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
｜
199
}
}
➊
基于拓扑和配置属性定义一个 KafkaStreams 对象。
➋
启动
Kafka Streams
引擎。
➌
过一段时间后将它停掉。
就是这么简单！本例只用了几行代码，就演示了如何实现
单事件处理
模式（在事件上使用
了
map
与
filter
），然后通过
group by
操作对数据进行
重新分区
，并为统计记录个数维护了
一个简单的
本地状态
。
建议运行完整的示例，
GitHub
库的
README
文件包含了如何运行示例的说明。
也许你会注意到，除了
Kafka
外，不需要在机器上安装任何软件，就可以运行完整的示
例。这类似于在“本地模式”下使用
Spark
。主要的不同之处在于，如果主题包含了多个
分区，就可以运行多个字数统计应用实例（在不同的命令行终端运行），而这也就是第一
个
Streams
集群。几个字数统计应用实例之间互相交互，协调处理任务。
Spark
的本地模
式非常简单，但要在生产环境运行集群，需要安装
YARN
或者
Mesos
，并在所有的机器上
安装
Spark
，然后将你的应用提交到集群上，所以
Spark
有较高的准入门槛。而如果使用
Streams API
，只需要启动几个应用实例就可以拥有一个集群。在开发机上运行和在生产环
境中运行几乎是一样的。
11.4.2
股票市场统计
接下来的这个例子会复杂一些，下面将从一个股票交易事件流里读取事件，这些事件包含
了股票代码、沽盘价和要价规模。在股票交易里，沽盘价是指卖方的出价，买入价是指买
方建议支付的价格，要价规模是指卖方愿意在相应价格基础上出售的股数。为了简单起 ...
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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.