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我们需要编写一个适用于任何提供XML输出的API的API解析器.
我们不会事先知道XML结构.
该解决方案应转换XML文件并将其保存在通用tsql表中,并将XML元素/属性名称作为第一行.
所以基本上它是任何API的XML反序列化器.
我们不能将任何第三方dll用于我们的C#类.
我不知道C#所以不知道它是否可能.但我已经能够使用OPENXML在tsql中编写一个genric XML->行转换器. tsql解决方案的问题是我们无法将巨大的XML文件成功导入数据库.
我可以提供所需的任何细节.请在评论/答案中告诉我.
我不希望任何人为我编写代码,任何合适的指针就足够了
资源：
JSON
[
{
"id" : 21953,"mainReqIdentity" : "xxxx","itemName" : "xxxx","kanbanPhase" : "xxxx","kanbanStatus" : "xxxx","backlogItemType" : "xxxx","identityDomain" : "xxxx","fromDatetime" : "2016-08-05 17:52:34","teams" : [],"releases" : [{
"id" : 1229,"release_name" : "xxxx","release_connection_type" : "xxxx"
}
],"fpReleases" : [],"sources" : [{
"sourceName" : "xxxx","sourceRecordUrl" : "xxxx","sourceRecordIdentity" : "xxxx"
}
],"productNumbers" : [],"tags" : [],"productComponents" : [],"ranPlatforms" : [],"subReleases" : [],"requirementAreaId" : xxxx,"requirementArea" : "xxxx","toBeHandledAtxxxx" : "xxxx"
},{
"id" : 22014,"releases" : [{
"id" : xxxx,"f0Date" : "2015-10-01","f1Date" : "2015-10-01","f2Date" : "2016-02-01","f4Date" : "2016-03-31","fgDate" : "2016-04-29","toBeHandledAtxxxx" : "xxxx"
}
]
XML：2个样本
样品1
<root type="array">
<id type="number">21286</id>
<mainReqIdentity type="string">xxxxxx</mainReqIdentity>
<itemName type="string">xxxxxx</itemName>
<kanbanPhase type="string">xxxxxx</kanbanPhase>
<kanbanStatus type="string">xxxxxx</kanbanStatus>
<kanbanNote type="string">xxxxxx</kanbanNote>
<backlogItemType type="string">xxxxxx</backlogItemType>
<identityDomain type="string">xxxxxx</identityDomain>
<fromDatetime type="string">2016-08-23 17:01:52</fromDatetime>
<teams type="array">
<item type="object">
<team_name type="string">xxxxxx</team_name>
<preliminary type="boolean">xxxxxx</preliminary>
</item>
</teams>
<releases type="array">
<item type="object">
<id type="number">xxxxxx</id>
<release_name type="string">xxxxxx</release_name>
<release_connection_type type="string">xxxxxx</release_connection_type>
</item>
</releases>
<fpReleases type="array">
</fpReleases>
<sources type="array">
<item type="object">
<sourceName type="string">xxxxxx</sourceName>
<sourceRecordUrl type="string">xxxxxx</sourceRecordUrl>
</item>
</sources>
<productNumbers type="array">
</productNumbers>
<tags type="array">
</tags>
<productComponents type="array">
</productComponents>
<ranPlatforms type="array">
</ranPlatforms>
<subReleases type="array">
</subReleases>
<requirementAreaId type="number">xxxxxx</requirementAreaId>
<requirementArea type="string">xxxxxx</requirementArea>
<itemContact type="string">xxxxxx</itemContact>
<toBeHandledAtxxx type="string">xxxxxx</toBeHandledAtLuca>
</item>
<item type="object">
<id type="number">xxxxxx</id>
<mainReqIdentity type="string">xxxxxx</mainReqIdentity>
<itemName type="string">xxxxxx</itemName>
<kanbanPhase type="string">xxxxxx</kanbanPhase>
<kanbanStatus type="string">xxxxxx</kanbanStatus>
<kanbanNote type="string">xxxxxx</kanbanNote>
<backlogItemType type="string">xxxxxx</backlogItemType>
<identityDomain type="string">xxxxxx</identityDomain>
<fromDatetime type="string">2016-08-23 17:01:52</fromDatetime>
<teams type="array">
<item type="object">
<team_name type="string">xxxxxx</team_name>
<preliminary type="boolean">xxxxxx</preliminary>
</item>
</teams>
<releases type="array">
<item type="object">
<id type="number">xxxxxx</id>
<release_name type="string">xxxxxx</release_name>
<release_connection_type type="string">xxxxxx</release_connection_type>
</item>
</releases>
<fpReleases type="array">
</fpReleases>
<sources type="array">
<item type="object">
<sourceName type="string">xxxxxx</sourceName>
<sourceRecordUrl type="string">xxxxxx</sourceRecordUrl>
</item>
</sources>
<productNumbers type="array">
</productNumbers>
<tags type="array">
</tags>
<productComponents type="array">
</productComponents>
<ranPlatforms type="array">
</ranPlatforms>
<subReleases type="array">
</subReleases>
<requirementAreaId type="number">xxxxxx</requirementAreaId>
<requirementArea type="string">xxxxxx</requirementArea>
<oaResultReference type="string">xxxxxx</oaResultReference>
<itemContact type="string">xxxxxx</itemContact>
<f0Date type="string">2014-10-17</f0Date>
<f1Date type="string">2015-01-16</f1Date>
<f2Date type="string">2015-02-13</f2Date>
<f4Date type="string">2015-06-12</f4Date>
<faDate type="string">2015-06-12</faDate>
<fgDate type="string">2015-06-12</fgDate>
<toBeHandledAtxxx type="string">xxxxxx</toBeHandledAtLuca>
</item>
</root>
样本2
<ROOT>
<Customer CustomerID="VINET" ContactName="Paul Henriot">
<Order CustomerID="VINET" EmployeeID="5" OrderDate="1996-07-04T00:00:00">
<OrderDetail OrderID="10248" ProductID="11" Quantity="12"/>
<OrderDetail OrderID="10248" ProductID="42" Quantity="10"/>
</Order>
</Customer>
<Customer CustomerID="LILAS" ContactName="Carlos Gonzlez">
<Order CustomerID="LILAS" EmployeeID="3" OrderDate="1996-08-16T00:00:00">
<OrderDetail OrderID="10283" ProductID="72" Quantity="3"/>
</Order>
</Customer>
</ROOT>
sql
通用登台表
create table ZZZZZZZZZ ( api_id int,record_type char(1),record_id INT,last_run_time datetime,last_run_by varchar(500),col1 VARCHAR(500),col2 VARCHAR(500),col3 VARCHAR(500),col4 VARCHAR(500),col5 VARCHAR(500),col6 VARCHAR(500),col7 VARCHAR(500),col8 VARCHAR(500),col9 VARCHAR(500),col10 VARCHAR(500),col11 VARCHAR(500),col12 VARCHAR(500),col13 VARCHAR(500),col14 VARCHAR(500),col15 VARCHAR(500),col16 VARCHAR(500),col17 VARCHAR(500),col18 VARCHAR(500),col19 VARCHAR(500),col20 VARCHAR(500),col21 VARCHAR(500),col22 VARCHAR(500),col23 VARCHAR(500),col24 VARCHAR(500),col25 VARCHAR(500),col26 VARCHAR(500),col27 VARCHAR(500),col28 VARCHAR(500),col29 VARCHAR(500),col30 VARCHAR(500),col31 VARCHAR(500),col32 VARCHAR(500),col33 VARCHAR(500),col34 VARCHAR(500),col35 VARCHAR(500),col36 VARCHAR(500),col37 VARCHAR(500),col38 VARCHAR(500),col39 VARCHAR(500),col40 VARCHAR(500),col41 VARCHAR(500),col42 VARCHAR(500),col43 VARCHAR(500),col44 VARCHAR(500),col45 VARCHAR(500),col46 VARCHAR(500),col47 VARCHAR(500),col48 VARCHAR(500),col49 VARCHAR(500),col50 VARCHAR(500),col51 VARCHAR(500),col52 VARCHAR(500),col53 VARCHAR(500),col54 VARCHAR(500),col55 VARCHAR(500),col56 VARCHAR(500),col57 VARCHAR(500),col58 VARCHAR(500),col59 VARCHAR(500),col60 VARCHAR(500),col61 VARCHAR(500),col62 VARCHAR(500),col63 VARCHAR(500),col64 VARCHAR(500),col65 VARCHAR(500),col66 VARCHAR(500),col67 VARCHAR(500),col68 VARCHAR(500),col69 VARCHAR(500),col70 VARCHAR(500),col71 VARCHAR(500),col72 VARCHAR(500),col73 VARCHAR(500),col74 VARCHAR(500),col75 VARCHAR(500),col76 VARCHAR(500),col77 VARCHAR(500),col78 VARCHAR(500),col79 VARCHAR(500),col80 VARCHAR(500),col81 VARCHAR(500),col82 VARCHAR(500),col83 VARCHAR(500),col84 VARCHAR(500),col85 VARCHAR(500),col86 VARCHAR(500),col87 VARCHAR(500),col88 VARCHAR(500),col89 VARCHAR(500),col90 VARCHAR(500),col91 VARCHAR(500),col92 VARCHAR(500),col93 VARCHAR(500),col94 VARCHAR(500),col95 VARCHAR(500),col96 VARCHAR(500),col97 VARCHAR(500),col98 VARCHAR(500),col99 VARCHAR(500),col100 VARCHAR(500),col101 VARCHAR(500),col102 VARCHAR(500),col103 VARCHAR(500),col104 VARCHAR(500),col105 VARCHAR(500),col106 VARCHAR(500),col107 VARCHAR(500),col108 VARCHAR(500),col109 VARCHAR(500),col110 VARCHAR(500),col111 VARCHAR(500),col112 VARCHAR(500),col113 VARCHAR(500),col114 VARCHAR(500),col115 VARCHAR(500),col116 VARCHAR(500),col117 VARCHAR(500),col118 VARCHAR(500),col119 VARCHAR(500),col120 VARCHAR(500),col121 VARCHAR(500),col122 VARCHAR(500),col123 VARCHAR(500),col124 VARCHAR(500),col125 VARCHAR(500),col126 VARCHAR(500),col127 VARCHAR(500),col128 VARCHAR(500),col129 VARCHAR(500),col130 VARCHAR(500),col131 VARCHAR(500),col132 VARCHAR(500),col133 VARCHAR(500),col134 VARCHAR(500),col135 VARCHAR(500),col136 VARCHAR(500),col137 VARCHAR(500),col138 VARCHAR(500),col139 VARCHAR(500),col140 VARCHAR(500),col141 VARCHAR(500),col142 VARCHAR(500),col143 VARCHAR(500),col144 VARCHAR(500),col145 VARCHAR(500),col146 VARCHAR(500),col147 VARCHAR(500),col148 VARCHAR(500),col149 VARCHAR(500),col150 VARCHAR(500) )
样本输出
用Tsql编写的通用XML解析器.代码中有很少的hacks和一些需要删除的杂散代码.这很好用.但问题是通过直接调用或通过文件从C#代码发送整个XML文档作为输入参数.
CREATE PROC ZZZZZZZ
(
@in_api_id int,@in_xml_doc XML,@in_xml_root varchar(100),@in_tot_result_col int = 150,@in_need_colnm_result CHAR(1) = 'Y',@in_debug_flg CHAR(1) = 'N'
)
AS
BEGIN
DECLARE
@idoc int,@sqlstr nvarchar(max) = '',@param nvarchar(200) = '',@runtime datetime = getdate(),@runby varchar(30) = suser_name(),@cnt int,@pre_stg_col_nm varchar(max) = '',@max_lvl int,@max_node varchar(500)='',@max_node_wo_slash varchar(500)='',@xml_col nvarchar(max) = '',@unq_col nvarchar(max) = '',@unq_xml_col nvarchar(max)=''
--Create an internal representation of the XML document.
EXEC sp_xml_preparedocument @idoc OUTPUT,@in_xml_doc;
-- Execute a SELECT statement that uses the OPENXML rowset provider.
set @in_xml_root = concat('/',@in_xml_root)
SELECT * into #tmp FROM OPENXML (@idoc,@in_xml_root,2) where id <> 0;
--select * from #tmp_xml_nodes
--select * from #tmp
--select * from #tmp_pre_staging
;with xml_cte(id,parentid,nodetype,localname,prefix,namespaceuri,datatype,prev,text,lvl,node,parent_localname)
AS
(
select id,1 as lvl,cast(CONCAT(@in_xml_root,'/',localname) as varchar(100)) node,cast('' as varchar(200))
from #tmp
where parentid = 0
UNION all
select t.id,t.parentid,t.nodetype,t.localname,t.prefix,t.namespaceuri,t.datatype,t.prev,t.text,iif(t.nodetype = 1,xc.lvl+1,xc.lvl),cast(
CONCAT (
xc.node,CONCAT (
'/',t.localname
),''
)
) AS VARCHAR(100)
),cast(xc.localname as varchar(200))
from #tmp t
inner join xml_cte xc
on xc.id = t.parentid
)
select * into #xmlcte from xml_cte
--select * from #xmlcte
--v2 change
select @max_lvl = max(lvl)--iif(max(lvl)>=4,1,0) -- the iif condition is just a hack,I dont kNow why it works
from #xmlcte
select
@max_node = concat(max(node),'/'),@max_node_wo_slash = max(node)
from #xmlcte
where lvl = @max_lvl
select *,concat(parent_localname,'_',' varchar(500)') fnl_col_nm,case
when lvl<@max_lvl then concat(replicate('../',@max_lvl-lvl+iif(nodetype=1,0)),iif(nodetype=1,'','@'),localname) --v2 change
when lvl>@max_lvl then concat(replace(node,@max_node,''),'/@'),localname)--v2 change
else concat('../','/@')),localname)--v2 change
end col_Struct,localname) col_unq_nm,ROW_NUMBER() over (order by(select 100)) sno,concat('xmlname.value(''/Names[1]/name[',ROW_NUMBER() over (order by(select 100)),']'',''varchar(500)'') AS ',localname)) col_splt_nm
into #xml_col_struct
from #xmlcte
where nodetype <= 2--v2 change
--select * from #xml_col_struct
set @cnt = (select count(distinct col_unq_nm) from #xml_col_struct)
select @pre_stg_col_nm =
(
select concat(',',COLUMN_NAME)
from informatION_SCHEMA.COLUMNS
where table_name = 'ZZZZZZ'
and COLUMN_NAME like 'col%'
and ORDINAL_POSITION <= @cnt+5
order by ORDINAL_POSITION
for xml path('')
)
set @sqlstr = concat(
'insert into ZZZZZ(api_id,record_type,record_id,last_run_time,last_run_by',@pre_stg_col_nm,')'
)
select @xml_col =
(
select distinct concat(',fnl_col_nm,' ''',col_Struct,'''',char(10))
from #xml_col_struct
order by 1
for xml path('')
)
set @xml_col = stuff(@xml_col,'')
select @unq_col =
(
select distinct concat(',col_unq_nm )
from #xml_col_struct
order by 1
for xml path('')
)
set @unq_col = stuff(@unq_col,'')
select @in_tot_result_col = @in_tot_result_col - count(distinct col_unq_nm)
from #xml_col_struct
select @unq_xml_col =
(
select
concat(',xmlname.value(''/Names[1]/name[',col_unq_nm,char(10))
from (select distinct col_unq_nm from #xml_col_struct) t
for xml path('')
)
set @unq_xml_col = stuff(@unq_xml_col,'')
set @sqlstr =
concat(
iif(@in_need_colnm_result = 'Y',concat('
;WITH Split_Names (xmlname)
AS
(
SELECT
CONVERT(XML,''<Names><name>''
+ REPLACE(''',@unq_col,''',''</name><name>'') + ''</name></Names>'') AS xmlname
)
'
--,@sqlstr,char(10),' SELECT ',@in_api_id,''H'',@runtime,@runby,@unq_xml_col,replicate(',NULL',@in_tot_result_col)--v2 change,'FROM Split_Names','union all'
),''
)
--,iif(@in_need_colnm_result = 'Y',@sqlstr),'
SELECT ',''D'',*','FROM OPENXML (@idoc_inn,@max_node_wo_slash,2)','WITH (',@xml_col,')'
)
if @in_debug_flg = 'Y'
begin
select @max_lvl+1,@max_lvl,@unq_xml_col
select * from #xml_col_struct--v2 change
end
else
begin
set @param = '@idoc_inn int'
exec sys.sp_executesql @sqlstr,@param,@idoc_inn = @idoc
end
EXEC sp_xml_removedocument @idoc
END
用于读取C#类加载的XML文件的sql代码.这也很好,但问题是所有行都在单独的行中,并且连接在一个点后截断
create table #tmp(data_line nvarchar(max))
bulk insert #tmp
FROM '\\Server\\ZZZZ\\Downloads\\Data.xml'
WITH
(
--firstrow = 1
ROWTERMINATOR ='\n'
);
select * from #tmp
C#类
Object httpConn = Dts.Connections["HTTP"].AcquireConnection(null);
HttpClientConnection myConnection = new HttpClientConnection(httpConn);
myConnection.ServerURL = string.Format(("http://xxxx.com/jjjj"),"userid","password");
byte[] webdata = myConnection.DownloadData();
String result_data = Convert.ToBase64String(webdata);
XmlDocument xd = new XmlDocument();
XmlDictionaryReader xr = JsonReaderWriterFactory.CreateJsonReader(webdata,XmlDictionaryReaderQuotas.Max);
xr.Read();
xd.LoadXml(xr.ReadOuterXml());
xd.Save("\\Server\\ZZZZ\\Downloads\\Data.xml");
解决方法
如果您获得格式正确的XML.您可以使用数据集.具体使用Dataset.readxml().这将在数据集对象中加载xml,而与xml标记无关.然后,您可以使用ADO.Net,linq2sql,EF或任何其他通信方法将其放入数据库中.
由于您在服务器上保存文件,因此可以使用以下代码：
DataSet ds = new DataSet();
ds.readxml("\\Server\\ZZZZ\\Downloads\\Data.xml");
然后你可以使用foreach循环迭代每个数据集表. xml中的属性将成为数据表中的列.
所以你的最终代码将类似于：
using (DataSet ds = new DataSet())
{
ds.readxml("\\Server\\ZZZZ\\Downloads\\Data.xml");
int nTableCounts = ds.Tables.Count;
foreach(DataTable dt in ds.Tables)
{
using (dt)
{
//Put data in sql table.
}
}
}
如果有什么不清楚,请告诉我.