In-Memory Data Segmentation for Database Processing Bottlenecks
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Solution Overview
Problem
Current database systems face performance bottlenecks due to inefficiencies in storage I/O, CPU, and memory interactions, particularly in handling large data sets, which are exacerbated by the use of general-purpose CPUs that are not optimized for database applications and rely on paging systems that reduce performance.
Innovation Solution
Implementing an in-memory processing system that preloads data into memory to ensure it is available for processing without using a paging system, allowing for pipelined data processing by storing and processing data portions sequentially and dynamically managing memory to maintain high performance even with data larger than the memory size.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data is stored in memory for in-memory processing, then processing speed is improved, but memory capacity is limited and cannot handle data larger than available memory
Solution Approach 1:
The patent segments data into multiple portions and divides memory into multiple channels (first memory channel, second memory channel, etc.). Each memory channel stores a specific portion of the data, allowing the system to handle data larger than single memory capacity while maintaining in-memory processing speed through parallel access to segmented data portions.
Solution Approach 2:
The patent introduces a new dimension by implementing multiple memory channels (first memory channel, second memory channel, third memory channel) instead of relying on a single memory space. This multi-channel architecture enables the system to expand data capacity beyond the limitations of individual memory modules while preserving fast in-memory access characteristics.
2Quantity of substance
If a paging system is used to manage memory, then data can be swapped between memory and disk, but performance is reduced due to paging overhead and latency
Solution Approach 1:
The patent extracts and eliminates the paging system from the architecture entirely. Instead of using traditional paging mechanisms that require data swapping between disk and memory with associated overhead, the system directly loads required data portions into multiple memory channels and processes them in-memory, removing the time-consuming paging layer while maintaining the ability to handle large datasets.
Solution Approach 2:
The patent implements preliminary data loading where data is pre-loaded into multiple memory channels before processing begins. This preliminary action ensures that all required data portions are already resident in memory when processing starts, eliminating the need for runtime paging operations and their associated latency.
3Adaptability or versatility
If general-purpose CPUs are used for database processing, then system versatility is improved, but performance is reduced due to lack of optimization for database operations
Solution Approach 1:
The patent maintains system versatility by using general-purpose processors while implementing a multi-functional memory architecture with multiple channels that can handle various database operations. The universal processor works with the specialized multi-channel memory system to achieve both versatility and optimized database processing performance through the memory architecture itself.
Data Source
AI summary
Data can be stored in a memory for an in-memory processing system such the data is available for processing as soon as it is needed to be processed. A first portion and a second portion of the data can be stored in the memory of the in-memory processing system for processing by the in-memory processing system, such that the second portion of the data is stored in the memory before the in-memory processing system completes the processing of the first portion of the data, thereby allowing the in-memory processing system to process the second portion of the data when the processing system is able to process the second portion of the data.