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: The disclosure relates to certain system and method embodiments for generating reports from unstructured data. In one embodiment, a method can include identifying events matching criteria of an initial search query (each of the events including a portion of raw machine data that is associated with a time), identifying a set of fields, each field defined for one or more of the identified events, causing display of an interactive graphical user interface (GUI) that includes one or more interactive elements enabling a user to define a report for providing information relating to the matching events (each interactive element enabling processing or presentation of information in the matching events using one or more fields in the identified set of fields), receiving, via the GUI, a report definition indicating how to report information relating to the matching events, and generating, based on the report definition, a report including information relating to the matching events.

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: The disclosure relates to certain system and method embodiments for generating reports from unstructured data. In one embodiment, a method can include identifying events matching criteria of an initial search query (each of the events including a portion of raw machine data that is associated with a time), identifying a set of fields, each field defined for one or more of the identified events, causing display of an interactive graphical user interface (GUI) that includes one or more interactive elements enabling a user to define a report for providing information relating to the matching events (each interactive element enabling processing or presentation of information in the matching events using one or more fields in the identified set of fields), receiving, via the GUI, a report definition indicating how to report information relating to the matching events, and generating, based on the report definition, a report including information relating to the matching events.

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: 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: 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: The disclosure relates to certain system and method embodiments for generating reports from unstructured data. In one embodiment, a method can include identifying events matching criteria of an initial search query (each of the events including a portion of raw machine data that is associated with a time), identifying a set of fields, each field defined for one or more of the identified events, causing display of an interactive graphical user interface (GUI) that includes one or more interactive elements enabling a user to define a report for providing information relating to the matching events (each interactive element enabling processing or presentation of information in the matching events using one or more fields in the identified set of fields), receiving, via the GUI, a report definition indicating how to report information relating to the matching events, and generating, based on the report definition, a report including information relating to the matching events.

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: 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: Fields may be discovered in events that are returned in response to an initial search. The events may comprise portions of raw data. Furthermore, the fields may be defined by extraction rules for extracting values from corresponding portions of raw data. The displaying of a graphical user interface (GUI) may be caused where the GUI enables a user to select or enter criteria for a subset of the discovered fields without entering a search query in a search bar. At least one criterion for at least one field from the subset of the discovered fields may be received through a portion of the GUI that does not include a search bar for entering a search query. The events returned in response to the initial search query may be caused to be filtered based on the received criterion.

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: 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: 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: 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: 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: 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: 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: 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: 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.