ETL Data Locator Bypassing Intermediate Stages
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Solution Overview
Problem
ETL operations are time-consuming due to the need to transmit data through multiple stages, delaying data analysis and requiring a solution to directly transmit data to stages that need it.
Innovation Solution
A method where the size of column data is assessed, and if it exceeds a threshold, a data locator is created to replace the data, allowing it to be transmitted directly to stages that require it, bypassing intermediate stages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is transmitted through each successive ETL stage, then data processing completeness is ensured, but ETL operation time increases significantly
Solution Approach 1:
The patent extracts only the essential data location information (data locator) from the full column data, separating the data reference function from the data itself. This allows the data locator to traverse ETL stages quickly while the actual data remains stationary, resolving the contradiction between complete data processing and time efficiency.
Solution Approach 2:
The data locator acts as an intermediary between the stationary column data and the downstream stages that need to access it. Instead of moving large volumes of data through multiple stages, the small data locator serves as a mediator that enables stages to locate and access data on-demand, significantly reducing transmission time while maintaining data processing completeness.
2Adaptability or versatility
If data is transmitted through multiple intermediate stages, then all stages can process the data, but data analysis is delayed until all processing is complete
Solution Approach 1:
The system performs preliminary action by creating and transmitting the data locator through ETL stages in advance, before the actual data is needed. Downstream stages can prepare and request data using the locator, enabling data analysis to begin as soon as the data is ready without waiting for sequential processing through all stages.
Solution Approach 2:
The data locator serves as an intermediary that enables downstream stages to access data independently and concurrently rather than waiting for sequential data transmission. This mediator allows multiple stages to work in parallel, reducing overall processing time while maintaining the ability of all stages to process the data.
3Loss of time
If column data is saved and replaced with data locator, then data transmission time is reduced, but system complexity increases
Solution Approach 1:
The system creates a simplified copy (data locator) that references the original column data. This copy contains only the essential location information needed to access the full data, reducing transmission requirements while maintaining the ability to retrieve complete data when needed. The copying approach balances time efficiency with manageable system complexity.
Data Source
AI summary
Performing an extract, transform, and load (ETL) process. Column data is received by a stage of the ETL process. The size of the received column data is ascertained by the stage. In response to determining that the size of the column data exceeds a predefined threshold, the stage saves the column data and creates a data locator associated with the column data. The created data locator advances through successive downstream stages of the ETL process as a replacement for the column data.