Editable Table Views With Uncommitted Edit Queue Merging
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Solution Overview
Problem
Manipulating and efficiently composing database queries for data stored in cloud-based data warehouses is beyond the abilities of most users, and handling uncommitted edits to editable tables in these systems is challenging.
Innovation Solution
Implementing a table manager that redirects requests for editable tables with uncommitted edits to an edit queue, combining these edits with the current data from the cloud-based data warehouse, and presenting the updated table on the client system, thereby incorporating uncommitted edits before they are committed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system presents the latest committed version of the editable table from the cloud-based data warehouse, then data consistency and reliability are maintained, but user-perceived latency increases when uncommitted edits need to be viewed
Solution Approach 1:
The system performs preliminary actions by retrieving and caching the latest committed version of the editable table in advance. When a user requests the table, the cached version is immediately available for presentation, eliminating the need to wait for cloud-based data warehouse retrieval. This preliminary caching action resolves the contradiction by providing fast access to consistent data without requiring real-time cloud queries.
Solution Approach 2:
The system introduces an intermediary caching layer between the user and the cloud-based data warehouse. This cache acts as a mediator that stores recently accessed table versions locally, allowing the system to serve users from the cache while maintaining data consistency with the committed version in the warehouse. The intermediary cache resolves the contradiction by decoupling user access speed from cloud query latency.
2Productivity
If the system redirects requests to an edit queue and combines uncommitted edits with the editable table, then system responsiveness and collaborative utility are enhanced, but device complexity and processing overhead increase
Solution Approach 1:
The system segments the table data into two distinct components: the committed version from the cloud-based data warehouse and the uncommitted edits from the edit queue. By separating these components, the system can independently manage and process each part, combining them only when necessary to present the latest view to users. This segmentation reduces processing overhead by avoiding the need to reprocess entire tables while maintaining responsiveness.
Solution Approach 2:
The system applies partial action by selectively combining only the relevant uncommitted edits with the corresponding portions of the committed table, rather than processing or transmitting entire tables. This partial combination approach enhances responsiveness by providing updated views quickly while minimizing the processing overhead associated with handling complete table datasets.
3Loss of information
If the system retrieves and combines uncommitted edits from the edit queue with the editable table from the cloud-based data warehouse, then data freshness and collaborative utility are improved, but query composition complexity and processing time increase
Solution Approach 1:
The system creates a copy of the committed table version from the cloud-based data warehouse and applies uncommitted edits to this copy rather than modifying the original committed data. This copying approach ensures data freshness by incorporating latest edits while maintaining the integrity of the committed version in the warehouse. The complexity of query composition is reduced because the system works with local copies rather than composing complex queries against the original data source for each edit view.
Data Source
AI summary
Live editing editable tables including receiving, via a client computing system by a table manager, a request for an editable table stored on a cloud-based data warehouse; determining, by the table manager, that an uncommitted edit to the editable table exists, wherein the uncommitted edit is an edit made to the editable table that has not been committed to the cloud-based data warehouse at a time when the request was received; redirecting, by the table manager, the request for the editable table to an edit queue accessible by the table manager, wherein the edit queue comprises the uncommitted edit; servicing by the table manager, the request for the editable table by combining the uncommitted edit from the edit queue with the editable table from the cloud-based data warehouse; and presenting, by the table manager, the editable table on the client computing system.