This is an automated email from the ASF dual-hosted git repository.
leesf pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-hudi.git
The following commit(s) were added to refs/heads/asf-site by this push:
new 46a1546 [HUDI-356][chinese] Sync changes in quickstart.cn and
admin_guide.cn pages (#1038)
46a1546 is described below
commit 46a1546259fcfb629a26508e829d3d3e4b9cee21
Author: hongdd <jn_...@163.com>
AuthorDate: Fri Nov 22 14:59:30 2019 +0800
[HUDI-356][chinese] Sync changes in quickstart.cn and admin_guide.cn pages
(#1038)
---
docs/admin_guide.cn.md | 2 +-
docs/quickstart.cn.md | 19 +++++++++++++------
2 files changed, 14 insertions(+), 7 deletions(-)
diff --git a/docs/admin_guide.cn.md b/docs/admin_guide.cn.md
index 4be569c..f980113 100644
--- a/docs/admin_guide.cn.md
+++ b/docs/admin_guide.cn.md
@@ -42,7 +42,7 @@ hudi->create --path /user/hive/warehouse/table1 --tableName
hoodie_table_1 --tab
18/09/06 15:57:15 INFO table.HoodieTableMetaClient: Finished Loading Table of
type COPY_ON_WRITE from ...
```
-To see the description of hudi table, use the command:
+使用desc命令可以查看hudi表的描述信息:
```Java
hoodie:hoodie_table_1->desc
diff --git a/docs/quickstart.cn.md b/docs/quickstart.cn.md
index b7e6e19..31d4911 100644
--- a/docs/quickstart.cn.md
+++ b/docs/quickstart.cn.md
@@ -20,7 +20,7 @@ bin/spark-shell --packages
org.apache.hudi:hudi-spark-bundle:0.5.0-incubating --
设置表名、基本路径和数据生成器来为本指南生成记录。
-```Java
+```Scala
import org.apache.hudi.QuickstartUtils._
import scala.collection.JavaConversions._
import org.apache.spark.sql.SaveMode._
@@ -40,7 +40,7 @@ val dataGen = new DataGenerator
## 插入数据 {#inserts}
生成一些新的行程样本，将其加载到DataFrame中，然后将DataFrame写入Hudi数据集中，如下所示。
-```Java
+```Scala
val inserts = convertToStringList(dataGen.generateInserts(10))
val df = spark.read.json(spark.sparkContext.parallelize(inserts, 2))
df.write.format("org.apache.hudi").
@@ -66,7 +66,7 @@ df.write.format("org.apache.hudi").
将数据文件加载到数据帧中。
-```Java
+```Scala
val roViewDF = spark.
read.
format("org.apache.hudi").
@@ -84,7 +84,7 @@ spark.sql("select _hoodie_commit_time, _hoodie_record_key,
_hoodie_partition_pat
这类似于插入新数据。使用数据生成器生成对现有行程的更新，加载到数据帧并将数据帧写入hudi数据集。
-```Java
+```Scala
val updates = convertToStringList(dataGen.generateUpdates(10))
val df = spark.read.json(spark.sparkContext.parallelize(updates, 2));
df.write.format("org.apache.hudi").
@@ -107,7 +107,14 @@ Hudi还提供了获取给定提交时间戳以来已更改的记录流的功能
这可以通过使用Hudi的增量视图并提供所需更改的开始时间来实现。
如果我们需要给定提交之后的所有更改(这是常见的情况)，则无需指定结束时间。
-```Java
+```Scala
+// reload data
+spark.
+ read.
+ format("org.apache.hudi").
+ load(basePath + "/*/*/*/*").
+ createOrReplaceTempView("hudi_ro_table")
+
val commits = spark.sql("select distinct(_hoodie_commit_time) as commitTime
from hudi_ro_table order by commitTime").map(k => k.getString(0)).take(50)
val beginTime = commits(commits.length - 2) // commit time we are interested in
@@ -128,7 +135,7 @@ spark.sql("select `_hoodie_commit_time`, fare, begin_lon,
begin_lat, ts from hu
让我们看一下如何查询特定时间的数据。可以通过将结束时间指向特定的提交时间，将开始时间指向"000"(表示最早的提交时间)来表示特定时间。
-```Java
+```Scala
val beginTime = "000" // Represents all commits > this time.
val endTime = commits(commits.length - 2) // commit time we are interested in
