IDENTIFYING SIMILAR FIELD SETS USING RELATED SOURCE TYPES

    公开(公告)号:US20200042626A1

    公开(公告)日:2020-02-06

    申请号:US16050487

    申请日:2018-07-31

    Applicant: SPLUNK INC.

    Abstract: Embodiments of the present invention are directed to identifying related data, in particular, data associated with different source types. In embodiments, a first source type related to a second source type associated with a search query is identified. Field set pairs are identified from a first data set associated with the first source type and a second data set associated with the second source type. Each field set pair can include one field set associated with the first source type and another field set associated with the second source type. For each field set pair, an extent of similarity is determined between the corresponding field sets. Based on the extent of similarities between the corresponding field sets, at least one pair of related field sets is identified. An indication of the at least one pair of related field sets is provided, for example, for presentation to a user.

    Automated anomaly detection for event-based system

    公开(公告)号:US10552728B2

    公开(公告)日:2020-02-04

    申请号:US15224493

    申请日:2016-07-29

    Applicant: Splunk, Inc.

    Abstract: Described herein is a technology that facilitates the production of and the use of automated datagens for event-based systems. A datagen (i.e., data-generator or data generation system) is a component, module, or subsystem of computer systems that searches, monitors, and analyzes machine data. Existing datagens are not capable of detecting an anomaly in machine data. An anomaly is a variance in the input data stream that exceeds some acceptable amount of deviation from the norm (i.e., standard, expectation, etc.). An embodiment of datagen, in accordance with the technology described herein, detects anomalies in the input machine data.

    Graphical user interface indicating anomalous events

    公开(公告)号:US11755938B2

    公开(公告)日:2023-09-12

    申请号:US16776302

    申请日:2020-01-29

    Applicant: SPLUNK INC.

    CPC classification number: G06N7/01 G06F3/00 G06N20/00

    Abstract: Methods and systems for determining event probabilities and anomalous events are provided. In one implementation, a method includes: receiving source data, where the source data is configured as a plurality of events with associated timestamps; searching the source data, where the searching provides a search result including N events from the plurality of events, where N is an integer greater than one, where each event of the N events includes a plurality of field values, where at least one event of the N events can include one or more categorical field values and one or more numerical field values; and for an event of the N events, determining a probability of occurrence for each field value of the plurality of field values; and using probabilities determined for the plurality of field values, determining a probability of occurrence for the event.

    Searching non-text machine data
    49.
    发明授权

    公开(公告)号:US11232146B2

    公开(公告)日:2022-01-25

    申请号:US15664991

    申请日:2017-07-31

    Applicant: SPLUNK, Inc.

    Inventor: Adam Oliner

    Abstract: Described herein are technologies that facilitate effective use (e.g., indexing and searching) of non-text machine data (e.g., audio/visual data) in an event-based machine-data intake and query system.

    Conditional processing based on inferred sourcetypes

    公开(公告)号:US11106681B2

    公开(公告)日:2021-08-31

    申请号:US16175636

    申请日:2018-10-30

    Applicant: Splunk, Inc.

    Abstract: Messages of a first data stream may be accessed from an ingestion buffer in communication with a streaming data processor to receive data from the first data stream. At the streaming data processor and using an inference model, a sourcetype associated with one or more messages from the first data stream may be determined. The one or more messages may include a portion of machine data. Using the streaming data processor, a second data stream may be generated from the first data stream. The second data stream may include a subset of messages from the first data stream. A message of the subset of messages may be included in the second data stream based on a condition associated with the sourcetype for the message. At least one processing operation may be performed on at least one of the subset of messages from the second data stream.

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