Database Query Row Scheduling Across Segments for Parallel Processing
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Solution Overview
Problem
Existing database systems face limitations in processing speed due to hardware constraints, data storage methods, and limited co-processing options, which hinder efficient execution of large-scale database operations.
Innovation Solution
A database system architecture that employs parallelized data input, storage, and query processing across multiple computing devices and nodes, utilizing segment chunking and scheduling to optimize query execution based on requested row sets, enabling concurrent processing of massive data volumes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data is stored in traditional sequential methods, then storage simplicity is maintained, but processing speed decreases
Solution Approach 1:
The patent divides data into multiple segments that are distributed across different storage devices and processed in parallel. Each segment can be independently accessed and processed, enabling simultaneous read operations across multiple devices, thereby significantly improving processing speed while managing complexity through structured segmentation
2Productivity
If hardware resources are increased, then processing capability improves, but system cost and complexity increase
Solution Approach 1:
The patent combines multiple storage devices and processing units into a unified parallel processing system. By merging resources and coordinating them through a standardized interface, the system achieves higher throughput than individual components could provide alone, while the modular architecture prevents excessive complexity
3Speed
If co-processing options are restricted, then system simplicity is maintained, but execution speed is limited
Solution Approach 1:
The patent implements a universal processing interface that can handle multiple types of operations and data formats through a common architecture. This multi-functional design enables various co-processing options without requiring separate specialized systems, thereby improving execution speed while maintaining adaptability
Data Source
AI summary
A processing module of a database system is operable to determining a query for execution. A plurality of row sets are processed over a temporal period in conjunction with execution of the query based on automatically selecting a requested number of rows to be included in each row set based on row scheduling parameters, generating a scheduling request for the requested number of rows, and receiving each row set for processing in response to the scheduling request via access to one segment of a set of segments required for execution of the query. A query resultant for the query is generated based on processing of the plurality of row sets, and further based on processing of an additional plurality of rows included in the set of segments via a set of other processing modules implemented in parallel with the processing module.