Database Table Access with Record-Count API Selection
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Solution Overview
Problem
Existing systems face challenges in optimizing system performance and managing API usage costs while accommodating usage restrictions for accessing data from databases, particularly in systems like Salesforce, where different API calls have varying efficiencies and quotas.
Innovation Solution
A method is implemented to identify subsets of database tables based on record counts and assign different API calls (e.g., REST and Bulk API) dynamically to optimize performance and adhere to usage limits, generating backup files like CSV files and managing them efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If different API calls are used to access database tables, then access performance and efficiency vary, but API usage quotas and costs increase
Solution Approach 1:
The patent segments database tables into different categories based on their record counts and assigns different API call types to each segment. Tables with fewer records use REST API calls while tables with more records use Bulk API calls, optimizing both performance and quota utilization.
Solution Approach 2:
The system dynamically changes the API call parameter selection based on table properties (record count thresholds). By adjusting which API type is used for different table segments, the system optimizes performance while managing quota consumption efficiently.
2Ease of operation
If API calls are made without considering table record counts, then simplicity is maintained, but system performance and cost optimization are compromised
Solution Approach 1:
The system performs preliminary classification of database tables into segments based on record counts before API calls are made. This pre-processing step automatically determines the optimal API type for each table, eliminating the need for manual selection while ensuring optimal performance.
Solution Approach 2:
The system automatically selects the appropriate API call type based on table properties without requiring manual intervention. The classification and selection process is self-executing, maintaining ease of operation while achieving optimization.
3Device complexity
If all tables are accessed using the same API call type, then implementation complexity is reduced, but API quota efficiency and cost management deteriorate
Solution Approach 1:
The patent divides tables into segments based on record count thresholds and applies different API call types to each segment. This segmentation enables differentiated API usage strategies that optimize quota efficiency while managing implementation complexity through automated classification.
Data Source
AI summary
Methods, storage systems and computer program products implement embodiments of the present invention for data access that include identifying a set of tables in a database to be accessed by an application, and identifying first and second application programming interface (API) calls having different, respective access properties for accessing records in the tables via an API. Respective numbers of the records in the tables are counted by a processor, and the set of tables are partitioned into first and second subsets responsively to the respective numbers. The records in the first subset of the tables are accessed by having the application convey the first API call to the API, and the records in the second subset of the tables are accessed by having the application convey the second API call to the API.