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    GENERATION OF A DATA MODEL APPLIED TO OBJECT QUERIES
    1.
    发明申请
    GENERATION OF A DATA MODEL APPLIED TO OBJECT QUERIES 有权
    适用于对象查询的数据模型的生成

    公开(公告)号：US20150339344A1

    公开(公告)日：2015-11-26

    申请号：US14815884

    申请日：2015-07-31

    Applicant: Splunk Inc.

    Inventor： Alice Emily Neels ,  Archana Sulochana Ganapathi ,  Marc Vincent Robichaud ,  Stephen Phillip Sorkin ,  Steve Yu Zhang

    IPC: G06F17/30

    CPC classification number: G06F17/30395 ,  G06F3/0482 ,  G06F17/248 ,  G06F17/30283 ,  G06F17/30424 ,  G06F17/30528 ,  G06F17/30554 ,  G06F17/30867

    Abstract: Embodiments include generating data models that may give semantic meaning for unstructured or structured data that may include data generated and/or received by search engines, including a time series engine. A method includes generating a data model for data stored in a repository. Generating the data model includes generating an initial query string, executing the initial query string on the data, generating an initial result set based on the initial query string being executed on the data, determining one or more candidate fields from one or results of the initial result set, generating a candidate data model based on the one or more candidate fields, iteratively modifying the candidate data model until the candidate data model models the data, and using the candidate data model as the data model.

    Abstract translation: 实施例包括生成可以给非结构化或结构化数据赋予语义意义的数据模型，其可以包括由搜索引擎（包括时间序列引擎）生成和/或接收的数据。 一种方法包括为存储在存储库中的数据生成数据模型。 生成数据模型包括生成初始查询字符串，对数据执行初始查询字符串，基于对数据执行的初始查询字符串生成初始结果集，从一个或多个初始查询字符串的结果确定一个或多个候选字段 生成基于一个或多个候选字段的候选数据模型，迭代地修改候选数据模型，直到候选数据模型对数据建模，并使用候选数据模型作为数据模型。

    DATA MODEL FOR MACHINE DATA FOR SEMANTIC SEARCH
    2.
    发明申请
    DATA MODEL FOR MACHINE DATA FOR SEMANTIC SEARCH 有权
    用于语义搜索的机器数据的数据模型

    公开(公告)号：US20140074817A1

    公开(公告)日：2014-03-13

    申请号：US13662369

    申请日：2012-10-26

    Applicant: SPLUNK INC.

    Inventor： Alice Emily Neels ,  Archara Sulochana Ganapathi ,  Marc Vincent Robichaud ,  Stephen Phillip Sorkin ,  Steve Yu Zhang

    IPC: G06F17/30

    CPC classification number: G06F17/30395 ,  G06F3/0482 ,  G06F17/248 ,  G06F17/30283 ,  G06F17/30424 ,  G06F17/30528 ,  G06F17/30554 ,  G06F17/30867

    Abstract: Embodiments are directed towards generating data models that may give semantic meaning for unstructured data or structured data that may include data generated and/or received by search engines, including a time series engine. Data models also may be generated to provide semantic meaning to structured data. A data model may be composed of a hierarchical data model objects analogous to an object-oriented programming class hierarchy. Users may employ a data modeling application to produce reports using search objects that may be part of, or associated with the data model. The data modeling application may employ the search object and the data model to generate a query string for searching a data repository to produce a result set. A data modeling application may map the result set data to data model objects that may be used to generate reports.

    Abstract translation: 实施例涉及生成可能给非结构化数据或结构化数据提供语义意义的数据模型，这些结构化数据或结构化数据可能包括由搜索引擎（包括时间序列引擎）生成和/或接收的数据。 也可以生成数据模型以为结构化数据提供语义。 数据模型可以由类似于面向对象的编程类层次结构的分层数据模型对象组成。 用户可以使用数据建模应用程序来生成使用可能是数据模型的一部分或与数据模型相关联的搜索对象的报告。 数据建模应用程序可以使用搜索对象和数据模型来生成用于搜索数据存储库以产生结果集的查询字符串。 数据建模应用程序可将结果集数据映射到可用于生成报告的数据模型对象。

    Generation of a data model applied to object queries
    4.
    发明授权
    Generation of a data model applied to object queries 有权
    生成应用于对象查询的数据模型

    公开(公告)号：US09589012B2

    公开(公告)日：2017-03-07

    申请号：US14815884

    申请日：2015-07-31

    Applicant: Splunk Inc.

    Inventor： Alice Emily Neels ,  Archana Sulochana Ganapathi ,  Marc Vincent Robichaud ,  Stephen Phillip Sorkin ,  Steve Yu Zhang

    IPC: G06F17/30 ,  G06F17/24

    CPC classification number: G06F17/30395 ,  G06F3/0482 ,  G06F17/248 ,  G06F17/30283 ,  G06F17/30424 ,  G06F17/30528 ,  G06F17/30554 ,  G06F17/30867

    Abstract: Embodiments include generating data models that may give semantic meaning for unstructured or structured data that may include data generated and/or received by search engines, including a time series engine. A method includes generating a data model for data stored in a repository. Generating the data model includes generating an initial query string, executing the initial query string on the data, generating an initial result set based on the initial query string being executed on the data, determining one or more candidate fields from one or results of the initial result set, generating a candidate data model based on the one or more candidate fields, iteratively modifying the candidate data model until the candidate data model models the data, and using the candidate data model as the data model.

    Abstract translation: 实施例包括生成可以给非结构化或结构化数据赋予语义意义的数据模型，其可以包括由搜索引擎（包括时间序列引擎）生成和/或接收的数据。 一种方法包括为存储在存储库中的数据生成数据模型。 生成数据模型包括生成初始查询字符串，对数据执行初始查询字符串，基于对数据执行的初始查询字符串生成初始结果集，从一个或多个初始查询字符串的结果确定一个或多个候选字段 生成基于一个或多个候选字段的候选数据模型，迭代地修改候选数据模型，直到候选数据模型对数据建模，并使用候选数据模型作为数据模型。

    Associating Metadata With Results Produced By Applying A Pipelined Search Command To Machine Data In Timestamped Events
    5.
    发明申请
    Associating Metadata With Results Produced By Applying A Pipelined Search Command To Machine Data In Timestamped Events 有权
    将元数据与通过应用流水线搜索命令生成的结果相关联以在时间戳事件中计算机数据

    公开(公告)号：US20150363460A1

    公开(公告)日：2015-12-17

    申请号：US14834361

    申请日：2015-08-24

    Applicant: Splunk Inc.

    Inventor： Archana Sulochana Ganapathi ,  Alice Emily Neels ,  Marc Vincent Robichaud ,  Stephen Phillip Sorkin ,  Steve Yu Zhang

    IPC: G06F17/30

    CPC classification number: G06F17/30395 ,  G06F17/30424 ,  G06F17/30477 ,  G06F17/30554

    Abstract: Embodiments are directed towards determining and tracking metadata for the generation of visualizations of requested data. A user may request data by providing a query that may be employed to search for the requested data. The query may include a plurality of commands, which may be employed in a pipeline to perform the search and to generate a table of the requested data. In some embodiments, each command may be executed to perform an action on a set of data. The execution of a command may generate one or more columns to append and/or insert into the table of requested data. Metadata for each generated column may be determined based on the actions performed by executing the commands. The table of requested data and the column metadata may be employed to generate and display a visualization of at least a portion of the requested data to a user.

    Abstract translation: 实施例旨在确定和跟踪用于生成所请求数据的可视化的元数据。 用户可以通过提供可用于搜索所请求的数据的查询来请求数据。 该查询可以包括多个命令，其可以在流水线中用于执行搜索并生成所请求的数据的表。 在一些实施例中，可以执行每个命令以对一组数据执行动作。 命令的执行可以生成一个或多个列来附加和/或插入到所请求的数据的表中。 可以基于通过执行命令执行的动作来确定每个生成的列的元数据。 可以使用所请求的数据和列元数据的表来生成并向用户显示所请求的数据的至少一部分的可视化。

    Data model selection and application based on data sources
    6.
    发明授权
    Data model selection and application based on data sources 有权

    公开(公告)号：US10169405B2

    公开(公告)日：2019-01-01

    申请号：US15421415

    申请日：2017-01-31

    Applicant: Splunk Inc.

    Inventor： Alice Emily Neels ,  Archana Sulochana Ganapathi ,  Marc Vincent Robichaud ,  Stephen Phillip Sorkin ,  Steve Yu Zhang

    IPC: G06F17/30 ,  G06F17/24 ,  G06F3/0482

    Abstract: Embodiments include generating data models that may give semantic meaning for unstructured or structured data that may include data generated and/or received by search engines, including a time series engine. A method includes generating a data model for data stored in a repository. Generating the data model includes generating an initial query string, executing the initial query string on the data, generating an initial result set based on the initial query string being executed on the data, determining one or more candidate fields from one or results of the initial result set, generating a candidate data model based on the one or more candidate fields, iteratively modifying the candidate data model until the candidate data model models the data, and using the candidate data model as the data model.

    Generation of a data model for searching machine data
    8.
    发明授权
    Generation of a data model for searching machine data 有权
    生成用于搜索机器数据的数据模型

    公开(公告)号：US08983994B2

    公开(公告)日：2015-03-17

    申请号：US14067203

    申请日：2013-10-30

    Applicant: Splunk Inc.

    Inventor： Alice Emily Neels ,  Archana Sulochana Ganapathi ,  Marc Vincent Robichaud ,  Stephen Phillip Sorkin ,  Steve Yu Zhang

    IPC: G06F17/30

    CPC classification number: G06F17/30395 ,  G06F3/0482 ,  G06F17/248 ,  G06F17/30283 ,  G06F17/30424 ,  G06F17/30528 ,  G06F17/30554 ,  G06F17/30867

    Abstract: Embodiments include generating data models that may give semantic meaning for unstructured or structured data that may include data generated and/or received by search engines, including a time series engine. A method includes generating a data model for data stored in a repository. Generating the data model includes generating an initial query string, executing the initial query string on the data, generating an initial result set based on the initial query string being executed on the data, determining one or more candidate fields from one or results of the initial result set, generating a candidate data model based on the one or more candidate fields, iteratively modifying the candidate data model until the candidate data model models the data, and using the candidate data model as the data model. The method further includes generating a new query string using the data model, executing the new query string on the data, and generating a new result set based on the new query string being executed on the data.

    Abstract translation: 实施例包括生成可以给非结构化或结构化数据赋予语义意义的数据模型，其可以包括由搜索引擎（包括时间序列引擎）生成和/或接收的数据。 一种方法包括为存储在存储库中的数据生成数据模型。 生成数据模型包括生成初始查询字符串，对数据执行初始查询字符串，基于对数据执行的初始查询字符串生成初始结果集，从一个或多个初始查询字符串的结果确定一个或多个候选字段 生成基于一个或多个候选字段的候选数据模型，迭代地修改候选数据模型，直到候选数据模型对数据建模，并使用候选数据模型作为数据模型。 该方法还包括使用数据模型生成新的查询字符串，对数据执行新的查询字符串，并且基于对数据执行的新查询字符串生成新的结果集。

    METADATA TRACKING FOR A PIPELINED SEARCH LANGUAGE (DATA MODELING FOR FIELDS)
    9.
    发明申请
    METADATA TRACKING FOR A PIPELINED SEARCH LANGUAGE (DATA MODELING FOR FIELDS) 审中-公开
    用于管道搜索语言的元数据跟踪（数据建模）

    公开(公告)号：US20140214807A1

    公开(公告)日：2014-07-31

    申请号：US14068651

    申请日：2013-10-31

    Applicant: Splunk Inc.

    Inventor： Archana Sulochana Ganapathi ,  Alice Emily Neels ,  Marc Vincent Robichaud ,  Stephen Phillip Sorkin ,  Steve Yu Zhang

    IPC: G06F17/30

    CPC classification number: G06F17/30395 ,  G06F17/30424 ,  G06F17/30477 ,  G06F17/30554

    Abstract: Embodiments are directed towards determining and tracking metadata for the generation of visualizations of requested data. A user may request data by providing a query that may be employed to search for the requested data. The query may include a plurality of commands, which may be employed in a pipeline to perform the search and to generate a table of the requested data. In some embodiments, each command may be executed to perform an action on a set of data. The execution of a command may generate one or more columns to append and/or insert into the table of requested data. Metadata for each generated column may be determined based on the actions performed by executing the commands. The table of requested data and the column metadata may be employed to generate and display a visualization of at least a portion of the requested data to a user.

    Abstract translation: 实施例旨在确定和跟踪用于生成所请求数据的可视化的元数据。 用户可以通过提供可用于搜索所请求的数据的查询来请求数据。 该查询可以包括多个命令，其可以在流水线中用于执行搜索并生成所请求的数据的表。 在一些实施例中，可以执行每个命令以对一组数据执行动作。 命令的执行可以生成一个或多个列来附加和/或插入到所请求的数据的表中。 可以基于通过执行命令执行的动作来确定每个生成的列的元数据。 可以使用所请求的数据和列元数据的表来生成并向用户显示所请求的数据的至少一部分的可视化。

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