Index for multi-level data structures

    公开(公告)号:US12013831B2

    公开(公告)日:2024-06-18

    申请号:US17162882

    申请日:2021-01-29

    IPC分类号: G06F16/22

    CPC分类号: G06F16/2264

    摘要: Techniques are disclosed relating to index metadata that is usable for accessing multi-level data structures. A computer system may operate a database, including maintaining a set of records having a set of corresponding keys. The computer system may create multi-level data structures that facilitate key range lookups against those records. A given multi-level data structure may store key information indicative of a subset of the corresponding keys. The computer system may create separate index metadata that is usable for accessing the multi-level data structures. The index metadata may specify indications of key information that is stored in the multi-level data structures and locations of the multi-level data structures. The computer system may perform a key range lookup that includes using the index metadata to determine a particular set of the multi-level data structures whose key information corresponds to a key range of the key range lookup.

    Lookup and relationship caches for dynamic fetching

    公开(公告)号:US12008020B2

    公开(公告)日:2024-06-11

    申请号:US17384857

    申请日:2021-07-26

    摘要: Disclosed are methods, systems, and computer-readable medium for providing report results. Viscous attributes and non-viscous may be identified. A smart cube may be received and may include viscous values for the viscous attributes. The smart cube may be stored at a local cache. A report associated with an organization may be initiated. A runtime generation of the report may be generated based on initiating the report. The report may call a viscous attribute from the viscous attributes and call a non-viscous attribute from the non-viscous attributes. The runtime generation may be modified to remove the viscous attribute from the runtime generation. A viscous value for the viscous attribute may be retrieved from the smart cube at the local cache. The modified runtime generation may be executed to retrieve a non-viscous value for the non-viscous attribute from a remote database and a report result may be provided.

    TASK DEPENDENCY EXTRACTION SHARING AND NOTIFICATION

    公开(公告)号:US20240126737A1

    公开(公告)日:2024-04-18

    申请号:US18046523

    申请日:2022-10-14

    IPC分类号: G06F16/22 G06F40/284

    CPC分类号: G06F16/2264 G06F40/284

    摘要: A method, computer program product, and computer system are provided. A processor receives message data from a natural language conversation among participants in a project. A processor identifies at least two tasks mentioned in the message data. A processor determines a dependency between the at least two tasks based on the output of a sequential language model, where the messages associated with the at least two tasks are inputs to the sequential language model. A processor generates a directed graph depicting the at least two tasks and the determined dependency of the at least two tasks. A processor shares a directed graph across participants. A processor notifies participants who are blocked when dependent tasks are complete.

    METHOD FOR MANAGING, EVALUATING AND IMPROVING IDENTITY GOVERNANCE AND ADMINISTRATION

    公开(公告)号:US20240037570A1

    公开(公告)日:2024-02-01

    申请号:US18484194

    申请日:2023-10-10

    申请人: Costidity, Inc.

    发明人: Vladislav Shapiro

    摘要: A system and related methods are disclosed for managing, evaluating and improving identity governance and administration. The system is configured to execute a method, which includes receiving, by a computing system, data associated with the identity governance and administration, classifying, by a computing system, the data associated with the identity governance and administration according to one or more rules, generating, by a computing system, a three-dimensional model using the classified data associated with the identity governance and administration, performing, by a computing system, a statistical analysis, and optionally displaying, by a computing system, the three-dimensional model or results of the statistical analysis, or both.