推荐理由：Dapper只有一个代码文件，完全开源，你可以放在项目里的任何位置，来实现数据到对象的ORM操作，体积小速度快：）
Google Code下载地址：
http://code.google.com/p/dapper-dot-net/
https://github.com/SamSaffron/dapper-dot-net
授权协议：Apache License 2.0
Dapper - a simple object mapper for .Net
Official Github clone: https://github.com/SamSaffron/dapper-dot-net
Documentation you can improve
The Dapper tag wiki on Stack Overflow can be improved by any Stack Overflow users. Feel free to add relevant information there.
Features
Dapper is a single file you can drop in to your project that will extend your IDbConnection interface.
It provides 3 helpers:
Execute a query and map the results to a strongly typed List
Note: all extension methods assume the connection is already open, they will fail if the connection is closed.
public static IEnumerable<T> Query<T>(this IDbConnection cnn, string sql, object param = null, SqlTransaction transaction = null, bool buffered = true)
Example usage:
publicclassDog
{
publicint?Age{get;set;}
publicGuidId{get;set;}
publicstringName{get;set;}
publicfloat?Weight{get;set;}
publicintIgnoredProperty{get{return1;}}
}
var guid =Guid.NewGuid();
var dog = connection.Query<Dog>("select Age = @Age, Id = @Id",new{Age=(int?)null,Id= guid });
dog.Count()
.IsEqualTo(1);
dog.First().Age
.IsNull();
dog.First().Id
.IsEqualTo(guid);
Execute a query and map it to a list of dynamic objects
public static IEnumerable<dynamic> Query (this IDbConnection cnn, string sql, object param = null, SqlTransaction transaction = null, bool buffered = true)
This method will execute SQL and return a dynamic list.
Example usage:
var rows = connection.Query("select 1 A, 2 B union all select 3, 4");
((int)rows[0].A)
.IsEqualTo(1);
((int)rows[0].B)
.IsEqualTo(2);
((int)rows[1].A)
.IsEqualTo(3);
((int)rows[1].B)
.IsEqualTo(4);
Execute a Command that returns no results
public static int Execute(this IDbConnection cnn, string sql, object param = null, SqlTransaction transaction = null)
Example usage:
connection.Execute(@"
set nocount on
create table #t(i int)
set nocount off
insert #t
select @a a union all select @b
set nocount on
drop table #t",new{a=1, b=2})
.IsEqualTo(2);
Execute a Command multiple times
The same signature also allows you to conveniently and efficiently execute a command multiple times (for example to bulk-load data)
Example usage:
connection.Execute(@"insert MyTable(colA, colB) values (@a, @b)",
new[]{new{ a=1, b=1},new{ a=2, b=2},new{ a=3, b=3}}
).IsEqualTo(3);// 3 rows inserted: "1,1", "2,2" and "3,3"
This works for any parameter that implements IEnumerable<T> for some T.
Performance
A key feature of Dapper is performance. The following metrics show how long it takes to execute 500 SELECT statements against a DB and map the data returned to objects.
The performance tests are broken in to 3 lists:
- POCO serialization for frameworks that support pulling static typed objects from the DB. Using raw SQL.
- Dynamic serialization for frameworks that support returning dynamic lists of objects.
- Typical framework usage. Often typical framework usage differs from the optimal usage performance wise. Often it will not involve writing SQL.
Performance of SELECT mapping over 500 iterations - POCO serialization
| Method | Duration | Remarks |
| Hand coded (using a SqlDataReader) | 47ms | |
| Dapper ExecuteMapperQuery<Post> | 49ms | |
| ServiceStack.OrmLite (QueryById) | 50ms | |
| PetaPoco | 52ms | Can be faster |
| BLToolkit | 80ms | |
| SubSonic CodingHorror | 107ms | |
| NHibernate SQL | 104ms | |
| Linq 2 SQL ExecuteQuery | 181ms | |
| Entity framework ExecuteStoreQuery | 631ms |
Performance of SELECT mapping over 500 iterations - dynamic serialization
| Method | Duration | Remarks |
| Dapper ExecuteMapperQuery (dynamic) | 48ms | |
| Massive | 52ms | |
| Simple.Data | 95ms |
Performance of SELECT mapping over 500 iterations - typical usage
| Method | Duration | Remarks |
| Linq 2 SQL CompiledQuery | 81ms | Not super typical involves complex code |
| NHibernate HQL | 118ms | |
| Linq 2 SQL | 559ms | |
| Entity framework | 859ms | |
| SubSonic ActiveRecord.SingleOrDefault | 3619ms |
Performance benchmarks are available here: http://code.google.com/p/dapper-dot-net/source/browse/Tests/PerformanceTests.cs , Feel free to submit patches that include other ORMs - when running benchmarks, be sure to compile in Release and not attach a debugger (ctrl F5)
Parameterized queries
Parameters are passed in as anonymous classes. This allow you to name your parameters easily and gives you the ability to simply cut-and-paste SQL snippets and run them in Query analyzer.
new{A =1, B ="b"}// A will be mapped to the param @A, B to the param @B
Advanced features
List Support
Dapper allow you to pass in IEnumerable<int> and will automatically parameterize your query.
For example:
connection.Query<int>("select * from (select 1 as Id union all select 2 union all select 3) as X where Id in @Ids", new { Ids = new int[] { 1, 2, 3 });
Will be translated to:
select*from(select1asIdunion all select2union all select3)as X whereIdin(@Ids1,@Ids2,@Ids3)" // @Ids1 = 1 , @Ids2 = 2 , @Ids2 = 3
Buffered vs Unbuffered readers
Dapper's default behavior is to execute your sql and buffer the entire reader on return. This is ideal in most cases as it minimizes shared locks in the db and cuts down on db network time.
However when executing huge queries you may need to minimize memory footprint and only load objects as needed. To do so pass, buffered: false into the Query method.
Multi Mapping
Dapper allows you to map a single row to multiple objects. This is a key feature if you want to avoid extraneous querying and eager load associations.
Example:
var sql =
@"select * from #Posts p
left join #Users u on u.Id = p.OwnerId
Order by p.Id";
var data = connection.Query<Post,User,Post>(sql,(post, user)=>{ post.Owner= user;return post;});
var post = data.First();
post.Content.IsEqualTo("Sams Post1");
post.Id.IsEqualTo(1);
post.Owner.Name.IsEqualTo("Sam");
post.Owner.Id.IsEqualTo(99);
important note Dapper assumes your Id columns are named "Id" or "id", if your primary key is different or you would like to split the wide row at point other than "Id", use the optional 'splitOn' parameter.
Multiple Results
Dapper allows you to process multiple result grids in a single query.
Example:
var sql =
@"
select * from Customers where CustomerId = @id
select * from Orders where CustomerId = @id
select * from Returns where CustomerId = @id";
using(var multi = connection.QueryMultiple(sql,new{id=selectedId}))
{
var customer = multi.Read<Customer>().Single();
var orders = multi.Read<Order>().ToList();
var returns = multi.Read<Return>().ToList();
...
}
Stored Procedures
Dapper supports fully stored procs:
var user = cnn.Query<User>("spGetUser",new{Id=1},
commandType:CommandType.StoredProcedure).First();}}}
If you want something more fancy, you can do:
var p =newDynamicParameters();
p.Add("@a",11);
p.Add("@b", dbType:DbType.Int32, direction:ParameterDirection.Output);
p.Add("@c", dbType:DbType.Int32, direction:ParameterDirection.ReturnValue);
cnn.Execute("spMagicProc", p, commandType: commandType.StoredProcedure);
int b = p.Get<int>("@b");
int c = p.Get<int>("@c");
Ansi Strings and varchar
Dapper supports varchar params, if you are executing a where clause on a varchar column using a param be sure to pass it in this way:
Query<Thing>("select * from Thing where Name = @Name",new{Name=newDbString{Value="abcde",IsFixedLength=true,Length=10,IsAnsi=true});
On Sql Server it is crucial to use the unicode when querying unicode and ansi when querying non unicode.