SQL Server分布式数据库性能测试
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])=13，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。
