Dapper - a simple object mapper for .Net

浏览数：10 / 时间：2015年06月11日

本文内容

特点
性能

跳槽了，新公司的数据库层，准确地说，数据库层和持久层使用 Dapper，这东西的确很方便。

特点

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

It provides 3 helpers:

执行一个查询，并把结果映射到一个强类型 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)

用法：

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);

执行一个查询，并把结果映射到一个动态 object 的 list

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.

用法：

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);

执行一个不返回结果的 Command

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

用法：

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)

用法：

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.

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.

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

Performance of SELECT mapping over 500 iterations - dynamic serialization

Performance of SELECT mapping over 500 iterations - typical usage

参数化的查询

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.

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

List 支持

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

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:

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

缓存和非缓存的 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.

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();

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.

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();

...

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 = 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");

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 = 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, sqlce, firebird, oracle, MySQL, PostgreSQL and SQL Server