Locating and categorizing data using inverted indexes

    公开(公告)号:US11061918B2

    公开(公告)日:2021-07-13

    申请号:US15479823

    申请日:2017-04-05

    Applicant: Splunk Inc.

    Abstract: Systems and methods are disclosed for locating data and categorizing a set of data using inverted indexes. The inverted indexes include token entries and field-value pair entries, as well as event references that correspond to events that include raw machine data. Using filter criteria, the inverted indexes are identified. In turn, the inverted indexes are used to identify a set of events that satisfy the filter criteria. The identified set of events are categorized based on categorization criteria and provided for display to a user.

    COLUMN-BASED CONTEXTUAL MENU WITH FORM ELEMENT TO ADD COMMANDS TO A SEARCH QUERY

    公开(公告)号:US20210209080A1

    公开(公告)日:2021-07-08

    申请号:US17212953

    申请日:2021-03-25

    Applicant: SPLUNK INC.

    Abstract: A search interface is displayed in a table format that includes a plurality of columns, each column including data items of an event attribute, the data items being of a set of events, each column being selectable by a user, and a plurality of rows forming cells with the one or more columns, each cell comprising one or more of the data items of the event attribute of a corresponding column. Based on the user selecting one or more of the columns, a list of options is displayed corresponding to the selected one or more columns, and one or more commands are added to a search query that corresponds to the set of events. The one or more commands are based on at least an option that is selected from the list of options and the event attribute of each of the selected one or more columns.

    Determining an extraction rule from positive and negative examples

    公开(公告)号:US11042697B2

    公开(公告)日:2021-06-22

    申请号:US16589445

    申请日:2019-10-01

    Applicant: SPLUNK INC.

    Abstract: The technology disclosed relates to formulating and refining field extraction rules that are used at query time on raw data with a late-binding schema. The field extraction rules identify portions of the raw data, as well as their data types and hierarchical relationships. These extraction rules are executed against very large data sets not organized into relational structures that have not been processed by standard extraction or transformation methods. By using sample events, a focus on primary and secondary example events help formulate either a single extraction rule spanning multiple data formats, or multiple rules directed to distinct formats. Selection tools mark up the example events to indicate positive examples for the extraction rules, and to identify negative examples to avoid mistaken value selection. The extraction rules can be saved for query-time use, and can be incorporated into a data model for sets and subsets of event data.

    PROVIDING EXTRACTION RESULTS FOR A PARTICULAR FIELD

    公开(公告)号:US20210174009A1

    公开(公告)日:2021-06-10

    申请号:US17169254

    申请日:2021-02-05

    Applicant: SPLUNK Inc.

    Abstract: The technology disclosed relates to formulating and refining field extraction rules that are used at query time on raw data with a late-binding schema. The field extraction rules identify portions of the raw data, as well as their data types and hierarchical relationships. These extraction rules are executed against very large data sets not organized into relational structures that have not been processed by standard extraction or transformation methods. By using sample events, a focus on primary and secondary example events help formulate either a single extraction rule spanning multiple data formats, or multiple rules directed to distinct formats. Selection tools mark up the example events to indicate positive examples for the extraction rules, and to identify negative examples to avoid mistaken value selection. The extraction rules can be saved for query-time use, and can be incorporated into a data model for sets and subsets of event data.

    User interface for defining custom threat rules in a network security system

    公开(公告)号:US11032307B2

    公开(公告)日:2021-06-08

    申请号:US15582739

    申请日:2017-04-30

    Applicant: Splunk Inc.

    Inventor: George Tsironis

    Abstract: The disclosed embodiments include a method performed by a computer system. The method includes causing display of one or more graphical controls enabling a user to define attributes of a threat rule, the attributes including a type of computer network entity and an anomaly pattern associated with the type of computer network entity. The method further includes generating the threat rule based on interaction by a user with the one or more graphical controls, wherein the threat rule identifies a security threat to the computer network that satisfies the attributes of the threat rule based on one or more detected anomalies on the computer network.

    Report acceleration using intermediate results in a distributed indexer system

    公开(公告)号:US11030173B1

    公开(公告)日:2021-06-08

    申请号:US16920187

    申请日:2020-07-02

    Applicant: Splunk Inc.

    Abstract: A method and system for managing searches of a data set that is partitioned based on a plurality of events. A structure of a search query may be analyzed to determine if logical computational actions performed on the data set is reducible. Data in each partition is analyzed to determine if at least a portion of the data in the partition is reducible. In response to a subsequent or reoccurring search request, intermediate summaries of reducible data and reducible search computations may be aggregated for each partition. Next, a search result may be generated based on at least one of the aggregated intermediate summaries, the aggregated reducible search computations, and a query of adhoc non-reducible data arranged in at least one of the plurality of partitions for the data set.

    Searching unstructured data in response to structured queries

    公开(公告)号:US11023504B2

    公开(公告)日:2021-06-01

    申请号:US15920434

    申请日:2018-03-13

    Applicant: Splunk Inc.

    Abstract: Technologies are described herein for executing queries expressed with reference to a structured query language against unstructured data. A user issues a structured query through a traditional structured data management (“SDM”) application. Upon receiving the structured query, an SDM driver analyzes the structured query and extracts a data structure from the unstructured data, if necessary. The structured query is then converted to an unstructured query based on the extracted data structure. The converted unstructured query may then be executed against the unstructured data. Results from the query are reorganized into structured data utilizing the extracted data structure and are then presented to the user through the SDM application.

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