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
｜
189
事件保存到流里。大部分数据库提供了用于捕捉变更的“
Change Data Capture
”（
CDC
）解
决方案，
Kafka
连接器将这些变更发送到
Kafka
，用于后续的流式处理。
为了将流转化成表，需要“应用”流里所包含的所有变更，这也叫作流的“物化”。首
先在内存里、内部状态存储或外部数据库里创建一个表，然后从头到尾遍历流里的所
有事件，逐个地改变状态。在完成这个过程之后，得到了一个表，它代表了某个时间
点的状态。
假设有一个鞋店，某零售活动可以使用一个事件流来表示：
“红色、蓝色和绿色鞋子到货”
“蓝色鞋子卖出”
“红色鞋子卖出”
“蓝色鞋子退货”
“绿色鞋子卖出”
如果想知道现在仓库里还有哪些库存，或者到目前为止赚了多少钱，需要对视图进行物
化。图
11-1
告诉我们，目前还有蓝色和黄色鞋子，账户上有
170
美元。如果想知道鞋店的
繁忙程度，可以查看整个事件流，会发现总共发生了
5
个交易，还可以查出为什么蓝色鞋
子被退货。
发货
仓库变更事件流
销售退货
蓝色鞋子
红色鞋子
蓝色鞋子
红色鞋子
绿色鞋子
红色鞋子
蓝色鞋子
绿色鞋子
蓝色鞋子
绿色鞋子
代表仓库最新状态
的表或物化视图
图 11-1：物化仓库变更事件流
11.2.4
时间窗口
大部分针对流的操作都是基于时间窗口的，比如移动平均数、一周内销量最好的产品、系
统的
99
百分位等。两个流的合并操作也是基于时间窗口的，我们会合并发生在相同时间
片段上的事件。不过，很少人会停下来仔细想想时间窗口的类型。例如，在计算移动平均
数时，需要知道以下几个问题。
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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.