SQLServer2005中利用xml类型实现批量操作的存储过程[原]

实现批量操作是常见的任务,比如批量删除一批数据,如果在应用程序端循环调用DAL.Entity.Delete则效率非常低,因为数据库往返次数取决与数据量大小。而编写一个存储过程效率更高。

做这个批量操作的存储过程使用什么作为参数是一个问题。如果使用VARCHAR(MAX),内容是,例如要删除记录的id并以逗号隔开,例如“1,2,3,4,…..”,这样的话就会存在最大长度受限制的问题。

这儿介绍一种使用XML的VARBINARY类型作为参数的高效方法。

首先是xml的格式:



<
Employees>
 <Employee EmployeeID="1" EmployeeName="Bush" EmployeeAddress="WashtonD.C." />
 <Employee EmployeeID="2" EmployeeName="Jamson" EmployeeAddress="Russia" />
 <Employee EmployeeID="3" EmployeeName="Brown" EmployeeAddress="London" />
</Employees>

 

把这个XML转换为Binary类型:

 

using System.IO;
using System.Xml;
 
private byte[] GetEmployeesListXmlStream(IList EmployeesList)
{
   byte[] result = null;
 
   using (MemoryStream stream = new MemoryStream())
   {
         XmlWriterSettings settings = new XmlWriterSettings();
 
         settings.Indent = true;
         settings.OmitXmlDeclaration = true;
         settings.IndentChars = "\t";
         XmlWriter writer = XmlWriter.Create(stream, settings);
 
         writer.WriteStartDocument();
         writer.WriteStartElement("Employees");
 
         foreach (Employee var in EmployeesList)
         {
             writer.WriteStartElement("Employee");
             writer.WriteAttributeString("EmployeeID", var.EmployeeID.ToString());
             writer.WriteAttributeString("EmployeeName", var.EmployeeName);
             writer.WriteAttributeString("EmployeeAddress", var.EmployeeAddress);
             writer.WriteEndElement();
         }
 
         writer.WriteEndElement();
         writer.WriteEndDocument();
 
         writer.Flush();
         writer.Close();
         result = stream.ToArray();
   }
   
   return result;
}

 

大家也知道,DataSet中的数据可以直接序列化成xml,通过dataSet.GetXml(),然后转化为binary即可。

 

XML的VARBINARY类型作为参数,批量删除的存储过程

 

   1: CREATE PROCEDURE [dbo].[_Employee_BulkDelete]    
   2: (    
   3:     @EmployeeList VARBINARY(MAX)
   4: )    
   5: AS    
   6:  
   7:     --XML ----
   8:     DECLARE @EmployeeListXML XML;
   9:  
  10:     -- TABLE to store XML records ----
  11:     DECLARE @TempEmployees TABLE
  12:     (
  13:         EmployeeID BIGINT NULL,
  14:         EmployeeName NVARCHAR(512) NULL DEFAULT(''),
  15:         EmployeeAddress NVARCHAR(512) NULL DEFAULT('')
  16:     )
  17:  
  18:     -- Get XML from binary stream -----
  19:     SET @EmployeeListXML = CONVERT(XML, @EmployeeList);
  20:  
  21:     -- Fill to table-------
  22:     INSERT INTO @TempEmployees    
  23:     (    
  24:         EmployeeID,
  25:         EmployeeName,
  26:         EmployeeAddress
  27:     )    
  28:     SELECT    
  29:         nref.value('@id', 'BIGINT'),
  30:         nref.value('@name', 'NVARCHAR(512)'),
  31:         nref.value('@address', 'NVARCHAR(512)')
  32:     FROM     
  33:         @EmployeeListXML.nodes('/Employees/Employee') R(nref)
  34:  
  35:     --- Delete ----Maybe more complicated routine here !----------
  36:  
  37:     DELETE [dbo].[TempEmployees]
  38:     FROM [dbo].[TempEmployees] AS T1
  39:       INNER JOIN @TempEmployees AS T2    
  40:             ON    (T1.EmployeeID = T2.EmployeeID)    
  41:     WHERE (EmployeeSalary > 500000)

 

最后,如果想进一步优化该存储过程的效率,可以优化索引,使用临时表等。


------- 批量插入可以用SqlBulkCopy 参考:http://www.cnblogs.com/xiaoweinet/archive/2010/03/02/1676478.html

posted on 2008-12-20 13:56  Mainz  阅读(1271)  评论(0编辑  收藏  举报

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