klion26 commented on a change in pull request #11971:
URL: https://github.com/apache/flink/pull/11971#discussion_r422456499
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File path: docs/training/datastream_api.zh.md
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@@ -24,30 +24,27 @@ specific language governing permissions and limitations
under the License.
-->
-The focus of this training is to broadly cover the DataStream API well enough
that you will be able
-to get started writing streaming applications.
+该练习的重点是充分全面地了解 DataStream API，以便于入门编写流式应用。
* This will be replaced by the TOC
{:toc}
-## What can be Streamed?
+## 什么能被转化成流？
-Flink's DataStream APIs for Java and Scala will let you stream anything they
can serialize. Flink's
-own serializer is used for
+Flink 的 Java 和 Scala DataStream API 可以将任何可序列化的对象转化为流。Flink 自带的序列化器有
-- basic types, i.e., String, Long, Integer, Boolean, Array
-- composite types: Tuples, POJOs, and Scala case classes
+- 基本类型，即String、Long、Integer、Boolean、Array
+- 复合类型：Tuples、POJOs 和 Scala case classes
-and Flink falls back to Kryo for other types. It is also possible to use other
serializers with
-Flink. Avro, in particular, is well supported.
+而且 Flink 可以交给 Kryo 序列化其他类型。也可以将其他序列化器和 Flink 一起使用。特别是有良好支持的 Avro。
Review comment:
这里我建议用 ”会交给“ 而不是 ”可以交给“ 是因为，从语义上来说，”可以交给“，那也可以 ”不“
交给，是一个可选项。但是这里的意思不是一个可选项，而是说，会直接使用 Kryo 进行序列化。
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