Dynamic Database Object Description Placement for Faster Access
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Solution Overview
Problem
Existing database management systems face performance issues due to high-cost I/O operations when accessing database object descriptions stored in disk, as memory is often limited and accessing these descriptions from disk results in lower performance.
Innovation Solution
A computer-implemented method dynamically manages the storage location of database object descriptions based on access frequency, execution order, and space availability, loading them into higher performance storage for upcoming workload groups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If database object descriptions are stored in disk, then storage capacity is sufficient, but access performance is low due to high-cost I/O operations
Solution Approach 1:
The patent segments database object descriptions into two storage locations: frequently accessed descriptions are stored in memory while less frequently accessed descriptions remain in disk storage. This segmentation allows the system to optimize for both speed (frequently accessed items in memory) and storage capacity (less frequently accessed items in disk), resolving the technical contradiction between access performance and storage capacity.
Solution Approach 2:
The patent applies local quality by assigning different storage media to different database object descriptions based on their access patterns. Specifically, frequently accessed database object descriptions are placed in high-performance memory storage, while less frequently accessed descriptions remain in disk storage. This localized optimization of storage quality for specific data items resolves the contradiction between overall access performance and total storage capacity.
2Speed
If database object descriptions are stored in memory, then access performance is improved, but memory space is limited
Solution Approach 1:
The patent uses preliminary action by proactively loading database object descriptions into memory before they are actually needed, based on predicted access patterns and upcoming workload groups. The system identifies database objects that are likely to be accessed and pre-loads their descriptions into memory, thereby improving access performance without permanently occupying memory space. This resolves the contradiction between access performance and memory space constraints.
Solution Approach 2:
The patent implements dynamics by dynamically adjusting which database object descriptions are stored in memory based on changing access patterns and workload characteristics. The system continuously monitors access frequency and workload group requirements, dynamically loading and unloading database object descriptions from memory to optimize for current performance needs while managing limited memory space. This dynamic adaptation resolves the contradiction between access performance and memory space availability.
3Productivity
If all database object descriptions are loaded into memory, then access performance is maximized, but system complexity increases for managing limited memory space
Solution Approach 1:
The patent applies partial action by loading only a subset of database object descriptions into memory - specifically those that are frequently accessed or predicted to be accessed by upcoming workload groups - rather than loading all descriptions. This partial loading approach maintains high database performance for the most critical operations while avoiding the excessive complexity of managing memory space for all possible database objects. The system selectively optimizes for the most important cases, resolving the contradiction between productivity and device complexity.
Data Source
AI summary
A computer implemented method manages a location of database object descriptions in a storage, the computer implemented method. A number of processor units identifies a set of workload groups that are coming up for execution. The number of processor units loads the database object descriptions for the set of workload groups into a highest performance storage in a storage system. The number of processor units manages the location of the database object descriptions in the storage system based on access to database objects by set of workload groups.