Federated Data Storage Search Segmentation
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Solution Overview
Problem
Current computer-based searching techniques in data storage systems lack efficiency in searching across multiple data storage systems, particularly in federated environments, where they fail to effectively query both physical and logical entities and their properties, leading to incomplete or inaccurate search results.
Innovation Solution
A method and apparatus for searching data storage configuration data that determines whether to perform searching based on storage provisioned for selected applications, involving first processing for physical entities and second processing for logical entities, allowing for the identification of specific objects and properties across multiple data storage systems, including physical and logical entities such as disks, storage processors, hosts, and applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If searching is performed across multiple data storage systems in a federated environment, then search coverage and completeness are improved, but search efficiency and accuracy deteriorate due to the complexity of querying both physical and logical entities
Solution Approach 1:
The search process is segmented into distinct processing paths: first processing for physical entities (disks, storage processors, power supplies) and second processing for logical entities (hosts, pools, logical storage devices, file systems, applications). This segmentation allows the system to handle different entity types systematically, improving both completeness and efficiency by avoiding redundant processing across all entity types simultaneously.
Solution Approach 2:
The management software acts as an intermediary between the user's search query and the distributed data storage systems. It receives search criteria, determines the appropriate processing path based on the criteria, and coordinates the search across relevant systems. This intermediary role enables comprehensive searching while maintaining efficiency through intelligent query routing and processing.
2Measurement precision
If the system distinguishes between physical and logical entities during searching, then search accuracy is improved, but processing complexity increases
Solution Approach 1:
Different processing qualities are applied locally to different entity types. Physical entities undergo first processing that queries physical storage configuration data, while logical entities undergo second processing that queries logical storage configuration data. This local differentiation ensures accurate search results for each entity type without requiring the system to handle all entity types with uniform complexity, thus improving accuracy while managing processing complexity through specialization.
Data Source
AI summary
Described are techniques for searching. Search criteria including parameters is received. It is determined whether to perform searching based on storage provisioned for one or more selected applications identified in the search criteria. If it is determined to perform searching based on storage provisioned for one or more selected applications, first processing is performed in accordance with the search criteria, and otherwise second processing is performed in accordance with the search criteria. Search results produced as a result of one of the first processing and the second processing are received.