Microsoft Technology Licensing, LLC

Tor Kreutzer

Jan-Ove Almli Karlberg

Åge Andre Kvalnes

Amund Kronen Johansen

Steffen Viken Valvåg

Dag Steinnes Eidesen

Peter Dahle Heen

Jon Meling

Helge Grenager Solheim

Øystein Torbjørnsen

Anders Tungeland Gjerdrum

Age Kvalnes

Steffen Viken Valvag

Øystein Fledsberg

Shamika Ruklan Jayasundara

Vegar Skjaerven Wang

Bård Kvalheim

Jeffrey L Wight

Andrei-Alin Corodescu

Runar Bergheim Olsen

Vidar Tveoy Knudsen

Theodoros Gkountouvas

Christian Thuv

Daniele Vettorel

Kai-Marius Sæther Pedersen

Bjørn Erik Olsrød

Bernhard Kohlmeier

Torbjørn Helvik

Jan Heier Johansen

Charitha Herath Daskon Herath Mudiyanselage

Bernt Lervik

Kaare Koehler Hoevik

Åge Andre Kvalnes

Åge Kvalnes

Iqra Ali

Anthony Acquah

Ronny Jensen

Kai-Marius Pedersen

Vincent Macharia Karuri

Vincent Mulwa Kyalo

Dag Brattli

Viola Lisa Viktoria Jonsson

Mohamed Azmil Macksood

A method is provided for caching a query submitted to a graph data storage system, including receiving a query from a query caller directed to the graph data storage system, and examining the query, via a cache suitability determination engine, to determine if the query is suitable for caching under a first graph query caching policy based on the query caller being a trusted caller and/or the query scenario being a trusted query scenario. If suitable, generating a query execution plan for the query via a graph query plan generating engine and examining the query plan to determine if the query plan is suitable for caching under the first policy. If not suitable, caching the query under a second or a third graph caching policy based on the geographic location of a memory system on which the query plan is stored, and providing the query execution plan.

System and method of privacy-preservation in caching of graph query execution plans

A method comprising: storing, in a database, a list of geographical regions in which the party consents to their data being stored; receiving a request to store data of the party, wherein at least one of the data has a region-restriction that restricts the regions in which that data can be stored; determining, based on a respective region-restriction of a respective one of the data, in which of the list of regions the respective data can be stored; storing the data, wherein each respective data is stored in at least one respective storage centre associated with one of the regions according to the determination; storing, in the database, a list comprising a pointer to each respective stored data, wherein the pointer identifies the respective storage centre; receiving a request to retrieve a respective stored data; and using the pointer to route the request to the respective storage centre.

Managing data resources

Techniques of federation of data during query time are disclosed herein. One example technique includes upon receiving an indication of interaction of a file by a user of a tenant, determining whether automatic replication of the file to a user shard corresponding to the user is permitted according to a company policy or a legal requirement, the user shard being in a second geographic region. The example technique can then include when automatic replication of the file is not permitted, storing the file in a tenant shard corresponding to the tenant in a network storage in the first geographic region and instead of replicating the file to the user shard in the second geographic region, creating, in the user shard in the second geographic region, a file reference that is a pointer to the file stored in the tenant shard in the network storage in the first geographic region.

Federation of data during query time in computing systems

The present disclosure relates to systems, methods, and computer-readable media for utilizing a content access authorization system to determine user access control efficiently and flexibly for digital documents that are stored in different geographic regions. For instance, the content access authorization system can convert sensitive user information for digital documents stored in a first geographic region into a probabilistic data structure that does not include user information and share the probabilistic data structure with a second geographic region. The content access authorization system can then utilize the probabilistic data structure to efficiently pre-filter user document access control for digital documents requested by a user in the second geographic region that are stored in the first geographic region, which significantly saves on latency and computing resource usage by reducing the number of document control access queries needed to be made to the first geographic region.

Utilizing probability data structures to improve access control of documents across geographic regions

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.

Distribution of federated graph queries using schemas

The disclosed technology is generally directed to identification resolution in distributed knowledge graphs. In one example of the technology, a graph query is received. A metagraph includes identifier acceptance information associated with which identifiers among the identifiers are accepted by the data stores in the plurality of data stores and identifier export information associated with which identifiers among the identifiers are exported by the data stores in the plurality of data stores. The metagraph and the cost information are used to select, from among query paths, a query path that is capable of fulfilling the graph query based on minimizing a cost according to a cost metric. Upon determining that a failure has occurred in the selected query path, the metagraph and the cost information are used to change the selected query path. A response to the graph query is provided based on the selected query path.

Identification resolution in distributed knowledge graphs

Examples of the present disclosure describe systems and methods for leveraging interlinking between resources to determine shared knowledge. In aspects, user interaction with one or more applications or services may be detected. User input associated with the user interaction may be processed to identify information, such as one or more content items, content topics, or entities. The identified information may be used to search one or more data sources for relationships between the identified information and content items, topics, and/or entities stored by the data sources. The results of the search may be collected and/or evaluated to identify the knowledge level of one or more entities with one or more topics. Based on the evaluation, an indication of the identified knowledge level(s) may be provided.

Leveraging interlinking between information resources to determine shared knowledge

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.

Instruction level parallelism in a declarative graph query language

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.

Computing resource conservation with balanced traversals and precomputations for connected data sets

Examples of the present disclosure describe systems and methods for ontology-based graph query optimization. In an example, ontology data relating to a graph or isolated collection may be collected. The ontology data may comprise uniqueness and topology information and may be used to reformulate a query in order to yield a query that is more performant than the original query when retrieving target information from a graph. In an example, reformulating a query may comprise reordering one or more parameters of the query relating to resources, relationships, and/or properties based on uniqueness information. In another example, the query may be reformulated by modifying the resource type to which the query is anchored based on the topology information. The reformulated query may then be executed to identify target information in the isolated collection, thereby identifying the same target information as the original query, but in a manner that is more performant.

Ontology-based graph query optimization

Methods and systems are disclosed for optimizing record placement in a graph by minimizing fragmentation when writing data. Issues with fragmented data within a graph database are addressed on the record level by placing data that is frequently accessed together contiguously within memory. For example, a dynamic rule set may be developed based on dynamically analyzing access patterns of the graph database, policies, system characteristics and/or other heuristics. Based on statistics regarding normal query patterns, the systems and methods may identify an optimal position for certain types of edges that are often traversed with respect to particular types of nodes.

Optimized record placement in graph database

Particular aspects of this disclosure relate to computerized systems for generating and using improved data structures and functionality to efficiently render different multiple access-controlled resources (or properties of access-controlled resources) that are part of a concept. Often times, two or more resources of a concept or properties of a resource are subject to different access controls. This adds computing complexity as to whether or not a user is granted access to the entire concept or resource, a portion of the concept or resource, or none of the concept or resources and what exactly is surfaced back to the user when there are resources or properties the user does and does not have access to. Some embodiments accordingly render an efficient composite view of concepts or resources where some resources or properties are accessible by the requesting user, while other resources or properties are not accessible by the requesting user.

Efficient retrieval and rendering of access-controlled computer resources

The technology described herein protects the privacy and security of data stored in a knowledge graph ('graph') by enforcing visibility policies when returning property information in response to a query or other attempt to extract property information from the graph and/or about the graph. The visibility policies may be stored with the object and used to prevent restricted properties from being extracted from the object, let alone the graph. The object-specific visibility policy may be stored in the storage layer of the knowledge-graph object with the object properties and content. Some implementations may include multiple visibility records for a single object. Together the visibility records form the object visibility policy. An object visibility policy may have a single visibility record or multiple visibility records.

Property-level visibilities for knowledge-graph objects

The disclosure herein describes processing data operation requests and performing associated operations on pages of a record data structure. A data operation is generated based on a received data operation request. The data operation request includes a bookkeeping page identifier. A bookkeeping page of the record index structure is identified based on the bookkeeping page identifier and an index page of the record index structure with a parameter of the data operation. If a timestamp in metadata of the identified index page matches a corresponding timestamp associated with the identified index page in metadata of the bookkeeping page, the data operation is performed on the identified index page. The disclosure enables the use and maintenance of large data indexes in data storage systems where data entries expire over time due to automatic temporal compaction processes.

Maintaining a record data structure using page metadata of a bookkeeping page

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.

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Tromsø, Norway

Tor Kreutzer