Event-Based Query Interface for Unstructured Data Indexing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Modern data centers face challenges in processing and analyzing large volumes of heterogeneous performance data due to its unstructured nature, which makes it difficult to apply semantic meaning, index, and query, leading to inefficiencies in data retrieval and analysis.
Innovation Solution
The implementation of an event-based system like SPLUNK ENTERPRISE, which uses a late-binding schema to process and store data, allowing for flexible extraction of information at search time, enables efficient indexing and querying of unstructured data by transforming raw data into timestamped events and applying extraction rules dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data is maintained in unstructured form to preserve more data for later use, then data completeness is improved, but indexing and searching operations become difficult
Solution Approach 1:
The patent segments unstructured data into discrete events with standardized fields and attributes. Each event is divided into identifiable components (timestamp, source, message, metadata) that can be independently indexed and queried, transforming the unstructured data into a structured format that maintains completeness while enabling efficient retrieval.
Solution Approach 2:
The patent introduces an event schema as an intermediary layer between raw unstructured data and query operations. This schema defines standardized fields and data types that mediate between the complete unstructured data and the indexing/searching requirements, allowing flexible querying without losing data completeness.
2Quantity of substance
If data is pre-processed and extracted to reduce storage size, then storage efficiency is improved, but data availability for future use deteriorates
Solution Approach 1:
The patent extracts only the essential structural elements (fields, data types, relationships) from the complete unstructured data during ingestion, while preserving the full original data. This extraction creates a lightweight schema that enables efficient storage and querying without discarding any actual data content.
Solution Approach 2:
The patent performs preliminary schema definition and field identification during data ingestion, preparing the data structure in advance for efficient querying. This preliminary action organizes the data into queryable fields without actually processing or discarding the raw data, enabling both storage efficiency and future data availability.
3Loss of information
If multiple separate query interfaces are used for different data types, then data retrieval completeness is improved, but system complexity increases
Solution Approach 1:
The patent creates a universal event-based query interface that can handle multiple data types and sources through a single standardized schema. This single interface can query structured logs, unstructured text, metrics, and other data types uniformly, eliminating the need for multiple separate interfaces while maintaining complete data retrieval capability.
Solution Approach 2:
The patent merges multiple data types and query interfaces into a unified event schema framework. By combining different data sources and query mechanisms under a single standardized event structure, the system achieves data retrieval completeness across all data types while reducing overall system complexity.
Data Source
AI summary
A method includes receiving, in a first query interface, a query composed by the user by typing commands into a query box of the first query interface and based on the receiving of the query, causing events corresponding to query results of the query to be displayed in the first query interface with fields corresponding to the events. Based on the selection by the user of an option, a second query interface is displayed with a table that includes events that correspond to query results of a loaded query. The table includes columns corresponding to event attributes, rows corresponding to events. Cells are populated with the data items of event attributes, where one of the columns corresponds to a field of the fields displayed in the first query interface. The table also includes interactive regions selectable by the user to add one or more commands to the loaded query.