Query Governor Memory Compression Runtime Control
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Solution Overview
Problem
As databases grow in size and workload, certain queries can consume excessive system resources, leading to prolonged execution times that may monopolize resources and impact other queries and tasks, necessitating control over query runtime.
Innovation Solution
A method that calculates an estimated execution time for queries based on historical data and determines a maximum allowable runtime, adjusting memory compression accordingly to optimize query execution and ensure timely completion without resource monopolization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If memory compression is increased to reduce memory usage, then memory efficiency improves, but query execution time increases
Solution Approach 1:
The patent applies dynamics by making the memory compression level adjustable and adaptive rather than fixed. The query governor dynamically selects different compression levels based on the specific query characteristics, data types, and system state, allowing the system to optimize between memory efficiency and execution speed for each query individually.
Solution Approach 2:
The patent changes the compression parameter to resolve the contradiction. By varying the compression level as a controllable parameter, the system can tune the balance between memory usage and execution time. The query governor evaluates query features and selects appropriate compression parameters to achieve optimal performance for each specific case.
2Loss of time
If query execution time is reduced to improve responsiveness, then user satisfaction improves, but memory usage increases
Solution Approach 1:
The system dynamically adjusts compression levels based on query requirements. For time-sensitive queries, the query governor selects lower compression levels to reduce execution time, while for less time-critical queries, higher compression levels are applied to optimize memory usage.
Solution Approach 2:
The compression parameter is adjusted based on query characteristics and system state. The query governor modifies this parameter to achieve the desired balance between execution speed and memory efficiency for each specific query scenario.
3Ease of operation
If no runtime control is applied to queries, then query processing simplicity is maintained, but system resource monopolization occurs
Solution Approach 1:
The query governor operates autonomously to evaluate incoming queries, determine appropriate compression levels, and enforce runtime limits without requiring manual intervention. The system self-manages resource allocation and query scheduling, preventing monopolization while maintaining operational simplicity for users.
Solution Approach 2:
The system implements feedback mechanisms where the query governor monitors query execution progress and system resource state, adjusting compression levels and runtime limits dynamically based on observed performance and resource availability to prevent resource monopolization.
Data Source
AI summary
Techniques for managing query execution using memory compression based on maximum allowable runtimes. Embodiments may receive a query from a requesting entity and calculate an estimated execution time for executing the query. Embodiments may further determine a maximum allowable runtime for the query. An amount of memory compression for use in processing the query may then be adjusted, based on the estimated execution time and the maximum allowable runtime. The query may then be executed using the adjusted memory compression rate to produce a set of query results, which may then be returned to the requesting entity.