Cloud Query Builder with Metadata-Driven Identifier Suggestions
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Solution Overview
Problem
Users face challenges in building queries directed to objects hosted on clouds due to the need to determine pre-defined objects, relationships, attributes, and syntax, which can be complex and error-prone.
Innovation Solution
A query builder that requests meta-data from cloud nodes, determines potential identifiers based on the meta-data and user input, and provides a user interface to select and incorporate these identifiers into the query, facilitating the construction of complete queries in Object Query Language (OQL).
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually build queries by determining pre-defined objects, relationships, attributes, and syntax, then query functionality is achieved, but the process becomes complex and error-prone
Solution Approach 1:
The patent introduces a query builder tool as an intermediary between the user and the cloud database system. This tool automatically generates OQL queries by interpreting user-friendly input parameters (such as selection criteria, date ranges, and object types) and translating them into the appropriate query syntax, thereby eliminating the need for users to manually construct complex queries while maintaining full query functionality
Solution Approach 2:
The system performs self-service by automatically retrieving metadata from the cloud database, identifying relevant objects and attributes, and constructing valid OQL syntax without requiring user expertise in the query language. The system validates queries and provides error correction, making the process error-free while preserving query capabilities
2Reliability
If users manually determine pre-defined objects, relationships, and attributes, then accurate queries can be built, but the process is time-consuming and error-prone
Solution Approach 1:
The system performs preliminary actions by pre-fetching and caching metadata from the cloud database, including information about pre-defined objects, relationships, and attributes. This metadata is prepared and validated in advance, allowing the query builder to quickly assemble accurate queries without requiring users to manually determine these elements, thereby reducing both time and errors
Solution Approach 2:
The query builder implements feedback mechanisms by validating user input against the pre-fetched metadata and providing real-time error detection and correction suggestions. This ensures query accuracy while significantly reducing the time required, as users receive immediate guidance rather than discovering errors after query execution
Data Source
AI summary
According to an aspect of the present disclosure, a query builder sends to a node in a cloud, a request for meta-data related to objects, and in response receives from the node, the meta-data specifying information related to objects exposed by the node. Upon receiving from a user a partial query and a current edit location during building of a corresponding complete query, the query builder determines, based on the received meta-data, the current edit location, and the partial query, a list of identifiers which are potential candidates for insertion at the current edit location. The query builder then displays the list of identifiers to the user, and receives a selection of an identifier from the displayed list. The query builder incorporates the selected identifier in the partial query at the current edit location to form a further developed query.