Mrzyxing commented on code in PR #20510:
URL: https://github.com/apache/flink/pull/20510#discussion_r948566977
##########
docs/content.zh/docs/try-flink/table_api.md:
##########
@@ -163,44 +161,41 @@ tEnv.executeSql("CREATE TABLE spend_report (\n" +
")");
```
-The second table, `spend_report`, stores the final results of the aggregation.
-Its underlying storage is a table in a MySql database.
+第二张 `spend_report` 表存储聚合后的最终结果，底层存储是 MySQL 数据库中的一张表。
-#### The Query
+#### 查询数据
-With the environment configured and tables registered, you are ready to build
your first application.
-From the `TableEnvironment` you can read `from` an input table to read its
rows and then write those results into an output table using `executeInsert`.
-The `report` function is where you will implement your business logic.
-It is currently unimplemented.
+配置好环境并注册好表后，你就可以开始开发你的第一个应用了。
+通过 `TableEnvironment` ，你可以 `from` 输入表读取数据，然后将结果调用 `executeInsert` 写入到输出表。
+函数 `report` 用于实现具体的业务逻辑，这里暂时未实现。
```java
Table transactions = tEnv.from("transactions");
report(transactions).executeInsert("spend_report");
```
-## Testing
+## 测试
-The project contains a secondary testing class `SpendReportTest` that
validates the logic of the report.
-It creates a table environment in batch mode.
+项目还包含一个测试类 `SpendReportTest`，辅助验证报表逻辑。
+该测试类的表环境使用的是批处理模式。
```java
EnvironmentSettings settings = EnvironmentSettings.inBatchMode();
TableEnvironment tEnv = TableEnvironment.create(settings);
```
-One of Flink's unique properties is that it provides consistent semantics
across batch and streaming.
-This means you can develop and test applications in batch mode on static
datasets, and deploy to production as streaming applications.
+提供批流统一的语义是 Flink 的特性，这意味着应用的开发和测试可以在批模式下使用静态数据集完成，而实际部署到生产时再切换为流式。
Review Comment:
Prefered '重要特性' so far.
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