Intelligent search-time determination and usage of fields extracted at index-time

    公开(公告)号:US12038926B1

    公开(公告)日:2024-07-16

    申请号:US17163220

    申请日:2021-01-29

    Applicant: SPLUNK INC.

    CPC classification number: G06F16/2455 G06F16/2228

    Abstract: A computer-implemented method of determining indexed fields at query time comprises mapping data from a first source type to indexed fields in batch form using a wildcard specifier. The method also comprises receiving a query to execute on a data set comprising data from the first source type and data from a second source type. Further, the method comprises transforming the query to execute on the data from the first source type separately from the data from the second source type. Additionally, the method comprises executing the query to operate on the data from the first source type using information associated with the indexed fields and to separately operate on the data from the second source type.

    DATA SOURCE VISUALIZATIONS
    602.
    发明公开

    公开(公告)号:US20240232219A9

    公开(公告)日:2024-07-11

    申请号:US18494312

    申请日:2023-10-25

    Applicant: Splunk Inc.

    Abstract: A data intake and query system processes and stores events, which are associated with token identifiers for tokens corresponding to data sources for the messages that the events are generated from. Thus, the data intake and query system can receive a request to provide analyses and visualizations regarding stored events associated with a particular component associated with a plurality of events, such as a data source for the messages from which the plurality of events are generated from. These requests and the resulting visualizations can be customized based on selected tokens and selected components.

    Automatic creation and updating of event group summaries

    公开(公告)号:US12034759B2

    公开(公告)日:2024-07-09

    申请号:US17507698

    申请日:2021-10-21

    Applicant: SPLUNK INC.

    Abstract: A disclosed computer-implemented method includes receiving and indexing the raw data. Indexing includes dividing the raw data into time stamped searchable events that include information relating to computer or network security. Store the indexed data in an indexed data store and extract values from a field in the indexed data using a schema. Search the extracted field values for the security information. Determine a group of security events using the security information. Each security event includes a field value specified by a criteria. Present a graphical interface (GI) including a summary of the group of security events, other summaries of security events, and a remove element (associated with the summary). Receive input corresponding to an interaction of the remove element. Interacting with the remove element causes the summary to be removed from the GI. Update the GI to remove the summary from the GI.

    Generating machine learning-based outlier detection models using timestamped event data

    公开(公告)号:US12014255B1

    公开(公告)日:2024-06-18

    申请号:US18334996

    申请日:2023-06-14

    Applicant: Splunk Inc.

    CPC classification number: G06N20/00 G06F16/9038 G06F17/18

    Abstract: Techniques are described for providing a machine learning (ML) data analytics application including guided ML workflows that facilitate the end-to-end training and use of various types of ML models, where such guided workflows may also be referred to as ML “experiments.” One such model is an outlier detection model to assist in the monitoring of computer network traffic and computer performance. For example, the ML data analytics application may generate an outlier detection model using user-identified data from a data source and parameter information. The generates outlier detection model can include distribution functions of distribution types selected from a plurality of distribution types by a distribution fitting algorithm.

    Dynamic resolution estimation for a detector

    公开(公告)号:US12013880B2

    公开(公告)日:2024-06-18

    申请号:US17721251

    申请日:2022-04-14

    Applicant: SPLUNK Inc.

    CPC classification number: G06F16/287 G06F16/24568 G06F16/2477 H04L43/08

    Abstract: Described are systems, methods, and techniques for collecting, analyzing, processing, and storing time series data and for evaluating and dynamically estimating a resolution of one or more streams of data points and updating an output resolution. Responsive to receiving a stream of data points, a data resolution can be derived and an output resolution can be set to a first value. When a change to the data resolution is detected, the output resolution can be changed, modifying a frequency at which output data points are generated and/or transmitted. In some instances, a detector can be implemented to trigger an alert responsive to ingested data points corresponding with triggering parameters. An output resolution for the detector can be dynamically modified based on dynamically detecting a change to the data resolution of the stream of data.

    Supporting graph data structure transformations in graphs generated from a query to event data

    公开(公告)号:US12001426B1

    公开(公告)日:2024-06-04

    申请号:US18295567

    申请日:2023-04-04

    Applicant: Splunk Inc.

    CPC classification number: G06F16/24526 G06F8/77 G06F16/212

    Abstract: Systems and methods are disclosed for supporting transformations of a graph generated from a query to event data. The event data may be unstructured event data, from which instances of a journey can be identified that represent sequences of related events describing actions performed in a computing environment. When evaluating journey instances, it can be helpful to visualize the instances as a graph. Depending on the instances viewed, a user may desire different modifications to the graph. While such modifications can be made when initially building instances from the unstructured event data, this can limit reuse of the resulting instances (since the modification would also be present when evaluating other subsets). To address this, embodiments of the present disclosure enable graph modifications to be applied to subsets of journey instances after building those instances from unstructured event data, increasing reuse of instances built from a query against the unstructured data.

Patent Agency Ranking