[GitHub] [incubator-hudi] leesf commented on a change in pull request #1006: [HUDI-276] Translate the Configurations page into Chinese

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leesf commented on a change in pull request #1006: [HUDI-276] Translate the Configurations page into Chinese
URL: https://github.com/apache/incubator-hudi/pull/1006#discussion_r344466045
 
 

 ##########
 File path: docs/configurations.cn.md
 ##########
 @@ -1,48 +1,46 @@
 ---
-title: Configurations
+title: 配置
 keywords: garbage collection, hudi, jvm, configs, tuning
 sidebar: mydoc_sidebar
 permalink: configurations.html
 toc: true
-summary: "Here we list all possible configurations and what they mean"
+summary: 在这里，我们列出了所有可能的配置及其含义。
 ---
-This page covers the different ways of configuring your job to write/read Hudi datasets. 
-At a high level, you can control behaviour at few levels. 
-
-- **[Spark Datasource Configs](#spark-datasource)** : These configs control the Hudi Spark Datasource, providing ability to define keys/partitioning, pick out the write operation, specify how to merge records or choosing view type to read.
-- **[WriteClient Configs](#writeclient-configs)** : Internally, the Hudi datasource uses a RDD based `HoodieWriteClient` api to actually perform writes to storage. These configs provide deep control over lower level aspects like 
-   file sizing, compression, parallelism, compaction, write schema, cleaning etc. Although Hudi provides sane defaults, from time-time these configs may need to be tweaked to optimize for specific workloads.
-- **[RecordPayload Config](#PAYLOAD_CLASS_OPT_KEY)** : This is the lowest level of customization offered by Hudi. Record payloads define how to produce new values to upsert based on incoming new record and 
-   stored old record. Hudi provides default implementations such as `OverwriteWithLatestAvroPayload` which simply update storage with the latest/last-written record. 
-   This can be overridden to a custom class extending `HoodieRecordPayload` class, on both datasource and WriteClient levels.
+该页面介绍了几种配置写入或读取Hudi数据集的作业的方法。
+简而言之，您可以在几个级别上控制行为。
+
+- **[Spark Datasource 配置](#spark-datasource)** : 这些配置控制Hudi Spark Datasource，提供如下功能：
+   定义键和分区、选择写操作、指定如何合并记录或选择要读取的视图类型。
+- **[WriteClient 配置](#writeclient-configs)** : 在内部，Hudi数据源使用基于RDD的`HoodieWriteClient` API
+   真正执行对存储的写入。 这些配置可对文件大小、压缩（compression）、并行性、压缩（compaction）、写入模式、清理等底层方面进行完全控制。
 
 Review comment:
   并行性 -> 并行度？

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