公开(公告)号：US08788526B2

公开(公告)日：2014-07-22

申请号：US13662369

申请日：2012-10-26

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 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.

公开(公告)号：US20140074889A1

公开(公告)日：2014-03-13

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。

公开(公告)号：US08583631B1

公开(公告)日：2013-11-12

申请号：US13756105

申请日：2013-01-31

Applicant: Splunk Inc.

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

IPC: G06F7/00

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。