SQL Server 批量插入数据的两种方法(SqlBulkCopy + 表值参数)

运行下面的脚本，建立测试数据库和表值特性类型的表。(下面测试要用)。

--Create DataBase
create database BulkTestDB;
go
use BulkTestDB;
go
--Create Table
Create table BulkTestTable
(
    Id int primary key,
    UserName nvarchar(32),
    Pwd varchar(16)
)
go
--Create Table Valued
CREATE TYPE BulkUdt AS TABLE
  (
    Id int,
    UserName nvarchar(32),
    Pwd varchar(16)
  )

使用最简单的Insert语句来插入100万条数据，代码如下：

Stopwatch sw = new Stopwatch();  
  
SqlConnection sqlConn = new SqlConnection(  
    ConfigurationManager.ConnectionStrings["ConnStr"].ConnectionString);//连接数据库  
  
SqlCommand sqlComm = new SqlCommand();  
sqlComm.CommandText = string.Format("insert into BulkTestTable(Id,UserName,Pwd)values(@p0,@p1,@p2)");//参数化SQL  
sqlComm.Parameters.Add("@p0", SqlDbType.Int);  
sqlComm.Parameters.Add("@p1", SqlDbType.NVarChar);  
sqlComm.Parameters.Add("@p2", SqlDbType.VarChar);  
sqlComm.CommandType = CommandType.Text;  
sqlComm.Connection = sqlConn;  
sqlConn.Open();  
try  
{  
    //循环插入100万条数据，每次插入10万条，插入10次。  
    for (int multiply = 0; multiply < 10; multiply++)  
    {  
        for (int count = multiply * 100000; count < (multiply + 1) * 100000; count++)  
        {  
  
            sqlComm.Parameters["@p0"].Value = count;  
            sqlComm.Parameters["@p1"].Value = string.Format("User-{0}", count * multiply);  
            sqlComm.Parameters["@p2"].Value = string.Format("Pwd-{0}", count * multiply);  
            sw.Start();  
            sqlComm.ExecuteNonQuery();  
            sw.Stop();  
        }  
        //每插入10万条数据后，显示此次插入所用时间  
        Console.WriteLine(string.Format("Elapsed Time is {0} Milliseconds", sw.ElapsedMilliseconds));  
    }  
}  
catch (Exception ex)  
{  
    throw ex;  
}  
finally  
{  
    sqlConn.Close();  
}  
  
Console.ReadLine();  

由于运行过慢，才插入10万条就耗时72390 milliseconds，所以我就手动强行停止了。

 

下面使用Bulk插入的情况：

bulk方法主要思想是通过在客户端把数据都缓存在Table中，然后利用SqlBulkCopy一次性把Table中的数据插入到数据库

代码如下：

public static void BulkToDB(DataTable dt)  
{  
    SqlConnection sqlConn = new SqlConnection(  
        ConfigurationManager.ConnectionStrings["ConnStr"].ConnectionString);  
    SqlBulkCopy bulkCopy = new SqlBulkCopy(sqlConn);  
    bulkCopy.DestinationTableName = "BulkTestTable";  
    bulkCopy.BatchSize = dt.Rows.Count;  
  
    try  
    {  
        sqlConn.Open();  
    if (dt != null && dt.Rows.Count != 0)  
        bulkCopy.WriteToServer(dt);  
    }  
    catch (Exception ex)  
    {  
        throw ex;  
    }  
    finally  
    {  
        sqlConn.Close();  
        if (bulkCopy != null)  
            bulkCopy.Close();  
    }  
}  
  
public static DataTable GetTableSchema()  
{  
    DataTable dt = new DataTable();  
    dt.Columns.AddRange(new DataColumn[]{  
        new DataColumn("Id",typeof(int)),  
        new DataColumn("UserName",typeof(string)),  
    new DataColumn("Pwd",typeof(string))});  
  
    return dt;  
}  
  
static void Main(string[] args)  
{  
    Stopwatch sw = new Stopwatch();  
    for (int multiply = 0; multiply < 10; multiply++)  
    {  
        DataTable dt = Bulk.GetTableSchema();  
        for (int count = multiply * 100000; count < (multiply + 1) * 100000; count++)  
        {  
            DataRow r = dt.NewRow();  
            r[0] = count;  
            r[1] = string.Format("User-{0}", count * multiply);  
            r[2] = string.Format("Pwd-{0}", count * multiply);  
            dt.Rows.Add(r);  
        }  
        sw.Start();  
        Bulk.BulkToDB(dt);  
        sw.Stop();  
        Console.WriteLine(string.Format("Elapsed Time is {0} Milliseconds", sw.ElapsedMilliseconds));  
    }  
  
    Console.ReadLine();  
}  

使用Bulk后，效率和性能明显上升。使用Insert插入10万数据耗时72390，而现在使用Bulk插入100万数据才耗时17583。

 

最后再看看使用表值参数的效率，会另你大为惊讶的。表值参数是SQL Server 2008新特性，简称TVPs。对于表值参数不熟悉的朋友，可以参考最新的book online，此次不对表值参数的概念做过多的介绍。言归正传，看代码：

public static void TableValuedToDB(DataTable dt)  
{  
    SqlConnection sqlConn = new SqlConnection(  
      ConfigurationManager.ConnectionStrings["ConnStr"].ConnectionString);  
    const string TSqlStatement =  
     "insert into BulkTestTable (Id,UserName,Pwd)" +  
     " SELECT nc.Id, nc.UserName,nc.Pwd" +  
     " FROM @NewBulkTestTvp AS nc";  
    SqlCommand cmd = new SqlCommand(TSqlStatement, sqlConn);  
    SqlParameter catParam = cmd.Parameters.AddWithValue("@NewBulkTestTvp", dt);  
    catParam.SqlDbType = SqlDbType.Structured;  
    //表值参数的名字叫BulkUdt，在上面的建立测试环境的SQL中有。  
    catParam.TypeName = "dbo.BulkUdt";  
    try  
    {  
      sqlConn.Open();  
      if (dt != null && dt.Rows.Count != 0)  
      {  
          cmd.ExecuteNonQuery();  
      }  
    }  
    catch (Exception ex)  
    {  
      throw ex;  
    }  
    finally  
    {  
      sqlConn.Close();  
    }  
}  
  
public static DataTable GetTableSchema()  
{  
    DataTable dt = new DataTable();  
    dt.Columns.AddRange(new DataColumn[]{  
      new DataColumn("Id",typeof(int)),  
      new DataColumn("UserName",typeof(string)),  
      new DataColumn("Pwd",typeof(string))});  
  
    return dt;  
}  
  
static void Main(string[] args)  
{  
    Stopwatch sw = new Stopwatch();  
    for (int multiply = 0; multiply < 10; multiply++)  
    {  
        DataTable dt = TableValued.GetTableSchema();  
        for (int count = multiply * 100000; count < (multiply + 1) * 100000; count++)  
        {          
            DataRow r = dt.NewRow();  
            r[0] = count;  
            r[1] = string.Format("User-{0}", count * multiply);  
            r[2] = string.Format("Pwd-{0}", count * multiply);  
            dt.Rows.Add(r);  
        }  
        sw.Start();  
        TableValued.TableValuedToDB(dt);  
        sw.Stop();  
        Console.WriteLine(string.Format("Elapsed Time is {0} Milliseconds", sw.ElapsedMilliseconds));  
    }  
  
    Console.ReadLine();  
}

比Bulk还快5秒。