Abstract: Example solutions for performing federated graph queries use schemas and include: generating a logical graph using a query input and generating a physical plan using a query planning schema for double-nested loops, the outer loop for each permutation of data stores in a set of data stores, and the inner loop for each data store—ceasing when the logical graph has been fully consumed. A query cost is determined for each of the permutations, and a physical plan is selected based on the query cost, for example minimizing the query cost, and the query is executed based on the selected physical plan. The cost may be determined based on a weighted combination of factors such as freshness of the data, latency, power consumption, environmental impact (e.g., carbon footprint), energy efficiency, and network burden.

Abstract: Example solutions are disclosed for performing a distributed data query for a connected data set, such as a property graph or a relational database, distributed across a plurality of regions (e.g., different geographic regions) under data flow limitations. For a restrictive limitation, a first region stores a data entity that is subject to a data flow limitation, and a second region stores only a reference to the data entity (e.g., a pseudonymous reference). The query is executed in the first region, and at least a partial representation of the state is injected into the query for execution in the second region. The query locates the reference to the data entity in the second region, and the state of the query from the second region is returned. Query results from the plurality of regions are synthesized into a final result. Further solutions address prohibitive limitations when references are not permitted.

Abstract: Techniques of reproduction of graph data during query time are disclosed herein. One example technique includes receiving, at a query processor, a query having a set of predicates to be evaluated on data in a graph. Upon receiving the query, the example technique includes evaluating the set of predicates based on data in the first or second partition of the graph and recording a sequence of query states of the first or second partition whose data is used to evaluate each of the set of predicates. Subsequently, the example technique includes constructing a set of snapshots of the data in the first or second partition based on the recorded query states and reevaluating the set of predicates on the constructed set of snapshots of the data in the first or second partition to troubleshoot the detected query error when the set of predicates were previously evaluated.

Abstract: Example solutions balance traversals and precomputations for connected data sets subject to access control. When a request for a commutative operation on a connected data set is received, a downwardly recursive process starts with the current hierarchy tier set to a highest hierarchy tier of the request. The process traverses the current hierarchy tier laterally. At each discovered node in the current hierarchy tier, a determination is made whether the requested operation is permitted to include a discovered node. If not, that node and any nodes hierarchically below it are omitted from the operation. That node and its subtree are skipped and the recursion halts for that branch. If, however, the requested operation is permitted to include the node, it is incorporated into the cumulative result and the recursion continues while there remains a lower hierarchy tier. Some examples leverage precomputed aggregates to avoid traversing branches having aggregates.

Abstract: Example solutions are disclosed for performing a distributed data query for a connected data set, such as a property graph or a relational database, distributed across a plurality of regions (e.g., different geographic regions) under data flow limitations. For a restrictive limitation, a first region stores a data entity that is subject to a data flow limitation, and a second region stores only a reference to the data entity (e.g., a pseudonymous reference). The query is executed in the first region, and at least a partial representation of the state is injected into the query for execution in the second region. The query locates the reference to the data entity in the second region, and the state of the query from the second region is returned. Query results from the plurality of regions are synthesized into a final result. Further solutions address prohibitive limitations when references are not permitted.

Abstract: Example solutions for executing a query in a declarative graph query language include receiving the query for data in a database and determining if one or both of i) a pattern in the query, and ii) the data in the database render the query suitable for being executed, at least in part, in parallel. If either condition indicates that the query is suitable for being executed, at least in part, in parallel, one or more fork operations and join operations are injected into a query plan, and the query is executed according to the query plan. Some examples further determine whether executing the query in parallel is computing resource-efficient, and only executes computing resource-efficient queries in parallel.

Abstract: Techniques of reproduction of graph data during query time are disclosed herein. One example technique includes receiving, at a query processor, a query having a set of predicates to be evaluated on data in a graph. Upon receiving the query, the example technique includes evaluating the set of predicates based on data in the first or second partition of the graph and recording a sequence of query states of the first or second partition whose data is used to evaluate each of the set of predicates. Subsequently, the example technique includes constructing a set of snapshots of the data in the first or second partition based on the recorded query states and reevaluating the set of predicates on the constructed set of snapshots of the data in the first or second partition to troubleshoot the detected query error when the set of predicates were previously evaluated.