress',
associated bit '$.associated',
band nvarchar(50) '$.band',
geoCoordinate nvarchar(max) AS JSON
)
CROSS APPLY OPENJSON(geoCoordinate) with (
latitude decimal(5,2) '$.latitude',
longitude decimal(5,2) '$.longitude'
)
将返回：
apMacAddress associated band latitude longitude
20:50:7a:09:5t:30 0 IEEE_802_11_A -999.00 -999.00
在早期版本中，您必须在将JSON字符串插入数据库之前解析它们，例如使用JSON.NET，这是.NET最流行的JSON解析器。
虽然早期版本有一些JSON解析器实现，例如this one，但它们很复杂，速度慢且难以使用
更新
要清楚，OPENJSON是一个像任何其他表值函数一样的函数，例如STRING_SPLIT。这意味着它可以使用CROSS APPLY：
SELECT *
from SomeTable
CROSS APPLY OPENJSON(SomeTable.MyJsonField, '$.notifications')
with (
apMacAddress nvarchar(500) '$.apMacAddress',
associated bit '$.associated',
band nvarchar(50) '$.band',
geoCoordinate nvarchar(max) AS JSON
)
CROSS APPLY OPENJSON(geoCoordinate)
with (
latitude decimal(5,2) '$.latitude',
longitude decimal(5,2) '$.longitude'
)
要提取更多嵌套结构，必须在顶部提取它们，然后使用OPENJSON解析，就像geoCoordinate一样：
SELECT apMacAddress,associated,band,latitude,longitude ,x,y
FROM OPENJSON(@json, '$.notifications')
with (
apMacAddress nvarchar(500) '$.apMacAddress',
associated bit '$.associated',
band nvarchar(50) '$.band',
geoCoordinate nvarchar(max) AS JSON,
locationCoordinate nvarchar(max) AS JSON
)
CROSS APPLY OPENJSON(geoCoordinate)
with (
latitude decimal(5,2) '$.latitude',
longitude decimal(5,2) '$.longitude'
)
CROSS APPLY OPENJSON(locationCoordinate) with (
x decimal(5,2) '$.x',
y decimal(5,2) '$.y'
)
将返回locationCoordinate.x和locationCoordinate.y值：
apMacAddress associated band latitude longitude x y
20:50:7a:09:5t:30 0 IEEE_802_11_A -999.00 -999.00 423.23 23.42
答案 1 :(得分：1)
除了Panagiotis Kanavos回复之外，假设您正在使用SQL Server 2016及更高版本（兼容级别130），您可以使用OPENJSON函数。
另一个假设是你的Json结构将不改变 您可以使用以下内容将元素解析为列
<强> UPDATE（!!）
SET NOCOUNT ON
IF OBJECT_ID ('tempdb..##DataSet') IS NOT NULL DROP TABLE ##DataSet
DECLARE @Table TABLE (Id int identity (1,1) , JsonCol NVARCHAR(MAX))
INSERT INTO @Table (JsonCol)
VALUES ('{
"notifications": [
{
"apMacAddress": "20:50:7a:09:5t:30",
"associated": false,
"band": "IEEE_802_11_A",
"confidenceFactor": 192,
"deviceId": "34:f4:23:23:f4:wr",
"entity": "Wired",
"eventId": 2343434,
"floorId": 3244234234234,
"floorRefId": 234235465234,
"geoCoordinate": {
"latitude": -888.0,
"longitude": -888.0,
"unit": "DEGREES"
},
"ipAddress": [
"23.423.23.234"
],
"lastSeen": "2018-02-09T12:24:53.512+0000",
"locationCoordinate": {
"x": 423.2342,
"y": 23.423,
"z": 0.0,
"unit": "FEET"
},
"locationMapHierarchy": "North Campus>North SIde>F4>F4 Academies ",
"manufacturer": "Sony Corporate",
"maxDetectedRssi": {
"antennaIndex": 0,
"apMacAddress": "234:23:56d:45d:5f:20",
"band": "IEEE_802_11_B",
"lastHeardInSeconds": 23,
"rssi": -54,
"slot": 2
},
"notificationType": "locationupdate",
"rawLocation": {
"RawX": 0.0,
"RawY": 0.0,
"Unit": null
},
"ssid": "aide",
"subscriptionName": " Lab Location",
"tagVendorData": null,
"timestamp": 2343657436,
"username": "abc.gmail.com"
}
]
}'),
('{
"notifications": [
{
"apMacAddress": "20:50:7a:09:5t:30",
"associated": false,
"band": "IEEE_802_11_A",
"confidenceFactor": 192,
"deviceId": "34:f4:23:23:f4:wr",
"entity": "Wired",
"eventId": 2343434,
"floorId": 3244234234234,
"floorRefId": 234235465234,
"geoCoordinate": {
"latitude": -999.0,
"longitude": -999.0,
"unit": "DEGREES"
},
"ipAddress": [
"23.423.23.234"
],
"lastSeen": "2018-02-09T12:24:53.512+0000",
"locationCoordinate": {
"x": 423.2342,
"y": 23.423,
"z": 0.0,
"unit": "FEET"
},
"locationMapHierarchy": "North Campus>North SIde>F4>F4 Academies ",
"manufacturer": "Sony Corporate",
"maxDetectedRssi": {
"antennaIndex": 0,
"apMacAddress": "234:23:56d:45d:5f:20",
"band": "IEEE_802_11_B",
"lastHeardInSeconds": 23,
"rssi": -54,
"slot": 2
},
"notificationType": "locationupdate",
"rawLocation": {
"RawX": 0.0,
"RawY": 0.0,
"Unit": null
},
"ssid": "aide",
"subscriptionName": " Lab Location",
"tagVendorData": null,
"timestamp": 2343657436,
"username": "abc.gmail.com"
}
]
}')
,(
'{
"notifications": [
{
"apMacAddress": "20:50:7a:09:5t:30",
"associated": false,
"band": "IEEE_802_11_A",
"confidenceFactor": 192,
"deviceId": "34:f4:23:23:f4:wr",
"entity": "Wired",
"eventId": 2343434,
"floorId": 3244234234234,
"floorRefId": 234235465234,
"geoCoordinate": {
"latitude": -777.0,
"longitude": -777.0,
"unit": "DEGREES"
},
"ipAddress": [
"23.423.23.234"
],
"lastSeen": "2018-02-09T12:24:53.512+0000",
"locationCoordinate": {
"x": 423.2342,
"y": 23.423,
"z": 0.0,
"unit": "FEET"
},
"locationMapHierarchy": "North Campus>North SIde>F4>F4 Academies ",
"manufacturer": "Sony Corporate",
"maxDetectedRssi": {
"antennaIndex": 0,
"apMacAddress": "234:23:56d:45d:5f:20",
"band": "IEEE_802_11_B",
"lastHeardInSeconds": 23,
"rssi": -54,
"slot": 2
},
"notificationType": "locationupdate",
"rawLocation": {
"RawX": 0.0,
"RawY": 0.0,
"Unit": null
},
"ssid": "aide",
"subscriptionName": " Lab Location",
"tagVendorData": null,
"timestamp": 2343657436,
"username": "abc.gmail.com"
}
]
}'
)
;WITH BrkJson as
(
SELECT *
FROM @Table
CROSS APPLY OPENJSON (JsonCol, '$.notifications[0]') R
)
,Dataset as
(
SELECT Id, [key] , [value]
FROM BrkJson
WHERE [type] != 5 /*Array*/
UNION ALL
SELECT b.Id ,b.[Key] +'_'+ t.[key] [key] , t.[value]
FROM BrkJson b
CROSS APPLY OPENJSON (value) t
WHERE b.[type] = 5
)
SELECT *
INTO ##DataSet
FROM Dataset
DECLARE @cols NVARCHAR(MAX)=''
DECLARE @pvt NVARCHAR(MAX)
SELECT @cols +=','+ QUOTENAME([key])
FROM ##DataSet
GROUP BY [key]
SET @cols = STUFF(@cols,1,1,'')
--PRINT @cols
SET @pvt =
'SELECT *
FROM ##DataSet
PIVOT
(
MAX([value]) FOR [key] in ('+@cols+')
) e
'
EXEC sp_executesql @Pvt
DROP TABLE ##DataSet