yihua commented on a change in pull request #884: [HUDI-240] Translate Use 
Cases page
URL: https://github.com/apache/incubator-hudi/pull/884#discussion_r324035236
 
 

 ##########
 File path: docs/use_cases.cn.md
 ##########
 @@ -4,73 +4,65 @@ keywords: hudi, data ingestion, etl, real time, use cases
 sidebar: mydoc_sidebar
 permalink: use_cases.html
 toc: false
-summary: "Following are some sample use-cases for Hudi, which illustrate the 
benefits in terms of faster processing & increased efficiency"
+summary: "下面展示一些使用Hudi的示例,示例说明了加快处理速度和提高效率的好处"
 
 ---
 
 
 
-## Near Real-Time Ingestion
+## 近实时摄取
 
-Ingesting data from external sources like (event logs, databases, external 
sources) into a [Hadoop Data Lake](http://martinfowler.com/bliki/DataLake.html) 
is a well known problem.
-In most (if not all) Hadoop deployments, it is unfortunately solved in a 
piecemeal fashion, using a medley of ingestion tools,
-even though this data is arguably the most valuable for the entire 
organization.
+将外部源(如事件日志,数据库,外部源)的数据摄取到[Hadoop数据湖](http://martinfowler.com/bliki/DataLake.html)是一个众所周知的问题。
+尽管这些数据对整个组织来说是最有价值的,但不幸的是,在大多数(可能不是全部)Hadoop部署中都使用零散的方式解决,即使用混合摄取工具。
 
 
-For RDBMS ingestion, Hudi provides __faster loads via Upserts__, as opposed 
costly & inefficient bulk loads. For e.g, you can read the MySQL BIN log or 
[Sqoop Incremental 
Import](https://sqoop.apache.org/docs/1.4.2/SqoopUserGuide.html#_incremental_imports)
 and apply them to an
-equivalent Hudi table on DFS. This would be much faster/efficient than a [bulk 
merge 
job](https://sqoop.apache.org/docs/1.4.0-incubating/SqoopUserGuide.html#id1770457)
-or [complicated handcrafted merge 
workflows](http://hortonworks.com/blog/four-step-strategy-incremental-updates-hive/)
+对于RDBMS摄取,Hudi提供__通过更新插入更快地加载__,而不是昂贵且低效的批量加载。例如,您可以读取MySQL 
BIN日志或[Sqoop增量导入](https://sqoop.apache.org/docs/1.4.2/SqoopUserGuide.html#_incremental_imports)并将其应用于
+DFS上的等效Hudi表。这比[批量合并任务](https://sqoop.apache.org/docs/1.4.0-incubating/SqoopUserGuide.html#id1770457)更快/更有效率或[复杂的手工合并工作流](http://hortonworks.com/blog/four-step-strategy-incremental-updates-hive/)
 
 
-For NoSQL datastores like [Cassandra](http://cassandra.apache.org/) / 
[Voldemort](http://www.project-voldemort.com/voldemort/) / 
[HBase](https://hbase.apache.org/), even moderately big installations store 
billions of rows.
-It goes without saying that __full bulk loads are simply infeasible__ and more 
efficient approaches are needed if ingestion is to keep up with the typically 
high update volumes.
+对于NoSQL数据存储,如[Cassandra](http://cassandra.apache.org/) / 
[Voldemort](http://www.project-voldemort.com/voldemort/) / 
[HBase](https://hbase.apache.org/),即使是中等规模大小也会存储数十亿行。
+毫无疑问, __全量加载不可行__ 如果摄取需要跟上较高的更新量,那么则需要更有效的方法。
 
 
-Even for immutable data sources like [Kafka](kafka.apache.org) , Hudi helps 
__enforces a minimum file size on HDFS__, which improves NameNode health by 
solving one of the [age old problems in Hadoop 
land](https://blog.cloudera.com/blog/2009/02/the-small-files-problem/) in a 
holistic way. This is all the more important for event streams, since typically 
its higher volume (eg: click streams) and if not managed well, can cause 
serious damage to your Hadoop cluster.
+即使对于像[Kafka](kafka.apache.org)这样的不可变数据源,Hudi也可以 __强制在HDFS上使用最小文件大小__, 
这以整体的方式解决[Hadoop中的一个老问题](https://blog.cloudera.com/blog/2009/02/the-small-files-problem/)来改善NameNode的健康状况。这对事件流来说更为重要,因为它通常具有较高容量(例如:点击流),如果管理不当,可能会对Hadoop群集造成严重损害。
 
-Across all sources, Hudi adds the much needed ability to atomically publish 
new data to consumers via notion of commits, shielding them from partial 
ingestion failures
+在所有源中,Hudi增加了通过提交概念以原子方式向消费者发布新数据所需的能力,使其免受部分摄取失败的影响。
 
+## 近实时分析
 
-## Near Real-time Analytics
+通常,实时[datamarts](https://en.wikipedia.org/wiki/Data_mart)由专业数据存储分析提供支持,例如[Druid](http://druid.io/)或[Memsql](http://www.memsql.com/)或[OpenTSDB](http://opentsdb.net/)。
+这对于较小规模([相比于这样安装Hadoop](https://blog.twitter.com/2015/hadoop-filesystem-at-twitter))的数据量来说绝对是完美的,这需要在亚秒级响应查询,例如系统监控或交互式实时分析。
 
 Review comment:
   “[相比于这样安装Hadoop]” should be after “完美的”?
   “这需要” => “这种情况需要”

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