剧情开始
- 为何相爱?
- 相处的问题?
- 女人的伟大?
- 剧情收尾?
有时候相识即是一种缘分,相爱也不需要太多的理由,一个眼神足矣,当EntityFramework遇上AutoMapper,就是如此,恋爱虽易,相处不易。
在DDD(领域驱动设计)中,使用AutoMapper一般场景是(Domain Layer)领域层与Presentation Layer(表现层)之间数据对象的转换,也就是DTO与Domin Model之间的相互转换,但是如果对AutoMapper有深入了解之后,就会发现她所涉及的领域不仅仅局限如此,应该包含所有对象之间的转换。另一边,当EntityFramework还在为单身苦恼时,不经意的一瞬间相识了AutoMapper,从此就深深的爱上了她。
AutoMapper是一个强大的Object-Object Mapping工具,关于AutoMapper请参照:
- 【AutoMapper官方文档】DTO与Domin Model相互转换(上)
- 【AutoMapper官方文档】DTO与Domin Model相互转换(中)
- 【AutoMapper官方文档】DTO与Domin Model相互转换(下)
为何相爱?
上面是AutoMapper对象转换示意图,可以看出AutoMapper的主要用途是用在对象映射转换上,她不管是什么对象,只是负责转换,就像一个女人在家只负责相夫教子一样。看下AutoMapper的基本用法:
1 // 配置 AutoMapper 2 Mapper.CreateMap(); 3 // 执行 mapping 4 OrderDto dto = Mapper.Map (order);
EntityFramework是什么?他是微软开发的基于ADO.NET的ORM(Object/Relational Mapping)框架,是个大人物,是有身份和地位的人,就像一个“王子”一样,而AutoMapper准确的来说只是一个小角色,就像“灰姑娘”一样,况且他们也不是一个世界的人,那为什么EntityFramework会看上AutoMapper呢?这里面必定有内情,我们来探查一番。
假如存在这样一个业务场景,Order表中存在百万条订单数据,而且Order表有几百列,根据业务场景要求,我们要对订单进行分离,比如:客户信息订单、产品订单等等,可能只是用到订单表中的某些字段,如果我们去做这样的一个操作,可以想象这样查询出的数据是怎样的,某些我们并不需要的字段会查询出来,而且数据并没有得到过滤,所以我们要在数据访问层做下面这样一个操作:
1 using (var context = new OrderContext()) 2 { 3 var orderConsignee = from order in context.Orders 4 select new OrderConsignee 5 { 6 OrderConsigneeId = order.OrderId, 7 //OrderItems = order.OrderItems, 8 OrderItemCount = order.OrderItemCount, 9 ConsigneeName = order.ConsigneeName, 10 ConsigneeRealName = order.ConsigneeRealName, 11 ConsigneePhone = order.ConsigneePhone, 12 ConsigneeProvince = order.ConsigneeProvince, 13 ConsigneeAddress = order.ConsigneeAddress, 14 ConsigneeZip = order.ConsigneeZip, 15 ConsigneeTel = order.ConsigneeTel, 16 ConsigneeFax = order.ConsigneeFax, 17 ConsigneeEmail = order.ConsigneeEmail 18 };
19 Console.ReadKey(); 20 }
orderConsignee表示订单客户,这只是订单信息分离的一种子集,如果有多种分离的子集,并且子集中的字段并不比订单表少多少,你就会发现在数据访问层填充这些子集要做的工作量有多少了,虽然它是高效的,从生成的SQL代码中就可以看出:
1 SELECT 2 [Extent1].[OrderItemCount] AS [OrderItemCount], 3 [Extent1].[OrderId] AS [OrderId], 4 [Extent1].[ConsigneeName] AS [ConsigneeName], 5 [Extent1].[ConsigneeRealName] AS [ConsigneeRealName], 6 [Extent1].[ConsigneePhone] AS [ConsigneePhone], 7 [Extent1].[ConsigneeProvince] AS [ConsigneeProvince], 8 [Extent1].[ConsigneeAddress] AS [ConsigneeAddress], 9 [Extent1].[ConsigneeZip] AS [ConsigneeZip], 10 [Extent1].[ConsigneeTel] AS [ConsigneeTel], 11 [Extent1].[ConsigneeFax] AS [ConsigneeFax], 12 [Extent1].[ConsigneeEmail] AS [ConsigneeEmail] 13 FROM [dbo].[Orders] AS [Extent1]
但是这种效果并不能让EntityFramework满意,于是他就盯上了人家AutoMapper,为什么?因为AutoMapper的一段代码就可以搞定上面的问题:
1 OrderDto dto = Mapper.Map<Order, OrderDto>(order);
相处的问题?
因为EntityFramework的疯狂追求,再加上他显赫的地位,让AutoMapper不得不接受了他,于是他们就交往了,但好像就是后羿和嫦娥的故事一样,不是一个世界的人,相处起来总会出现一些问题。虽然AutoMapper在对象转换方面很强大,而且大部分应用场景是Domain与ViewModel之间的映射转换,当涉及到数据访问时,AutoMapper就不是那么有用了。换句话说,AutoMapper工作在内存中的对象转换,而不是应用在数据访问中IQueryable的接口,在数据访问层我们使用EntityFramework把要查询的对象转化为SQL命令,如果在数据访问层使用AutoMapper,那么查询数据一定会发生在映射转换之后,而且查询出的数据一定会比转换的数据多,从而产生性能问题。
上面的示例我们修改下:
1 Mapper.CreateMap(); 2 var details = Mapper.Map , IEnumerable >(context.Orders).ToList();
其实这就是EntityFramework看上AutoMapper的原因,也是EntityFramework想要的效果,看下生成的SQL语句:
1 SELECT 2 [Extent1].[OrderId] AS [OrderId], 3 [Extent1].[OrderItemCount] AS [OrderItemCount], 4 [Extent1].[UserId] AS [UserId], 5 [Extent1].[ReceiverId] AS [ReceiverId], 6 [Extent1].[ShopDate] AS [ShopDate], 7 [Extent1].[OrderDate] AS [OrderDate], 8 [Extent1].[ConsigneeRealName] AS [ConsigneeRealName], 9 [Extent1].[ConsigneeName] AS [ConsigneeName], 10 [Extent1].[ConsigneePhone] AS [ConsigneePhone], 11 [Extent1].[ConsigneeProvince] AS [ConsigneeProvince], 12 [Extent1].[ConsigneeAddress] AS [ConsigneeAddress], 13 [Extent1].[ConsigneeZip] AS [ConsigneeZip], 14 [Extent1].[ConsigneeTel] AS [ConsigneeTel], 15 [Extent1].[ConsigneeFax] AS [ConsigneeFax], 16 [Extent1].[ConsigneeEmail] AS [ConsigneeEmail], 17 [Extent1].[WhetherCouAndinte] AS [WhetherCouAndinte], 18 [Extent1].[ParvalueAndInte] AS [ParvalueAndInte], 19 [Extent1].[PaymentType] AS [PaymentType], 20 [Extent1].[Payment] AS [Payment], 21 [Extent1].[Courier] AS [Courier], 22 [Extent1].[TotalPrice] AS [TotalPrice], 23 [Extent1].[FactPrice] AS [FactPrice], 24 [Extent1].[Invoice] AS [Invoice], 25 [Extent1].[Remark] AS [Remark], 26 [Extent1].[OrderStatus] AS [OrderStatus], 27 [Extent1].[SaleUserID] AS [SaleUserID], 28 [Extent1].[SaleUserType] AS [SaleUserType], 29 [Extent1].[BusinessmanID] AS [BusinessmanID], 30 [Extent1].[Carriage] AS [Carriage], 31 [Extent1].[PaymentStatus] AS [PaymentStatus], 32 [Extent1].[OgisticsStatus] AS [OgisticsStatus], 33 [Extent1].[OrderType] AS [OrderType], 34 [Extent1].[IsOrderNormal] AS [IsOrderNormal] 35 FROM [dbo].[Orders] AS [Extent1]
通过上面的SQL语句,会发现,虽然数据访问层代码写的简单了,但是查询的字段并不是我们想要的,也就是说查询发生在映射之前,可以想象如果存在上百万的数据或是上百行,使用AutoMapper进行映射转换是多么的不靠谱,难道EntityFramework和AutoMapper就没有缘分?或者只是EntityFramework的一厢情愿?请看下面。
女人的伟大?
在EntityFramework和AutoMapper的相处过程中,虽然出现了某些问题,但其实也并不是EntityFramework的错,错就错在他们生不逢地,通过相处AutoMapper也发现EntityFramework是真心对她好,于是AutoMapper决定要做些改变,为了EntityFramework,也为了他们的将来。
EntityFramework和AutoMapper不在一个世界的原因,前面我们也分析过,一个存在于内存中,一个存在于数据访问中,AutoMapper要做的就是去扩展IQueryable表达式(有点嫦娥下凡的意思哈),从而使他们可以存在于一个世界,于是她为了EntityFramework就做了以下工作:
1 public static class QueryableExtensions 2 { 3 public static ProjectionExpressionProject (this IQueryable source) 4 { 5 return new ProjectionExpression (source); 6 } 7 } 8 9 public class ProjectionExpression 10 { 11 private static readonly Dictionary<string, Expression> ExpressionCache = new Dictionary<string, Expression>(); 12 13 private readonly IQueryable _source; 14 15 public ProjectionExpression(IQueryable source) 16 { 17 _source = source; 18 } 19 20 public IQueryable To () 21 { 22 var queryExpression = GetCachedExpression () ?? BuildExpression (); 23 24 return _source.Select(queryExpression); 25 } 26 27 private static Expression > GetCachedExpression () 28 { 29 var key = GetCacheKey (); 30 31 return ExpressionCache.ContainsKey(key) ? ExpressionCache[key] as Expression > : null; 32 } 33 34 private static Expression > BuildExpression () 35 { 36 var sourceProperties = typeof(TSource).GetProperties(); 37 var destinationProperties = typeof(TDest).GetProperties().Where(dest => dest.CanWrite); 38 var parameterExpression = Expression.Parameter(typeof(TSource), "src"); 39 40 var bindings = destinationProperties 41 .Select(destinationProperty => BuildBinding(parameterExpression, destinationProperty, sourceProperties)) 42 .Where(binding => binding != null); 43 44 var expression = Expression.Lambda >(Expression.MemberInit(Expression.New(typeof(TDest)), bindings), parameterExpression); 45 46 var key = GetCacheKey (); 47 48 ExpressionCache.Add(key, expression); 49 50 return expression; 51 } 52 53 private static MemberAssignment BuildBinding(Expression parameterExpression, MemberInfo destinationProperty, IEnumerable sourceProperties) 54 { 55 var sourceProperty = sourceProperties.FirstOrDefault(src => src.Name == destinationProperty.Name); 56 57 if (sourceProperty != null) 58 { 59 return Expression.Bind(destinationProperty, Expression.Property(parameterExpression, sourceProperty)); 60 } 61 62 var propertyNames = SplitCamelCase(destinationProperty.Name); 63 64 if (propertyNames.Length == 2) 65 { 66 sourceProperty = sourceProperties.FirstOrDefault(src => src.Name == propertyNames[0]); 67 68 if (sourceProperty != null) 69 { 70 var sourceChildProperty = sourceProperty.PropertyType.GetProperties().FirstOrDefault(src => src.Name == propertyNames[1]); 71 72 if (sourceChildProperty != null) 73 { 74 return Expression.Bind(destinationProperty, Expression.Property(Expression.Property(parameterExpression, sourceProperty), sourceChildProperty)); 75 } 76 } 77 } 78 79 return null; 80 } 81 82 private static string GetCacheKey () 83 { 84 return string.Concat(typeof(TSource).FullName, typeof(TDest).FullName); 85 } 86 87 private static string[] SplitCamelCase(string input) 88 { 89 return Regex.Replace(input, "([A-Z])", " $1", RegexOptions.Compiled).Trim().Split(' '); 90 } 91 }
修改示例代码:
1 Mapper.CreateMap(); 2 var details = context.Orders.Project().To ();
通过AutoMapper所做的努力,使得代码更加简化,只要配置一个类型映射,传递目标类型,就可以得到我们想要的转换对象,代码如此简洁,我们再来看下生成SQL代码:
1 SELECT 2 [Project1].[OrderId] AS [OrderId], 3 [Project1].[OrderItemCount] AS [OrderItemCount], 4 [Project1].[ConsigneeRealName] AS [ConsigneeRealName], 5 [Project1].[ConsigneeName] AS [ConsigneeName], 6 [Project1].[ConsigneePhone] AS [ConsigneePhone], 7 [Project1].[ConsigneeProvince] AS [ConsigneeProvince], 8 [Project1].[ConsigneeAddress] AS [ConsigneeAddress], 9 [Project1].[ConsigneeZip] AS [ConsigneeZip], 10 [Project1].[ConsigneeTel] AS [ConsigneeTel], 11 [Project1].[ConsigneeFax] AS [ConsigneeFax], 12 [Project1].[ConsigneeEmail] AS [ConsigneeEmail], 13 [Project1].[C1] AS [C1], 14 [Project1].[OrderItemId] AS [OrderItemId], 15 [Project1].[ProName] AS [ProName], 16 [Project1].[ProImg] AS [ProImg], 17 [Project1].[ProPrice] AS [ProPrice], 18 [Project1].[ProNum] AS [ProNum], 19 [Project1].[AddTime] AS [AddTime], 20 [Project1].[ProOtherPara] AS [ProOtherPara], 21 [Project1].[Order_OrderId] AS [Order_OrderId] 22 FROM ( SELECT 23 [Extent1].[OrderId] AS [OrderId], 24 [Extent1].[OrderItemCount] AS [OrderItemCount], 25 [Extent1].[ConsigneeRealName] AS [ConsigneeRealName], 26 [Extent1].[ConsigneeName] AS [ConsigneeName], 27 [Extent1].[ConsigneePhone] AS [ConsigneePhone], 28 [Extent1].[ConsigneeProvince] AS [ConsigneeProvince], 29 [Extent1].[ConsigneeAddress] AS [ConsigneeAddress], 30 [Extent1].[ConsigneeZip] AS [ConsigneeZip], 31 [Extent1].[ConsigneeTel] AS [ConsigneeTel], 32 [Extent1].[ConsigneeFax] AS [ConsigneeFax], 33 [Extent1].[ConsigneeEmail] AS [ConsigneeEmail], 34 [Extent2].[OrderItemId] AS [OrderItemId], 35 [Extent2].[ProName] AS [ProName], 36 [Extent2].[ProImg] AS [ProImg], 37 [Extent2].[ProPrice] AS [ProPrice], 38 [Extent2].[ProNum] AS [ProNum], 39 [Extent2].[AddTime] AS [AddTime], 40 [Extent2].[ProOtherPara] AS [ProOtherPara], 41 [Extent2].[Order_OrderId] AS [Order_OrderId], 42 CASE WHEN ([Extent2].[OrderItemId] IS NULL) THEN CAST(NULL AS int) ELSE 1 END AS [C1] 43 FROM [dbo].[Orders] AS [Extent1] 44 LEFT OUTER JOIN [dbo].[OrderItems] AS [Extent2] ON [Extent1].[OrderId] = [Extent2].[Order_OrderId] 45 ) AS [Project1] 46 ORDER BY [Project1].[OrderId] ASC, [Project1].[C1] ASC
可以看出因为Order和OrderConsignee包含对OrderItems子集的映射关系:
1 ///2 /// 订单项 3 /// 4 public virtual ICollection OrderItems { get; set; }
所以AutoMapper会自动匹配关联子集进行查询,当然也可以在创建映射关系的时候对OrderItems进行忽略:Mapper.CreateMap
剧情收尾?
示例代码下载:http://pan.baidu.com/s/1c0h9TNM
经过一切风风雨雨,EntityFramework终于和AutoMapper过上了幸福美满的日子,但是看似幸福,但是问题还是不断,有人又提出疑问:
- http://rogeralsing.com/2013/12/01/why-mapping-dtos-to-entities-using-automapper-and-entityframework-is-horrible/
文章的标题用了“horrible”这个单词,翻译为可怕的,难道说EntityFramework和AutoMapper在一起有那么可怕吗?当然这只是针对EntityFramework使用AutoMapper进行CURD操作,但是我相信EntityFramework和AutoMapper会克服重重困难,生死不渝的。我们也会一直关注他们的婚后生活,未完待续。。。
如果你也祝福EntityFramework和AutoMapper会永远在一起,那就疯狂的“戳”右下角的“推荐”吧。^_^