Query Translation Layer for Unified Complex Object Search
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Solution Overview
Problem
Existing content management systems face challenges in efficiently searching complex objects that comprise multiple types of objects and their relations, as different types of objects require specific searching methods, making it difficult to perform unified searches across various object types.
Innovation Solution
The system translates abstract queries into concrete query languages suitable for different types of objects by creating mappings between the object model and relational database tables and indexer schemas, allowing for transparent execution of queries across multiple types of objects using full text index searching and relational database searching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If different searching methods are used for different types of objects, then search accuracy for each object type is improved, but system complexity increases and unified searching becomes difficult
Solution Approach 1:
The patent implements a universal query translation layer that can handle multiple object types (emails, attachments, comments, calendar events, etc.) through a single unified interface. The system translates high-level queries into type-specific search operations automatically, allowing one search mechanism to serve multiple functions across diverse object types while maintaining search accuracy for each type.
Solution Approach 2:
The patent introduces a query translation component as an intermediary between the user and the diverse object storage systems. This translator converts unified queries into appropriate query languages for different object types (full-text search for emails, metadata search for attachments, relational database queries for structured data), thereby managing system complexity while preserving search accuracy for each object type.
2Productivity
If type-specific search methods are implemented for each object type, then search effectiveness for that type is improved, but ease of operation decreases due to multiple search interfaces
Solution Approach 1:
The system provides a single unified search interface that can search across multiple object types simultaneously. The query translation layer handles the complexity of different search methods internally, allowing users to perform effective searches on emails, attachments, comments, and other objects through one consistent interface rather than multiple type-specific interfaces.
Solution Approach 2:
The patent segments the search system into two distinct layers: a simplified user-facing query interface and a backend translation execution layer. This segmentation allows users to interact with a simple unified interface while the complex type-specific search operations are handled automatically in the background through query translation and execution.
3Reliability
If complex query translation is performed to search across multiple object types, then search completeness is improved, but processing time increases
Solution Approach 1:
The patent implements preliminary indexing and metadata extraction for different object types during the object creation and storage phase. Full-text indexes are built for emails and attachments in advance, and metadata is pre-processed for structured objects. When a unified query is executed, the system leverages these pre-computed indexes and metadata rather than performing complete analysis at query time, thereby maintaining search completeness while reducing processing time.
Data Source
AI summary
Searching stored content is disclosed. A first mapping is created from an object to one or more stored relational database tables. A second mapping is created from the object to an indexer schema. One or both of the following is done: 1) using the first mapping to translate a search request expressed in an abstract query language to a first query language associated with the relational database; and 2) using the second mapping to translate the search request to a second query language associated with the indexer schema.