我使用三台SQL Server 2012 搭建分布式数据库，将一年的1.4亿条数据大致均匀存储在这三台Server中，每台Server 存储4个月的数据，Physical Server的配置基本相同，内存16G，双核 CPU 3.6GHz。
　　1，创建分区视图，Linked Server的Alias是db2 和 db3，Catalog 是 tdw（test data warehouse）。
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
)
) ON [PRIMARY]
GO
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，使用Basic Table测试，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，跟Test1有明显的差距。
select count(0)
from dbo.view_commits c  with(nolock)
where day(c.[CreatedDate])=1

　　3，使用OpenQuery查询，OpenQuery将查询语句直接在Linked Server上执行，返回查询的结果。
OpenQuery Executes the specified pass-through query on the specified linked server.
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
cost:105s，还是很高.
　　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=0， c2=0， c3=0;
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。