Data Summarization Recovery via Exclusive Lock and Scope Management
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Solution Overview
Problem
Existing systems face challenges in efficiently recovering from failed summarization instances and managing overlapping scopes in data summarization, leading to user frustration and incomplete data presentation, particularly due to issues like source system corruption, environment problems, and resource limitations.
Innovation Solution
A method that allows a new summarization instance to wait for and process existing instances, acquire exclusive locks, and handle overlapping scopes by rolling back, resubmitting, or skipping tasks, ensuring minimal user input while recording incomplete data and errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a new summarization instance is submitted while overlapping instances are running, then the new instance can wait for completion, but the user experience deteriorates due to indefinite waiting or timeout failures
Solution Approach 1:
The system performs preliminary actions by checking for existing running instances before allowing a new summarization instance to execute. When overlapping instances are detected, the new instance waits for their completion or timeout, ensuring data consistency while managing user expectations through proper notification mechanisms.
2Device complexity
If failed summarization instances are left for external cleanup, then system complexity is reduced, but user frustration increases due to manual intervention requirements
Solution Approach 1:
The system implements self-service by enabling automatic cleanup of failed summarization instances. When a summarization instance fails, the system automatically detects the failure state and cleans up the failed instance without requiring external user intervention, thereby improving ease of operation while maintaining acceptable system complexity.
3Productivity
If multiple users concurrently run summarization on overlapping scopes, then system utilization improves, but data consistency deteriorates due to conflicts
Solution Approach 1:
The system uses feedback mechanisms to monitor the state of summarization instances and their scope overlaps. When conflicts are detected through this feedback, the system adjusts by having new instances wait for running instances to complete or timeout, thereby maintaining data consistency while still allowing high system utilization through concurrent non-conflicting operations.
Data Source
AI summary
Embodiments of the invention provide systems and methods for recovering a failed data summarization. According to one embodiment, recovering a failed instance can comprise processing existing summarization instances identified as instances for which a new data summarization instance needs to wait. Upon a completion or a timeout of each of the instances identified as instances for which the new data summarization instance needs to wait, an exclusive lock can be acquired on a table storing scope information for the plurality of data summarization instances. One or more existing data summarization instances that match the new data summarization instance or that have an overlapping scope with the new data summarization instance can be processed, remaining tasks to be performed by the new data summarization instance can be defined, the exclusive lock can be released, and the remaining tasks to be performed by the new data summarization instance can be performed.