参考链接：https://github.com/StackExchange/dapper-dot-net

Dapper - a simple object mapper for .Net

Dapper is a single file you can drop in to your project that will extend your IDbConnection interface.

It provides 3 helpers:

Dapper 只有一个文件，你可以把它放入你的项目，它扩展IDbConnection 接口，提供了三个帮助扩展方法。

1 Execute a query and map the results to a strongly typed List

( 执行一个查询，并且映射结果到一个强类型列表)

Note: all extension methods assume the connection is already open, they will fail if the connection is closed.

注意，所有的扩展方法假定连接已经打开，如果连接没打开，执行将失败。

public static IEnumerable<T> Query<T>(this IDbConnection cnn, string sql, object param = null, SqlTransaction transaction = null, bool buffered = true)

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使用示例：

public class Dog

{

    public int? Age { get; set; }

    public Guid Id { get; set; }

    public string Name { get; set; }

    public float? Weight { get; set; }

    public int IgnoredProperty { get { return 1; } }

}            

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);

2 Execute a query and map it to a list of dynamic objects

(执行一个查询，并且映射结果到动态对象列表)

public static IEnumerable<dynamic> Query (this IDbConnection cnn, string sql, object param = null, SqlTransaction transaction = null, bool buffered = true)

使用示例：

var rows = connection.Query("select 1 A, 2 B union all select 3, 4");

// 验证结果

((int)rows[0].A)

   .IsEqualTo(1);

((int)rows[0].B)

   .IsEqualTo(2);

((int)rows[1].A)

   .IsEqualTo(3);

((int)rows[1].B)

    .IsEqualTo(4);

查询结果：

3 Execute a Command that returns no results

执行命令，返回无结果（这里根据实例，认为是返回受影响行数）

public static int Execute(this IDbConnection cnn, string sql, object param = null, SqlTransaction transaction = null)

使用示例：

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);

命令执行结果：

Execute a Command multiple times

执行命令多次（批量操作）。

The same signature also allows you to conveniently and efficiently execute a command multiple times (for example to bulk-load data)

这个签名方法也允许你方便地，高效地执行命令多次（例如，大容量负载数据）

使用示例：

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 for some T.

任何实现了IEnumerable 接口的参数泛型T都可以运行。（如果是集合参数，object param 必须是实现 IEnumerable接口）

4 Performance （性能）

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.

Dapper 的一个关键特性就是性能，下面的指标显示了执行500个查询语句，并且映射数据到返回对象上需要花费多长时间。

The performance tests are broken in to 3 lists: 性能测试带入3个列表

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.

1）Performance of SELECT mapping over 500 iterations - POCO serialization

Method	Duration	Remarks
Hand coded (using a `SqlDataReader`)	47ms	Can be faster
Dapper `ExecuteMapperQuery`	49ms
ServiceStack.OrmLite (QueryById)	50ms
PetaPoco	52ms
BLToolkit	80ms
SubSonic CodingHorror	107ms
NHibernate SQL	104ms
Linq 2 SQL `ExecuteQuery`	181ms
Entity framework `ExecuteStoreQuery`	631ms

2） Performance of SELECT mapping over 500 iterations - dynamic serialization

3） Performance of SELECT mapping over 500 iterations - typical usage

5 Parameterized queries 参数化查询

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.

参数被当做匿名类传入，这允许你命名你的参数更容易，给予你能简单粘贴拷贝sql 片段并且在查询分析器中运行的能力。

new {A = 1, B = "b"} // A will be mapped to the param @A, B to the param @B

6 List Support 列表支持

Dapper allow you to pass in IEnumerable and will automatically parameterize your query.

Dapper 允许你传入IEnumable 接口，并自动参数化你的查询语句

例如：

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: （被转化为）

select * from (select 1 as Id union all select 2 union all select 3) as X where Id in (@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.

7 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.

Dapper 允许你映射一行记录到多个对象，这是一个关键特点，如果你想避免额外查询并且乐意加载关联对象。

例如：

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();

// 验证

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.

重要提醒：Dapper默认你的Id 列被命名为“Id”或者“id”，如果你的主键不是这样或者你想拆分宽行在某点上而不是Id 列，使用‘SplitOn’参数选项

8 Multiple Results （多结果）

Dapper allows you to process multiple result grids in a single query.

Dapper 允许你在一个查询中处理多结果网格数据。

例如：

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();

   ...

}

9 Stored Procedures （存储过程）

Dapper fully supports stored procs:

Dapper完全支持存储过程

var user = cnn.Query<User>("spGetUser", new {Id = 1},

        commandType: CommandType.StoredProcedure).SingleOrDefault();

If you want something more fancy, you can do: 如果你想一些更不错的，你可以这样

var p = new DynamicParameters();

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");

（其实就是参数化支持，输入参数，输出参数，返回值）

10 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:

Dapper 支持变量参数，如果你在一个变量列上执行一个where 子句，必须确保用这种方式传入参数

Query<Thing>("select * from Thing where Name = @Name", new {Name = new DbString { 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.

Limitations and caveats

Dapper caches information about every query it runs, this allow it to materialize objects quickly and process parameters quickly. The current implementation caches this information in a ConcurrentDictionary object. The objects it stores are never flushed. If you are generating SQL strings on the fly without using parameters it is possible you will hit memory issues. We may convert the dictionaries to an LRU Cache.

Dapper's simplicity means that many feature that ORMs ship with are stripped out, there is no identity map, there are no helpers for update / select and so on.

Dapper does not manage your connection's lifecycle, it assumes the connection it gets is open AND has no existing datareaders enumerating (unless MARS is enabled)

Will Dapper work with my DB provider?

Dapper has no DB specific implementation details, it works across all .NET ADO providers including SQLite, SQL CE, Firebird, Oracle, MySQL, PostgreSQL and SQL Server.

Do you have a comprehensive list of examples?

Dapper has a comprehensive test suite in the test project

Who is using this?

Dapper is in production use at:

Stack Overflow, helpdesk

(if you would like to be listed here let me know)

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Dapper.net ORM

Dapper - a simple object mapper for .Net

1 Execute a query and map the results to a strongly typed List

2 Execute a query and map it to a list of dynamic objects

3 Execute a Command that returns no results

Execute a Command multiple times

4 Performance （性能）

1）Performance of SELECT mapping over 500 iterations - POCO serialization

2） Performance of SELECT mapping over 500 iterations - dynamic serialization

3） Performance of SELECT mapping over 500 iterations - typical usage

5 Parameterized queries 参数化查询

6 List Support 列表支持

Buffered vs Unbuffered readers

7 Multi Mapping

8 Multiple Results （多结果）

9 Stored Procedures （存储过程）

10 Ansi Strings and varchar

Limitations and caveats

Will Dapper work with my DB provider?

Do you have a comprehensive list of examples?

Who is using this?

Dapper.net ORM的更多相关文章

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