公开(公告)号：US20150339344A1

公开(公告)日：2015-11-26

申请号：US14815884

申请日：2015-07-31

申请人： Splunk Inc.

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

IPC分类号： G06F17/30

CPC分类号： G06F17/30395 ,  G06F3/0482 ,  G06F17/248 ,  G06F17/30283 ,  G06F17/30424 ,  G06F17/30528 ,  G06F17/30554 ,  G06F17/30867

摘要： 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.

摘要翻译： 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。

公开(公告)号：US20170316337A1

公开(公告)日：2017-11-02

申请号：US15142346

申请日：2016-04-29

申请人： Splunk Inc.

发明人： Archana Sulochana Ganapathi

IPC分类号： G06N99/00 ,  G06F17/30

摘要： Disclosed is a guidance technique that can be applied to guide search and analysis of stored data by a user. The technique can include inputting from a user a portion of a search query expressed in a pipelined search language, at a system for indexing and searching machine data. The system generates and outputs search guidance for the user as the user builds the search query, by applying the portion of the query to an operation flow model, where the operation flow model represents a plurality of searches performable by the system. The operation flow model has been generated based on multi-user historical search data and includes a plurality of states, each representing a different group of related commands of the pipelined search language.

公开(公告)号：US09589012B2

公开(公告)日：2017-03-07

申请号：US14815884

申请日：2015-07-31

申请人： Splunk Inc.

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

IPC分类号： G06F17/30 ,  G06F17/24

CPC分类号： G06F17/30395 ,  G06F3/0482 ,  G06F17/248 ,  G06F17/30283 ,  G06F17/30424 ,  G06F17/30528 ,  G06F17/30554 ,  G06F17/30867

摘要： 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.

摘要翻译： 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。

公开(公告)号：US20150363460A1

公开(公告)日：2015-12-17

申请号：US14834361

申请日：2015-08-24

申请人： Splunk Inc.

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

IPC分类号： G06F17/30

CPC分类号： G06F17/30395 ,  G06F17/30424 ,  G06F17/30477 ,  G06F17/30554

摘要： 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.

摘要翻译： 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。

公开(公告)号：US11080641B1

公开(公告)日：2021-08-03

申请号：US16812206

申请日：2020-03-06

申请人： Splunk Inc.

发明人： Peter Sicilia ,  Archana Sulochana Ganapathi ,  Frederick Dean de Boer ,  Matthew Green

IPC分类号： G06Q10/06

摘要： Disclosed is a system and method for cross-silo acquisition, reporting and analysis of enterprise data. A computer system receives enterprise data related to various vertical units of an enterprise, including machine-generated data and human-generated data. The computer system stores the machine-generated data with associations to at least some of the human generated data, and associates persona data representing a plurality of personas with the plurality of vertical units of the enterprise, such that at least one persona is associated with each of the vertical units. The computer system further associates a plurality of user-defined key performance indicators (KPIs) with the personas, and associates each of a plurality of users with at least one of the personas. The computer system computes the KPIs based on the enterprise data, and controls access by the users to the computed KPIs, based on personas to which the users are assigned.

公开(公告)号：US10169405B2

公开(公告)日：2019-01-01

申请号：US15421415

申请日：2017-01-31

申请人： Splunk Inc.

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

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

摘要： 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.

公开(公告)号：US09817862B2

公开(公告)日：2017-11-14

申请号：US14834361

申请日：2015-08-24

申请人： Splunk Inc.

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

IPC分类号： G06F17/30

CPC分类号： G06F17/30395 ,  G06F17/30424 ,  G06F17/30477 ,  G06F17/30554

摘要： 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.

公开(公告)号：US08983994B2

公开(公告)日：2015-03-17

申请号：US14067203

申请日：2013-10-30

申请人： Splunk Inc.

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

IPC分类号： G06F17/30

CPC分类号： G06F17/30395 ,  G06F3/0482 ,  G06F17/248 ,  G06F17/30283 ,  G06F17/30424 ,  G06F17/30528 ,  G06F17/30554 ,  G06F17/30867

摘要： 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.

摘要翻译： 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。

公开(公告)号：US20140214807A1

公开(公告)日：2014-07-31

申请号：US14068651

申请日：2013-10-31

申请人： Splunk Inc.

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

IPC分类号： G06F17/30

CPC分类号： G06F17/30395 ,  G06F17/30424 ,  G06F17/30477 ,  G06F17/30554

摘要： 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.

摘要翻译： 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。

公开(公告)号：US11893010B1

公开(公告)日：2024-02-06

申请号：US17734786

申请日：2022-05-02

申请人： SPLUNK INC.

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

IPC分类号： G06F16/242 ,  G06F16/27 ,  G06F16/245 ,  G06F16/248 ,  G06F16/9535 ,  G06F16/2457 ,  G06F40/186 ,  G06F3/0482

CPC分类号： G06F16/2425 ,  G06F3/0482 ,  G06F16/245 ,  G06F16/248 ,  G06F16/24575 ,  G06F16/27 ,  G06F16/9535 ,  G06F40/186

摘要： 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.