Graph Server Querying for Social Network Path Analysis
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Solution Overview
Problem
Online social networking sites face significant challenges in managing increasing load demands due to rapid growth and the complexity of member relationships, leading to inefficiencies in processing speeds.
Innovation Solution
Implementing graph servers to handle CPU-intensive computational tasks related to member relationships, storing a social network map in dedicated memory, and processing queries to reduce database lookups and enhance processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the social networking site adds more servers and switches to handle increasing demand, then the system capacity increases, but the device complexity and cost increase
Solution Approach 1:
The patent segments the social networking system into two distinct server types: application servers for database management and graph servers for CPU-intensive computational tasks. This segmentation allows each server type to be optimized for its specific function, improving overall system capacity without proportionally increasing complexity, as the workload is divided into manageable, specialized components
2Ease of operation
If the system stores relationship information in a database, then data management is simplified, but the processing speed decreases due to frequent database lookups
Solution Approach 1:
The patent implements preliminary action by pre-computing and storing relationship data in graph data structures on graph servers before queries are executed. This allows the system to maintain simplified database management while dramatically improving processing speed, as the graph servers can directly query pre-processed relationship data without frequent database lookups
Solution Approach 2:
The patent introduces graph servers as an intermediary layer between the application servers and the database. These graph servers maintain graph data structures that mediate between the stored relationship information and query processing, enabling fast relationship queries without direct database access for each operation
3Reliability
If the system tracks multiple relationships per member, then the social network map becomes more comprehensive, but the load on the system increases dramatically
Solution Approach 1:
The patent segments the computational load by dedicating specific graph servers to handle relationship tracking and analysis. This allows the system to maintain a comprehensive social network map with multiple relationships per member while distributing the processing load across specialized servers, preventing any single server from becoming overwhelmed
Data Source
AI summary
An online social network is managed using one server for database management tasks and another server, preferably in a distributed configuration, for CPU-intensive computational tasks, such as finding a shortest path between two members or a degree of separation between two members. The additional server has a memory device containing relationship information between members of the online social network and carries out the CPU-intensive computational tasks using this memory device. With this configuration, the number of database lookups is decreased and processing speed is thereby increased.