Database Workload Feedback Control for Service Level Consistency
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Solution Overview
Problem
Database management systems face challenges in managing diverse workloads with varying resource demands and execution times, particularly due to complex data types and query processing requirements, leading to difficulties in achieving consistent response times across different workload classes.
Innovation Solution
A method and system for dynamically sorting requests into workload groups with specific service level goals, assigning system resources, and monitoring execution to adjust resource allocation and prioritize requests to meet performance objectives, using a closed-loop feedback mechanism to maintain service levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the database system handles diverse workloads with varying resource demands, then the system can support more complex data types and query processing, but the consistency of response times across different workload classes deteriorates
Solution Approach 1:
The patent segments the workload into different classes (OLTP, OLAP, OLE, OLM) based on their resource demands and characteristics. Each workload class is then managed separately with dedicated resource allocation and performance targets, allowing the system to maintain response time consistency within each class while supporting overall workload diversity.
Solution Approach 2:
The patent applies local quality by assigning different service levels and resource allocation strategies to different workload classes. Each workload class receives customized management tailored to its specific needs, rather than a uniform approach, thereby maintaining consistent response times for each class while accommodating diverse workload types.
2Adaptability or versatility
If the database system increases function and expands into new application areas, then the system becomes more versatile, but the complexity of administering workloads increases
Solution Approach 1:
The patent implements self-service through automatic workload classification and resource allocation. The system automatically identifies workload types, assigns them to appropriate classes, and manages resource distribution without requiring manual intervention, thereby reducing administration complexity as the system handles diverse applications.
Solution Approach 2:
The patent employs feedback mechanisms to continuously monitor workload performance and adjust resource allocation dynamically. This closed-loop control allows the system to adapt to changing workload patterns and maintain optimal performance automatically, reducing the need for manual workload administration.
3Reliability
If the database system uses closed-loop feedback to monitor and adjust resource allocation, then the service level compliance improves, but the system complexity increases
Solution Approach 1:
The patent implements feedback by continuously monitoring workload performance metrics and comparing them against defined service level targets. The system automatically adjusts resource allocation based on this feedback, ensuring service level compliance through a systematic closed-loop control mechanism.
Solution Approach 2:
The patent applies dynamics by making resource allocation flexible and adaptive rather than static. The system dynamically adjusts resource distribution in real-time based on current workload conditions and performance feedback, allowing the feedback mechanism to respond to changing conditions without requiring overly complex predetermined rules.
Data Source
AI summary
In a method, computer program and process for administering the workload of a database system as it executes one or more requests the one or more requests are sorted into one or more workload groups. Each workload group has an associated level of service desired from the database system. The one or more requests are executed in an order intended to achieve the levels of service associated with each of the workload groups. The system resources are assigned to the one or more workload groups as necessary to provide the level of service associated with each workload group. The execution of requests is monitored on a short-term basis to detect a deviation from the level of service greater than a short-term threshold. If such a deviation is detected, the assignment of system resources to workload groups is adjusted to reduce the deviation. Monitoring is also performed on a long-term basis to detect deviations from the expected level of service greater than a long-term threshold. If such a deviation is detected, the execution of requests is adjusted to better provide the expected level of service.