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    WIZARD FOR CONFIGURING A FIELD EXTRACTION RULE
    3.
    发明申请
    WIZARD FOR CONFIGURING A FIELD EXTRACTION RULE 审中-公开

    公开(公告)号：US20200012715A1

    公开(公告)日：2020-01-09

    申请号：US16541637

    申请日：2019-08-15

    Applicant: SPLUNK INC.

    Inventor： Jesse Miller ,  Micah James Delfino ,  Marc Robichaud ,  Catherine Anne Hanson ,  David Carasso

    IPC: G06F17/24 ,  G06F16/2458

    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.

    Syntax templates for coding
    4.
    发明授权
    Syntax templates for coding 有权

    公开(公告)号：US10528607B2

    公开(公告)日：2020-01-07

    申请号：US15223598

    申请日：2016-07-29

    Applicant: SPLUNK INC.

    Inventor： Jindrich Dinga ,  Yuan Xie ,  Katherine Kyle Feeney ,  Jesse Miller

    IPC: G06F9/44 ,  G06F16/33 ,  G06F8/33 ,  G06F11/30

    Abstract: Various approaches for automating code completion are described herein. More particularly, approaches are provided that automatically generate coded commands of a coding language (i.e., code) that function and operate as intended by the user. As the user codes the commands, such approaches assist a user in various ways. For example, such automated assistance provides the user an understanding of various coding options available in the coding language. The assistance also enforces the proper employment of the available coding options, as well as provides an understanding of the functionality of the generated code. Automating code completion provides various benefits to the user, such as decreasing the time the user spends generating code, increasing the likelihood that the generated code functions and operates on a system as intended, and reducing the number of code versions required to be executed or compiled by the system.

    Refining extraction rules based on selected text within events
    5.
    发明授权
    Refining extraction rules based on selected text within events 有权

    公开(公告)号：US10394946B2

    公开(公告)日：2019-08-27

    申请号：US15694654

    申请日：2017-09-01

    Applicant: SPLUNK INC.

    Inventor： Jesse Miller ,  Micah James Delfino ,  Marc Robichaud ,  Catherine Anne Hanson ,  David Carasso

    IPC: G06F3/048 ,  G06F17/24 ,  G06F16/2458

    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.

    SOURCE TYPE DEFINITION CONFIGURATION USING A GRAPHICAL USER INTERFACE
    7.
    发明申请
    SOURCE TYPE DEFINITION CONFIGURATION USING A GRAPHICAL USER INTERFACE 审中-公开

    公开(公告)号：US20180300349A1

    公开(公告)日：2018-10-18

    申请号：US16013381

    申请日：2018-06-20

    Applicant: Splunk Inc.

    Inventor： Alexander Munk ,  Jesse Miller

    IPC: G06F17/30 ,  G06F3/0482

    Abstract: A data intake and query system provides interfaces that enable users to configure source type definitions used by the system. A data intake and query system generally refers to a system for collecting and analyzing data including machine-generated data. Such a system may be configured to consume many different types of machine data generated by any number of different data sources including various servers, network devices, applications, etc. At a high level, a source type definition comprises one or more properties that define how various components of a data intake and query system collect, index, store, search and otherwise interact with particular types of data consumed by the system. The interfaces provided by the system generally comprise one or more interface components for configuring various attributes of a source type definition.

    ADVANCED FIELD EXTRACTOR WITH MODIFICATION OF AN EXTRACTED FIELD
    8.
    发明申请
    ADVANCED FIELD EXTRACTOR WITH MODIFICATION OF AN EXTRACTED FIELD 审中-公开

    公开(公告)号：US20170139887A1

    公开(公告)日：2017-05-18

    申请号：US15417430

    申请日：2017-01-27

    Applicant: Splunk, Inc.

    Inventor： Jesse Miller ,  Micah James Delfino ,  Marc Robichaud ,  David Carasso

    IPC: G06F17/24 ,  G06F3/0484 ,  G06F17/30

    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.

    ADVANCED FIELD EXTRACTOR WITH MULTIPLE POSITIVE EXAMPLES
    9.
    发明申请
    ADVANCED FIELD EXTRACTOR WITH MULTIPLE POSITIVE EXAMPLES 有权
    具有多个积极实例的先进场提取器

    公开(公告)号：US20150149879A1

    公开(公告)日：2015-05-28

    申请号：US14610668

    申请日：2015-01-30

    Applicant: Splunk Inc.

    Inventor： Jesse Miller ,  Micah James Delfino ,  Marc Robichaud ,  Catherine Anne Hanson ,  David Carasso

    IPC: G06F17/24

    CPC classification number: G06F17/243 ,  G06F17/30551

    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.

    Abstract translation: 所公开的技术涉及制定和提炼在查询时使用具有后期绑定模式的原始数据的字段提取规则。 字段提取规则识别原始数据的部分，以及它们的数据类型和层次关系。 这些提取规则是针对未组织成尚未通过标准提取或转换方法处理的关系结构的非常大的数据集执行的。 通过使用示例事件，关注主要和次要示例事件有助于制定跨多个数据格式的单个提取规则，或者针对不同格式的多个规则。 选择工具标记示例事件以指示提取规则的正例，并确定负面示例以避免错误的值选择。 提取规则可以保存以供查询时间使用，并且可以被并入事件数据的集合和子集的数据模型中。

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