January 2018
Beginner to intermediate
234 pages
7h 8m
Chinese
Content preview from Kafka权威指南
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流式处理
｜
187
式处理有一些特有的概念，对于那些有数据处理经验但是首次尝试开发流式处理应用程序
的人来说，很容易造成混淆。下面将试着澄清这些概念。
11.2.1
时间
时间或许就是流式处理最为重要的概念，也是最让人感到困惑的。在讨论分布式系统时，
该如何理解复杂的时间概念？推荐阅读
Justin Sheehy
的论文“
There is No Now
”。在流式
处理里，时间是一个非常重要的概念，因为大部分流式应用的操作都是基于时间窗口的。
例如，流式应用可能会计算股价的
5
分钟移动平均数。如果生产者因为网络问题离线了
2
小时，然后带着
2
小时的数据重新连线，我们需要知道该如何处理这些数据。这些数据大
部分都已经超过了
5
分钟，而且没有参与之前的计算。
流式处理系统一般包含如下几个时间概念。
事件时间
事件时间是指所追踪事件的发生时间和记录的创建时间。例如，度量的获取时间、商店
里商品的出售时间、网站用户访问网页的时间，等等。在
Kafka 0.10.0
和更高版本里，
生产者会自动在记录中添加记录的创建时间。如果这个时间戳与应用程序对“事件时
间”的定义不一样，例如，
Kafka
的记录是基于事件发生后的数据库记录创建的，那就
需要自己设置这个时间戳字段。在处理数据流时，事件时间是很重要的。
日志追加时间
日志追加时间是指事件保存到
broker
的时间。在
Kafka 0.10.0
和更高版本里，如果启用
了自动添加时间戳的功能，或者记录是使用旧版本的生产者客户端生成的，而且没有包
含时间戳，那么
broker
会在接收这些记录时自动添加时间戳 ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.