File Browser Interface for Real-Time Cross-Platform Data Parsing
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Solution Overview
Problem
Big data intake and search systems face challenges in managing large volumes of data across disparate platforms, making it difficult to analyze and summarize data comprehensively, especially when moving data between systems is not feasible.
Innovation Solution
A search support system allows customers to browse and perform data processing tasks on external storage systems like Hadoop, with real-time results displayed in a graphical user interface, and utilizes a late binding schema to parse and index timestamped events from raw data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is stored in disparate big data intake and search systems, then data storage capacity increases, but data analysis capability across systems deteriorates
Solution Approach 1:
The patent implements a universal search interface that can query across multiple disparate big data intake and search systems simultaneously. The system provides a unified search functionality that works across different data sources (Hadoop, Splunk, SQL databases, etc.) without requiring separate analysis tools for each system, thereby maintaining data storage in distributed systems while enabling cohesive cross-system data analysis.
2Quantity of substance
If large volumes of data are stored across multiple platforms, then data retention increases, but data mobility deteriorates
Solution Approach 1:
The patent implements a virtualization layer that creates virtual copies of data access interfaces across different platforms. Instead of physically moving large volumes of data between systems, the system creates virtual representations that allow data to be accessed and analyzed across multiple platforms simultaneously, maintaining data retention while enabling flexible mobility through virtual access points.
3Productivity
If real-time data processing is implemented, then analysis speed increases, but system complexity increases
Solution Approach 1:
The patent segments the real-time data processing system into independent modular components: data collection modules, processing modules, and display modules. Each component handles specific tasks independently, allowing real-time processing capability while reducing overall system complexity through modular architecture. The segmented design enables independent optimization and maintenance of each component.
4Measurement precision
If comprehensive data parsing and indexing is performed, then data search accuracy increases, but processing time increases
Solution Approach 1:
The patent implements preliminary parsing and indexing of data during the data ingestion phase, before actual search operations are performed. By pre-processing and organizing data into indexed structures in advance, the system achieves high search accuracy when queries are executed, while minimizing processing time during actual search operations since the heavy lifting of parsing and indexing has already been completed.
Data Source
AI summary
A search support system allows a customer to browse data contained in files stored on an external storage system. The search support system allows a customer to specify data processing tasks to be performed on raw data retrieved from a file stored on the external storage system. The customer specifies each data processing task and the search support system performs each task as it is selected by the customer on raw data retrieved from the file. The search support system concurrently displays the results of each data processing task in real time in a graphical user interface. The search support system saves the customer's settings as a late binding schema that can be applied to raw data retrieved from the external storage system in order to parse the raw data and to create, index, and search timestamped events derived from the raw data.