SQL批量插入数据几种方案的性能详细对比

http://www.jb51.net/article/22533.htm

在SQL Server 中插入一条数据使用Insert语句，但是如果想要批量插入一堆数据的话，循环使用Insert不仅效率低，而且会导致SQL一系统性能问题。下面介绍SQL Server支持的两种批量数据插入方法：Bulk和表值参数(Table-Valued Parameters)。

运行下面的脚本，建立测试数据库和表值参数。

--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))

--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))

下面我们使用最简单的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();

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();

耗时图如下：

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。

下面看一下使用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();
}

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(); }

耗时图如下：

可见，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，我也会另外写一篇关于表值参数的博客，不过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();
}

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(); }

耗时图如下：

比Bulk还快5秒。

如需转载，请注明此文原创自CSDN TJVictor专栏：http://blog.csdn.net/tjvictor/archive/2009/07/18/4360030.aspx