EF 剥坑

Posted 2020-07-10 EchoSong

 

1、简单 count 会生成不必要的嵌套

var xs = (from x in dbContext.db_API_Operationallog where x.id<1  select 1 ).Count();

结果：

SELECT 
[GroupBy1].[A1] AS [C1]
FROM ( SELECT 
    COUNT(1) AS [A1]
    FROM [dbo].[db_API_Operationallog] AS [Extent1]
    WHERE [Extent1].[id] < 1
)  AS [GroupBy1]

2、查询某些列的时候会整个模型查询

    context.db_API_Operationallog.FirstOrDefault(p => p.Id == postId).Hits;
    或者：
    context.db_API_Operationallog.Find(postId).Hits;

会把整个post表数据都查出然后再内存里面找了hits这个列

优化：

    context.db_API_Operationallog.Where(p => p.Id == postId).Select(p => p.Hits).FirstOrDefault();

3、不要轻易的把数据全部加载到内存

有时候一个不小心在查询的sql build 里面加了个tolist(), toArray()等，这种真正的执行了查询，这样在开发环境往往表的数据比较少，程序运行比较快，但是一到线上环境数据量比较大的情况下就会出现内存爆满的问题，这个问题相对来说比较隐蔽，所以开发的时候一定要小心。

4、IQueryable, IEnumerable

IEnumerable 执行的where 先是走内存，在走内存查询

    public IEnumerable<db_API_Operationallog> GetAllPost()
    {
            return context.Post;
    }

    int id = 2000;
    var log = GetAllPost().Where(s => s.id <id).ToList();

Sql Server Profiler 抓到的信息

 SELECT 
[Extent1].[id] AS [id], 
[Extent1].[uid] AS [uid], 
[Extent1].[types] AS [types], 
[Extent1].[events] AS [events], 
[Extent1].[more] AS [more], 
[Extent1].[money] AS [money], 
[Extent1].[lastmoney] AS [lastmoney], 
[Extent1].[nowmoney] AS [nowmoney], 
[Extent1].[bak] AS [bak], 
[Extent1].[times] AS [times]
FROM [dbo].[db_API_Operationallog] AS [Extent1]

把上面的 IEnumerable 换成 IQueryable

exec sp_executesql N\'SELECT 
[Extent1].[id] AS [id], 
[Extent1].[uid] AS [uid], 
[Extent1].[types] AS [types], 
[Extent1].[events] AS [events], 
[Extent1].[more] AS [more], 
[Extent1].[money] AS [money], 
[Extent1].[lastmoney] AS [lastmoney], 
[Extent1].[nowmoney] AS [nowmoney], 
[Extent1].[bak] AS [bak], 
[Extent1].[times] AS [times]
FROM [dbo].[db_API_Operationallog] AS [Extent1]
WHERE [Extent1].[id] < @p__linq__0\',N\'@p__linq__0 int\',@p__linq__0=2000

这个坑是比较同样也是比较隐蔽的注意下

5、使用 NoTracking 降低 状态开销

  dbContext.db_API_Operationallog.Where(s => s.id < id).AsNoTracking().ToList();

总结

平时写EF的时候一定要把脚步停下了 多使用 Sql Server Profiler 琢磨下自己的代码