Dynamic Index Management for Storage Resources
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Solution Overview
Problem
Existing storage systems face inefficiencies due to outdated indexes as storage resources and data evolve over time, leading to suboptimal performance.
Innovation Solution
Implement a dynamic index management system that collects current performance data and predicts optimized index configurations based on both current and predicted performance metrics, using a combination of hardware and software modules to adapt and maintain efficient index usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If static indexes are used for storage resources, then initial data retrieval is efficient, but performance degrades over time as data evolves
Solution Approach 1:
The patent implements dynamic index management where indexes are automatically updated based on changing data characteristics and workload patterns. The system monitors data evolution and adjusts index configurations in real-time, transforming the static index structure into a dynamic one that adapts to current storage conditions, thereby maintaining index effectiveness without manual intervention.
Solution Approach 2:
The system employs feedback mechanisms by continuously monitoring data changes, query patterns, and index performance metrics. This feedback loop enables the automatic detection of when indexes become outdated and triggers reindexing operations, ensuring that index structures remain optimized for current data states while minimizing unnecessary updates.
2Productivity
If indexes are frequently updated to maintain optimality, then data retrieval efficiency is maintained, but system overhead and complexity increase
Solution Approach 1:
The patent implements self-service index management where the storage system automatically monitors its own data characteristics and workload patterns, then autonomously determines when and how to update indexes. This eliminates the need for external manual intervention or complex external management systems, reducing overall system complexity while maintaining optimal retrieval efficiency through automated adaptation.
Solution Approach 2:
The system dynamically adjusts index parameters such as index type, selectivity thresholds, and update frequency based on monitored data characteristics and performance metrics. By changing these parameters adaptively rather than using fixed configurations, the system maintains high retrieval efficiency while avoiding the complexity of manual parameter tuning and management.
Data Source
AI summary
Methods that provide dynamic index management for a set of computing storage resources are disclosed herein. One method includes collecting, by a processor, a set of current performance data for a set of storage resources storing data and implementing a set of indexes for the data stored on the set of storage resources based on an optimized performance predicted for the set of storage resources based on the collected set of current performance data and a set of predicted performance data that identifies the set of indexes. Also disclosed herein are apparatus, systems, and computer program products that can include, perform, and/or implement the methods for providing dynamic index management for a set of computing storage resources.