shaofengshi closed pull request #189: Fix comma symbol to English version
URL: https://github.com/apache/kylin/pull/189
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diff --git a/website/_docs/tutorial/kylin_sample.cn.md
b/website/_docs/tutorial/kylin_sample.cn.md
index 8673af0f57..a58a8a0e95 100644
--- a/website/_docs/tutorial/kylin_sample.cn.md
+++ b/website/_docs/tutorial/kylin_sample.cn.md
@@ -12,7 +12,7 @@ Kylin 提供了一个创建样例 Cube 脚本；脚本会创建五个样例 hive
3. 选择名为 "kylin_sales_cube" 的样例 cube，点击 "Actions" -> "Build"，选择一个在 2014-01-01
之后的日期（覆盖所有的 10000 样例记录);
4. 点击 "Monitor" 标签，查看 build 进度直至 100%;
5. 点击 "Insight" 标签，执行 SQLs，例如:
- select part_dt，sum(price) as total_selled，count(distinct seller_id) as
sellers from kylin_sales group by part_dt order by part_dt
+ `select part_dt, sum(price) as total_selled, count(distinct seller_id)
as sellers from kylin_sales group by part_dt order by part_dt`
6. 您可以验证查询结果且与 hive 的响应时间进行比较;
@@ -22,11 +22,11 @@ Kylin 也提供了 streaming 样例 cube 脚本。该脚本将会创建 Kafka to
1. 首先设置 KAFKA_HOME，然后启动 Kylin。
2. 运行 ${KYLIN_HOME}/bin/sample.sh，它会在 learn_kylin 工程中生成
DEFAULT.KYLIN_STREAMING_TABLE 表，kylin_streaming_model 模型，Cube
kylin_streaming_cube。
-3. 运行 ${KYLIN_HOME}/bin/sample-streaming.sh，他会在 localhost:9092 broker 中创建名为
kylin_streaming_topic 的 Kafka Topic。它也会每秒随机发送 100 条 messages 到
kylin_streaming_topic。
+3. 运行 ${KYLIN_HOME}/bin/sample-streaming.sh，它会在 localhost:9092 broker 中创建名为
kylin_streaming_topic 的 Kafka Topic。它也会每秒随机发送 100 条 messages 到
kylin_streaming_topic。
4. 遵循标准 cube build 过程，并触发 Cube kylin_streaming_cube build。
5. 点击 "Monitor" 标签，查看 build 进度直至至少有一个 job 达到 100%。
6. 点击 "Insight" 标签，执行 SQLs，例如:
- select count(*)，HOUR_START from kylin_streaming_table group by
HOUR_START
+ `select count(*), HOUR_START from kylin_streaming_table group by
HOUR_START`
7. 验证查询结果。
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