EXECUTING A DISTRIBUTED EXECUTION MODEL WITH UNTRUSTED COMMANDS

    公开(公告)号:US20190095488A1

    公开(公告)日:2019-03-28

    申请号:US15714133

    申请日:2017-09-25

    Applicant: Splunk Inc.

    Abstract: Systems and methods are disclosed for executing a distributed execution model with untrusted commands. The distributed execution model can be distributed to multiple nodes in a distributed computing environment. At least one node can process the distributed execution model to identify an untrusted command. The node can use data associated with the untrusted command to identify one or more files associated with the untrusted command. Based on the files, the node can generate a data structure, and execute at least a portion of the data structure.

    Partially typed semantic based query execution optimization

    公开(公告)号:US12141143B2

    公开(公告)日:2024-11-12

    申请号:US17944065

    申请日:2022-09-13

    Applicant: Splunk Inc.

    Abstract: A method includes receiving an initial pipeline including a sequence of commands for execution on a computing system, and obtaining, for each command in the sequence of commands, semantic information. The sequence of commands includes a command with incomplete semantic information. The method further includes generating an abstract semantic tree (AST) with the semantic information and a placeholder for the incomplete semantic information, and manipulating the AST to generate a revised AST. The revised AST corresponds to a revised pipeline that reduces an execution time on the computing system. The method further includes executing the revised pipeline.

    DYNAMIC QUERY PROCESSOR FOR STREAMING AND BATCH QUERIES

    公开(公告)号:US20230244673A1

    公开(公告)日:2023-08-03

    申请号:US18192136

    申请日:2023-03-29

    Applicant: Splunk Inc.

    CPC classification number: G06F16/24568 G06F16/24542 G06F16/901 G06F16/90335

    Abstract: Operational machine components of an information technology (IT) or other microprocessor- or microcontroller-permeated environment generate disparate forms of machine data. Network connections are established between these components and processors of data intake and query system (DIQS). The DIQS conducts network transactions on a periodic and/or continuous basis with the machine components to receive disparate data and ingest certain of the data as entries of a data store that is searchable for DIQS query processing. The DIQS may receive queries to process against the received and ingested data via an exposed network interface. In one example embodiment, the DIQS receives a query identifying data to be processed, dynamically generates a query processing scheme based on the state of the data to be processed, such as streaming or at rest, and dynamically communicates the query processing scheme to a query executor based on the state of the data to be processed.

    Query execution optimization for partially typed semantics

    公开(公告)号:US11487759B1

    公开(公告)日:2022-11-01

    申请号:US16669429

    申请日:2019-10-30

    Applicant: Splunk Inc.

    Abstract: A method includes receiving an initial pipeline including a sequence of commands for execution on a computing system, and obtaining, for each command in the sequence of commands, semantic information. The sequence of commands includes a command with incomplete semantic information. The method further includes generating an abstract semantic tree (AST) with the semantic information and a placeholder for the incomplete semantic information, and manipulating the AST to generate a revised AST. The revised AST corresponds to a revised pipeline that reduces an execution time on the computing system. The method further includes executing the revised pipeline.

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