Tutorial: Add multiple node and edge types from one mapping table

Note

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This tutorial explains the more advanced situation where you need to use one mapping table to create multiple node types.

Adventure Works Employee table

In the Adventure Works data model, the Employees data source table has the following columns:

• EmployeeID_K
• ManagerID
• EmployeeFullName
• JobTitle
• OrganizationLevel
• MaritalStatus
• Gender
• Territory
• Country
• Group

You can use the Employees table to create an Employee node type and a Country node type, which are connected by a lives_in edge type.

Create a Country node type

Create a node type named Country using the Employees table by following the steps in Add node types to your graph. Retain only the Country property and remove all other properties.

Modify the Employee node type as needed

If it's not necessary for the Employee node type to have the Territory, Country, and Group properties during your queries or analyses, you may remove these properties.

Tip

Excessive properties make your graph harder to maintain and use. Generally, for all node types you should remove properties that are

• Not required for the uniqueness of the nodes
• Not necessary during your queries or analyses

In the case of the Country node type, since it's created from the Employees table, you should remove properties like EmployeeID_K, ManagerID, EmployeeFullName, JobTitle, OrganizationLevel, MaritalStatus, and Gender, at a minimum.

Create a lives_in edge

Create an edge type named lives_in using the Employees table by following the steps in Add edge types to your graph. Configure the edge schema like so:

• Label: lives_in
• Mapping table: adventureworks_employees
• Source node: Employee
• Mapping table column to be linked to source node key: EmployeeID_K
• Target node: Country
• Mapping table column to be linked to target node key: Country

Load the graph

After configuring all node types and edge types, load the graph:

• Select Save to verify the graph model, load data from OneLake, construct the graph, and make it ready for querying. Be patient, as this process might take some time depending on the size of your data.

Next step

Query the graph with the query builder