[ISSUE-375] Optimize the Quick Start documentation to allow users to experience it more quickly

README.md

@@ -38,10 +38,10 @@ For GeaFlow design paper: [GeaFlow: A Graph Extended and Accelerated Dataflow Sy
 
 1. Prepare Git、JDK8、Maven、Docker environment。
 2. Download Code：`git clone https://github.com/TuGraph-family/tugraph-analytics`
-3. Build Project：`mvn clean install -DskipTests`
+3. Build Project：`./build.sh --module=gealfow --output=package` or `mvn clean install -DskipTests`
 4. Test Job：`./bin/gql_submit.sh --gql geaflow/geaflow-examples/gql/loop_detection.sql`
-3. Build Image：`./build.sh --all`
-4. Start Container：`docker run -d --name geaflow-console -p 8888:8888 geaflow-console:0.1`
+3. Build console JAR and image (requires starting Docker)：`./build.sh --module=gealfow-console`
+4. Start Console：`docker run -d --name geaflow-console -p 8888:8888 geaflow-console:0.1`
 
 For more details：[Quick Start](docs/docs-cn/source/3.quick_start/1.quick_start.md)。
 

README_cn.md

@@ -38,10 +38,10 @@ GeaFlow设计论文参考：[GeaFlow: A Graph Extended and Accelerated Dataflow
 
 1. 准备Git、JDK8、Maven、Docker环境。
 2. 下载源码：`git clone https://github.com/TuGraph-family/tugraph-analytics`
-3. 项目构建：`mvn clean install -DskipTests`
+3. 引擎构建：`./build.sh --module=gealfow --output=package` 或 `mvn clean install -DskipTests`
 4. 测试任务：`./bin/gql_submit.sh --gql geaflow/geaflow-examples/gql/loop_detection.sql`
-3. 构建镜像：`./build.sh --all`
-4. 启动容器：`docker run -d --name geaflow-console -p 8888:8888 geaflow-console:0.1`
+3. 构建控制台jar和镜像(需启动Docker)：`./build.sh --module=gealfow-console`
+4. 启动控制台：`docker run -d --name geaflow-console -p 8888:8888 geaflow-console:0.1`
 
 更多详细内容请参考：[快速上手文档](docs/docs-cn/source/3.quick_start/1.quick_start.md)。
 

docs/docs-cn/source/3.quick_start/1.quick_start.md

@@ -15,7 +15,7 @@
 ```shell
 git clone https://github.com/TuGraph-family/tugraph-analytics.git
 cd tugraph-analytics/
-mvn clean package -DskipTests
+./build.sh --module=gealfow --output=package
 ```
 
 ## 本地运行流图作业

docs/docs-cn/source/3.quick_start/2.quick_start_docker.md

@@ -11,12 +11,12 @@
 
 x86架构拉取x86镜像：
 ```shell
-docker pull tugraph/geaflow-console:0.1
+docker pull tugraph/geaflow-console:<version>
 ```
 
 如果是arm架构，拉取arm镜像：
 ```shell
-docker pull tugraph/geaflow-console-arm:0.1
+docker pull tugraph/geaflow-console-arm:<version>
 ```
 
 如果遇到网络问题导致拉取失败，也可以通过下面命令直接构建镜像(构建镜像之前需要先启动docker容器,构建脚本根据机器类型build对应类型的镜像):
@@ -25,7 +25,7 @@ docker pull tugraph/geaflow-console-arm:0.1
 ```shell
 git clone https://github.com/TuGraph-family/tugraph-analytics.git
 cd tugraph-analytics/
-bash ./build.sh --all
+./build.sh --module=gealfow-console
 
 ```
 

docs/docs-en/source/3.quick_start/1.quick_start.md

@@ -10,7 +10,7 @@ Execute the following commands to compile the GeaFlow source code:
 ```shell
 git clone https://github.com/TuGraph-family/tugraph-analytics.git
 cd tugraph-analytics/
-mvn clean package -DskipTests
+./build.sh --module=gealfow --output=package
 ```
 
 ## Running Job In Local

docs/docs-en/source/3.quick_start/2.quick_start_docker.md

@@ -10,12 +10,12 @@ Run the following command to pull the remote geaflow console image:
 
 For x86 architecture pull x86 image:
 ```shell
-docker pull tugraph/geaflow-console:0.1
+docker pull tugraph/geaflow-console:<version>
 ```
 
 If it is arm architecture, pull the arm image:
 ```shell
-docker pull tugraph/geaflow-console-arm:0.1
+docker pull tugraph/geaflow-console-arm:<version>
 ```
 
 If the pull fails due to network problems, you can also run the following command to directly build the local image 
@@ -25,7 +25,7 @@ corresponding type based on the machine type):
 ```shell
 git clone https://github.com/TuGraph-family/tugraph-analytics.git
 cd tugraph-analytics/
-bash ./build.sh --all
+./build.sh --module=gealfow-console
 
 ```