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feat: update docs
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docs/interactive/pages/interactive/visualization/data_modeling.md

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title: Visual Modeling
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---
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After creating the draft instance, we need to click on "Modeling" to enter the visual graph modeling page.
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Here, we have two ways to build the model:
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## Create Graph Model
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After creating the draft instance, we need to click on "Modeling" to enter the visual graph modeling page.
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Here, we have three ways to build the model:
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### Options 1: Manual Creation
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#### Create Vertex and Vertex Properties
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<img src="/visualization/modeling/auto_parse_3.png" />
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### Options 3: Creation from Configuration File
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Click the third button in the sidebar to upload the schema's YAML configuration file here.
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<img src="/visualization/modeling/via_config.png" />
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## Save Model
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Once the model is created and passes the system's validation, we can save the model. Here,there are two key points that <strong> require special attention:</strong>
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title: Visual Modeling
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title: Visual Importing
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After creating the draft instance, we need to click on "Modeling" to enter the visual graph modeling page.
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Here, we have two ways to build the model:
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## Upload source data
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## Create Graph Model
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Once the graph model is created, we can begin importing data.there are three ways to import data:
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### Options 1: Manual Creation
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### Option 1: Manual Import
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#### Create Vertex and Vertex Properties
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Each label contains a location field. Click the "upload" button to upload the corresponding CSV file to the interactive service.
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We need to click the fourth button, "Create new vertex," in the sidebar to create a node on the canvas. The initial name of the node will be "Vertex_1.
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<img src="/visualization/importing/upload_start.png" />
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After clicking on the node, we can manually modify its label in the right-hand panel, or simply double-click the node to edit it directly on the canvas.
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<img src="/visualization/modeling/add_vertex_edit.png" />
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Upon success, a location path will be returned, indicating the data has been imported.
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Next, following the prompts, we need to complete the property information for this node. Click the "Plus" button under Properties to add attributes, and fill them out one by one.
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<img src="/visualization/modeling/add_property.png" />
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<img src="/visualization/importing/upload_end.png" />
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If we want to delete a node’s property, check the properties you wish to remove in the Checkbox area and click the delete button.
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<img src="/visualization/modeling/delete_property.png" />
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### Option 2: Automatic Import After CSV Parsing
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#### Create Edges
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This Option extends the convenience of automatic CSV modeling. During CSV parsing, the system caches the source file locally in the browser. As a result, the data can be automatically uploaded on the data loading page.
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Now let's create edges. To create an edge, hover over the edge of the starting node, then click and drag.
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<img src="/visualization/modeling/drag_start.png" />
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### Option 3: Import via Configuration File
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If the endpoint is an empty area of the canvas, a new node will automatically be created.
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<img src="/visualization/modeling/drag_end.png" />
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<img src="/visualization/importing/via_config.png" />
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If the endpoint is another existing node, an edge will be established between the two nodes.
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<img src="/visualization/modeling/drag_other_edge_end.png" />
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## Bind Data Source
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### Option 2: Parsing CSV Files for Creation
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After uploading the data, click the "data source binding" button to bind the data path to the model label. If successful, a configuration panel will appear.
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<img src="/visualization/importing/load_data.png" />
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Manually creating a graph model is particularly helpful when designing complex business models. However, when we already have some graph data, automatically deriving the graph model based on the existing data becomes a more convenient approach.
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Click "import" to proceed to the job page.
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Note: There are two constraints for the CSV files here:
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## Verify Results
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- Each CSV file, by default, represents one type of label. The file name should ideally be the label name, such as person.csv.
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- The CSV file must include a header row.
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At this point, validate the data on the query page. We will cover this in detail in the next chapter. Let’s move on to the next chapter!
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When the above two requirements are met, we can utilize the "Automatic Parsing and Modeling" feature provided by GraphScope Portal, which is located in the second option of the right-hand sidebar.
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<img src="/visualization/modeling/auto_parse_1.png" />
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After uploading the data, we only need to verify each CSV file to ensure that the automatically inferred node and edge types are accurate.
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<img src="/visualization/modeling/auto_parse_2.png" />
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Once confirmed, we can click "Generate Graph Model" , and the system will automatically derive the graph model.
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<img src="/visualization/modeling/auto_parse_3.png" />
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## Save Model
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Once the model is created and passes the system's validation, we can save the model. Here,there are two key points that <strong> require special attention:</strong>
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> - Each `vertex label` must have a `primary key` in its properties, and each `edge label` can only have one property field.
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> - <span style='color:red'>The `GraphScope Interactive` engine does not support modifications to the graph model. If you need to modify the graph model, you must create a new graph instance.</span>
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<img src="/visualization/modeling/save_model.png" />
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Now, let's goto importing page
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<img src="/visualization/importing/test_query.png" />
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