Catherine D Hanson

US Patent:

20200012715, Jan 9, 2020

Filed:

Aug 15, 2019

Appl. No.:

16/541637

Inventors:

- San Francisco CA, US
Micah James Delfino - San Francisco CA, US
Marc Robichaud - San Francisco CA, US
Catherine Anne Hanson - San Francisco CA, US
David Carasso - San Francisco CA, US

International Classification:

G06F 17/24
G06F 16/2458

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.

US Patent:

20180267947, Sep 20, 2018

Filed:

Sep 1, 2017

Appl. No.:

15/694654

Inventors:

- San Francisco CA, US
Micah James Delfino - San Francisco CA, US
Marc Robichaud - San Francisco CA, US
Catherine Anne Hanson - San Francisco CA, US
David Carasso - San Francisco CA, US

International Classification:

G06F 17/24
G06F 17/30

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.

US Patent:

20150149879, May 28, 2015

Filed:

Jan 30, 2015

Appl. No.:

14/610668

Inventors:

- San Francisco CA, US
Micah James Delfino - San Francisco CA, US
Marc Robichaud - San Francisco CA, US
Catherine Anne Hanson - San Francisco CA, US
David Carasso - , US

Assignee:

Splunk Inc. - San Francisco CA

International Classification:

G06F 17/24

US Classification:

715226

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.