klion26 commented on a change in pull request #8341: [FLINK-11633][docs-zh]
Translate "Working with state" into Chinese
URL: https://github.com/apache/flink/pull/8341#discussion_r280979970
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File path: docs/dev/stream/state/state.zh.md
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@@ -22,122 +22,87 @@ specific language governing permissions and limitations
under the License.
-->
-This document explains how to use Flink's state abstractions when developing
an application.
-
-* ToC
+本文档主要介绍如何在 Flink 作业中使用状态
+* 目录
{:toc}
## Keyed State and Operator State
-There are two basic kinds of state in Flink: `Keyed State` and `Operator
State`.
+Flink 中有两种基本的状态：`Keyed State` 和 `Operator State`
### Keyed State
-*Keyed State* is always relative to keys and can only be used in functions and
operators on a `KeyedStream`.
+*Keyed State* 通常和键相关，仅可使用在 `KeyedStream` 的方法和算子中。
-You can think of Keyed State as Operator State that has been partitioned,
-or sharded, with exactly one state-partition per key.
-Each keyed-state is logically bound to a unique
-composite of <parallel-operator-instance, key>, and since each key
-"belongs" to exactly one parallel instance of a keyed operator, we can
-think of this simply as <operator, key>.
+你可以把 Keyed State 看作分区或者共享的 Operator State, 而且每个键仅出现在一个分区内。
+逻辑上每个 keyed-state 和 <算子并发实例, key> 相绑定，由于每个 key 仅"属于"
+算子的一个并发，因此简化为 <算子, key>。
-Keyed State is further organized into so-called *Key Groups*. Key Groups are
the
-atomic unit by which Flink can redistribute Keyed State;
-there are exactly as many Key Groups as the defined maximum parallelism.
-During execution each parallel instance of a keyed operator works with the keys
-for one or more Key Groups.
+Keyed State 会按照 *Key Group* 进行管理。Key Group 是 Flink 分发 Keyed State 的最小单元；
+Key Groups 的数目等于作业的最大并发数。在执行过程中，每个 keyed operator 会对应到一个或多个 Key Group
### Operator State
-With *Operator State* (or *non-keyed state*), each operator state is
-bound to one parallel operator instance.
-The [Kafka Connector]({{ site.baseurl }}/dev/connectors/kafka.html) is a good
motivating example for the use of Operator State
-in Flink. Each parallel instance of the Kafka consumer maintains a map
-of topic partitions and offsets as its Operator State.
+对于 *Operator State* (或者 *non-keyed state*) 来说，每个 operator state 和一个并发实例进行绑定。
+[Kafka Connector]({{ site.baseurl }}/zh/dev/connectors/kafka.html) 是 Flink 中使用
operator state 的一个很好的示例。
+每个 Kafka 消费者的并发在 Operator State 中维护一个 topic partition 到 offset 的映射关系。
-The Operator State interfaces support redistributing state among
-parallel operator instances when the parallelism is changed. There can be
different schemes for doing this redistribution.
+Operator State 在 Flink 作业的并发改变后，会重新分发状态，分发的策略和 Keyed State 不一样。
Review comment:
`Operator State 在 Flink 作业的并发改变后` --> `Operator State 在 Flink 作业改变并发后`
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