Data-Freshness Query Scheduling for Responsive Information Retrieval
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing query scheduling methods fail to differentiate between queries with differing response time requirements, leading to time-sensitive queries being delayed behind less time-sensitive ones, and cannot efficiently handle queries of varying execution times.
Innovation Solution
A method and system for optimal query scheduling that considers data freshness requirements by identifying specific fields in a query, determining data volatility, and rescheduling queries to maintain data freshness while utilizing underutilized system resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If queries are executed in first-come-first-serve order, then system simplicity is maintained, but time-sensitive queries are delayed behind less time-sensitive ones
Solution Approach 1:
The patent implements dynamic query scheduling by continuously monitoring data freshness requirements and adjusting query execution priorities in real-time. The system evaluates the age of data returned by queries and dynamically repositions queries in the execution queue based on their freshness requirements, transforming a static first-come-first-serve approach into a dynamic system that adapts to changing data freshness needs.
2Loss of time
If fixed priority scheduling is used, then time-sensitive queries are prioritized, but heavy queries with long execution times cannot be differentiated from light queries
Solution Approach 1:
The patent introduces data freshness requirements as a new scheduling parameter that fundamentally changes how queries are prioritized. Instead of using fixed priorities or execution time estimates, the system uses the freshness parameter to dynamically determine query execution order. This parameter change enables the system to differentiate between queries based on their actual data freshness needs rather than predetermined priorities or execution time predictions.
3Productivity
If queries are rescheduled to utilize underutilized system resources, then resource utilization is optimized, but data freshness requirements may be violated
Solution Approach 1:
The patent implements a feedback mechanism that continuously monitors the age of data returned by queries and compares it against the query's freshness requirements. This feedback loop enables the system to verify whether rescheduled queries still meet their freshness constraints, allowing the system to safely utilize underutilized resources while maintaining reliability guarantees for data freshness.
Data Source
Figure 1
Figure 2~3
AI summary
A method for optimal query scheduling includes receiving at an information retrieval data processing system (200), a request (110) to accelerate query execution of a specified query (120) to a time (130) prior to a scheduled time (190). The method includes identifying a specific field (140) corresponding to data in a database (250) in the query and a freshness of data requirement (160) for the specific field retrieved along with a frequency of change (150) the data corresponding to the specific field. The method includes determining if execution of the specific query at the time prior to the scheduled time instead of the scheduled time violates the freshness of the data requirement based upon the frequency of change of the data corresponding of the specific field. When execution does not violate the freshness, the method includes scheduling the specific query for execution at the time prior to the scheduled time.