我在三台安装SQL Server 2012的服务器上搭建分布式数据库，把产品环境中一年近1.4亿条数据大致均匀地存储在这三台服务器中，每台Server 存储4个月的数据，物理机的系统配置基本相同：内存16G，双核 CPU 3.6GHz，软件环境是Windows Server 2012 R，和SQL Server 2012。
1，创建水平分区视图
基础表是dbo.Commits，每个基础表大致存储4个月的数据，近5000万条记录：
CREATE TABLE [dbo].[Commits]
(
[CommitID] [bigint] IDENTITY(1,1) NOT FOR REPLICATION NOT NULL,
[AuthorID] [bigint] NOT NULL,
[CreatedDate] [datetime2](7) NOT NULL,
[CreatedDateKey] [int] NOT NULL,
CONSTRAINT [PK__Commits_CommitID] PRIMARY KEY CLUSTERED
(
[CommitID] ASC,
[CreatedDateKey] ASC
)
)
创建分区视图，Linked Server的Alias是db2 和 db3，Catalog 是 tdw（test data warehouse）：
CREATE view [dbo].[view_commits]
as select [CommitID]
,[AuthorID]
,[CreatedDate]
,[CreatedDateKey]
from dbo.commits c with(nolock)
where c.[CreatedDateKey] between 20150900 and 20160000 union ALL
select [CommitID]
,[AuthorID]
,[CreatedDate]
,[CreatedDateKey]
from db3.tdw.dbo.commits c with(nolock)
where c.[CreatedDateKey] between 20150000 and 20150500 union ALL
select [CommitID]
,[AuthorID]
,[CreatedDate]
,[CreatedDateKey]
from db2.tdw.dbo.commits c with(nolock)
where c.[CreatedDateKey] between 20150500 and 20150900
WITH check OPTION;
GO
2，查询性能测试
Test1，在基础表上测试，基础表是全部的数据，cost：79s
select count(0)
from dbo.commits_total c with(nolock)
where day(c.[CreatedDate])=1
Test2，使用分区视图测试，cost=134s，比Test1的查询性能明显降低。
select count(0)
from dbo.view_commits c with(nolock)
where day(c.[CreatedDate])=1
3，使用OpenQuery查询
OpenQuery把查询语句直接发送到Linked Server上执行，返回查询的结果，cost:105s，还是很高，相对提高20%的性能。
select sum(t.cnt) as cnt
from
(
select count(0) as cnt
from dbo.commits c with(nolock)
where day(c.[CreatedDate])=1 UNION all
select p.cnt
from openquery(db2,
N'select count(0) as cnt
from dbo.commits c with(nolock)
where day(c.[CreatedDate])=1') as p UNION all
select p.cnt
from openquery(db3,
N'select count(0) as cnt
from dbo.commits c with(nolock)
where day(c.[CreatedDate])=1') as p
) as t
4，使用C# 多线程编程
创建三个Task同时运行在三台Server上，Cost：28s
static void Main(string[] args)
{
List<Task> tasks = new List<Task>();
int c1=, c2=, c3=; Task t1 = new Task(()=>
{
c1= GetCount("xxx");
}); Task t2 = new Task(() =>
{
c2= GetCount("xxx");
}); Task t3 = new Task(() =>
{
c3= GetCount("xxx");
});
tasks.Add(t1);
tasks.Add(t2);
tasks.Add(t3); Stopwatch sw = new Stopwatch();
sw.Start();
t1.Start();
t2.Start();
t3.Start(); Task.WaitAll(tasks.ToArray()); int sum = c1 + c2 + c3;
sw.Stop(); Console.Read();
} static int GetCount(string str)
{
using (SqlConnection con = new SqlConnection(str))
{
con.Open();
var cmd = con.CreateCommand();
cmd.CommandText = @" select count(0) as cnt
from dbo.commits c with(nolock)
where day(c.[CreatedDate]) = 1";
int count = (int)cmd.ExecuteScalar();
con.Close();
return count;
}
}
5，结论
- 将数据水平切分，分布式部署在不同的SQL Server上，其查询性能并不一定比单一DB性能更好。
- 使用OpenQuery函数将查询语句在Remote Server上执行，返回查询结果，能够优化Linked Server 的查询性能。
- 在使用分布式数据库查询数据时，针对特定的应用，编写特定的代码，这需要fore-end 更多的参与。
参考doc：