relation-creation

To create entity relationships, you specify join types, directionality, and cross-filtering behavior. Connections can be established through field mapping or custom SQL expressions, ensuring accurate data links for metric calculations and analysis.

Yes, you can use custom SQL expressions for join definitions. This allows you to define complex connection methods between entities beyond simple field mapping, providing flexibility in how data relationships are structured for analysis.

To link entities like orders and customers, you define a many-to-one relation using a foreign key such as 'customer_id'. This connects the entities so metrics on orders can correctly reference attributes from the customers entity.

Yes, Honeydew includes mandatory post-creation validation for entity relations. After updating the entity YAML configurations via MCP tools, the system validates the relationships to ensure they are correctly defined and functional.

Cross-filtering behavior in entity relationship modeling determines how filtering on one entity affects another. When defining relations in a semantic layer, you can specify this behavior to control the flow of filter context between connected entities.

Entity relationships in Honeydew are stored and updated through entity YAML configurations. The updated configurations are pushed to the semantic layer via MCP tools, ensuring the relationship definitions are persisted and available for analysis.