MongoDB:调用Count()与跟踪集合中的计数 [英] MongoDB: Calling Count() vs tracking counts in a collection

问题描述

我正在将消息传递系统迁移到MongoDB，并且很好奇如何处理各种统计信息，例如每个用户的消息数等.在MS SQL数据库中，我有一个表，其中每个用户的计数不同，它们得到了通过在相应表上的触发器进行更新，因此，例如，我可以知道UserA拥有多少未读消息，而无需调用昂贵的SELECT Count(*)操作.

I am moving our messaging system to MongoDB and am curious what approach to take with respect to various stats, like number of messages per user etc. In MS SQL database I have a table where I have different counts per user and they get updated by trigger on corresponding tables, so I can for example know how many unread messages UserA has without calling an expensive SELECT Count(*) operation.

MongoDB中的count函数是否也很昂贵? 我开始阅读有关map/reduce的信息，但是我的网站负载很大，因此统计信息必须实时更新，我的理解是map/reduce的操作非常耗时.

Is count function in MongoDB also expensive? I started reading about map/reduce but my site is high load, so statistics has to update in real time, and my understanding is that map/reduce is time consuming operation.

在MongoDB中收集各种汇总计数的最佳(性能方面)方法是什么?

What would be the best (performance-wise) approach on gathering various aggregate counts in MongoDB?

推荐答案

如果您有很多数据，那么我会坚持使用相同的方法，并在为用户添加新消息时增加聚合计数器. ，使用类似这样的集合:

If you've got a lot of data, then I'd stick with the same approach and increment an aggregate counter whenever a new message is added for a user, using a collection something like this:

计数

{
    userid: 123,
    messages: 10
}

不幸的是(或幸运的是?)MongoDB中没有触发器，因此您需要从应用程序逻辑中增加计数器:

Unfortunately (or fortunately?) there are no triggers in MongoDB, so you'd increment the counter from your application logic:

db.counts.update( { userid: 123 }, { $inc: { messages: 1 } } )

这将为您提供最佳性能，并且您可能还会在userid字段上添加索引以进行快速查找:

This'll give you the best performance, and you'd probably also put an index on the userid field for fast lookups:

db.counts.ensureIndex( { userid: 1 } )

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