Abstract: A system is disclosed that includes one or more hardware processors and at least one memory storing instructions. The system receives a first query directed towards a shared dataset and accesses a first set of data from a first table in the shared dataset. The system determines that an aggregation constraint policy is attached to the first table, which restricts output of data values stored in the table. The system performs a uniqueness check on join keys for a join operation associated with the first table, verifying that at least one row from the first table is not amplified in the result. The system enforces the aggregation constraint policy on the first query based on this verification. The system generates an output to the first query based on the first set of data. This approach helps control data aggregation and ensures privacy when accessing shared datasets.

Abstract: Described is a system for join constraints for query processing by receiving a first query directed towards a shared dataset in a data clean room; assessing the first query to identify that the one or more functions s at least a join function; determining that the first query is configured to join a first set of data from the shared dataset with a second set of data using the join function; determining that a join constraint policy is to be enforced in relation to the first query; and generating an output to the first query based on the execution of the one or more functions, the output to the first query without data values stored in the portion of the first set of data based on determining that the join constraint policy is to be enforced in relation to the first query.

Abstract: An entity-level privacy system receives a query directed towards a shared dataset, the shared dataset comprising one or more data entries associated with one or more distinct entities, each entity of the one or more distinct entities being identifiable by one or more unique entity identifiers. The entity-level privacy system implements an entity-level privacy constraint, the entity-level privacy constraint comprising a dynamic aggregation constraint based on the one or more unique entity identifiers. The entity-level privacy system determines that the one or more unique entity identifiers satisfy a threshold condition comprising a minimum number of entities. The entity-level privacy system enforces the entity-level privacy constraint on the query and generates an output to the query based on the entity-level privacy constraint and the dynamic aggregation constraint while maintaining entity-level privacy associated with the one or more distinct entities.

Abstract: Some embodiments include receiving a first query directed towards a shared dataset, accessing a first set of data from the shared dataset to perform the one or more functions, determining that a row access policy is to be enforced in relation to the first query, and generating an output to the first query based on an execution of the one or more functions.

Abstract: The cloud data platform receives a first query directed towards a shared dataset, the first query identifying a first operation. The platform accesses a first set of data from the shared dataset to perform the first operation, the first set of data including data accessed from a first table of the shared dataset. The cloud data platform determines that an aggregation constraint policy is attached to the first table, the aggregation constraint policy restricts output of data values stored in the first table and enforces the aggregation constraint policy on the first query based on a context of the first query. The cloud data platform generates an output to the first query based on the first set of data and the first operation, based on enforcing the aggregation constraint policy on the first query.