Event Query Routing via Bit Vector Indexing
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Solution Overview
Problem
Enterprises face challenges in accessing and processing real-time event data across multiple systems and geographic locations due to the vast amount of data and numerous systems, leading to operational data visibility loss and high costs in creating operational reports, which is time-consuming and inefficient.
Innovation Solution
The implementation of an enterprise system that uses descriptive name identifiers and bit vectors to index and route queries for real-time event data, allowing for efficient access and processing of data by parsing queries into components and sending them to relevant data sources, thereby reducing the need for extensive data warehousing and centralized repositories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If enterprises store events in operational databases across multiple systems and geographic locations, then data availability and system distribution are improved, but data access complexity and operational report creation time increase significantly
Solution Approach 1:
The patent segments the monolithic operational database into multiple distributed event sources across different systems and locations. Each event source maintains local data, and the system routes queries to appropriate sources based on event types, eliminating the need to search entire centralized databases and reducing report creation time while maintaining data availability.
Solution Approach 2:
The patent introduces an event routing system as an intermediary layer between query sources and distributed event sources. This mediator uses bit vectors and descriptive identifiers to efficiently route queries to relevant data sources, reducing the time required to access distributed data without sacrificing availability.
2Ease of operation
If enterprises use traditional data warehousing and centralized repositories to access operational data, then data access is simplified, but infrastructure costs and resource requirements increase
Solution Approach 1:
The patent extracts the data access functionality from centralized data warehouses and distributes it directly to event sources. By routing queries directly to distributed event sources using bit vectors and descriptive identifiers, the system eliminates the need for expensive centralized repositories while maintaining ease of data access through automated query routing.
Solution Approach 2:
The patent uses descriptive identifiers and bit vectors as lightweight copies or representations of event data characteristics. Instead of physically copying and storing entire datasets in centralized repositories, the system uses compact bit vector representations to enable efficient query routing to distributed sources, reducing infrastructure requirements while maintaining access simplicity.
3Loss of information
If enterprises create detailed operational reports by searching and transforming data from multiple systems, then data completeness is improved, but processing costs and resource requirements increase
Solution Approach 1:
The patent applies preliminary action by pre-tagging events with descriptive identifiers and bit vectors at the source systems. This preparation work is done once when events are generated, allowing the routing system to quickly identify and retrieve relevant events from distributed sources without requiring expensive real-time searching and transformation processes, thus maintaining data completeness while reducing processing costs.
Data Source
AI summary
Indexing and routing to event data is described. Event data is assigned an identifier that identifies the data type and the contents of event data within an enterprise system. The event data may be real-time event data. With the identifier, a source of the event data is determined, and the source can be queried for the event data in real-time. The identifier is indexed along with other event data identifiers. Based on the location of the event data, the system sends out a query toward the data source to obtain the information, but also to route the query to the data source, rather than attempting to pull data towards the query source and process it at the query source.