YngwieWang commented on a change in pull request #9299: [FLINK-13405][docs-zh]
Translate "Basic API Concepts" page into Chinese
URL: https://github.com/apache/flink/pull/9299#discussion_r317597048
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File path: docs/dev/api_concepts.zh.md
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@@ -605,46 +523,35 @@ data.map (new RichMapFunction[String, Int] {
</div>
-Rich functions provide, in addition to the user-defined function (map,
-reduce, etc), four methods: `open`, `close`, `getRuntimeContext`, and
-`setRuntimeContext`. These are useful for parameterizing the function
-(see [Passing Parameters to Functions]({{ site.baseurl
}}/dev/batch/index.html#passing-parameters-to-functions)),
-creating and finalizing local state, accessing broadcast variables (see
-[Broadcast Variables]({{ site.baseurl
}}/dev/batch/index.html#broadcast-variables)), and for accessing runtime
-information such as accumulators and counters (see
-[Accumulators and Counters](#accumulators--counters)), and information
-on iterations (see [Iterations]({{ site.baseurl }}/dev/batch/iterations.html)).
+富函数为用户定义函数（map、reduce 等）额外提供了 4 个方法： `open`、`close`、`getRuntimeContext` 和
`setRuntimeContext`。这些方法有助于向函数传参（请参阅 [向函数传递参数]({{ site.baseurl
}}/zh/dev/batch/index.html#passing-parameters-to-functions)）、
+创建和终止本地状态、访问广播变量（请参阅
+[广播变量]({{ site.baseurl
}}/zh/dev/batch/index.html#broadcast-variables)）、访问诸如累加器和计数器等运行时信息（请参阅
+[累加器和计数器](#accumulators--counters)）和迭代信息（请参阅 [迭代]({{ site.baseurl
}}/zh/dev/batch/iterations.html)）。
{% top %}
-Supported Data Types
+支持的数据类型
--------------------
-Flink places some restrictions on the type of elements that can be in a
DataSet or DataStream.
-The reason for this is that the system analyzes the types to determine
-efficient execution strategies.
+Flink 对于 DataSet 或 DataStream 中可以包含的元素类型做了一些限制。这么做是为了使系统能够分析类型以确定有效的执行策略。
-There are six different categories of data types:
+有六种不同的数据类型：
-1. **Java Tuples** and **Scala Case Classes**
-2. **Java POJOs**
-3. **Primitive Types**
-4. **Regular Classes**
-5. **Values**
-6. **Hadoop Writables**
-7. **Special Types**
+1. **Java Tuple** 和 **Scala Case Class**
+2. **Java POJO**
+3. **基本数据类型**
+4. **常规的类**
+5. **值**
+6. **Hadoop Writable**
+7. **特殊类型**
-#### Tuples and Case Classes
+#### Tuple 和 Case Class
<div class="codetabs" markdown="1">
<div data-lang="java" markdown="1">
-Tuples are composite types that contain a fixed number of fields with various
types.
-The Java API provides classes from `Tuple1` up to `Tuple25`. Every field of a
tuple
-can be an arbitrary Flink type including further tuples, resulting in nested
tuples. Fields of a
-tuple can be accessed directly using the field's name as `tuple.f4`, or using
the generic getter method
-`tuple.getField(int position)`. The field indices start at 0. Note that this
stands in contrast
-to the Scala tuples, but it is more consistent with Java's general indexing.
+Tuple 是复合类型，包含固定数量的各种类型的字段。
+Java API 提供了从 `Tuple1` 到 `Tuple25` 的类。 Tuple 的每一个字段可以是任意 Flink 类型，包括
Tuple，即嵌套的 Tuple。Tuple 的字段可以通过字段序号如 `tuple.f4` 直接访问，也可以使用通常的 getter 方法
`tuple.getField(int position)`。字段索引从 0 开始。请注意，这与 Scala Tuple 形成鲜明对比，但与 Java
的常规索引更为一致。
Review comment:
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