Layered Database OS Architecture for Parallel Query Processing
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Solution Overview
Problem
Current database systems face limitations in processing speed due to hardware constraints, data storage methods, and restricted co-processing options, particularly when multiple operating systems share resources, leading to potential deadlocks and reduced performance.
Innovation Solution
A parallelized database system architecture that includes a parallelized data input sub-system, data store and process sub-system, query and response sub-system, administrative sub-system, and configuration sub-system, utilizing multiple computing devices and nodes with independent processing core resources to handle queries and data storage efficiently, optimizing query plans, and managing resources to prevent deadlocks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple operating systems share computer resources, then resource utilization is improved, but system reliability deteriorates due to potential deadlocks
Solution Approach 1:
The patent segments the operating system into multiple independent layers (kernel layer, system service layer, application layer) that can operate independently. Each layer handles specific functions, allowing the system to maintain multiple operating system instances without mutual interference, thus preventing deadlocks while utilizing resources efficiently.
Solution Approach 2:
The patent introduces a virtual machine or container as an intermediary layer between multiple operating systems and the hardware resources. This intermediary manages resource allocation and isolation, allowing multiple OS instances to coexist without conflicting for resources, thereby maintaining system reliability while improving resource utilization.
2Device complexity
If database processing is centralized, then system complexity is reduced, but processing speed deteriorates due to hardware limitations
Solution Approach 1:
The patent segments the database system into multiple independent nodes distributed across different computing devices. Each node processes queries independently, parallelizing the processing workload. This distributed architecture increases processing speed while managing complexity through standardized node interfaces and coordination protocols.
Solution Approach 2:
The patent transitions from a single-dimensional centralized processing model to a multi-dimensional distributed architecture. Queries are processed across multiple dimensions (different nodes, different layers), enabling parallel execution and significantly improving processing speed without proportionally increasing system complexity through hierarchical management.
3Device complexity
If data is stored in traditional storage methods, then storage simplicity is maintained, but query execution speed deteriorates
Solution Approach 1:
The patent segments data storage into multiple distributed storage nodes across the network. Each node stores portions of the database, allowing parallel read operations during query execution. This segmented storage approach maintains relative simplicity through standardized storage interfaces while dramatically improving query execution speed through concurrent data retrieval from multiple nodes.
Data Source
AI summary
A computing device comprises a plurality of nodes and a plurality of operating system layers. The plurality of operating system layers includes a local database operating system and a sub-system database operating system. The plurality of nodes utilize the local database operating system to execute at least one database operation independently of other ones of the plurality of nodes. The computing device utilizes the sub-system database operating system in conjunction with other ones of a plurality of computing devices of at least one sub-system to facilitate execution of at least one sub-system operation of the at least one sub-system.