Constraint querying for collaborative intelligence and constraint computing

Abstract

Embodiments of the present disclosure are directed to techniques for constraint querying that allow data consumers to query collaborative data in a trustee environment, subject to configurable constraints, to derive collaborative intelligence without exposing underlying raw data provided by the tenants or collaborative data shielded by the trustee environment. Constraints can be applied in response to a query in multiple ways, including reformatting a query prior to execution, applying constraints after executing a query, constraining eligible queries for execution, applying access constraints prior to execution, and others. To reformat a query subject to constraints, the query can be parsed into an execution tree, which can be reformatted into a constrained execution tree by replacing executable units of logic inconsistent with a particular constraint with custom executable units of logic consistent with the constraint. The constrained execution tree can be translated into the language used by the trustee environment and forwarded for execution.