Generating a subquery for an external data system using a configuration file

    公开(公告)号:US11636105B2

    公开(公告)日:2023-04-25

    申请号:US17196577

    申请日:2021-03-09

    Applicant: Splunk Inc.

    Abstract: Systems and methods are disclosed for receiving, at a data intake and query system, a query that includes an indication to process data managed by a third-party data storage and processing system that supports a different query language than the data intake and query system. The data intake and query system identifies a third-party data storage and processing system that manages the data to be processed and generates a subquery for execution by the third-party data storage and processing system, generates instructions for one or more worker nodes to receive and process results of the subquery from the third-party data storage and processing system, and instructs the worker nodes to provide results of the processing to the data intake and query system.

    EXECUTING COMMANDS FROM A DISTRIBUTED EXECUTION MODEL

    公开(公告)号:US20230049579A1

    公开(公告)日:2023-02-16

    申请号:US17960286

    申请日:2022-10-05

    Applicant: Splunk Inc.

    Abstract: Systems and methods are disclosed for generating a distributed execution model with untrusted commands. The system can receive a query, and process the query to identify the untrusted commands. The system can use data associated with the untrusted command to identify one or more files associated with the untrusted command. Based on the files, the system can generate a data structure and include one or more identifiers associated with the data structure in the distributed execution model. The system can distribute the distributed execution model to one or more nodes in a distributed computing environment for execution.

    Multi-partition operation in combination operations

    公开(公告)号:US11151137B2

    公开(公告)日:2021-10-19

    申请号:US15713976

    申请日:2017-09-25

    Applicant: Splunk Inc.

    Abstract: In an environment where multiple datasets are to be combined, systems and methods are disclosed for allocating a group of data entries from at least one dataset into multiple partitions. For a particular partition, the subgroup in the partition can be combined with data entries from the other dataset. In some cases, groups of data entries from each dataset are assigned to different partitions. For a particular partition, a subgroup is duplicated, some of the data entries of the subgroup are reassigned to other partitions, the subgroup is reformed to include data entries from other partitions, and the reformed subgroup is combined with the subgroup from the other dataset(s).

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