Graph Data Indexing via Segmented Forward and Reverse Structures
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Solution Overview
Problem
Conventional relational databases face inefficiencies in scalability and performance when handling graph data structures, particularly in queries that require traversal of interconnected objects, leading to increased database lookups and reduced query response times.
Innovation Solution
A distributed indexing system that provides denormalization and replica index functionality to improve query performance, enabling flexible search capabilities and efficient handling of graph data by storing and serving information modeled as a graph with nodes and edges, allowing for combined queries involving associations and objects, and supporting a scalable and cost-effective infrastructure for social network environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional relational databases are used to store and query graph data, then data storage is simple and standardized, but query performance degrades and scalability is limited due to increased database lookups required for traversal operations
Solution Approach 1:
The patent segments the database system into multiple specialized index structures (forward index, reverse index, edge index) that divide the graph data into manageable components. Each index handles specific query patterns independently, reducing the complexity of traversal operations and improving query performance by avoiding full-table scans and multiple sequential lookups.
2Reliability
If graph data is stored using traditional relational tables, then data integrity and ACID properties are maintained, but traversal operations require multiple database lookups increasing latency
Solution Approach 1:
The patent performs preliminary actions by pre-computing and storing graph traversal paths, relationships, and connectivity information in specialized index structures. This allows the system to quickly retrieve pre-prepared data during query operations without performing multiple sequential database lookups, significantly reducing query response time while maintaining data integrity through consistent indexing operations.
3Adaptability or versatility
If relational databases are used for social networking data, then ease of use and standard SQL operations are maintained, but scalability is reduced due to inefficiencies in handling interconnected data
Solution Approach 1:
The patent introduces an intermediary layer consisting of specialized index structures that sit between the relational database storage and the query interface. This intermediary layer handles the complexity of graph traversal operations, allowing users to continue using standard SQL operations while the system internally manages the scalable storage and retrieval of interconnected data through optimized index structures.
Data Source
AI summary
This application is directed to an indexing system for graph data. In particular implementations, the indexing system uses a database index infrastructure that provides for flexible search capability to data objects and associations between data objects. Particular embodiments relate to an indexing system for storing and serving information modeled as a graph that includes nodes and edges that define associations or relationships between nodes that the edges connect in the graph.