Issue Rank Rebalancing via Locking and Congestion Detection
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Solution Overview
Problem
Issue tracking systems face challenges in maintaining accurate issue ranking in clustered architectures due to concurrent modifications by multiple users, leading to corruption of rank orders and congestion in the rank address space, which affects the ability to reorder issues effectively.
Innovation Solution
Implementing a lock mechanism to prevent rank operations from interfering with each other, along with a balancing process that uses a balancing component and normal component in issue rank values to redistribute issues and alleviate congestion, ensuring that the order of issues remains unchanged during rebalancing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a clustered architecture is used to increase capacity for concurrent users, then system capacity and concurrency are improved, but issue rank corruption and ordering errors occur due to multiple concurrent modifications
Solution Approach 1:
The system performs preliminary actions by checking for congestion in the rank address space before allowing rank operations to proceed. The congestion detection mechanism proactively identifies potential conflicts and prevents rank operations that would cause ordering errors, thereby maintaining reliability while allowing clustered architecture to provide high capacity.
2Productivity
If rank operations are allowed to proceed without locks to maintain performance, then system performance is improved, but rank order corruption occurs due to concurrent modifications
Solution Approach 1:
Instead of locking the entire data structure, the system applies locks only to specific issues that are congested or undergoing rank operations. This localized locking approach maintains high system performance by allowing unrelated operations to proceed concurrently while ensuring rank order integrity for the specific issues being modified.
3Reliability
If the entire data structure is locked to prevent rank corruption, then rank order integrity is maintained, but system performance and concurrency are significantly reduced
Solution Approach 1:
The system segments the data structure into individual issue records, each with its own lock. This allows concurrent rank operations on different issues to proceed simultaneously without interfering with each other, maintaining both rank order integrity and high system performance through fine-grained locking.
4Measurement precision
If rank operations are performed frequently to maintain accurate issue ordering, then issue ranking accuracy is improved, but rank address space congestion occurs
Solution Approach 1:
The system performs continuous congestion detection and automatic rebalancing of the rank address space. By continuously monitoring and redistributing rank values to eliminate congestion, the system maintains accurate issue ranking without requiring excessive rank operations, thus preventing address space congestion while preserving ranking precision.
Data Source
AI summary
Described herein is a computer implemented method for maintaining a plurality of issues, each issue having an associated rank value, the rank values of the plurality of issues defining an order of the plurality of issues. The method comprises receiving a rank operation request to change the rank of a subject issue; determining relevant issues to the rank operation request; and attempting to acquire locks on each of the relevant issues. In response to successfully acquiring locks on each of the relevant issues a new rank value for the subject issue is calculated and saved.