This is an automated email from the ASF dual-hosted git repository. shaofengshi pushed a commit to branch document in repository https://gitbox.apache.org/repos/asf/kylin.git
The following commit(s) were added to refs/heads/document by this push: new 00f1670 Remove unnecessary extra characters 00f1670 is described below commit 00f1670f8646f755daa2d67d1b4e834355b3062d Author: rupengwang <wangrup...@live.cn> AuthorDate: Thu May 7 10:51:18 2020 +0800 Remove unnecessary extra characters --- website/_docs/tutorial/cube_spark.cn.md | 21 +++++++++++++++++++++ website/_docs/tutorial/sql_reference.cn.md | 2 +- website/_docs30/tutorial/cube_spark.cn.md | 21 +++++++++++++++++++++ website/_docs30/tutorial/sql_reference.cn.md | 2 +- website/_docs31/tutorial/cube_spark.cn.md | 21 +++++++++++++++++++++ website/_docs31/tutorial/sql_reference.cn.md | 2 +- 6 files changed, 66 insertions(+), 3 deletions(-) diff --git a/website/_docs/tutorial/cube_spark.cn.md b/website/_docs/tutorial/cube_spark.cn.md index 0bc7dee..68d3597 100644 --- a/website/_docs/tutorial/cube_spark.cn.md +++ b/website/_docs/tutorial/cube_spark.cn.md @@ -133,6 +133,27 @@ Kylin 启动后,访问 Kylin 网站,在 "Advanced Setting" 页,编辑名 所有步骤成功执行后,Cube 的状态变为 "Ready" 且您可以像往常那样进行查询。 +## 通过Apache Livy使用Spark +开启使用Livy需要修改如下配置: + +{% highlight Groff markup %} +kylin.engine.livy-conf.livy-enabled=true +kylin.engine.livy-conf.livy-url=http://ip:8998 +kylin.engine.livy-conf.livy-key.file=hdfs:///path/kylin-job-3.0.0-SNAPSHOT.jar +kylin.engine.livy-conf.livy-arr.jars=hdfs:///path/hbase-client-1.2.0-{$env.version}.jar,hdfs:///path/hbase-common-1.2.0-{$env.version}.jar,hdfs:///path/hbase-hadoop-compat-1.2.0-{$env.version}.jar,hdfs:///path/hbase-hadoop2-compat-1.2.0-{$env.version}.jar,hdfs:///path/hbase-server-1.2.0-{$env.version}.jar,hdfs:///path/htrace-core-3.2.0-incubating.jar,hdfs:///path/metrics-core-2.2.0.jar +{% endhighlight %} + +需要注意的是jar包路径之间不能存在空格。 + +## 可选功能 + +现在构建步骤中的'extract fact table distinct value' 和 'build dimension dictionary' 两个步骤也可以使用Spark进行构建了。相关的配置如下: + +{% highlight Groff markup %} +kylin.engine.spark-fact-distinct=true +kylin.engine.spark-dimension-dictionary=true +{% endhighlight %} + ## 疑难解答 当出现 error,您可以首先查看 "logs/kylin.log". 其中包含 Kylin 执行的所有 Spark 命令,例如: diff --git a/website/_docs/tutorial/sql_reference.cn.md b/website/_docs/tutorial/sql_reference.cn.md index d645fff..43901af 100644 --- a/website/_docs/tutorial/sql_reference.cn.md +++ b/website/_docs/tutorial/sql_reference.cn.md @@ -185,7 +185,7 @@ SELECT cal_dt ,sum(price) AS sum_price FROM (SELECT kylin_cal_dt.cal_dt, kylin_s 在表中存在至少一个匹配时,```INNER JOIN``` 关键字返回行。 例子: {% highlight Groff markup %} -SELECT kylin_cal_dt.cal_dt, kylin_sales.price FROM kylin_sales INNER JOIN kylin_cal_dt AS kylin_cal_dt ON kylin_sales.part_dt**** = kylin_cal_dt.cal_dt; +SELECT kylin_cal_dt.cal_dt, kylin_sales.price FROM kylin_sales INNER JOIN kylin_cal_dt AS kylin_cal_dt ON kylin_sales.part_dt = kylin_cal_dt.cal_dt; {% endhighlight %} ### LEFT JOIN {#LEFTJOIN} diff --git a/website/_docs30/tutorial/cube_spark.cn.md b/website/_docs30/tutorial/cube_spark.cn.md index 7379887..b0b1249 100644 --- a/website/_docs30/tutorial/cube_spark.cn.md +++ b/website/_docs30/tutorial/cube_spark.cn.md @@ -133,6 +133,27 @@ Kylin 启动后,访问 Kylin 网站,在 "Advanced Setting" 页,编辑名 所有步骤成功执行后,Cube 的状态变为 "Ready" 且您可以像往常那样进行查询。 +## 通过Apache Livy使用Spark +开启使用Livy需要修改如下配置: + +{% highlight Groff markup %} +kylin.engine.livy-conf.livy-enabled=true +kylin.engine.livy-conf.livy-url=http://ip:8998 +kylin.engine.livy-conf.livy-key.file=hdfs:///path/kylin-job-3.0.0-SNAPSHOT.jar +kylin.engine.livy-conf.livy-arr.jars=hdfs:///path/hbase-client-1.2.0-{$env.version}.jar,hdfs:///path/hbase-common-1.2.0-{$env.version}.jar,hdfs:///path/hbase-hadoop-compat-1.2.0-{$env.version}.jar,hdfs:///path/hbase-hadoop2-compat-1.2.0-{$env.version}.jar,hdfs:///path/hbase-server-1.2.0-{$env.version}.jar,hdfs:///path/htrace-core-3.2.0-incubating.jar,hdfs:///path/metrics-core-2.2.0.jar +{% endhighlight %} + +需要注意的是jar包路径之间不能存在空格。 + +## 可选功能 + +现在构建步骤中的'extract fact table distinct value' 和 'build dimension dictionary' 两个步骤也可以使用Spark进行构建了。相关的配置如下: + +{% highlight Groff markup %} +kylin.engine.spark-fact-distinct=true +kylin.engine.spark-dimension-dictionary=true +{% endhighlight %} + ## 疑难解答 当出现 error,您可以首先查看 "logs/kylin.log". 其中包含 Kylin 执行的所有 Spark 命令,例如: diff --git a/website/_docs30/tutorial/sql_reference.cn.md b/website/_docs30/tutorial/sql_reference.cn.md index 149523f..8231d07 100644 --- a/website/_docs30/tutorial/sql_reference.cn.md +++ b/website/_docs30/tutorial/sql_reference.cn.md @@ -185,7 +185,7 @@ SELECT cal_dt ,sum(price) AS sum_price FROM (SELECT kylin_cal_dt.cal_dt, kylin_s 在表中存在至少一个匹配时,```INNER JOIN``` 关键字返回行。 例子: {% highlight Groff markup %} -SELECT kylin_cal_dt.cal_dt, kylin_sales.price FROM kylin_sales INNER JOIN kylin_cal_dt AS kylin_cal_dt ON kylin_sales.part_dt**** = kylin_cal_dt.cal_dt; +SELECT kylin_cal_dt.cal_dt, kylin_sales.price FROM kylin_sales INNER JOIN kylin_cal_dt AS kylin_cal_dt ON kylin_sales.part_dt = kylin_cal_dt.cal_dt; {% endhighlight %} ### LEFT JOIN {#LEFTJOIN} diff --git a/website/_docs31/tutorial/cube_spark.cn.md b/website/_docs31/tutorial/cube_spark.cn.md index 58037e3..184e0a7 100644 --- a/website/_docs31/tutorial/cube_spark.cn.md +++ b/website/_docs31/tutorial/cube_spark.cn.md @@ -133,6 +133,27 @@ Kylin 启动后,访问 Kylin 网站,在 "Advanced Setting" 页,编辑名 所有步骤成功执行后,Cube 的状态变为 "Ready" 且您可以像往常那样进行查询。 +## 通过Apache Livy使用Spark +开启使用Livy需要修改如下配置: + +{% highlight Groff markup %} +kylin.engine.livy-conf.livy-enabled=true +kylin.engine.livy-conf.livy-url=http://ip:8998 +kylin.engine.livy-conf.livy-key.file=hdfs:///path/kylin-job-3.0.0-SNAPSHOT.jar +kylin.engine.livy-conf.livy-arr.jars=hdfs:///path/hbase-client-1.2.0-{$env.version}.jar,hdfs:///path/hbase-common-1.2.0-{$env.version}.jar,hdfs:///path/hbase-hadoop-compat-1.2.0-{$env.version}.jar,hdfs:///path/hbase-hadoop2-compat-1.2.0-{$env.version}.jar,hdfs:///path/hbase-server-1.2.0-{$env.version}.jar,hdfs:///path/htrace-core-3.2.0-incubating.jar,hdfs:///path/metrics-core-2.2.0.jar +{% endhighlight %} + +需要注意的是jar包路径之间不能存在空格。 + +## 可选功能 + +现在构建步骤中的'extract fact table distinct value' 和 'build dimension dictionary' 两个步骤也可以使用Spark进行构建了。相关的配置如下: + +{% highlight Groff markup %} +kylin.engine.spark-fact-distinct=true +kylin.engine.spark-dimension-dictionary=true +{% endhighlight %} + ## 疑难解答 当出现 error,您可以首先查看 "logs/kylin.log". 其中包含 Kylin 执行的所有 Spark 命令,例如: diff --git a/website/_docs31/tutorial/sql_reference.cn.md b/website/_docs31/tutorial/sql_reference.cn.md index 28f6a92..2cd53a0 100644 --- a/website/_docs31/tutorial/sql_reference.cn.md +++ b/website/_docs31/tutorial/sql_reference.cn.md @@ -185,7 +185,7 @@ SELECT cal_dt ,sum(price) AS sum_price FROM (SELECT kylin_cal_dt.cal_dt, kylin_s 在表中存在至少一个匹配时,```INNER JOIN``` 关键字返回行。 例子: {% highlight Groff markup %} -SELECT kylin_cal_dt.cal_dt, kylin_sales.price FROM kylin_sales INNER JOIN kylin_cal_dt AS kylin_cal_dt ON kylin_sales.part_dt**** = kylin_cal_dt.cal_dt; +SELECT kylin_cal_dt.cal_dt, kylin_sales.price FROM kylin_sales INNER JOIN kylin_cal_dt AS kylin_cal_dt ON kylin_sales.part_dt = kylin_cal_dt.cal_dt; {% endhighlight %} ### LEFT JOIN {#LEFTJOIN}