Object Search Machine Persistence Query Conversion
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Solution Overview
Problem
Conventional data storage systems require users to manually reenter lengthy and cumbersome CIM Query Language (CQL) search requests for object searches, making the process time-consuming, especially for repeated or similar searches.
Innovation Solution
An object search machine saves search requests as persistence queries with each parameter stored as a separate entity, allowing for quick recall and execution of similar searches by converting the parameters into a protocol query format compatible with the data storage system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually enter CQL search requests for object searches, then the search can be conducted with precise criteria, but the process becomes time-consuming and cumbersome, especially for repeated searches
Solution Approach 1:
The system performs preliminary action by automatically generating and storing persistence queries based on user search criteria. When a user conducts a search, the system pre-processes the CQL query into a persistence query format and stores it for future use. This eliminates the need for users to manually re-enter identical search requests, significantly reducing time loss while maintaining search precision.
Solution Approach 2:
The system creates copies of search requests in a different format (persistence queries) that can be stored and reused. Instead of requiring users to re-enter the original CQL queries, the system copies the search intent into a stored format that can be quickly retrieved and executed, reducing manual input time while preserving the original search criteria precision.
2Productivity
If the system stores search criteria in a format with each parameter as a separate entity, then future searches can be quickly recalled and executed, but the storage and processing structure becomes more complex
Solution Approach 1:
The system applies segmentation by breaking down search criteria into individual parameter entities within persistence queries. Each parameter (such as device type, status, capacity) is stored as a separate entity, allowing the system to quickly retrieve and modify specific parameters without processing entire query strings. This segmentation increases search execution speed while managing complexity through structured parameter organization.
Solution Approach 2:
The system changes parameters by transforming CQL query formats into persistence query formats with distinct parameter structures. This parameter transformation enables more efficient storage and retrieval operations, as each parameter can be independently accessed and modified. The complexity is managed by establishing clear transformation rules between the two formats, making the system more productive without uncontrolled complexity increase.
Data Source
AI summary
The method of object searching in a data storage system includes receiving, by an object search machine, a search criteria, the search criteria including a plurality of parameters and storing, by the object search machine, the search criteria as a persistence query having a first query format. The method also includes creating, by the object search machine, a protocol query based upon the persistence query, the protocol query having a second query format, the second query format distinct from the first query format. The method additionally includes utilizing, by the object search machine, the protocol query to request at least one object associated with the protocol query from the data storage system.