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.

    Retrieving event records from a field searchable data store using references values in inverted indexes

    公开(公告)号:US11960545B1

    公开(公告)日:2024-04-16

    申请号:US17829179

    申请日:2022-05-31

    Applicant: Splunk Inc.

    CPC classification number: G06F16/90335 G06F16/901

    Abstract: Embodiments of the present disclosure provide techniques for performing searches of event records by leveraging reference values in an inverted index. A method of searching comprises accessing a query associated with a first set of event records in a field searchable data store, each event record comprising a time-stamped portion of raw machine data. The method further comprises evaluating the query and generating results for the query by accessing an inverted index, wherein each entry in the inverted index comprises at least one field, a corresponding at least one field value and a reference value that identifies a location in the field searchable data store where an associated event record is stored. The method further comprises performing a search to filter out a second set of event records and retrieving the second set of event records from the field searchable data store using reference values in the inverted index.

    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.

    Parallelization of collection queries

    公开(公告)号:US11163738B2

    公开(公告)日:2021-11-02

    申请号:US16451450

    申请日:2019-06-25

    Applicant: SPLUNK INC.

    Abstract: Embodiments are directed are towards the parallelization of collection queries. A method of parallelizing collection queries comprises providing a field searchable data store comprising a plurality of field searchable time stamped event records. The method further comprises receiving, at a search head, a collection query that references a field name that identifies portions of one or more event records to be summarized. Further, the method comprises determining if the collection query can be concurrently executed on a first plurality of indexers, wherein the search head is configured to communicate with the first plurality of indexers, and wherein each indexer of the first plurality of indexers comprises one or more field searchable time stamped event records. Responsive to an affirmative determination, the method also comprises determining a second plurality of indexers relevant to the collection query and executing the collection query to generate a respective summarization table at each indexer.

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