Live Editable Tables with Local Edit Queues for Cloud Data Warehouses
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Solution Overview
Problem
Manipulating and editing data stored in cloud-based databases is complex and often beyond the abilities of most users, requiring efficient query composition and management that existing technologies struggle to address.
Innovation Solution
Implementing a table manager on an intermediary computing system that receives requests for editable tables, identifies uncommitted edits, redirects them to an edit queue, and services these edits locally to ensure real-time updates without direct access to the cloud-based data warehouse.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If direct access to cloud-based data warehouse is used for data manipulation, then data consistency is maintained, but system responsiveness and user-perceived latency are worsened due to remote database access delays
Solution Approach 1:
The patent introduces an intermediary computing system with a local cache that mediates between the user interface and the remote cloud-based data warehouse. The cache stores copies of editable tables locally, allowing users to interact with data immediately without waiting for remote database responses. This intermediary layer provides both fast local access (improving speed) and maintains data consistency by synchronizing with the remote warehouse (preserving reliability).
Solution Approach 2:
The system performs preliminary actions by pre-loading and caching editable table data from the cloud-based data warehouse into the local cache before users need to access it. This advance preparation ensures that data is readily available for immediate manipulation, improving system responsiveness while the subsequent synchronization mechanisms maintain data consistency with the remote warehouse.
2Loss of information
If complex database queries are used to manipulate data, then data retrieval completeness is improved, but ease of operation is worsened as most users lack query composition skills
Solution Approach 1:
The patent creates simplified local copies of editable tables from the cloud-based data warehouse. Instead of requiring users to write complex SQL queries to access complete data, the system generates local table copies that can be manipulated through simple point-and-click operations. These local copies maintain the essential data structure and relationships, enabling users to work with complete data sets without needing database query skills.
Solution Approach 2:
The system segments the complex database access task into two parts: (1) the intermediary computing system handles complex query composition and data retrieval from the cloud warehouse, and (2) users interact with simplified local table representations. This segmentation allows users to focus on data manipulation while the system handles the complexity of complete data retrieval, resolving the contradiction between information completeness and ease of operation.
3Productivity
If uncommitted edits are stored locally for real-time editing, then collaborative utility and responsiveness are improved, but device complexity increases due to edit queue management
Solution Approach 1:
The intermediary computing system acts as a mediator that manages the complexity of edit queue operations. It handles the tracking, storage, and synchronization of uncommitted edits between multiple users and the cloud-based data warehouse. This intermediary layer shields users from the underlying complexity, allowing them to collaborate efficiently with real-time editing capabilities while the system automatically manages the edit queue and synchronization protocols.
Solution Approach 2:
The system implements self-service mechanisms where the intermediary computing system automatically manages edit queue operations, conflict resolution, and synchronization with the cloud warehouse without requiring user intervention. The system autonomously handles commit operations, resolves editing conflicts, and maintains data consistency, reducing the perceived complexity for users while enabling robust collaborative editing capabilities.
Data Source
AI summary
Live editing editable tables including receiving, via a client computing system by a table manager on an intermediary computing system, a request for an editable table stored on a cloud-based data warehouse; determining, by the table manager, that the requested editable table includes an uncommitted edit, wherein the uncommitted edit is an edit made to the editable table that has not been committed to the cloud-based data warehouse; redirecting, by the table manager, the request for the editable table to an edit queue on the intermediary computing system, wherein the edit queue comprises the uncommitted edit; and servicing, by the table manager, the request for the editable table using the edit queue on the intermediary computing system.