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This request relates to
As a developer I want to make queries on the datamodel that retain information about the connections between objects.
Making large queries on the graph connected by Relationships requires the client-side to re-construct the graph in memory. There are no semantics in CDF for preserving ordering in relationship queries, or imputation for order preservation. Meaning that for each step in the graph when making parallel queries, the graph has to be reconstructed locally.
We understand that this feature is largely addressed by Flexible Data Models, but we’re curious how this will resolve in the query language for FDMs. Especially when we have unions of types that edges can refer to in the graph.
This feature has the highest priority for the Data modelling and App teams at Statnett.
Hi Robert, thanks for providing the detailed request and relevant initiative from Statnett end.
In short, we will enable end-users to be able to create data models with properties, types, relationships that will be queryable through GraphQL. Subsequently, extract and retain information about the connections between objects to create advanced solutions/outputs through the relevant APIs - making full use of the process-centricity in a data modelling context.
This request relates to
As a developer I want to make queries on the datamodel that retain information about the connections between objects.
Making large queries on the graph connected by Relationships requires the client-side to re-construct the graph in memory. There are no semantics in CDF for preserving ordering in relationship queries, or imputation for order preservation. Meaning that for each step in the graph when making parallel queries, the graph has to be reconstructed locally.
We understand that this feature is largely addressed by Flexible Data Models, but we’re curious how this will resolve in the query language for FDMs. Especially when we have unions of types that edges can refer to in the graph.
This feature has the highest priority for the Data modelling and App teams at Statnett.