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The following commit(s) were added to refs/heads/document by this push:
new 897c186 fix typos
897c186 is described below
commit 897c18649f974a5156c664fe502d9a7b511ac932
Author: yaqian.zhang <[email protected]>
AuthorDate: Wed Sep 1 18:47:08 2021 +0800
fix typos
---
website/_docs40/install/deploy_without_hadoop.cn.md | 9 ++++-----
website/_docs40/install/deploy_without_hadoop.md | 11 +++++------
2 files changed, 9 insertions(+), 11 deletions(-)
diff --git a/website/_docs40/install/deploy_without_hadoop.cn.md
b/website/_docs40/install/deploy_without_hadoop.cn.md
index c1b9826..c7f1252 100644
--- a/website/_docs40/install/deploy_without_hadoop.cn.md
+++ b/website/_docs40/install/deploy_without_hadoop.cn.md
@@ -5,12 +5,12 @@ categories: install
permalink: /cn/docs40/install/deploy_without_hadoop.html
---
-相比于 Kylin3，Kylin4.0 实现了全新 spark 构建引擎和 parquet 存储，使 kylin 不依赖 hadoop
环境部署成为可能。与在 AWS EMR 之上部署 Kylin3 相比，直接在 AWS EC2 实例上部署 Kylin4 存在以下优势：
+相比于 Kylin 3.x，Kylin 4.0 实现了全新 spark 构建引擎和 parquet 存储，使 kylin 不依赖 hadoop
环境部署成为可能。与在 AWS EMR 之上部署 Kylin 3.x 相比，直接在 AWS EC2 实例上部署 Kylin 4.0 存在以下优势：
1. 节省成本。相比 AWS EMR 节点，AWS EC2 节点的成本更低。
2. 更加灵活。在 EC2 节点上，用户可以更加自主选择自己所需的服务以及组件进行安装部署。
3. 去 Hadoop。Hadoop 生态比较重，需要投入一定的人力成本进行维护，去 Hadoop 可以更加贴近云原生。
-在实现了支持在 spark standalone 模式下进行构建和查询的功能之后，我们在 AWS 的 EC2 实例上对无 hadoop 部署 Kylin4
做了尝试，并成功构建 cube 和进行了查询。
+在实现了支持在 Spark Standalone 模式下进行构建和查询的功能之后，我们在 AWS 的 EC2 实例上对无 Hadoop 部署 Kylin
4.0 做了尝试，并成功构建 Cube 和进行了查询。
### 环境准备
@@ -55,7 +55,7 @@ permalink: /cn/docs40/install/deploy_without_hadoop.html
```shell
mkdir /usr/local/java
- tar -xvf jdk-8u291-linux-x64.tar -C /usr/local/java
+ tar -xvf java-1.8.0-openjdk.tar -C /usr/local/java
```
#### 3 配置 Hadoop
@@ -313,8 +313,7 @@ permalink: /cn/docs40/install/deploy_without_hadoop.html
kylin.metadata.url=kylin_metadata@jdbc,url=jdbc:mysql://hostname:3306/kylin,username=root,password=password,maxActive=10,maxIdle=10
kylin.env.zookeeper-connect-string=hostname
kylin.engine.spark-conf.spark.master=spark://hostname:7077
- # 当 spark.submit.deployMode 配置为 cluster 时，需要额外配置
kylin.engine.spark.standalone.master.httpUrl
- kylin.engine.spark-conf.spark.submit.deployMode=client/cluster
+ kylin.engine.spark-conf.spark.submit.deployMode=client
kylin.env.hdfs-working-dir=s3://bucket/kylin
kylin.engine.spark-conf.spark.eventLog.dir=s3://bucket/kylin/spark-history
kylin.engine.spark-conf.spark.history.fs.logDirectory=s3://bucket/kylin/spark-history
diff --git a/website/_docs40/install/deploy_without_hadoop.md
b/website/_docs40/install/deploy_without_hadoop.md
index a2fcdee..779176d 100644
--- a/website/_docs40/install/deploy_without_hadoop.md
+++ b/website/_docs40/install/deploy_without_hadoop.md
@@ -5,12 +5,12 @@ categories: install
permalink: /docs40/install/deploy_without_hadoop.html
---
-Compared with kylin3, kylin4 implements a new spark build engine and parquet
storage, making it possible for kylin to deploy without Hadoop environment.
Compared with deploying kylin3 on AWS EMR, deploying kylin4 directly on AWS EC2
instances has the following advantages:
+Compared with Kylin 3.x, Kylin 4.0 implements a new Spark build engine and
parquet storage, making it possible for Kylin to deploy without Hadoop
environment. Compared with deploying Kylin 3.x on AWS EMR, deploying kylin4
directly on AWS EC2 instances has the following advantages:
1. Cost saving. Compared with AWS EMR node, AWS EC2 node has lower cost.
2. More flexible. On the EC2 node, users can more independently select the
services and components they need for installation and deployment.
3. Remove Hadoop dependency. Hadoop ecology is heavy and needs to be
maintained at a certain labor cost. Remove hadoop can be closer to the
cloud-native.
-After realizing the feature of supporting build and query in spark standalone
mode, we tried to deploy kylin4.0 without Hadoop on the EC2 instance of AWS,
and successfully built the cube and query.
+After realizing the feature of supporting build and query in Spark Standalone
mode, we tried to deploy Kylin 4.0 without Hadoop on the EC2 instance of AWS,
and successfully built the cube and query.
### Environment preparation
- Apply for AWS EC2 Linux instances as required
@@ -53,7 +53,7 @@ The component version information provided here is that we
selected during the t
```shell
mkdir /usr/local/java
- tar -xvf jdk-8u291-linux-x64.tar -C /usr/local/java
+ tar -xvf java-1.8.0-openjdk.tar -C /usr/local/java
```
@@ -326,8 +326,7 @@ The component version information provided here is that we
selected during the t
kylin.metadata.url=kylin_metadata@jdbc,url=jdbc:mysql://hostname:3306/kylin,username=root,password=password,maxActive=10,maxIdle=10
kylin.env.zookeeper-connect-string=hostname
kylin.engine.spark-conf.spark.master=spark://hostname:7077
- # 当 spark.submit.deployMode 配置为 cluster 时，需要额外配置
kylin.engine.spark.standalone.master.httpUrl
- kylin.engine.spark-conf.spark.submit.deployMode=client/cluster
+ kylin.engine.spark-conf.spark.submit.deployMode=client
kylin.env.hdfs-working-dir=s3://bucket/kylin
kylin.engine.spark-conf.spark.eventLog.dir=s3://bucket/kylin/spark-history
kylin.engine.spark-conf.spark.history.fs.logDirectory=s3://bucket/kylin/spark-history
@@ -338,7 +337,7 @@ The component version information provided here is that we
selected during the t
- Execute `bin/kylin.sh start`
-- Kylin may encounter ClassNotFound type errors during startup. Please refer
to the following methods to restart kylin:
+- Kylin may encounter ClassNotFound type errors during startUp. Please refer
to the following methods to restart kylin:
```shell
# Download commons-collections-3.2.2.jar
