Last Thread Lock Management for Distributed Data Systems
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Solution Overview
Problem
In distributed data systems, concurrent access to shared data by multiple processes leads to inconsistencies and data loss, particularly in multithreaded environments where managing locks is complex and prone to 'data clobbering', where updates from one process can overwrite changes made by another.
Innovation Solution
A distributed data system with a lock mechanism that grants locks to processes for portions of data, allowing only the thread that requested the lock to access and release it, with buffering for other processes' requests and automatic release by the last thread accessing the data, reducing resource consumption and minimizing data loss.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple processes concurrently access shared distributed data, then system productivity and resource utilization improve, but data consistency and integrity deteriorate due to data clobbering
Solution Approach 1:
The patent segments the lock management into process-level locks and thread-level locks. Process locks are managed by the lock mechanism to control access to portions of primary data, while thread locks are managed locally by each thread to control access to local data. This segmentation allows multiple processes to concurrently access different portions of distributed data without conflict, improving productivity while maintaining data consistency through hierarchical lock control.
2Reliability
If a lock mechanism is implemented to prevent data clobbering, then data integrity is improved, but device complexity and resource consumption worsen
Solution Approach 1:
The lock management complexity is segmented between a centralized lock mechanism and distributed thread lock managers. The lock mechanism only needs to manage process-level locks for portions of primary data, while thread-level locks are managed autonomously by each thread's lock manager. This segmentation reduces the complexity of the central lock mechanism while maintaining comprehensive data integrity protection.
Solution Approach 2:
Each thread is equipped with a lock manager that autonomously manages thread-level locks for local data access. The lock manager automatically acquires, holds, and releases locks based on thread execution state, eliminating the need for complex centralized thread lock management and reducing overall system complexity while ensuring data integrity.
3Measurement precision
If thread-level lock management is implemented, then access control precision is improved, but ease of operation worsens due to increased management overhead
Solution Approach 1:
The lock manager associated with each thread automatically performs lock management operations based on the thread's execution state. When a thread accesses local data, the lock manager automatically acquires the appropriate thread lock. When the thread completes or transitions state, the lock manager automatically releases the lock. This self-service approach provides precise access control while maintaining ease of operation by eliminating manual lock management overhead.
Data Source
AI summary
A distributed data system may include nodes hosting at least one multi-threaded process operable to access portions of distributed data. A lock mechanism may grant locks to multi-threaded processes for portions of the distributed data. Only a process holding a lock may access a portion corresponding to the lock. Threads of other processes may not access the portion. A process may include one or more threads that may acquire a locks for the distributed data portion on behalf of the process. In one embodiment, the lock mechanism may allow any thread of a process release a lock held by the process. In embodiments, the last thread to access the distributed data portion corresponding to the lock may release the lock in response to no more threads of the process require access to the distributed data portion and/or in response to a request to release the lock.