实现SQL Server 原生数据从XML生成JSON数据的实例代码

实现SQL Server 原生数据从XML生成JSON数据的实例代码

   SQL Server 是关系数据库,查询结果通常都是数据集,但是在一些特殊需求下,我们需要XML数据,最近这些年,JSON作为WebAPI常用的交换数据格式,那么数据库如何生成JSON数据呢?今天就写了一个DEMO.

       1.创建表及测试数据

SET NOCOUNT ON

IF OBJECT_ID('STATS') IS NOT NULL DROP TABLE STATS

IF OBJECT_ID('STATIONS') IS NOT NULL DROP TABLE STATIONS

IF OBJECT_ID('OPERATORS') IS NOT NULL DROP TABLE OPERATORS

IF OBJECT_ID('REVIEWS') IS NOT NULL DROP TABLE REVIEWS

-- Create and populate table with Station

CREATE TABLE STATIONS(ID INTEGER PRIMARY KEY, CITY NVARCHAR(20), STATE CHAR(2), LAT_N REAL, LONG_W REAL);

INSERT INTO STATIONS VALUES (13, 'Phoenix', 'AZ', 33, 112);

INSERT INTO STATIONS VALUES (44, 'Denver', 'CO', 40, 105);

INSERT INTO STATIONS VALUES (66, 'Caribou', 'ME', 47, 68);

-- Create and populate table with Operators

CREATE TABLE OPERATORS(ID INTEGER PRIMARY KEY, NAME NVARCHAR(20), SURNAME NVARCHAR(20));

INSERT INTO OPERATORS VALUES (50, 'John "The Fox"', 'Brown');

INSERT INTO OPERATORS VALUES (51, 'Paul', 'Smith');

INSERT INTO OPERATORS VALUES (52, 'Michael', 'Williams');

-- Create and populate table with normalized temperature and precipitation data

CREATE TABLE STATS (

STATION_ID INTEGER REFERENCES STATIONS(ID),

MONTH INTEGER CHECK (MONTH BETWEEN 1 AND 12),

TEMP_F REAL CHECK (TEMP_F BETWEEN -80 AND 150),

RAIN_I REAL CHECK (RAIN_I BETWEEN 0 AND 100), PRIMARY KEY (STATION_ID, MONTH));

INSERT INTO STATS VALUES (13, 1, 57.4, 0.31);

INSERT INTO STATS VALUES (13, 7, 91.7, 5.15);

INSERT INTO STATS VALUES (44, 1, 27.3, 0.18);

INSERT INTO STATS VALUES (44, 7, 74.8, 2.11);

INSERT INTO STATS VALUES (66, 1, 6.7, 2.10);

INSERT INTO STATS VALUES (66, 7, 65.8, 4.52);

-- Create and populate table with Review

CREATE TABLE REVIEWS(STATION_ID INTEGER,STAT_MONTH INTEGER,OPERATOR_ID INTEGER)

insert into REVIEWS VALUES (13,1,50)

insert into REVIEWS VALUES (13,7,50)

insert into REVIEWS VALUES (44,7,51)

insert into REVIEWS VALUES (44,7,52)

insert into REVIEWS VALUES (44,7,50)

insert into REVIEWS VALUES (66,1,51)

insert into REVIEWS VALUES (66,7,51)

2.查询结果集

select STATIONS.ID as ID,

STATIONS.CITY as City,

STATIONS.STATE as State,

STATIONS.LAT_N as LatN,

STATIONS.LONG_W as LongW,

STATS.MONTH as Month,

STATS.RAIN_I as Rain,

STATS.TEMP_F as Temp,

OPERATORS.NAME as Name,

OPERATORS.SURNAME as Surname

from stations

inner join stats on stats.STATION_ID=STATIONS.ID

left join reviews on reviews.STATION_ID=stations.id

and reviews.STAT_MONTH=STATS.[MONTH]

left join OPERATORS on OPERATORS.ID=reviews.OPERATOR_ID

结果:

2.查询xml数据

select stations.*,

(select stats.*,

(select OPERATORS.*

from OPERATORS

inner join reviews on OPERATORS.ID=reviews.OPERATOR_ID

where reviews.STATION_ID=STATS.STATION_ID

and reviews.STAT_MONTH=STATS.MONTH

for xml path('operator'),type

) operators

from STATS

where STATS.STATION_ID=stations.ID

for xml path('stat'),type

) stats

from stations

for xml path('station'),type

结果:

<station>

<ID>13</ID>

<CITY>Phoenix</CITY>

<STATE>AZ</STATE>

<LAT_N>3.3000000e+001</LAT_N>

<LONG_W>1.1200000e+002</LONG_W>

<stats>

<stat>

<STATION_ID>13</STATION_ID>

<MONTH>1</MONTH>

<TEMP_F>5.7400002e+001</TEMP_F>

<RAIN_I>3.1000000e-001</RAIN_I>

<operators>

<operator>

<ID>50</ID>

<NAME>John "The Fox"</NAME>

<SURNAME>Brown</SURNAME>

</operator>

</operators>

</stat>

<stat>

<STATION_ID>13</STATION_ID>

<MONTH>7</MONTH>

<TEMP_F>9.1699997e+001</TEMP_F>

<RAIN_I>5.1500001e+000</RAIN_I>

<operators>

<operator>

<ID>50</ID>

<NAME>John "The Fox"</NAME>

<SURNAME>Brown</SURNAME>

</operator>

</operators>

</stat>

</stats>

</station>

<station>

<ID>44</ID>

<CITY>Denver</CITY>

<STATE>CO</STATE>

<LAT_N>4.0000000e+001</LAT_N>

<LONG_W>1.0500000e+002</LONG_W>

<stats>

<stat>

<STATION_ID>44</STATION_ID>

<MONTH>1</MONTH>

<TEMP_F>2.7299999e+001</TEMP_F>

<RAIN_I>1.8000001e-001</RAIN_I>

</stat>

<stat>

<STATION_ID>44</STATION_ID>

<MONTH>7</MONTH>

<TEMP_F>7.4800003e+001</TEMP_F>

<RAIN_I>2.1099999e+000</RAIN_I>

<operators>

<operator>

<ID>51</ID>

<NAME>Paul</NAME>

<SURNAME>Smith</SURNAME>

</operator>

<operator>

<ID>52</ID>

<NAME>Michael</NAME>

<SURNAME>Williams</SURNAME>

</operator>

<operator>

<ID>50</ID>

<NAME>John "The Fox"</NAME>

<SURNAME>Brown</SURNAME>

</operator>

</operators>

</stat>

</stats>

</station>

<station>

<ID>66</ID>

<CITY>Caribou</CITY>

<STATE>ME</STATE>

<LAT_N>4.7000000e+001</LAT_N>

<LONG_W>6.8000000e+001</LONG_W>

<stats>

<stat>

<STATION_ID>66</STATION_ID>

<MONTH>1</MONTH>

<TEMP_F>6.6999998e+000</TEMP_F>

<RAIN_I>2.0999999e+000</RAIN_I>

<operators>

<operator>

<ID>51</ID>

<NAME>Paul</NAME>

<SURNAME>Smith</SURNAME>

</operator>

</operators>

</stat>

<stat>

<STATION_ID>66</STATION_ID>

<MONTH>7</MONTH>

<TEMP_F>6.5800003e+001</TEMP_F>

<RAIN_I>4.5200000e+000</RAIN_I>

<operators>

<operator>

<ID>51</ID>

<NAME>Paul</NAME>

<SURNAME>Smith</SURNAME>

</operator>

</operators>

</stat>

</stats>

</station>

3.如何生成JSON数据

1)创建辅助函数

CREATE FUNCTION [dbo].[qfn_XmlToJson](@XmlData xml)

RETURNS nvarchar(max)

AS

BEGIN

declare @m nvarchar(max)

SELECT @m='['+Stuff

(

(SELECT theline from

(SELECT ','+' {'+Stuff

(

(SELECT ',"'+coalesce(b.c.value('local-name(.)', 'NVARCHAR(255)'),'')+'":'+

case when b.c.value('count(*)','int')=0

then dbo.[qfn_JsonEscape](b.c.value('text()[1]','NVARCHAR(MAX)'))

else dbo.qfn_XmlToJson(b.c.query('*'))

end

from x.a.nodes('*') b(c)

for xml path(''),TYPE).value('(./text())[1]','NVARCHAR(MAX)')

,1,1,'')+'}'

from @XmlData.nodes('/*') x(a)

) JSON(theLine)

for xml path(''),TYPE).value('.','NVARCHAR(MAX)')

,1,1,'')+']'

return @m

END

CREATE FUNCTION [dbo].[qfn_JsonEscape](@value nvarchar(max) )

returns nvarchar(max)

as begin

if (@value is null) return 'null'

if (TRY_PARSE( @value as float) is not null) return @value

set @value=replace(@value,'\','\\')

set @value=replace(@value,'"','\"')

return '"'+@value+'"'

end

3)查询sql

select dbo.qfn_XmlToJson

(

(

select stations.ID,stations.CITY,stations.STATE,stations.LAT_N,stations.LONG_W ,

(select stats.*,

(select OPERATORS.*

from OPERATORS inner join reviews

on OPERATORS.ID=reviews.OPERATOR_ID

where reviews.STATION_ID=STATS.STATION_ID

and reviews.STAT_MONTH=STATS.MONTH

for xml path('operator'),type

) operators

from STATS

where STATS.STATION_ID=stations.ID for xml path('stat'),type

) stats

from stations for xml path('stations'),type

)

)

结果:

[ {"ID":13,"CITY":"Phoenix","STATE":"AZ","LAT_N":3.3000000e+001,"LONG_W"

:1.1200000e+002,"stats":[ {"STATION_ID":13,"MONTH":1,"TEMP_F":5.7400002e+001,"

RAIN_I":3.1000000e-001,"operators":[ {"ID":50,"NAME":"John \"The Fox\"","SURNAME":"Brown"}]},

{"STATION_ID":13,"MONTH":7,"TEMP_F":9.1699997e+001,"RAIN_I":5.1500001e+000,"operators":

[ {"ID":50,"NAME":"John \"The Fox\"","SURNAME":"Brown"}]}]}, {"ID":44,"CITY":"Denver",

"STATE":"CO","LAT_N":4.0000000e+001,"LONG_W":1.0500000e+002,"stats":[ {"STATION_ID":44,

"MONTH":1,"TEMP_F":2.7299999e+001,"RAIN_I":1.8000001e-001}, {"STATION_ID":44,"MONTH":7,

"TEMP_F":7.4800003e+001,"RAIN_I":2.1099999e+000,"operators":[ {"ID":51,"NAME":"Paul",

"SURNAME":"Smith"}, {"ID":52,"NAME":"Michael","SURNAME":"Williams"}, {"ID":50,"NAME"

:"John \"The Fox\"","SURNAME":"Brown"}]}]}, {"ID":66,"CITY":"Caribou","STATE":"ME","LAT_N":

4.7000000e+001,"LONG_W":6.8000000e+001,"stats":[ {"STATION_ID":66,"MONTH":1,"TEMP

_F":6.6999998e+000,"RAIN_I":2.0999999e+000,"operators":[ {"ID":51,"NAME":"Paul","

SURNAME":"Smith"}]}, {"STATION_ID":66,"MONTH":7,"TEMP_F":6.5800003e+001,"RAIN_I":

4.5200000e+000,"operators":[ {"ID":51,"NAME":"Paul","SURNAME":"Smith"}]}]}]

总结:

JSON作为灵活的Web通信交换架构,如果把配置数据存放在数据库中,直接获取JSON,那配置就会非常简单了,也能够大量减轻应用服务器的压力!

感谢阅读,希望能帮助到大家,谢谢大家对本站的支持!

以上是 实现SQL Server 原生数据从XML生成JSON数据的实例代码 的全部内容, 来源链接: utcz.com/z/333716.html

回到顶部