Interactive Visualization Framework Using Modular Static Libraries
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Solution Overview
Problem
Analyzing and searching massive quantities of machine-generated data presents challenges due to the vast types and formats of data generated by thousands of components in computing environments, making it time-consuming and inefficient to derive insights from this data.
Innovation Solution
An event-based data intake and query system, such as the SPLUNK® ENTERPRISE system, is used to collect, index, and search machine-generated data, employing a late-binding schema that allows for flexible data extraction and visualization, enabling users to search all data rather than just pre-specified sets, and interactive visualizations are generated using a visualization framework that allows users to modify and interact with visual representations of the data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If massive quantities of machine-generated data are stored for later analysis, then data flexibility and analysis options are improved, but data processing time and computational complexity increase
Solution Approach 1:
The system performs preliminary indexing and classification of machine data during the data ingestion phase, organizing data into structured formats with metadata tags before analysis is needed. This pre-processing creates an optimized data structure that enables rapid querying and flexible analysis later without requiring full data processing at analysis time.
Solution Approach 2:
The patent introduces an intermediary indexing layer that sits between raw data storage and analysis tools. This intermediary structure pre-organizes data into searchable indexes and metadata frameworks, allowing analysts to quickly access and flexibly analyze data without processing the entire raw data set, thus reducing processing time while maintaining analysis flexibility.
2Productivity
If pre-specified data items are extracted and stored during pre-processing, then data retrieval efficiency is improved, but data flexibility and analysis options are reduced
Solution Approach 1:
The system creates a universal indexing framework that organizes data in a multi-functional structure capable of supporting multiple analysis types simultaneously. The index structure is designed to accommodate various query patterns and analysis approaches, allowing the same pre-processed data structure to serve diverse analytical needs without requiring separate extraction processes for different analysis types.
Solution Approach 2:
The patent implements a dynamic indexing system where the data structure can adapt to different analysis requirements. The index maintains core efficient retrieval structures while allowing flexible querying capabilities that can dynamically access different data aspects based on analysis needs, combining retrieval efficiency with analytical flexibility.
3Adaptability or versatility
If interactive visualizations are created from scratch, then customization and interactivity are improved, but development complexity and time increase
Solution Approach 1:
The visualization system is segmented into modular components including base visualization templates, data binding layers, and interaction handlers. Each component can be independently configured and combined, allowing users to create customized interactive visualizations by assembling pre-built modules rather than developing entire visualization systems from scratch, thus reducing development complexity while maintaining customization capabilities.
Data Source
AI summary
Disclosed is a framework for generating for display an interactive visualization of event data based on a static visualization library. In an embodiment, event data is received based on a user search query. A computer system implementing a visualization framework accesses a visualization library that includes instructions for rendering a static visualization based on input data. The computer system then processes the received event data with the visualization library to generate an interactive visualization of the received event data and causes display of the interactive visualization, the interactive visualization being dynamically modifiable in response to a user input.