Application Server Data Compression for Database Transfer Bottlenecks
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Solution Overview
Problem
Current database systems face performance limitations due to large volume data transfer delays, with no unified methodology to optimize database function calls, leading to inefficient data exchange between application and data servers.
Innovation Solution
An encode-decode framework is implemented where application data is compressed at the application server and decoded at the data server, and vice versa, to reduce data volume and enhance transfer speeds, allowing for improved overall system performance without significant resource impairment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is transferred in large volumes between application server and data server, then complete data exchange is achieved, but data transfer time increases significantly
Solution Approach 1:
The patent extracts only the necessary data elements for processing by creating temporary database tables that store only the required data subsets. This extraction approach reduces the volume of data that needs to be transferred between servers while ensuring that the application receives exactly what it needs for processing, thereby reducing transfer time without compromising data completeness.
Solution Approach 2:
The patent segments large data transfers into smaller, manageable units by using temporary database tables to hold intermediate data. This segmentation allows data to be transferred in controlled portions rather than as a single large block, improving transfer efficiency and enabling parallel processing operations.
2Adaptability or versatility
If different developers use different approaches to call database functions, then flexibility in implementation is achieved, but system reliability decreases due to connection reset issues
Solution Approach 1:
The patent creates a universal framework using temporary database tables that can accommodate different database types and calling approaches. This multi-functional approach allows various developers to call database functions using their preferred methods while the underlying temporary table mechanism ensures consistent, reliable data storage and retrieval, preventing connection reset issues.
Solution Approach 2:
The temporary database table acts as an intermediary layer between the application server and data server. This mediator ensures that data persists reliably even if connections are reset, while still allowing flexible calling approaches from different developers. The intermediate table buffers data transfers and ensures data availability independent of connection stability.
3Speed
If data server is optimized to accelerate SELECT queries, then query processing speed is improved, but overall system performance is still limited by data transfer time
Solution Approach 1:
The patent extracts only the essential data needed for processing into temporary tables, reducing the volume of data that must be transferred. This extraction complements query optimization by ensuring that even with fast query processing, the actual data transfer time is minimized because less data needs to move between servers.
Solution Approach 2:
The patent performs preliminary data preparation by creating temporary database tables with the required data before the main processing occurs. This preliminary action reduces the data transfer burden during critical processing phases, allowing query optimizations to have their full effect without being bottlenecked by large data transfers.
Data Source
AI summary
Described herein is a technology to facilitate large volume data transfer. In one implementation, an application server determines if an application is invoking a procedure in a data server. If the application is determined to be invoking the procedure, the application data is encoded to compress application data volume. The encoded application data is then transferred from the application server to a data server. At the data server, the application data is decoded for processing by the data server.