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: 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: 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: 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: A processing device performs a preliminary grouping of data items in a dataset to define one or more clusters and for each cluster, identifies a set of search terms for a search query that would retrieve data items in the cluster upon execution of the search query against the dataset.

Abstract: The disclosed embodiments include techniques for navigating sections with exposable content in a viewing area. A method includes causing display, on a display device, of a view panel including contiguous sections. Each contiguous section includes a heading bar and content. The method further includes causing a portion of a first content of a first section to display on the display device by positioning a first heading bar of the first section at a first distance from a second heading bar of a second section. In response to a selection of the first heading bar, the first heading bar and/or the second heading bar is repositioned a second distance from each other. The second distance is greater than the first distance such that more of the first content is displayed.

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: 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: 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: 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: 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: 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: 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: 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: 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: 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: A processing device performs a preliminary grouping of data items in a dataset to define one or more clusters and for each cluster, identifies a set of search terms for a search query that would retrieve data items in the cluster upon execution of the search query against the dataset.

Abstract: A processing device performs a preliminary grouping of data items in a dataset to define one or more clusters and for each cluster, identifies a set of search terms for a search query that would retrieve data items in the cluster upon execution of the search query against the dataset.

Abstract: The disclosed embodiments include techniques for navigating sections with exposable content in a viewing area. A method includes causing display, on a display device, of a view panel including contiguous sections. Each contiguous section includes a heading bar and content. The method further includes causing a portion of a first content of a first section to display on the display device by positioning a first heading bar of the first section at a first distance from a second heading bar of a second section. In response to a selection of the first heading bar, the first heading bar and/or the second heading bar is repositioned a second distance from each other. The second distance is greater than the first distance such that more of the first content is displayed.

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.