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new f063d5f [HUDI-823] fix typo (#1545)
f063d5f is described below
commit f063d5f4b6024b81154ed76fe61e15c9eccf5493
Author: wanglisheng81 <37138788+wanglishen...@users.noreply.github.com>
AuthorDate: Tue Apr 21 19:31:39 2020 +0800
[HUDI-823] fix typo (#1545)
---
docs/_docs/1_1_quick_start_guide.cn.md | 4 ++--
docs/_docs/1_1_quick_start_guide.md | 2 +-
2 files changed, 3 insertions(+), 3 deletions(-)
diff --git a/docs/_docs/1_1_quick_start_guide.cn.md
b/docs/_docs/1_1_quick_start_guide.cn.md
index d8bf2e7..7404bb8 100644
--- a/docs/_docs/1_1_quick_start_guide.cn.md
+++ b/docs/_docs/1_1_quick_start_guide.cn.md
@@ -54,7 +54,7 @@ df.write.format("org.apache.hudi").
`mode(Overwrite)`覆盖并重新创建数据集(如果已经存在)。
您可以检查在`/tmp/hudi_cow_table/<region>/<country>/<city>/`下生成的数据。我们提供了一个记录键
-([schema](#sample-schema)中的`uuid`)，分区字段(`region/county/city`）和组合逻辑([schema](#sample-schema)中的`ts`)
+([schema](#sample-schema)中的`uuid`)，分区字段(`region/country/city`）和组合逻辑([schema](#sample-schema)中的`ts`)
以确保行程记录在每个分区中都是唯一的。更多信息请参阅
[对Hudi中的数据进行建模](https://cwiki.apache.org/confluence/pages/viewpage.action?pageId=113709185#FAQ-HowdoImodelthedatastoredinHudi)，
有关将数据提取到Hudi中的方法的信息，请参阅[写入Hudi数据集](/cn/docs/writing_data.html)。
@@ -158,4 +158,4 @@ spark.sql("select `_hoodie_commit_time`, fare, begin_lon,
begin_lat, ts from hu
这里我们使用Spark演示了Hudi的功能。但是，Hudi可以支持多种存储类型/视图，并且可以从Hive，Spark，Presto等查询引擎中查询Hudi数据集。
我们制作了一个基于Docker设置、所有依赖系统都在本地运行的[演示视频](https://www.youtube.com/watch?v=VhNgUsxdrD0)，
我们建议您复制相同的设置然后按照[这里](/cn/docs/docker_demo.html)的步骤自己运行这个演示。
-另外，如果您正在寻找将现有数据迁移到Hudi的方法，请参考[迁移指南](/cn/docs/migration_guide.html)。
\ No newline at end of file
+另外，如果您正在寻找将现有数据迁移到Hudi的方法，请参考[迁移指南](/cn/docs/migration_guide.html)。
diff --git a/docs/_docs/1_1_quick_start_guide.md
b/docs/_docs/1_1_quick_start_guide.md
index 8111acf..08269ec 100644
--- a/docs/_docs/1_1_quick_start_guide.md
+++ b/docs/_docs/1_1_quick_start_guide.md
@@ -70,7 +70,7 @@ df.write.format("hudi").
`mode(Overwrite)` overwrites and recreates the table if it already exists.
You can check the data generated under
`/tmp/hudi_trips_cow/<region>/<country>/<city>/`. We provided a record key
-(`uuid` in
[schema](https://github.com/apache/incubator-hudi/blob/master/hudi-spark/src/main/java/org/apache/hudi/QuickstartUtils.java#L58)),
partition field (`region/county/city`) and combine logic (`ts` in
+(`uuid` in
[schema](https://github.com/apache/incubator-hudi/blob/master/hudi-spark/src/main/java/org/apache/hudi/QuickstartUtils.java#L58)),
partition field (`region/country/city`) and combine logic (`ts` in
[schema](https://github.com/apache/incubator-hudi/blob/master/hudi-spark/src/main/java/org/apache/hudi/QuickstartUtils.java#L58))
to ensure trip records are unique within each partition. For more info, refer
to
[Modeling data stored in
Hudi](https://cwiki.apache.org/confluence/pages/viewpage.action?pageId=113709185#FAQ-HowdoImodelthedatastoredinHudi)
and for info on ways to ingest data into Hudi, refer to [Writing Hudi
Tables](/docs/writing_data.html).
