Snapshot Object Translation Across Data Models
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Solution Overview
Problem
Computer systems face challenges in processing data across different data models, where data is collected in one model but presented in another, requiring translation and mapping to provide a coherent view to users, which is inefficient and resource-intensive.
Innovation Solution
A method involving a business logic provider that receives requests, constructs snapshot objects by querying databases with different data models, and updates objects in response to changes, using database join clauses and foreign keys to combine data, facilitating data sharing and access across multiple hosts and storage devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If data is collected in one data model and translated to another data model for presentation, then users can access data in a familiar format, but the translation and mapping process increases computational overhead and processing time
Solution Approach 1:
The system performs data model translation and mapping operations in advance, before the actual data access request is processed. By pre-translating data from the first data model to the second data model and caching the results, the system eliminates the need for time-consuming translation operations at the moment of data access, thus reducing processing time while maintaining ease of operation
Solution Approach 2:
The patent introduces an intermediary layer (the second data model) that sits between the raw data collection system (first data model) and the user access interface. This intermediary data model acts as a mediator that pre-processes and structures data in a way that is optimized for user access, eliminating the need for real-time translation operations and reducing processing delays
2Adaptability or versatility
If multiple providers construct objects by querying databases with different data models, then data can be shared across multiple hosts and storage devices, but the system complexity increases due to multiple data models and translation requirements
Solution Approach 1:
The patent creates a universal second data model that can represent and describe objects from multiple different first data models. This universal data model serves multiple functions: it can represent snapshots, storage devices, and other objects regardless of their source data model, enabling data sharing across multiple hosts and storage devices while providing a consistent interface that reduces system complexity
Solution Approach 2:
The system changes the parameters and structure of data when translating from the first data model to the second data model. By transforming data into a standardized format with consistent parameters and relationships, the system enables versatile data sharing across different providers and hosts while reducing the complexity of managing multiple disparate data models
Data Source
AI summary
Described are techniques for processing a request received at a business logic provider from a client. The request includes a snapshot identifier uniquely identifying a snapshot having a snapshot object in a first data model and requests properties of a storage device providing a data source for the snapshot identified by the snapshot identifier. The snapshot object is requested from, and returned by, a snapshot provider. The business logic provider requests, from a storage device provider using a first property of the snapshot object, a storage device object corresponding to the storage device identified by the first property. The storage device provider returns the storage device object to the business logic provider. The storage device object is then returned to the client.