• 自己实现的.NET数据库访问框架Chloe.ORM
  • Cathy 发表于 2016/7/4 10:23:00 | 分类标签: .NET ORM框架 LINQ
  • 13年毕业之际，进入第一家公司实习，接触了 EntityFramework，当时就觉得这东西太牛了，访问数据库都可以做得这么轻松、优雅！毕竟那时还年轻，没见过世面。工作之前为了拿个实习机会混个工作证明，匆匆忙忙学了两个月的 C#，就这样，稀里糊涂的做了程序员，从此走上了一条不归路。那会也只知道 SqlHelper，DataTable。ORM？太高档上，没听说过。虽然在第一家公司只呆了两个月，但让我认识了 EntityFramework，从此也走上了 ORM 的不归路...纯纯的实体，增改删超级简单，查询如行云流水，真心没理由抗拒！以至于后来进入第二家公司做开发极其不适应，因为他们没用 EF，也不用类 linq 的 ORM，他们有自己数据库访问框架。那套东西实体设计复杂，支持的功能少，查询条件还依赖字符串，开发容错率太低，DB操作入口接口设计也很重，里面方法不下60个，看心凉，用心累！那时，好怀念 EF~在新公司工作的时间内，来回都是增改页面，做增删查改，修复BUG，多少有点枯燥乏味，渐渐感觉编码能力提升太慢。同时鉴于用公司的 ORM 也不是很顺手，于是，萌生了自己写 ORM 的念头，再然后...Chloe.ORM 面世了~

    Chloe.ORM

    Chloe 查询接口设计借(zhao)鉴(ban) linq，但不支持 linq。开发之前，我给我的 ORM 查询条件接口定义一定要支持lambda表达式(潮流、趋势，在这不讨论表达式树的性能)。开发之初，也有自己设计过查询接口，想了一套又一套，始终没 linq 设计的接口方便，后来，不想了，直接抄 linq，不解释！前人如此伟大设计，不用真对不起他们，我要站在他们的肩膀上！

    先看下 IDbContext 接口：

    public interface IDbContext : IDisposable
{
    IDbSession CurrentSession { get; }

    IQuery<T> Query<T>() where T : new();
    IEnumerable<T> SqlQuery<T>(string sql, params DbParam[] parameters) where T : new();

    T Insert<T>(T entity);
    object Insert<T>(Expression<Func<T>> body);

    int Update<T>(T entity);
    int Update<T>(Expression<Func<T, T>> body, Expression<Func<T, bool>> condition);

    int Delete<T>(T entity);
    int Delete<T>(Expression<Func<T, bool>> condition);

    void TrackEntity(object entity);
}
    复制代码

    Chloe 操作入口是 IDbContext。IDbContext 仅有两个 Query、两个 Insert、两个 Update 、两个 Delete 和一个 TrackEntity 方法，以及一个 CurrentDbSession 的属性，设计很简单，但绝对能满足81%的需求(多一点满足，多一分热爱)！
    这篇文章，主要介绍 Query 接口使用。

    实体：

    public enum Gender
{
    Man = 1,
    Woman
}

[TableAttribute("Users")]
public class User
{
    [Column(IsPrimaryKey = true)]
    [AutoIncrementAttribute]
    public int Id { get; set; }
    public string Name { get; set; }
    public Gender? Gender { get; set; }
    public int? Age { get; set; }
    public int? CityId { get; set; }
    public DateTime? OpTime { get; set; }
}

public class City
{
    [Column(IsPrimaryKey = true)]
    public int Id { get; set; }
    public string Name { get; set; }
    public int ProvinceId { get; set; }
}

public class Province
{
    [Column(IsPrimaryKey = true)]
    public int Id { get; set; }
    public string Name { get; set; }
}

    首先，创建一个 DbContext：

    IDbContext context = new MsSqlContext(DbHelper.ConnectionString);

    再创建一个 IQuery<T>：

    IQuery<User> q = context.Query<User>();

    基本查询

    IQuery<User> q = context.Query<User>();
q.Where(a => a.Id > 0).FirstOrDefault();
q.Where(a => a.Id > 0).ToList();
q.Where(a => a.Id > 0).OrderBy(a => a.Age).ToList();
q.Where(a => a.Id > 0).Take(999).OrderBy(a => a.Age).ToList();

//分页。避免生成的 sql 语句太长占篇幅，只选取 Id 和 Name 两个字段
q.Where(a => a.Id > 0).OrderBy(a => a.Age).ThenByDesc(a => a.Id).Select(a => new { a.Id, a.Name }).Skip(1).Take(999).ToList();
/*
 * SELECT TOP (999) [T].[Id] AS [Id],[T].[Name] AS [Name] FROM (SELECT [Users].[Id] AS [Id],[Users].[Name] AS [Name],ROW_NUMBER() OVER(ORDER BY [Users].[Age] ASC,[Users].[Id] DESC) AS [ROW_NUMBER_0] FROM [Users] AS [Users] WHERE [Users].[Id] > 0) AS [T] WHERE [T].[ROW_NUMBER_0] > 1
 */

//如果需要多个条件的话
q.Where(a => a.Id > 0).Where(a => a.Name.Contains("lu")).ToList();
/*
 * SELECT [Users].[Id] AS [Id],[Users].[Name] AS [Name],[Users].[Gender] AS [Gender],[Users].[Age] AS [Age],[Users].[CityId] AS [CityId],[Users].[OpTime] AS [OpTime] FROM [Users] AS [Users] WHERE ([Users].[Id] > 0 AND [Users].[Name] LIKE '%' + N'lu' + '%')
 */

//选取指定字段
q.Select(a => new { a.Id, a.Name, a.Age }).ToList();
//或者
q.Select(a => new User() { Id = a.Id, Name = a.Name, Age = a.Age }).ToList();
/*
 * SELECT [Users].[Id] AS [Id],[Users].[Name] AS [Name],[Users].[Age] AS [Age] FROM [Users] AS [Users]
 */

    连接查询

    建立连接：

    MsSqlContext context = new MsSqlContext(DbHelper.ConnectionString);
IQuery<User> users = context.Query<User>();
IQuery<City> cities = context.Query<City>();
IQuery<Province> provinces = context.Query<Province>();

IJoiningQuery<User, City> user_city = users.InnerJoin(cities, (user, city) => user.CityId == city.Id);
IJoiningQuery<User, City, Province> user_city_province = user_city.InnerJoin(provinces, (user, city, province) => city.ProvinceId == province.Id);

    只获取 UserId,CityName,ProvinceName：

    user_city_province.Select((user, city, province) => new { UserId = user.Id, CityName = city.Name, ProvinceName = province.Name }).Where(a => a.UserId == 1).ToList();
/*
 * SELECT [Users].[Id] AS [UserId],[City].[Name] AS [CityName],[Province].[Name] AS [ProvinceName] FROM [Users] AS [Users] INNER JOIN [City] AS [City] ON [Users].[CityId] = [City].[Id] INNER JOIN [Province] AS [Province] ON [City].[ProvinceId] = [Province].[Id] WHERE [Users].[Id] = 1
 */

    调用 Select 方法返回一个包含所有信息的 IQuery<T> 对象：

    var view = user_city_province.Select((user, city, province) => new { User = user, City = city, Province = province });

    查出一个用户及其隶属的城市和省份：

    view.Where(a => a.User.Id == 1).ToList();
/*
 * SELECT [Users].[Id] AS [Id],[Users].[Name] AS [Name],[Users].[Gender] AS [Gender],[Users].[Age] AS [Age],[Users].[CityId] AS [CityId],[Users].[OpTime] AS [OpTime],[City].[Id] AS [Id0],[City].[Name] AS [Name0],[City].[ProvinceId] AS [ProvinceId],[Province].[Id] AS [Id1],[Province].[Name] AS [Name1] FROM [Users] AS [Users] INNER JOIN [City] AS [City] ON [Users].[CityId] = [City].[Id] INNER JOIN [Province] AS [Province] ON [City].[ProvinceId] = [Province].[Id] WHERE [Users].[Id] = 1
 */

    这时候也可以选取指定的字段：

    view.Where(a => a.User.Id == 1).Select(a => new { UserId = a.User.Id, CityName = a.City.Name, ProvinceName = a.Province.Name }).ToList();
/*
 * SELECT [Users].[Id] AS [UserId],[City].[Name] AS [CityName],[Province].[Name] AS [ProvinceName] FROM [Users] AS [Users] INNER JOIN [City] AS [City] ON [Users].[CityId] = [City].[Id] INNER JOIN [Province] AS [Province] ON [City].[ProvinceId] = [Province].[Id] WHERE [Users].[Id] = 1
 */

    Chloe 也支持 Left Join、Right Join、Full Join连接，用法和 Inner Join 一样，就不一一介绍了。

    聚合函数

    IQuery<User> q = context.Query<User>();

q.Select(a => DbFunctions.Count()).First();
/*
 * SELECT TOP (1) COUNT(1) AS [C] FROM [Users] AS [Users]
 */

q.Select(a => new { Count = DbFunctions.Count(), LongCount = DbFunctions.LongCount(), Sum = DbFunctions.Sum(a.Age), Max = DbFunctions.Max(a.Age), Min = DbFunctions.Min(a.Age), Average = DbFunctions.Average(a.Age) }).First();
/*
 * SELECT TOP (1) COUNT(1) AS [Count],COUNT_BIG(1) AS [LongCount],SUM([Users].[Age]) AS [Sum],MAX([Users].[Age]) AS [Max],MIN([Users].[Age]) AS [Min],CAST(AVG([Users].[Age]) AS FLOAT) AS [Average] FROM [Users] AS [Users]
 */

var count = q.Count();
/*
 * SELECT COUNT(1) AS [C] FROM [Users] AS [Users]
 */

var longCount = q.LongCount();
/*
 * SELECT COUNT_BIG(1) AS [C] FROM [Users] AS [Users]
 */

var sum = q.Sum(a => a.Age);
/*
 * SELECT SUM([Users].[Age]) AS [C] FROM [Users] AS [Users]
 */

var max = q.Max(a => a.Age);
/*
 * SELECT MAX([Users].[Age]) AS [C] FROM [Users] AS [Users]
 */

var min = q.Min(a => a.Age);
/*
 * SELECT MIN([Users].[Age]) AS [C] FROM [Users] AS [Users]
 */

var avg = q.Average(a => a.Age);
/*
 * SELECT CAST(AVG([Users].[Age]) AS FLOAT) AS [C] FROM [Users] AS [Users]
 */

    分组查询

    IQuery<User> q = context.Query<User>();

IGroupingQuery<User> g = q.Where(a => a.Id > 0).GroupBy(a => a.Age);
g = g.Having(a => a.Age > 1 && DbFunctions.Count() > 0);

g.Select(a => new { a.Age, Count = DbFunctions.Count(), Sum = DbFunctions.Sum(a.Age), Max = DbFunctions.Max(a.Age), Min = DbFunctions.Min(a.Age), Avg = DbFunctions.Average(a.Age) }).ToList();
/*
 * SELECT [Users].[Age] AS [Age],COUNT(1) AS [Count],SUM([Users].[Age]) AS [Sum],MAX([Users].[Age]) AS [Max],MIN([Users].[Age]) AS [Min],CAST(AVG([Users].[Age]) AS FLOAT) AS [Avg] FROM [Users] AS [Users] WHERE [Users].[Id] > 0 GROUP BY [Users].[Age] HAVING ([Users].[Age] > 1 AND COUNT(1) > 0)
 */

    SqlQuery

    上面是纯面向对象的方式查询。连接查询、聚合查询、分组查询如此轻松，有没有觉得很方便？当然，始终和 linq 那种接近 sql 的 from v in q where v > 3 select v 写法没法比！同时，ORM始终是个工具，它并不是万能的，对于一些复杂的语句，还是得需要手写，因此，DbContext 也提供原生 sql 查询接口

    context.SqlQuery<User>("select Id,Name,Age from Users where [email protected]", DbParam.Create("@name", "lu")).ToList();
context.SqlQuery<int>("select Id from Users").ToList();

    经测试，非 Debug 情况下，且都经过预热后，相同的查询在速度、性能上与 Dapper 相当，甚至比 Dapper 还快那么一丢丢。

    使用进阶

    IQuery<T> 接口支持连接查询、聚合查询、分组查询，这几个接口配合使用可以减少很多我们开发中的烦恼。比如：

    去视图

    做数据库开发，多表关联的数据结构肯定不少，难免会有多表连接查询，很多时候，为了方便查询，一般我们都会建立视图。在我看来视图很烦，真的烦。

    int 烦 = 0;

    1.建视图的时候，字段多的话，烦++，如果出现字段重名的情况，必须起别名，烦++。

    2.视图建立起来了以后，查询是方便了，但后面维护就不那么友好了，比如某个表字段名改了、增加一个字段、删除一个字段等情况，得修改相应的视图(1个或多个)，烦++；同时又要去修改相映射的实体，烦++。总之，Console.Write("烦烦烦: " + 烦.ToString()); 对于我这种懒程序员，这简直就是种煎熬！如果一套 ORM 支持连接查询，在一定程度上可以减少在数据库上建视图数量，无形中省出好多时间。

    为了让 Chloe 支持连接查询，费了我不少劲。连接查询的好处可以看上面连接查询部分。

    勉强应付一些复杂查询

    比如，本文中的 User 表、City 表，他们的关系是一个 User 隶属一个 City，一个 City 有多个用户。假设，现在有需求要查出 City 的信息，同时也要把该 City 下用户最小的年龄输出，如果用原生 sql 写的话大概是：

    select City.*,T.MinAge from City left join (select CityId,Min(Users.Age) as MinAge from Users group by Users.CityId) as T on City.Id=T.CityId

    虽然也不是很复杂。来看看 Chloe 如何实现：

    IQuery<User> users = context.Query<User>();
IQuery<City> cities = context.Query<City>();
var gq = users.GroupBy(a => a.CityId).Select(a => new { a.CityId, MinAge = DbFunctions.Min(a.Age) });

cities.LeftJoin(gq, (city, g) => city.Id == g.CityId).Select((city, g) => new { City = city, MinAge = g.MinAge }).ToList();
/*
 * SELECT [T].[MinAge] AS [MinAge],[City].[Id] AS [Id],[City].[Name] AS [Name],[City].[ProvinceId] AS [ProvinceId] FROM [City] AS [City] LEFT JOIN (SELECT [Users].[CityId] AS [CityId],MIN([Users].[Age]) AS [MinAge] FROM [Users] AS [Users] GROUP BY [Users].[CityId]) AS [T] ON [City].[Id] = [T].[CityId]
 */

    完全可以用面向对象的方式就可以实现，怎么样？很实用吧，免去拼 sql，让更多的时间去做业务开发！

    更多的用法还有待挖掘。

    支持的lambda

    Chloe 查询条件依赖 lambda 表达式，从对 lambda 表达式树零认知到完成对其解析这块，花了我好多精力，费了好多神，掉了不少头发。现在对谓语支持很丰富，可以说爱怎么写就怎么写~

    IQuery<User> q = context.Query<User>();

List<int> ids = new List<int>();
ids.Add(1);
ids.Add(2);
ids.Add(2);

string name = "lu";
string nullString = null;
bool b = false;
bool b1 = true;

q.Where(a => true).ToList();
q.Where(a => a.Id == 1).ToList();
q.Where(a => a.Id == 1 || a.Id > 1).ToList();
q.Where(a => a.Id == 1 && a.Name == name && a.Name == nullString && a.Id == FeatureTest.ID).ToList();
q.Where(a => ids.Contains(a.Id)).ToList();
q.Where(a => !b == (a.Id > 0)).ToList();
q.Where(a => a.Id > 0).Where(a => a.Id == 1).ToList();
q.Where(a => !(a.Id > 10)).ToList();
q.Where(a => !(a.Name == name)).ToList();
q.Where(a => a.Name != name).ToList();
q.Where(a => a.Name == name).ToList();
q.Where(a => (a.Name == name) == (a.Id > 0)).ToList();
q.Where(a => a.Name == (a.Name ?? name)).ToList();
q.Where(a => (a.Age == null ? 0 : 1) == 1).ToList();

//运算操作符
q.Select(a => new
{
    Add = 1 + 2,
    Subtract = 2 - 1,
    Multiply = 2 * 11,
    Divide = 4 / 2,
    And = true & false,
    IntAnd = 1 & 2,
    Or = true | false,
    IntOr = 3 | 1,
}).ToList();

    常用的函数

      IQuery<User> q = context.Query<User>();

  var space = new char[] { ' ' };

  DateTime startTime = DateTime.Now;
  DateTime endTime = DateTime.Now.AddDays(1);
  q.Select(a => new
{
    Id = a.Id,

    String_Length = (int?)a.Name.Length,//LEN([Users].[Name])
    Substring = a.Name.Substring(0),//SUBSTRING([Users].[Name],0 + 1,LEN([Users].[Name]))
    Substring1 = a.Name.Substring(1),//SUBSTRING([Users].[Name],1 + 1,LEN([Users].[Name]))
    Substring1_2 = a.Name.Substring(1, 2),//SUBSTRING([Users].[Name],1 + 1,2)
    ToLower = a.Name.ToLower(),//LOWER([Users].[Name])
    ToUpper = a.Name.ToUpper(),//UPPER([Users].[Name])
    IsNullOrEmpty = string.IsNullOrEmpty(a.Name),//太长，不贴了
    Contains = (bool?)a.Name.Contains("s"),//太长，略
    Trim = a.Name.Trim(),//RTRIM(LTRIM([Users].[Name]))
    TrimStart = a.Name.TrimStart(space),//LTRIM([Users].[Name])
    TrimEnd = a.Name.TrimEnd(space),//RTRIM([Users].[Name])
    StartsWith = (bool?)a.Name.StartsWith("s"),//太长，略
    EndsWith = (bool?)a.Name.EndsWith("s"),//太长，略

    SubtractTotalDays = endTime.Subtract(startTime).TotalDays,//CAST(DATEDIFF(DAY,@P_0,@P_1)
    SubtractTotalHours = endTime.Subtract(startTime).TotalHours,//CAST(DATEDIFF(HOUR,@P_0,@P_1)
    SubtractTotalMinutes = endTime.Subtract(startTime).TotalMinutes,//CAST(DATEDIFF(MINUTE,@P_0,@P_1)
    SubtractTotalSeconds = endTime.Subtract(startTime).TotalSeconds,//CAST(DATEDIFF(SECOND,@P_0,@P_1)
    SubtractTotalMilliseconds = endTime.Subtract(startTime).TotalMilliseconds,//CAST(DATEDIFF(MILLISECOND,@P_0,@P_1)

    Now = DateTime.Now,//GETDATE()
    UtcNow = DateTime.UtcNow,//GETUTCDATE()
    Today = DateTime.Today,//CAST(GETDATE() AS DATE)
    Date = DateTime.Now.Date,//CAST(GETDATE() AS DATE)
    Year = DateTime.Now.Year,//DATEPART(YEAR,GETDATE())
    Month = DateTime.Now.Month,//DATEPART(MONTH,GETDATE())
    Day = DateTime.Now.Day,//DATEPART(DAY,GETDATE())
    Hour = DateTime.Now.Hour,//DATEPART(HOUR,GETDATE())
    Minute = DateTime.Now.Minute,//DATEPART(MINUTE,GETDATE())
    Second = DateTime.Now.Second,//DATEPART(SECOND,GETDATE())
    Millisecond = DateTime.Now.Millisecond,//DATEPART(MILLISECOND,GETDATE())
    DayOfWeek = DateTime.Now.DayOfWeek,//(DATEPART(WEEKDAY,GETDATE()) - 1)

    Int_Parse = int.Parse("1"),//CAST(N'1' AS INT)
    Int16_Parse = Int16.Parse("11"),//CAST(N'11' AS SMALLINT)
    Long_Parse = long.Parse("2"),//CAST(N'2' AS BIGINT)
    Double_Parse = double.Parse("3"),//CAST(N'3' AS FLOAT)
    Float_Parse = float.Parse("4"),//CAST(N'4' AS REAL)
    Decimal_Parse = decimal.Parse("5"),//CAST(N'5' AS DECIMAL)
    Guid_Parse = Guid.Parse("D544BC4C-739E-4CD3-A3D3-7BF803FCE179"),//CAST(N'xxx' AS UNIQUEIDENTIFIER) AS [Guid_Parse]

    Bool_Parse = bool.Parse("1"),//CASE WHEN CAST(N'1' AS BIT) = CAST(1 AS BIT) THEN CAST(1 AS BIT) WHEN NOT (CAST(N'1' AS BIT) = CAST(1 AS BIT)) THEN CAST(0 AS BIT) ELSE NULL END AS [Bool_Parse]
    DateTime_Parse = DateTime.Parse("1992-1-16"),//CAST(N'1992-1-16' AS DATETIME) AS [DateTime_Parse]

    B = a.Age == null ? false : a.Age > 1,
}).ToList();

    Chloe 的查询，基本就这些用法。因为查询接口直接借鉴 linq，所以，看起来就好像在介绍 linq 一样，抱歉- -。也正因为这点，之前我把项目中的 EF 替换成 Chloe 的时候，因为我个人不怎么用 linq 的 from in select 那种语法，所以，替换的时候几乎不用改什么代码，就可以成功编译运行。EF 对实体间的关系处理得非常好，如一对多，一对一导航，Chloe 倒没那么强大。就目前的 Chloe 的 Query 接口，基本可以满足大部分查询需求了。

    现在市面上各种ORM，层出不穷，有人可能会问 LZ 为什么还要重复造轮子？

    1. 这确实是一个ORM齐放的年代，各色各样，千奇百怪的都有。但让人满意的框架(EF除外，EF在我心中是神一样的存在)少之又少。做得不错的，也总有些方面不足，恰恰却因为一些小小的不足让我止步，如实体复杂，不支持 lambda，支持lambda的但支持的写法又不多，连接查询不是很友好、便捷等等，都怪我太挑剔，抱歉。
    2. 文章开头也说过，增删查改，烦了。想用业余时间做点有意思的东西，提升自己编码能力的同时也可以学到更多知识。因为写了这个框架，我对面对对象的理解更加深刻了，如果不尝试的话，我估计我在程序员职业生涯内连个抽象类、接口都不会设计，更别说会什么设计模式，面对对象编程原则了。之所以选择做 ORM 来开刀，因为 ORM 很贴切我们日常开发，只要涉及数据库，就可以用到！
    3. 如果上面两点还不足以让您明白我为什么要造轮子，那最后我要告诉您的是：我是一枚任性的程序员，我就是要造轮子！

    结语

    Chloe.ORM 完全开源，遵循 Apache2.0 协议，托管于GitHub，供大伙学习参考，如果能参与开发与完善 Chloe 那再好不过了，项目地址：https://github.com/shuxinqin/Chloe。感兴趣或觉得不错的望赏个star，不胜感激！

    若能顺手点个赞，更加感谢！

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