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PullRequest: 900 PullRequest: 899 dev geaflow update
Merge branch dev_opensource_doc_update of [email protected]:AntGraph/GeaFlow.git into dev_opensource https://code.alipay.com/AntGraph/GeaFlow/pull_requests/900 Signed-off-by: 文韬 <[email protected]> * PullRequest: 899 dev geaflow update
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‎README.md

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<!--intro-start-->
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## Introduction
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**TuGraph Analytics** (alias: GeaFlow) is a distributed graph compute engine developed by Ant Group. It supports core capabilities such as trillion-level graph storage, hybrid graph and table processing, real-time graph computation, and interactive graph analysis. Currently, it is widely used in scenarios such as data warehousing acceleration, financial risk control, knowledge graph, and social networks.
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GeaFlow is a distributed graph compute engine developed by Ant Group. It supports core capabilities such as trillion-level graph storage, hybrid graph and table processing, real-time graph computation, and interactive graph analysis. Currently, it is widely used in scenarios such as data warehousing acceleration, financial risk control, knowledge graph, and social networks.
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For more information about GeaFlow: [GeaFlow Introduction](docs/docs-en/source/2.introduction.md)
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@@ -38,7 +38,7 @@ For GeaFlow design paper: [GeaFlow: A Graph Extended and Accelerated Dataflow Sy
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Step 1: Package the JAR and submit the Quick Start task
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1. Prepare Git、JDK8、Maven、Docker environment。
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2. Download Code：`git clone https://github.com/TuGraph-family/tugraph-analytics`
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2. Download Code：`git clone https://github.com/TuGraph-family/tugraph-analytics geaflow`
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3. Build Project：`./build.sh --module=geaflow --output=package`
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4. Test Job：`./bin/gql_submit.sh --gql geaflow/geaflow-examples/gql/loop_detection_file_demo.sql`
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‎README_cn.md

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# TuGraph Analytics 文档地图
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# GeaFlow 文档地图
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[![Star](https://shields.io/github/stars/tugraph-family/tugraph-analytics?logo=startrek&label=Star&color=yellow)](https://github.com/TuGraph-family/tugraph-analytics/stargazers)
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[![Fork](https://shields.io/github/forks/tugraph-family/tugraph-analytics?logo=forgejo&label=Fork&color=orange)](https://github.com/TuGraph-family/tugraph-analytics/forks)
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<!--intro-start-->
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## 介绍
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**TuGraph Analytics** (别名：GeaFlow) 是蚂蚁集团开源的流图计算引擎，支持万亿级图存储、图表混合处理、实时图计算、交互式图分析等核心能力，目前广泛应用于数仓加速、金融风控、知识图谱以及社交网络等场景。
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GeaFlow 是蚂蚁集团开源的流图计算引擎，支持万亿级图存储、图表混合处理、实时图计算、交互式图分析等核心能力，目前广泛应用于数仓加速、金融风控、知识图谱以及社交网络等场景。
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关于GeaFlow更多介绍请参考：[GeaFlow介绍文档](docs/docs-cn/source/2.introduction.md)
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第一步 打包jar包并提交quick start任务
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1. 准备Git、JDK8、Maven、Docker环境。
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2. 下载源码：`git clone https://github.com/TuGraph-family/tugraph-analytics`
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2. 下载源码：`git clone https://github.com/TuGraph-family/tugraph-analytics geaflow`
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3. 项目构建：`./build.sh --module=geaflow --output=package`
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4. 测试任务：`./bin/gql_submit.sh --gql geaflow/geaflow-examples/gql/loop_detection_file_demo.sql`
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‎docs/docs-cn/source/3.quick_start/2.quick_start_docker.md

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```shell
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git clone https://github.com/TuGraph-family/tugraph-analytics.git
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cd tugraph-analytics/
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git clone https://github.com/TuGraph-family/tugraph-analytics.git geaflow
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cd geaflow/
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./build.sh --module=geaflow-console
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```
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```
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## K8S部署
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GeaFlow支持K8S部署, 部署详细文档请参考文档：[K8S部署](../7.deploy/1.install_guide.md)
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GeaFlow支持K8S部署, 部署详细文档请参考文档：[K8S部署](../7.deploy/1.install_guide.md)

‎docs/docs-cn/source/7.deploy/1.install_guide.md

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## 构建镜像
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下载GeaFlow源码，构建GeaFlow引擎镜像和GeaFlow Console平台镜像。
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```shell
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git clone https://github.com/TuGraph-family/tugraph-analytics.git
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cd tugraph-analytics/
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git clone https://github.com/TuGraph-family/tugraph-analytics.git geaflow
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cd geaflow/
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bash ./build.sh --all
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```
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‎docs/docs-cn/source/7.deploy/2.quick_start_operator.md

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2. 拉取GeaFlow镜像
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```shell
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docker pull tugraph/geaflow:0.4
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docker pull tugraph/geaflow:0.6
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```
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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):
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```shell
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git clone https://github.com/TuGraph-family/tugraph-analytics.git
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cd tugraph-analytics/
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git clone https://github.com/TuGraph-family/tugraph-analytics.git geaflow
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cd geaflow/
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bash ./build.sh --module=geaflow
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```
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```shell
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docker images
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```
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远程拉取的镜像名称为：**tugraph/geaflow:0.4**。
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远程拉取的镜像名称为：**tugraph/geaflow:0.6**。
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本地镜像名称为：**geaflow:0.1**，只需选择一种方式构建镜像即可。
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## 安装Geaflow Kubernetes Operator
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下面介绍如何安装Geaflow Kubernetes Operator。
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1. 下载GeaFlow代码。
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```shell
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git clone https://github.com/TuGraph-family/tugraph-analytics.git
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cd tugraph-analytics/
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git clone https://github.com/TuGraph-family/tugraph-analytics.git geaflow
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cd geaflow/
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```
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2. 构建Geaflow Kubernetes Operator的镜像
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```shell
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docker pull tugraph/geaflow-kubernetes-operator:0.4
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docker pull tugraph/geaflow-kubernetes-operator:0.6
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```
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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:
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```shell
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cd tugraph-analytics/geaflow-kubernetes-operator/
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cd geaflow/geaflow-kubernetes-operator/
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bash ./build-operator.sh
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```
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operator项目最低要求jdk11。整个编译过程可能持续一段时间，请耐心等待。镜像编译成功后，通过以下命令查看镜像：
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```shell
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docker images
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```
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远程拉取的镜像名称为：**tugraph/geaflow-kubernetes-operator:0.4**。
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远程拉取的镜像名称为：**tugraph/geaflow-kubernetes-operator:0.6**。
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本地镜像名称为：**geaflow-kubernetes-operator:0.1**，只需选择一种方式构建镜像即可。
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3. 确认helm的镜像名称
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4. 通过helm安装Geaflow Kubernetes Operator
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```shell
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cd tugraph-analytics/geaflow-kubernetes-operator/
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cd geaflow/geaflow-kubernetes-operator/
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helm install geaflow-kubernetes-operator helm/geaflow-kubernetes-operator
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```
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![img.png](../../../static/img/helm_install_operator.png)
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然后通过如下命令即可将作业提交到k8s集群。
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```shell
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cd tugraph-analysis/geaflow-kubernetes-operator/example
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cd geaflow/geaflow-kubernetes-operator/example
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kubectl apply example_hla.yml
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```
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### 提交HLA作业
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执行以下命令可以查看CR的状态
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```shell
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kubectl get geaflowjob geaflow-example
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```
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```

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

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Execute the following commands to compile the GeaFlow source code:
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```shell
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git clone https://github.com/TuGraph-family/tugraph-analytics.git
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cd tugraph-analytics/
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git clone https://github.com/TuGraph-family/tugraph-analytics.git geaflow
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cd geaflow/
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./build.sh --module=geaflow --output=package
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```
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## Visualization of flow graph computation jobs using G6VP
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G6VP is an extensible visual analysis platform, including data source management, composition, personalized configuration of graphic elements, visual analysis and other functional modules. Using G6VP, it is easy to visualize the results of Geaflow calculations. Document address: [Document](../7.deploy/4.collaborate_with_g6vp.md)
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G6VP is an extensible visual analysis platform, including data source management, composition, personalized configuration of graphic elements, visual analysis and other functional modules. Using G6VP, it is easy to visualize the results of Geaflow calculations. Document address: [Document](../7.deploy/4.collaborate_with_g6vp.md)

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

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corresponding type based on the machine type):
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```shell
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git clone https://github.com/TuGraph-family/tugraph-analytics.git
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cd tugraph-analytics/
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git clone https://github.com/TuGraph-family/tugraph-analytics.git geaflow
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cd geaflow/
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./build.sh --module=geaflow-console
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```
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## K8S Deployment
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GeaFlow supports K8S deployment. For details about the deployment mode, see the document: [K8S Deployment](../7.deploy/1.install_guide.md).
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GeaFlow supports K8S deployment. For details about the deployment mode, see the document: [K8S Deployment](../7.deploy/1.install_guide.md).

‎docs/docs-en/source/7.deploy/1.install_guide.md

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Download GeaFlow source code, build GeaFlow engine image and GeaFlow Console image.
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```shell
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git clone https://github.com/TuGraph-family/tugraph-analytics.git
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cd tugraph-analytics/
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git clone https://github.com/TuGraph-family/tugraph-analytics.git geaflow
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cd geaflow/
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bash ./build.sh --all
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‎docs/docs-en/source/7.deploy/2.quick_start_operator.md

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docker pull tugraph/geaflow:0.6
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If the pull fails due to network problems, you can also run the following command to directly build the local image
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(before building the image, start the docker container):
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```shell
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git clone https://github.com/TuGraph-family/tugraph-analytics.git
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cd tugraph-analytics/
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git clone https://github.com/TuGraph-family/tugraph-analytics.git geaflow
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cd geaflow/
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bash ./build.sh --module=geaflow
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The name of the remotely pulled image is: **tugraph/geaflow:0.4**
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The name of the remotely pulled image is: **tugraph/geaflow:0.6**
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. The name of the local image is **geaflow:0.1**. You only need to select one method to build the image.
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## Install Geaflow Kubernetes Operator
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Below is an introduction on installation of Geaflow Kubernetes Operator。
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1. Download the code of GeaFlow。
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```shell
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git clone https://github.com/TuGraph-family/tugraph-analytics.git
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cd tugraph-analytics/
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git clone https://github.com/TuGraph-family/tugraph-analytics.git geaflow
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cd geaflow/
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```
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2. Build the image of Geaflow Kubernetes Operator
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docker pull tugraph/geaflow-kubernetes-operator:0.4
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docker pull tugraph/geaflow-kubernetes-operator:0.6
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```
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If the pull fails due to network problems, you can also run the following command to directly build the local image
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(before building the image, start the docker container):
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```shell
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cd tugraph-analytics/geaflow-kubernetes-operator/
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cd geaflow/geaflow-kubernetes-operator/
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bash ./build-operator.sh
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```shell
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The name of the remotely pulled image is: **tugraph/geaflow-kubernetes-operator:0.4**
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. The name of the local image is **geaflow-kubernetes-operator:0.1**. You only need to select one
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method to build the image.
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4. Install Geaflow Kubernetes Operator by Helm
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cd geaflow/geaflow-kubernetes-operator/
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helm install geaflow-kubernetes-operator helm/geaflow-kubernetes-operator
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```
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![img.png](../../../static/img/helm_install_operator.png)
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Then run the following command to submit the job:
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```shell
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cd geaflow/geaflow-kubernetes-operator/example
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kubectl apply example_hla.yml
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Run the following command to view the status of CR
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kubectl get geaflowjob geaflow-example
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```
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```

‎geaflow/geaflow-analytics-service/geaflow-analytics-service-client/src/main/java/com/antgroup/geaflow/analytics/service/client/jdbc/AnalyticsConnection.java

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int port = Integer.parseInt(split[1]);
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.withHost(host).withPort(port).build();
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LOGGER.info("init tugraph analytics connection with host [{}] and port [{}]",
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LOGGER.info("init geaflow analytics connection with host [{}] and port [{}]",
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host, port);
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} else {
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LOGGER.warn("illegal authority: [{}]", authority);

‎geaflow/geaflow-analytics-service/geaflow-analytics-service-client/src/main/java/com/antgroup/geaflow/analytics/service/client/utils/JDBCUtils.java

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public class JDBCUtils {
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public static final String DRIVER_URL_START = "jdbc:tugraph://";
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public static final String DRIVER_URL_START = "jdbc:geaflow://";
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public static boolean acceptsURL(String url) {
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if (url.startsWith(JDBCUtils.DRIVER_URL_START)) {

‎geaflow/geaflow-analytics-service/geaflow-analytics-service-client/src/test/java/com/antgroup/geaflow/analytics/service/client/jdbc/AnalyticsDriverURITest.java

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@Test
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public void testInvalidURI() {
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assertInvalid("jdbc:geaflow://localhost/", "No port number specified:");
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}
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private static void assertInvalid(String url, String prefix) {

‎pom.xml

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<developers>
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<developer>
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<id>pengzhiwei2018</id>
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<name>pengzhiwei</name>
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<id>Loognqiang</id>
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<name>zhouqiang</name>
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<roles>
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<role>Developer</role>
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</roles>
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<exclude>**/resources/zip_test.txt</exclude>
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<exclude>**/resources/demo/demo_job_data.txt</exclude>
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<exclude>**/resources/input/**</exclude>
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<exclude>**/resources/i18n/**</exclude>
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<exclude>**/resources/public/**</exclude>
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<exclude>**/dependency-reduced-pom.xml</exclude>
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<exclude>**/*.log</exclude>
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<exclude>**/**/Filter.template</exclude>
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<exclude>**/**/version.txt</exclude>
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<exclude>**/**/graph_data.fbs</exclude>
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<exclude>**/**/Cargo.lock</exclude>
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<exclude>**/**/*.toml</exclude>
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<exclude>**/**/.helmignore</exclude>
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<exclude>**/**/templates/NOTES.txt</exclude>

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