KarmaGYZ commented on a change in pull request #11401: [FLINK-15991][doc][zh]
Translate memory configuration docs into Chinese.
URL: https://github.com/apache/flink/pull/11401#discussion_r392801162
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File path: docs/ops/memory/mem_tuning.zh.md
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@@ -22,66 +22,55 @@ specific language governing permissions and limitations
under the License.
-->
-In addition to the [main memory setup guide](mem_setup.html), this section
explains how to setup memory of task executors
-depending on the use case and which options are important in which case.
+本文在的基本的[配置指南](mem_setup.html)的基础上，介绍如何根据具体的使用场景调整 TaskExecutor
的内存配置，以及在不同使用场景下分别需要重点关注哪些配置参数。
* toc
{:toc}
-## Configure memory for standalone deployment
+## 独立部署模式（Standalone Deployment）下的内存配置
-It is recommended to configure [total Flink memory](mem_setup.html#配置总内存)
-([`taskmanager.memory.flink.size`](../config.html#taskmanager-memory-flink-size))
or its [components](mem_detail.html)
-for [standalone deployment](../deployment/cluster_setup.html) where you want
to declare how much memory is given to Flink itself.
-Additionally, you can adjust *JVM metaspace* if it causes
[problems](mem_trouble.html#outofmemoryerror-metaspace).
+[独立部署模式](../deployment/cluster_setup.html)，我们通常更关注 Flink 应用本身使用的内存大小。
+建议配置 [Flink
总内存](mem_setup.html#配置总内存)（[`taskmanager.memory.flink.size`](../config.html#taskmanager-memory-flink-size)）或者它的[组成部分](mem_detail.html)。
+此外，如果出现 [Metaspace 不足的问题](mem_trouble.html#outofmemoryerror-metaspace)，可以调整
*JVM Metaspace* 的大小。
-The *total Process memory* is not relevant because *JVM overhead* is not
controlled by Flink or deployment environment,
-only physical resources of the executing machine matter in this case.
+这种情况下通常无需配置*进程总内存*，因为不管是 Flink 还是部署环境都不会对 *JVM 开销* 进行限制，它只与机器的物理资源相关。
-## Configure memory for containers
+## 容器（Container）的内存配置
-It is recommended to configure [total process memory](mem_setup.html#配置总内存)
-([`taskmanager.memory.process.size`](../config.html#taskmanager-memory-process-size))
for the containerized deployments
-([Kubernetes](../deployment/kubernetes.html),
[Yarn](../deployment/yarn_setup.html) or [Mesos](../deployment/mesos.html)).
-It declares how much memory in total should be assigned to the Flink *JVM
process* and corresponds to the size of the requested container.
+在容器化部署模式（Containerized
Deployment）下（[Kubernetes](../deployment/kubernetes.html)、[Yarn](../deployment/yarn_setup.html)
或
[Mesos](../deployment/mesos.html)），建议配置[进程总内存](mem_setup.html#配置总内存)（[`taskmanager.memory.process.size`](../config.html#taskmanager-memory-process-size)）。
+该配置参数用于指定分配给 Flink *JVM 进程*的总内存，也就是需要申请的容器大小。
-<span class="label label-info">Note</span> If you configure the *total Flink
memory* Flink will implicitly add JVM memory components
-to derive the *total process memory* and request a container with the memory
of that derived size,
-see also [detailed Memory Model](mem_detail.html).
+<span class="label label-info">提示</span> 如果配置了 *Flink 总内存*，Flink 会自动加上 JVM
相关的内存部分，根据推算出的*进程总内存*大小申请容器。
+请参考[内存模型详解](mem_detail.html)。
<div class="alert alert-warning">
- <strong>Warning:</strong> If Flink or user code allocates unmanaged off-heap
(native) memory beyond the container size
- the job can fail because the deployment environment can kill the offending
containers.
+ <strong>注意：</strong> 如果 Flink
或者用户代码分配超过容器大小的非托管的堆外（本地）内存，部署环境可能会杀掉超用内存的容器，造成作业执行失败。
</div>
-See also description of [container memory
exceeded](mem_trouble.html#container-memory-exceeded) failure.
+请参考[容器内存超用](mem_trouble.html#container-memory-exceeded)中的相关描述。
-## Configure memory for state backends
+## State Backend 的内存配置
-When deploying a Flink streaming application, the type of [state
backend](../state/state_backends.html) used
-will dictate the optimal memory configurations of your cluster.
+在部署 Flink 流处理应用时，可以根据 [State Backend](../state/state_backends.html)
的类型对集群的配置进行优化。
-### Heap state backend
+### Heap State Backend
-When running a stateless job or using a heap state backend
([MemoryStateBackend](../state/state_backends.html#the-memorystatebackend)
-or [FsStateBackend](../state/state_backends.html#the-fsstatebackend)), set
[managed memory](mem_setup.html#托管内存) to zero.
-This will ensure that the maximum amount of memory is allocated for user code
on the JVM.
+执行无状态作业或者使用 Heap State
Backend（[MemoryStateBackend](../state/state_backends.html#the-memorystatebackend)
+或
[FsStateBackend](../state/state_backends.html#the-fsstatebackend)）时，建议将[托管内存](mem_setup.html#托管内存)设置为
0。
+这样能够最大化分配给 JVM 上用户代码的内存。
-### RocksDB state backend
+### RocksDB State Backend
-The
[RocksDBStateBackend](../state/state_backends.html#the-rocksdbstatebackend)
uses native memory. By default,
-RocksDB is setup to limit native memory allocation to the size of the [managed
memory](mem_setup.html#托管内存).
-Therefore, it is important to reserve enough *managed memory* for your state
use case. If you disable the default RocksDB memory control,
-task executors can be killed in containerized deployments if RocksDB allocates
memory above the limit of the requested container size
-(the [total process memory](mem_setup.html#配置总内存)).
-See also [how to tune RocksDB
memory](../state/large_state_tuning.html#tuning-rocksdb-memory)
-and
[state.backend.rocksdb.memory.managed](../config.html#state-backend-rocksdb-memory-managed).
+[RocksDBStateBackend](../state/state_backends.html#the-rocksdbstatebackend)
使用本地内存。
Review comment:
Broken link. Should be #rocksdbstatebackend
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