Query Parameter Recommendation via Automatic Query Generation
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Solution Overview
Problem
Current data intake and query systems face challenges in efficiently searching and analyzing large sets of raw machine data due to the lack of user-friendly tools for visually identifying data subsets, particularly in IT environments generating diverse and massive amounts of structured, semi-structured, and unstructured data.
Innovation Solution
A data intake and query system that utilizes a flexible schema to process and store raw machine data, allowing for late-binding schema application during search time, enabling field-searchability and facilitating the extraction of insights through a graphical user interface that recommends query parameters and templates based on user interactions and automatically generated queries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If tools allow analysts to search data systems separately and collect results over a network, then data analysis capability is provided, but the analysis process becomes piecemeal and lacks visual identification of data subsets
Solution Approach 1:
The patent combines multiple separate data system searches into a unified visual interface that presents integrated results. The system merges search capabilities across distributed data systems while providing a single visual workspace where analysts can see and interact with all data subsets together, eliminating the piecemeal nature of previous approaches.
Solution Approach 2:
The patent introduces a visual dimension to data search and analysis by presenting data subsets in a graphical interface rather than through traditional network-based result collection. This visual dimension allows analysts to spatially organize and identify patterns across data subsets that would be difficult to perceive in linear, text-based results.
2Adaptability or versatility
If massive quantities of raw data are stored for later retrieval and analysis, then greater flexibility and completeness of analysis are enabled, but the complexity of searching and analyzing the data increases
Solution Approach 1:
The patent introduces a visual interface as an intermediary between the stored raw data and the analyst. This intermediary layer provides tools for filtering, organizing, and visualizing data subsets, reducing the complexity of searching through massive raw data stores while maintaining the ability to perform comprehensive analysis.
Solution Approach 2:
The patent segments massive raw data into manageable visual subsets that can be independently analyzed and explored. The system divides the overwhelming entirety of stored data into discrete, visually-presented portions that analysts can selectively examine, reducing the perceived complexity while maintaining access to the complete data set.
3Productivity
If pre-processing is performed to reduce the vast amount of generated data, then efficient retrieval and analysis of specified data items is facilitated, but the remainder of the data is discarded and cannot be analyzed later
Solution Approach 1:
The patent implements a dynamic approach where the level of data processing and presentation adapts based on analyst needs. Rather than static pre-processing that permanently discards data, the system dynamically adjusts what data is processed, filtered, or displayed based on the specific analysis task, allowing efficient retrieval when needed while preserving access to all original data.
4Ease of operation
If UI tools are designed to allow quick search and analysis of large sets of raw machine data, then visual identification of data subsets becomes easier, but the tool complexity and development difficulty increases
Solution Approach 1:
The patent creates a universal visual interface that handles multiple data system types and search scenarios through a single toolset. Rather than developing specialized tools for each data system or search type, the system provides a multi-functional interface that adapts to different data sources and analysis needs, reducing overall tool complexity while maintaining ease of operation.
Data Source
AI summary
Systems and methods are disclosed for generating queries based on a portion of a query that is entered in a user interface. The system can identify a token query parameter from the query entered in the user interface and use the token parameter to generate one or more other queries. The other queries can include query commands that return information or characteristics about the data that is to be searched. Using the results of the one or more queries, the system can provide one or more recommended query parameters for the user to include the query entered in the user interface.