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SQL Server的批量上传策略

[英]Bulk upload strategy for SQL server

I am uploading data from CSV to SQL table using the following function. 我正在使用以下功能将数据从CSV上传到SQL表。

Is there a better way to do it? 有更好的方法吗?

I am concerned about , right now, connection hold for long time. 我关注的是,现在,连接保持了很长时间。 Hence need to be reduced. 因此需要减少。

   public bool SaveProxyBulkUploadData(List<AddServerPError> saveBulkUploadData)
        {
            try
            {
                foreach (AddServerPError addServetData in saveBulkUploadData)
                {
                    DbCommand dbCmd = CitiScriptExecutionDB.GetStoredProcCommand("USP_HS_InsertProxyBulkUploadData");
                    CitiScriptExecutionDB.AddInParameter(dbCmd, "@groupid", DbType.String, addServetData.GroupId);
                    CitiScriptExecutionDB.AddInParameter(dbCmd, "@proxyname", DbType.String, addServetData.ProxyName);
                    CitiScriptExecutionDB.AddInParameter(dbCmd, "@proxytype", DbType.String, addServetData.ProxyType);
                    CitiScriptExecutionDB.AddInParameter(dbCmd, "@sa_spoc_dl", DbType.String, addServetData.SA_SPOC_DL);
                    CitiScriptExecutionDB.AddInParameter(dbCmd, "@assignmentgroup", DbType.String, addServetData.AssignmentGroup);
                    CitiScriptExecutionDB.AddInParameter(dbCmd, "@createdby", DbType.String, addServetData.CreatedBy);
                    CitiScriptExecutionDB.ExecuteNonQuery(dbCmd);
                }

                return true;
            }
            catch (Exception ex)
            {
                string msg = ex.Message + ex.StackTrace;
                throw;
            }
        }

Stored Procedure 储存程序

CREATE PROCEDURE USP_HS_InsertBulkUploadData   
 @groupid  int,  
 @hostname varchar(50),   
 @type1 varchar(50),  
 @type2 varchar(50),  
 @createdby varchar(50)       
AS        
BEGIN       

 Insert into [dbo].[EUCUsecaseGroupInputParam]    
 (    
  GroupId,  
  HostName,    
  Type1,    
  Type2,     
  CreatedBy,     
  CreatedDate,     
  UpdatedBy,    
  UpdatedDate,    
  IsActive    
  )        
 Values(   
  @groupId,  
  @hostname,    
  @type1,    
  @type2,    
  @createdby,    
  GetDate(),    
  null,    
  null,    
  1    
  )       
END 

Your best bet here is probably SqlBulkCopy , which throws raw TDS at the server very efficiently. 您最好的选择可能是SqlBulkCopy ,它可以非常有效地将原始TDS SqlBulkCopy服务器。 SqlBulkCopy takes two types of input: SqlBulkCopy接受两种类型的输入:

  • DataTable
  • IDataReader

So at that point you have 3 options: 因此,此时您有3个选择:

You can consider using Cinchoo ETL , an open source library to do the bulk upload CSV file to database. 您可以考虑使用Cinchoo ETL (一种开放源代码库)将CSV文件批量上传到数据库。

Option 1: 选项1:

Load the CSV file straight to database 直接将CSV文件加载到数据库

string connectionstring = @"#YOUR DB ConnectionString#";
using (SqlBulkCopy bcp = new SqlBulkCopy(connectionstring))
{
    using (var p = new ChoCSVReader("#YOUR CSV FILE#"))
    {
        bcp.DestinationTableName = "#TABLENAME#";
        bcp.EnableStreaming = true;
        bcp.BatchSize = 10000;
        bcp.BulkCopyTimeout = 0;
        bcp.NotifyAfter = 100;
        bcp.SqlRowsCopied += delegate (object sender, SqlRowsCopiedEventArgs e)
        {
            Console.WriteLine(e.RowsCopied.ToString("#,##0") + " rows copied.");
        };
        bcp.WriteToServer(p.AsDataReader());
    }
}

Option 2: 选项2:

If the load of CSV done already and outputted as List<AddServerPError> , you still can upload them to database as below 如果已经完成了CSV的加载并以List<AddServerPError>输出,则仍然可以按如下所示将它们上传到数据库

List<AddServerPError> objs = # Your input objects #;

string connectionstring = @"#YOUR DB ConnectionString#";
using (SqlBulkCopy bcp = new SqlBulkCopy(connectionstring))
{
    bcp.DestinationTableName = "#TABLENAME#";
    bcp.EnableStreaming = true;
    bcp.BatchSize = 10000;
    bcp.BulkCopyTimeout = 0;
    bcp.NotifyAfter = 100;
    bcp.SqlRowsCopied += delegate (object sender, SqlRowsCopiedEventArgs e)
    {
        Console.WriteLine(e.RowsCopied.ToString("#,##0") + " rows copied.");
    };
    bcp.WriteToServer(objs.AsDataReader());
}

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