Building a Model

You can start building a model from scratch in the builder, or click "Import" in the top navigation bar to import an XML template of a visual model onto the canvas.

Adding Tools

Users can add tools from the tool list, model list, and shared list in the left sidebar.

• Tools: Built-in tools from the hosting iServer
• Models: Built-in models from the hosting iServer, models published by the user, and models shared with me (by department or organization)
• Shared List: Models published by the user, and published models from the hosting iServer (visible to administrators, who can decide which users, departments, or organizations to share them with)

You can add  tools in the following ways:

• In the tool or model list on the left sidebar, select a tool and drag it onto the canvas; the tool and its nodes will appear on the canvas.
• Use the search box above the tool or model list to quickly find a tool, then drag it onto the canvas for modeling.
• Select multiple tools on the canvas by dragging a box, and copy (Ctrl+C) and paste (Ctrl+V) them within the same canvas or across canvases.

Moving Tools

Left-click a tool node on the canvas and drag it to move the entire tool.

Connecting Tools

A model usually consists of multiple processing automation tools, and connections between tools need to be established. The connection methods are:

• Drawing a connection line: Move the mouse to the output node of the preceding tool until the node highlights. Hold down the left mouse button and drag to the input node of the target tool; release when that node highlights. To ensure the model runs correctly, the output parameters of the preceding node must match the input parameters of the subsequent node.
• Deleting a connection line: Select the tool or connection line, then choose "Delete" from the right-click menu, or press the Delete key. If you accidentally delete a tool, you don't need to drag it again; all operations on the modeling canvas support undo (Ctrl+Z) and redo (Ctrl+Y).

Renaming Tools

If a model contains multiple tools with the same name or a tool name does not fit the usage scenario, left-click the tool node and select "Rename" from the right-click menu to rename it.

Simplifying Tool Display

When a tool has too many parameters or the canvas is cluttered with many tools, you can optimize the visual modeling display as follows.

• Right-click an empty area on the canvas and select "Collapse All" to hide tool parameters. Collapsed tools can still be moved.
• In the right-side menu of the canvas, select "Horizontal Auto Layout" or "Vertical Auto Layout" to automatically organize the canvas layout with one click.

Adding Labels

When a model is complex and the business process is difficult to understand, you can add labels to model elements to improve readability.

• Add a label to the model: Right-click an empty area on the canvas and select "Add Label".
• Add a label to a single tool: Left-click the tool node and select "Add Label" from the right-click menu. When moving the tool node, the label moves with it.

 

Setting Parameters

Setting Model Parameters

To specify parameter settings for a tool in the model, left-click the input node. A parameter panel will appear on the right side with input instructions. Enter the parameter value according to the required format. After all required parameters for the current tool are filled, the tool node border will change from gray to blue, allowing you to quickly check parameter completion by the node's border color.

• File Path: The path information of the data to be imported. Sources include local upload, adding from Resource Center, and My Folder. Data in My Folder comes from the "personalDir / {userid}" folder under the GPA shared storage path. You can copy required data to My Folder for direct use without uploading.

If you do not want to use the default configuration of a tool's parameters, you can customize them according to your needs. For details, see:  Customizing Tool Parameters.

Configuring the Cluster Environment

To perform distributed spatial big data analysis using Apache Spark, you can configure cluster environment parameters before running a model in the following two ways:

Method 1: Configure cluster environment parameters for a single model

When using big data tools on the GPAModelBuilder page, click the tool node, switch to the "Spark Environment Settings" tab on the parameter panel, and set the following cluster environment parameters. The model will connect to the cluster and submit GPA tasks when run.

• Mode: Includes local (single-process), local (multi-process), client, cluster
• Master Address: Required parameter, e.g., spark://172.16.16.8:7077
• The name of the custom appcation: Required parameter, e.g., geoprocessing
• Spark Attribute Parameter Settings: Optional cluster configuration parameters, e.g., spark.cores.max=4, spark.executor.memory=16g, spark.driver.host=192.168.17.43

Method 2: Configure global cluster environment parameters

To facilitate reuse of cluster environment parameters, global Spark environment parameter configuration is provided. The steps are as follows:

1. Click the "Settings" button in the upper‑right corner of the GPAModelBuilder interface to configure global Spark environment parameters.

2. On the Spark Environment Settings panel, click "Add Setting" to configure environment parameters. You can set a group of parameters as the default mode. After checking "Default Spark Mode", when you create a new model with big data tools, these parameters will be automatically filled. 

3. In the model's right‑side parameter panel > the "Environment Settings" tab, a new environment parameter mode parameter appears in "Mode". You can configure custom environment parameters or switch to global ones via the drop‑down menu, and modify the pre‑filled global parameters as needed.

 

Running a Model

In the builder, you can run part of a model or the entire model.

• Run part of a model: Right‑click a tool and select "Execute to" to run the processing automation workflow up to the selected tool. This helps verify if tool parameters are correct.
• Run the entire model: Click the "Run" button in the upper‑right corner to run the entire model sequentially through the complete processing automation workflow.

For a successfully run tool, a green success indicator appears in the upper‑right corner of the tool node; otherwise, a red failure indicator appears. During model execution, you can view execution logs in real time in the log panel at the bottom of the page. You can also filter log messages by level to quickly diagnose model errors.

Task Center

Click the "Task Center" button in the upper‑right corner to view the list of data analysis tasks for the current user, track model execution in real time, and check execution progress, duration, details, and logs of historical tasks.

 

Model Metadata

Model metadata is important descriptive information about a model. Detailed metadata helps others fully understand how to use the model and its scope of application, reducing barriers to knowledge and application sharing. You can view model metadata as follows:

• Right‑click an empty area on the canvas and select "View Metadata" to open the metadata window.
• After publishing the model to the model list, click "View Metadata" in the tool's menu to open the metadata window.

Model metadata includes:

• Name: A descriptive title summarizing the model.
• Author: The model creator's name.
• Create Time and Last Update Time: Automatically generated timestamps for model metadata creation and modification.
• Abstract: An overview of the project background in which the model is applied.
• Description: Explains how to use the model and its applicable scope.
• Tags: Keywords associated with the model.
• Thumbnail: Can be automatically generated for the model.

If you need to edit metadata, click "Edit Metadata" in the metadata window. You can edit the model title, author, abstract, description, and tags, and generate a thumbnail with one click. After editing, click "OK" to save the metadata to the model file.