Database Volatility Attributes for Memory Retention

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Solution Overview

Problem

Current database management systems face inefficiencies when dealing with volatile tables, as existing techniques for optimizing query execution strategies often fail to adapt to rapid changes, leading to poor performance and increased resource utilization.

Innovation Solution

The implementation of volatility attributes to manage database tables by preferentially retaining volatile data in memory, adjusting extension sizes, and optimizing storage and indexing strategies, allowing for dynamic adaptation to table changes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If query execution strategies are optimized using traditional methods, then query performance is improved, but the system fails to adapt to rapid changes in volatile tables, leading to degraded performance over time

Engineering Contradiction:

Improvequery performanceVSAvoidadaptability to table changes

Core Design Contradiction:

ProductivityVSAdaptability or versatility

Solution Approach 1:

The patent implements dynamic query execution strategies that automatically adapt to changing table characteristics. The system continuously monitors table volatility and adjusts query plans in real-time, transitioning from static optimization to dynamic adaptation. This resolves the contradiction by making the query execution strategy flexible and responsive to rapid changes in volatile tables while maintaining high performance.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system incorporates feedback mechanisms that monitor table characteristics and query performance, using this information to continuously refine query execution strategies. The feedback loop detects changes in table volatility and triggers automatic re-optimization, ensuring the system adapts to rapid changes while maintaining optimal performance.

Inventive Principle:

Principle #23Feedback

2Speed

If more data is retained in memory, then data retrieval speed is improved, but memory resource utilization increases

Engineering Contradiction:

Improvedata retrieval speedVSAvoidmemory resource utilization

Core Design Contradiction:

SpeedVSUse of energy by moving object

Solution Approach 1:

The patent applies local quality by differentiating memory retention strategies based on table volatility characteristics. Volatile tables receive preferential memory retention while stable tables use traditional storage approaches. This selective approach improves data retrieval speed for frequently changing data without unnecessarily increasing overall memory resource utilization.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system dynamically changes memory allocation parameters based on table volatility metrics. By adjusting memory retention policies according to measured volatility parameters, the system optimizes the balance between data retrieval speed and memory resource utilization, allocating memory resources only where they provide the most benefit.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS10372669B2Preferentially retaining memory pages using a volatile database table attribute

Publication Date: 2019.08.06 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

A respective volatility attribute associated with each of one or more tables of a computerized database is used to determine circumstances under which a page of table data is paged out of memory, by preferentially retaining pages from volatile database tables in memory. Various optional additional uses of a volatility attribute to manage a database are disclosed. Preferably, database parameters are automatically monitored over time and database table volatility state is automatically determined and periodically adjusted.