wuchong commented on a change in pull request #9749: [FLINK-14115][docs-zh]
Translate DataStream Code Walkthrough to Chinese
URL: https://github.com/apache/flink/pull/9749#discussion_r340056277
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File path: docs/getting-started/walkthroughs/datastream_api.zh.md
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@@ -24,43 +24,43 @@ specific language governing permissions and limitations
under the License.
-->
-Apache Flink offers a DataStream API for building robust, stateful streaming
applications.
-It provides fine-grained control over state and time, which allows for the
implementation of advanced event-driven systems.
-In this step-by-step guide you'll learn how to build a stateful streaming
application with Flink's DataStream API.
+Apache Flink 提供了 DataStream API 来实现稳定可靠的、有状态的流处理应用程序。
+Flink 支持对状态和时间的细粒度控制，以此来实现复杂的事件驱动数据处理系统。
+这个入门指导手册讲述了如何通过 Flink DataStream API 来实现一个有状态流处理程序。
-* This will be replaced by the TOC
+* 这里使用 TOC 替换
{:toc}
-## What Are You Building?
+## 你要搭建一个什么系统
-Credit card fraud is a growing concern in the digital age.
-Criminals steal credit card numbers by running scams or hacking into insecure
systems.
-Stolen numbers are tested by making one or more small purchases, often for a
dollar or less.
-If that works, they then make more significant purchases to get items they can
sell or keep for themselves.
+在当今数字时代，信用卡欺诈行为越来越被重视。
+罪犯可以通过诈骗或者入侵安全级别较低系统来盗窃信用卡卡号。
+用盗得的信用卡进行很小额度的例如一美元或者更小额度的消费进行测试。
+如果测试消费成功，那么他们就会用这个信用卡进行大笔消费，来购买一些他们希望得到的，或者可以倒卖的财物。
-In this tutorial, you will build a fraud detection system for alerting on
suspicious credit card transactions.
-Using a simple set of rules, you will see how Flink allows us to implement
advanced business logic and act in real-time.
+在这个教程中，你将会建立一个针对可疑信用卡交易行为的反欺诈检测系统。
+通过使用一组简单的规则，你将了解到 Flink 如何为我们实现复杂业务逻辑并实时执行
-## Prerequisites
+## 准备条件
-This walkthrough assumes that you have some familiarity with Java or Scala,
but you should be able to follow along even if you are coming from a different
programming language.
+这个代码练习假定你对 Java 或 Scala 有一定的了解，当然，如果你之前使用的是其他开发语言，你也应该能够跟随本教程进行学习。
-## Help, I’m Stuck!
+## 困难求助
-If you get stuck, check out the [community support
resources](https://flink.apache.org/gettinghelp.html).
-In particular, Apache Flink's [user mailing
list](https://flink.apache.org/community.html#mailing-lists) is consistently
ranked as one of the most active of any Apache project and a great way to get
help quickly.
+如果遇到困难，可以参考 [社区支持资源](https://flink.apache.org/zh/gettinghelp.html)。
+当然也可以在邮件列表提问，Flink 的
[用户邮件列表](https://flink.apache.org/zh/community.html#mailing-lists)
一直被评为所有Apache项目中最活跃的一个，这也是快速获得帮助的好方法。
-## How to Follow Along
+## 怎样跟着教程练习
-If you want to follow along, you will require a computer with:
+首先，你需要在你的电脑上准备以下环境：
-* Java 8
-* Maven
+* Java 8
+* Maven
-A provided Flink Maven Archetype will create a skeleton project with all the
necessary dependencies quickly, so you only need to focus on filling out the
business logic.
-These dependencies include `flink-streaming-java` which is the core dependency
for all Flink streaming applications and `flink-walkthrough-common` that has
data generators and other classes specific to this walkthrough.
+一个准备好的 Flink Maven Archetype 能够快速创建一个包含了必要依赖的 Flink
程序骨架，基于此，你可以把精力集中在编写业务逻辑上即可。
+这些已包含的依赖包括 `flink-streaming-java`、`flink-walkthrough-common` 等，他们分别是 Flink
应用程序的核心依赖项和这个代码练习需要的数据生成器，当然还包括其他本代码练习所依赖的类
Review comment:
```suggestion
这些已包含的依赖包括 `flink-streaming-java`、`flink-walkthrough-common` 等，他们分别是 Flink
应用程序的核心依赖项和这个代码练习需要的数据生成器，当然还包括其他本代码练习所依赖的类。
```
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