Database Merge Segregation Hash Index Processing
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Solution Overview
Problem
As databases grow in size, the time and resources required for merging tables increase significantly, necessitating more efficient database systems for quick merging processes.
Innovation Solution
A server is configured to segregate update records into two sections and apply different merging processes, using a hash merging process for one section and an index merging process for the other, reducing overall computational resources and time by generating hash tables only for specific portions of the data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional merging processes are used for large databases, then data accuracy is maintained, but merging time and computational resources increase significantly
Solution Approach 1:
The patent divides the target table into multiple sections based on date ranges (e.g., recent data vs. historical data) and applies different merging strategies to each section. This segmentation allows the system to optimize for both accuracy and speed by treating different data portions differently, thereby reducing overall merging time while maintaining data accuracy.
Solution Approach 2:
The patent applies different merging processes to different sections of the target table based on their specific characteristics. Recent data sections receive more rigorous processing to ensure accuracy, while historical data sections use faster merging methods. This local quality approach ensures that each data section receives the appropriate level of processing, balancing accuracy requirements with time constraints.
2Reliability
If traditional merging processes are used for large databases, then complete data processing is achieved, but computational resources and storage requirements increase
Solution Approach 1:
By segmenting the merging process into different sections with different processing requirements, the system reduces the computational resources needed for each individual merging operation. This allows complete data processing to be achieved through multiple smaller, more efficient operations rather than one resource-intensive operation.
Solution Approach 2:
The patent applies partial action by using different levels of merging processing for different data sections. Not all data sections require the same level of processing intensity, so the system applies appropriate processing levels to each section, reducing overall computational resource consumption while maintaining data completeness.
Data Source
AI summary
Described herein are systems, computer readable mediums, and methods for merging a source file with a target table using different merging processes. The source file may be logically segregated into new records and update records. The update records may be logically segregated into a first update record section and a second update record section. The target table may be logically segregated into a target table section. In one implementation, a server may use a hash merging process to merge the first update record section with the target table section and use an index merging process to merge the second update record section with the target table.