Backup Job Management via Parallel Execution Prediction
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Solution Overview
Problem
Traditional methods for predicting the time required for data backup operations are inefficient, as they rely on historical data traversal, which becomes time-consuming as data size grows, making it unacceptable for timely backup operations.
Innovation Solution
A method for job management that involves obtaining an execution plan for backup jobs, determining which jobs to execute in parallel, calculating a predicted backup speed, and estimating the time required for a target backup job based on the predicted speed and data size, allowing for more accurate and efficient prediction of backup times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional historical data traversal methods are used for prediction, then prediction accuracy can be maintained, but prediction time becomes excessively long as data size grows
Solution Approach 1:
The patent segments the prediction process by dividing backup jobs into different priority levels (first priority jobs that must be completed before target job, second priority jobs that can run in parallel). This segmentation allows the system to predict time by analyzing only the critical path jobs rather than traversing all historical data, thus reducing prediction time while maintaining accuracy.
Solution Approach 2:
The patent performs preliminary analysis of the execution plan to identify which jobs must be completed before the target backup job can start. By determining the critical path and parallel execution groups in advance, the system avoids time-consuming traversal of all historical backup data during the prediction phase.
2Productivity
If backup jobs are executed in parallel to improve efficiency, then productivity increases, but job scheduling complexity increases
Solution Approach 1:
The patent segments backup jobs into priority groups based on their execution dependencies. First priority jobs are identified as those that must complete before the target job, while other jobs form parallel execution groups. This segmentation simplifies scheduling complexity by providing clear execution rules for each group while maintaining high productivity through parallel execution of independent jobs.
3Speed
If more backup jobs are executed in parallel, then backup speed increases, but resource consumption increases
Solution Approach 1:
The patent implements dynamic parallel execution by determining which jobs can run in parallel based on real-time resource availability and job dependencies. The system dynamically adjusts the number of parallel jobs rather than running all jobs simultaneously, thus increasing backup speed when resources are available while conserving resources when capacity is limited.
Data Source
AI summary
Embodiments of the present disclosure relate to method, device and computer program product for job management. The method comprises: obtaining an execution plan associated with a plurality of backup jobs including a target backup job, the execution plan at least indicating a size of backup data and start times of the plurality of backup jobs; determining, based on the execution plan, a first set of backup jobs to be executed in parallel at a start time of the target backup job; determining a predicted backup speed of executing the first set of backup jobs in parallel at the start time of the target backup job; and determining, at least based on the predicted backup speed and the size of the backup data of the target backup job, time required for executing the target backup job. Accordingly, the time required for executing the backup jobs can be more accurately predicted.