Merge pull request #586 from yangj1211/fix81

update docs
matrixorigin · Aug 1, 2024 · b9f79b2 · b9f79b2
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diff --git a/...atrixOne/Deploy/deploy-Matrixone-cluster/deploy-MatrixOne-cluster-without-k8.md b/...atrixOne/Deploy/deploy-Matrixone-cluster/deploy-MatrixOne-cluster-without-k8.md
@@ -61,7 +61,7 @@ In addition, for container management and orchestration on Kubernetes, we need t
 The overall deployment architecture is shown in the following figure:
 
  <div align="center">
-  <img src=https://community-shared-data-1308875761.cos.ap-beijing.myqcloud.com/artwork/docs/deploy/deploy-mo-cluster-arch-overall.png width=80% heigth=80%/>
+  <img src=https://github.com/matrixorigin/artwork/blob/main/docs/deploy/deploy-mo-cluster-arch-overall.png?raw=true width=80% heigth=80%/>
  </div>
 
 The overall architecture consists of the following components:
@@ -87,7 +87,7 @@ MatrixOne creates a series of Kubernetes objects based on Operator's rules that
 - PV:PV (Persistent Volume) is an abstract representation of a storage medium that can be viewed as a storage unit. After the PVC has been requested, the PV is created through software that implements the CSI interface and binds it to the PVC requesting the resource.
 
 <div align="center">
-<img src=https://community-shared-data-1308875761.cos.ap-beijing.myqcloud.com/artwork/docs/deploy/deploy-mo-cluster-arch-pod.png width=80% heigth=80%/>
+<img src=https://github.com/matrixorigin/artwork/blob/main/docs/deploy/deploy-mo-cluster-arch-pod.png?raw=true width=80% heigth=80%/>
 </div>
 
 ## 1\. Deploy a Kubernetes cluster
@@ -181,7 +181,7 @@ docker run -d \
 
 Once this is done, you can enter `http://1.13.2.100` (Springboard IP address) in your browser to open the Kuboard-Spray web interface, enter the username `admin`, the default password `Kuboard123`, and log into the Kuboard-Spray interface as follows:
 
-![](https://community-shared-data-1308875761.cos.ap-beijing.myqcloud.com/artwork/docs/deploy/deploy-mo-cluster-1.png)
+![](https://github.com/matrixorigin/artwork/blob/main/docs/deploy/deploy-mo-cluster-1.png?raw=true)
 
 Once logged in, you can begin deploying Kubernetes clusters.
 
@@ -197,33 +197,33 @@ The installation interface downloads the resource package corresponding to the K
 
     Download version `spray-v2.18.0b-2_k8s-v1.23.17_v1.24-amd64`
 
-    ![](https://community-shared-data-1308875761.cos.ap-beijing.myqcloud.com/artwork/docs/deploy/deploy-mo-cluster-2.png)
+    ![](https://github.com/matrixorigin/artwork/blob/main/docs/deploy/deploy-mo-cluster-2.png?raw=true)
 
 2. After clicking **Import**, select **Load Resource Package**, select the appropriate download source, and wait for the resource package download to complete.
 
     !!! note It is recommended that you choose Docker as the container engine for the K8s cluster. After selecting Docker as the container engine for K8s, Kuboard-Spray automatically uses Docker to run the various components of the K8s cluster, including containers on the Master node and the Worker node.
 
-    ![](https://community-shared-data-1308875761.cos.ap-beijing.myqcloud.com/artwork/docs/deploy/deploy-mo-cluster-3.png)
+    ![](https://github.com/matrixorigin/artwork/blob/main/docs/deploy/deploy-mo-cluster-3.png?raw=true)
 
 3. This `pulls` the relevant mirror dependencies:
 
-    ![](https://community-shared-data-1308875761.cos.ap-beijing.myqcloud.com/artwork/docs/deploy/deploy-mo-cluster-4.png)
+    ![](https://github.com/matrixorigin/artwork/blob/main/docs/deploy/deploy-mo-cluster-4.png?raw=true)
 
 4. After the mirrored resource pack is pulled successfully, return to Kuboard-Spray's web interface and see that the corresponding version of the resource pack has been imported.
 
-    ![](https://community-shared-data-1308875761.cos.ap-beijing.myqcloud.com/artwork/docs/deploy/deploy-mo-cluster-5.png)
+    ![](https://github.com/matrixorigin/artwork/blob/main/docs/deploy/deploy-mo-cluster-5.png?raw=true)
 
 #### Installing a Kubernetes Cluster
 
 This chapter will guide you through the installation of the Kubernetes cluster.
 
 1. Select **Cluster Management** and select **Add Cluster Installation Plan**:
 
-    ![](https://community-shared-data-1308875761.cos.ap-beijing.myqcloud.com/artwork/docs/deploy/deploy-mo-cluster-6.png)
+    ![](https://github.com/matrixorigin/artwork/blob/main/docs/deploy/deploy-mo-cluster-6.png?raw=true)
 
 2. In the pop-up dialog box, define the name of the cluster, select the version of the resource package you just imported, and click **OK**. As shown in the following figure:
 
-    ![](https://community-shared-data-1308875761.cos.ap-beijing.myqcloud.com/artwork/docs/deploy/deploy-mo-cluster-7.png)
+    ![](https://github.com/matrixorigin/artwork/blob/main/docs/deploy/deploy-mo-cluster-7.png?raw=true)
 
 ##### Cluster planning
 
@@ -233,16 +233,16 @@ After defining the completion cluster name in the previous step and selecting th
 
 1. Select the role and name of the corresponding node:
 
-    ![](https://community-shared-data-1308875761.cos.ap-beijing.myqcloud.com/artwork/docs/deploy/deploy-mo-cluster-8.png)
+    ![](https://github.com/matrixorigin/artwork/blob/main/docs/deploy/deploy-mo-cluster-8.png?raw=true)
 
     - master node: Select the ETCD and control node and name it master0\. (You can also select the working node if you want the master node to work.) This approach improves resource utilization, but reduces the high availability of Kubernetes.)
     - worker node: Select only the worker node and name it node0.
 
 2. After each node has filled in the role and node name, fill in the connection information for the corresponding node to the right, as shown in the following figure:
 
-    ![](https://community-shared-data-1308875761.cos.ap-beijing.myqcloud.com/artwork/docs/deploy/deploy-mo-cluster-9.png)
+    ![](https://github.com/matrixorigin/artwork/blob/main/docs/deploy/deploy-mo-cluster-9.png?raw=true)
 
-    ![](https://community-shared-data-1308875761.cos.ap-beijing.myqcloud.com/artwork/docs/deploy/deploy-mo-cluster-9-1.png)
+    ![](https://github.com/matrixorigin/artwork/blob/main/docs/deploy/deploy-mo-cluster-9-1.png?raw=true)
 
 3. Click **Save** when you have filled out all the roles. Next you are ready to install the Kubernetes cluster.
 
@@ -252,7 +252,7 @@ After completing all roles in the previous step and **saving** them, click **Exe
 
 1. Click **OK** to begin installing the Kubernetes cluster as shown in the following figure:
 
-    ![](https://community-shared-data-1308875761.cos.ap-beijing.myqcloud.com/artwork/docs/deploy/deploy-mo-cluster-10.png)
+    ![](https://github.com/matrixorigin/artwork/blob/main/docs/deploy/deploy-mo-cluster-10.png?raw=true)
 
 2. When you install a Kubernetes cluster, the Kubernetes cluster is installed by executing an `ansible` script on the corresponding node. The overall event can take anywhere from 5 to 10 minutes depending on the machine configuration and network and the time to wait.
 
@@ -275,7 +275,7 @@ After completing all roles in the previous step and **saving** them, click **Exe
     vim /etc/resolve.conf 
     ```
 
-    ![](https://community-shared-data-1308875761.cos.ap-beijing.myqcloud.com/artwork/docs/deploy/deploy-mo-cluster-10-1.png)
+    ![](https://github.com/matrixorigin/artwork/blob/main/docs/deploy/deploy-mo-cluster-10-1.png?raw=true)
 
 ## 2. Deployment helm
 
@@ -432,13 +432,13 @@ __Note:__ This chapter operates at the master0 node.
 
 3. Once launched, use <http://118.195.255.252:32001/> to log into MinIO's page and create the information stored by the object. As shown in the following figure, the account password is the rootUser and rootPassword set by `--set rootUser=rootuser,rootPassword=rootpass123` in the above steps:
 
-    ![](https://community-shared-data-1308875761.cos.ap-beijing.myqcloud.com/artwork/docs/deploy/deploy-mo-cluster-13.png)
+    ![](https://github.com/matrixorigin/artwork/blob/main/docs/deploy/deploy-mo-cluster-13.png?raw=true)
 
 4. Once the login is complete, you need to create an object to store the relevant information:
 
     Click **Bucket > Create Bucket** and fill in Bucket's name **minio-mo** in **Bucket Name**. Once completed, click the button **Create Bucket** at the bottom right.
 
-    ![](https://community-shared-data-1308875761.cos.ap-beijing.myqcloud.com/artwork/docs/deploy/deploy-mo-cluster-14.png)
+    ![](https://github.com/matrixorigin/artwork/blob/main/docs/deploy/deploy-mo-cluster-14.png?raw=true)
 
 ## 5. MatrixOne Cluster Deployment
 

diff --git a/docs/MatrixOne/Develop/Ecological-Tools/BI-Connection/FineBI-connection.md b/docs/MatrixOne/Develop/Ecological-Tools/BI-Connection/FineBI-connection.md
@@ -19,11 +19,11 @@ MatrixOne supports integration with the data visualization tool FineBI. This art
 
 1. After logging into FineBI, select **Management System > Data Connection > Data Connection Management > New Data Connection** as shown below, then choose **MySQL**:
 
-    ![image-20230808174909411](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/select-mysql.png)
+    ![image-20230808174909411](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/select-mysql.png?raw=true)
 
 2. Fill in the MatrixOne connection configuration, including the database name, host, port, username, and password. Other parameters can be left at their default settings. You can click the **Test Connection** button to verify if the connection is functional and then click **Save** :
 
-    ![image-20230808182330603](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/testing.png)
+    ![image-20230808182330603](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/testing.png?raw=true)
 
 ## Creating Visual Reports Using MatrixOne Data
 
@@ -127,7 +127,7 @@ MatrixOne supports integration with the data visualization tool FineBI. This art
 
     You can click the **Preview** button to view the results of the SQL query and then click **OK** to save it:
 
-    ![image-20230809091306270](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/preview.png)
+    ![image-20230809091306270](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/preview.png?raw=true)
 
     Below are examples of all the query SQL used in this demo:
 
@@ -232,7 +232,7 @@ MatrixOne supports integration with the data visualization tool FineBI. This art
 
     After saving the dataset, you need to click the **Update Data** button and wait for the data update to complete before proceeding with the analysis:
 
-    ![image-20230809091814920](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/update-data.png)
+    ![image-20230809091814920](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/update-data.png?raw=true)
 
 4. Create Analytic Themes:
 
@@ -241,30 +241,30 @@ MatrixOne supports integration with the data visualization tool FineBI. This art
     - Click **My Analysis**, then click **New Folder** to create and select a folder.
     - Click **New Analytic Theme**, select the dataset created in the previous step, and then click **OK**.
 
-    ![image-20230809092959252](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/create-analytic.png)
+    ![image-20230809092959252](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/create-analytic.png?raw=true)
 
     __Note:__ You can use the **Batch Selection** feature to select multiple datasets for theme analysis.
 
-    ![image-20230809092959252](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/batch-select.png)
+    ![image-20230809092959252](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/batch-select.png?raw=true)
 
     Click the **Add Component** button, choose the chart type, drag the fields from the left to the right as needed, double-click to modify the field visualization name, and change the component name below to describe the content of the report analyzed by the component:
 
-    ![image-20230809092959252](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/add-compon-1.png)
+    ![image-20230809092959252](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/add-compon-1.png?raw=true)
 
-    ![image-20230809092959252](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/add-compon-2.png)
+    ![image-20230809092959252](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/add-compon-2.png?raw=true)
 
 5. Assemble Dashboards:
 
     Click **Add Dashboard** to add the components you just created to the dashboard. You can freely drag and resize the components and change the component names below to describe the report's content analyzed by the component.
 
-    ![image-20230810123913230](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/add-dashboard.png)
+    ![image-20230810123913230](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/add-dashboard.png?raw=true)
 
 6. Publish Dashboards:
 
     After assembling the dashboard, click **Publish**, set the publication name, publication node, and display platform. Then click **Confirm**, and your dashboard will be successfully published.
 
-    ![image-20230810123913230](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/publish.png)
+    ![image-20230810123913230](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/publish.png?raw=true)
 
     Now, see the newly published dashboard under **Navigation** and see how it looks.
 
-    ![image-20230810131752645](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/published.png)
+    ![image-20230810131752645](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/finebi/published.png?raw=true)
diff --git a/docs/MatrixOne/Develop/Ecological-Tools/BI-Connection/Superset-connection.md b/docs/MatrixOne/Develop/Ecological-Tools/BI-Connection/Superset-connection.md
@@ -84,13 +84,13 @@ Here are the steps for deploying a single-node Superset using Docker:
 
 1. Access the Superset login page, typically at `http://ip:8080`. Then, enter your username and password to log in to Superset.
 
-    ![Superset Login Page](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/superset/superset-login.png)
+    ![Superset Login Page](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/superset/superset-login.png?raw=true)
 
     __Note:__ The port for Superset may be either 8080 or 8088, depending on your configuration. The username and password are the ones you set during the Superset deployment.
 
     After logging in, you will see the main interface of Superset.
 
-    ![Superset Main Interface](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/superset/superset-dashboard.png)
+    ![Superset Main Interface](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/superset/superset-dashboard.png?raw=true)
 
 2. Create a database connection:
 
@@ -100,19 +100,19 @@ Here are the steps for deploying a single-node Superset using Docker:
 
     Fill in the connection information for the MatrixOne database, including the host, port, username, and password.
 
-    ![Create Database Connection](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/superset/superset-create-db-connection.png)
+    ![Create Database Connection](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/superset/superset-create-db-connection.png?raw=true)
 
     After filling in the details, click the **CONNECT** button and then click **FINISH**.
 
-    ![Create Query](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/superset/superset-create-query.png)
+    ![Create Query](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/superset/superset-create-query.png?raw=true)
 
 ## Creating Visual Monitoring Dashboards
 
 Now, you can use the MatrixOne database to create a monitoring dashboard.
 
 1. Click on **SQL > SQL Lab** on the page, select the MatrixOne database connection you created earlier, and write SQL queries to select the tables you want to monitor.
 
-    ![image-20230807201143069](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/superset/sql-lab.png)
+    ![image-20230807201143069](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/superset/sql-lab.png?raw=true)
 
     You can write multiple queries to monitor different metrics. Here are example SQL statements for some queries:
 
@@ -194,11 +194,11 @@ Now, you can use the MatrixOne database to create a monitoring dashboard.
 
     Here, we'll use one of the queries as an example to demonstrate how to edit a visual chart. First, select the 'disk_read_write' query as the data source for the chart. In the SQL Lab, click **CREATE CHART** below the corresponding query, or if you've saved the query in the previous step, the page will redirect to the Chart editing page:
 
-    ![Create Dashboard](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/superset/superset-create-dashboard.png)
+    ![Create Dashboard](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/superset/superset-create-dashboard.png?raw=true)
 
 4. In the chart editing page, choose chart type, time field, metric columns from the query, grouping columns, and other options. Once configured, select **RUN**:
 
-    ![View Dashboard](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/superset/superset-view-dashboard.png)
+    ![View Dashboard](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/superset/superset-view-dashboard.png?raw=true)
 
 5. Click **UPDATE CHART > SAVE** to save the edited chart.
 
@@ -208,10 +208,10 @@ Now, you can use the MatrixOne database to create a monitoring dashboard.
 
     Click on **Dashboards**, then click **+ DASHBOARD** to create a new dashboard or edit an existing one.
 
-    ![image-20230808101636134](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/superset/superset-add-dashboard.png)
+    ![image-20230808101636134](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/superset/superset-add-dashboard.png?raw=true)
 
 2. In the dashboard editing page, you can drag the charts you've created from the CHARTS list on the right onto the dashboard for assembly. You can also freely adjust the position of charts, add titles, and more.
 
-    ![image-20230808102033250](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/superset/superset-edit-dashboard.png)
+    ![image-20230808102033250](https://github.com/matrixorigin/artwork/blob/main/docs/develop/bi-connection/superset/superset-edit-dashboard.png?raw=true)
 
 You have successfully connected the MatrixOne database with Superset and created a simple monitoring dashboard to visualize key metrics of the MatrixOne database.