Database Workload Management via Dynamic Resource Enforcement
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Solution Overview
Problem
Existing workload management rules in database systems rely on inaccurate estimates for resource usage, leading to inefficient execution or rejection of queries, particularly for product joins, which can negatively impact system performance.
Innovation Solution
A method that calculates actual resource requirements based on populated input tables, comparing these parameters to specified maximum values to determine if a query can proceed, allowing accurate enforcement of workload management rules only after input tables are populated and before execution, thereby preventing resource-intensive product joins from degrading system performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If workload management rules are enforced prior to query execution using estimated sizes from the query optimizer, then queries can be rejected or delayed based on estimated resource usage, but the estimates can be inaccurate resulting in efficient queries being rejected or resource-intensive queries being allowed to execute
Solution Approach 1:
The patent performs preliminary population of input tables with actual data before calculating resource parameters, rather than relying solely on optimizer estimates. This preliminary action with actual data enables accurate assessment of resource requirements before query execution, resolving the contradiction between reliable rule enforcement and avoiding unnecessary query delays
Solution Approach 2:
The patent implements a feedback mechanism where actual resource usage parameters are calculated from populated input tables and compared against specified maximum values. This feedback loop provides accurate information about actual resource requirements, enabling reliable workload management decisions that avoid both rejecting efficient queries and allowing resource-intensive queries to execute
2Productivity
If workload management rules are enforced using optimizer estimates, then queries can be controlled before execution, but the rules may not properly identify resource-intensive queries leading to system performance degradation
Solution Approach 1:
The patent performs preliminary population of input tables with actual data before calculating resource parameters. This preliminary action replaces inaccurate optimizer estimates with actual measurements from populated tables, enabling precise identification of resource-intensive queries while maintaining system productivity through accurate workload management
Solution Approach 2:
The patent substitutes the mechanical estimation system (query optimizer estimates) with an actual measurement system (calculating parameters from populated input tables). This substitution replaces inaccurate predictive mechanics with accurate empirical measurements, resolving the contradiction between measurement precision and system productivity
3Reliability
If accurate resource parameters are calculated from populated input tables, then workload management rule enforcement accuracy is improved, but additional runtime processing is required
Solution Approach 1:
The patent performs resource parameter calculations as a preliminary action during the input table population phase, before query execution. By integrating this calculation into the existing population process rather than adding separate processing steps, the patent achieves accurate workload management enforcement with minimal additional runtime complexity
Solution Approach 2:
The patent merges the resource parameter calculation process with the input table population process. By combining these two operations into a single integrated workflow, the patent achieves accurate measurement of resource requirements without adding separate processing overhead, resolving the contradiction between reliability and device complexity
Data Source
AI summary
An improved workload management system and method for a database system. The improved workload management system evaluates certain workload management rules dynamically at key points during database query execution rather than relying on enforcement prior to query activation. In the case of product join operations, the workload management system evaluates the potential impact on system performance by the product join operation after input tables have been populated, but prior to the execution of the join operation. Delaying workload management enforcement to this point ensures that the sizes of inputs and outputs are reliably known and improves system performance impact estimates at a point early enough to prevent any serious performance degradation from an inefficient product join.