事件流最大的问题是可见性和性能;您需要将显示的事件限制为只显示该特定用户感兴趣的事件，并且需要保持整理和识别这些事件所需的时间。我建立了一个小型的社交网络;我发现，在小范围内，在数据库中保留“事件”表是可行的，但在中等负载下就会出现性能问题。

对于较大的消息流和用户，最好使用消息传递系统，将事件作为消息发送到单个配置文件。这意味着您不能很容易地订阅人们的事件流，也不能很容易地查看以前的事件，但是当您需要为特定用户呈现流时，您只是呈现了一小组消息。

I believe this was Twitter's original design flaw- I remember reading that they were hitting the database to pull in and filter their events. This had everything to do with architecture and nothing to do with Rails, which (unfortunately) gave birth to the "ruby doesn't scale" meme. I recently saw a presentation where the developer used Amazon's Simple Queue Service as their messaging backend for a twitter-like application that would have far higher scaling capabilities- it may be worth looking into SQS as part of your system, if your loads are high enough.

我认为Plurk的方法很有趣:他们以一种看起来很像谷歌Finance的股票图表的格式提供你的整个时间轴。

想要了解一个社交网络是如何运作的，不妨看看Ning。开发人员页面看起来特别有用。

我在几个月前解决了这个问题，但我认为我的实现太基础了。 我创建了以下模型:

HISTORY_TYPE

ID           - The id of the history type
NAME         - The name (type of the history)
DESCRIPTION  - A description

HISTORY_MESSAGES

ID
HISTORY_TYPE - A message of history belongs to a history type
MESSAGE      - The message to print, I put variables to be replaced by the actual values

HISTORY_ACTIVITY

ID
MESSAGE_ID    - The message ID to use
VALUES        - The data to use

例子

MESSAGE_ID_1 => "User %{user} created a new entry"
ACTIVITY_ID_1 => MESSAGE_ID = 1, VALUES = {user: "Rodrigo"}

事件流最大的问题是可见性和性能;您需要将显示的事件限制为只显示该特定用户感兴趣的事件，并且需要保持整理和识别这些事件所需的时间。我建立了一个小型的社交网络;我发现，在小范围内，在数据库中保留“事件”表是可行的，但在中等负载下就会出现性能问题。

对于较大的消息流和用户，最好使用消息传递系统，将事件作为消息发送到单个配置文件。这意味着您不能很容易地订阅人们的事件流，也不能很容易地查看以前的事件，但是当您需要为特定用户呈现流时，您只是呈现了一小组消息。

I believe this was Twitter's original design flaw- I remember reading that they were hitting the database to pull in and filter their events. This had everything to do with architecture and nothing to do with Rails, which (unfortunately) gave birth to the "ruby doesn't scale" meme. I recently saw a presentation where the developer used Amazon's Simple Queue Service as their messaging backend for a twitter-like application that would have far higher scaling capabilities- it may be worth looking into SQS as part of your system, if your loads are high enough.

After implementing activity streams to enable social feeds, microblogging, and collaboration features in several applications, I realized that the base functionality is quite common and could be turned into an external service that you utilize via an API. If you are building the stream into a production application and do not have unique or deeply complex needs, utilizing a proven service may be the best way to go. I would definitely recommend this for production applications over rolling your own simple solution on top of a relational database.

我的公司collaboration (http://www.collabinate.com)就是从这种实现中发展出来的，我们在图形数据库上实现了一个可伸缩的高性能活动流引擎来实现它。实际上，我们使用了Graphity算法的变体(改编自@RenePickhardt的早期工作，他也在这里提供了答案)来构建引擎。

如果您希望自己托管引擎或需要特殊功能，其核心代码实际上是非商业用途的开源代码，因此欢迎您查看。

如果你决定用Rails实现，也许你会发现下面的插件很有用:

ActivityStreams: http://github.com/face/activity_streams/tree/master

如果没有其他问题，您将从数据模型和为推拉活动提供的API两方面来研究一个实现。