Concurrent Query Execution Plan Processing for Distributed Data
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Solution Overview
Problem
Conventional database systems face inefficiencies in pattern matching and data retrieval due to the need to manage large numbers of individual records across normalized schemas, requiring complex query execution plans and sequential processing that can slow down data access operations.
Innovation Solution
A system utilizing multiple processors to concurrently execute a query execution plan across multiple data sources, employing thread assignment and access methods such as index-based and scan-based methods to efficiently identify and retrieve data, thereby reducing processing time and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If conventional database systems use normalized schemas with large numbers of individual tables, then data redundancy is reduced, but query execution becomes slower due to sequential processing requirements
Solution Approach 1:
The patent divides the query execution process into multiple independent segments that can be processed concurrently. Each processor handles a portion of the query execution plan, allowing parallel processing of normalized schema tables while maintaining data redundancy reduction benefits
Solution Approach 2:
The system pre-compiles query execution plans that identify all required tables and access methods before actual query execution. This preliminary analysis enables optimized parallel execution paths to be established in advance, reducing the overhead of sequential processing while maintaining normalized schema benefits
2Measurement precision
If database engines build complex query execution plans to identify patterns across multiple tables, then data retrieval accuracy is improved, but processing time increases
Solution Approach 1:
The query execution plan is segmented into independent tasks that can be executed in parallel across multiple processors. Each processor handles a specific portion of the pattern matching operation, maintaining accuracy while reducing overall processing time through concurrent execution
Solution Approach 2:
The patent introduces a temporal dimension to query execution by implementing concurrent processing across multiple time steps. Instead of executing queries sequentially through all tables, the system processes multiple table accesses simultaneously in different time dimensions, reducing total processing time while maintaining pattern matching precision
3Device complexity
If single processor systems execute query execution plans sequentially, then system complexity is reduced, but data access efficiency deteriorates
Solution Approach 1:
The system segments the query execution workload across multiple processors, with each processor handling a portion of the execution plan. This segmentation enables parallel data access operations while maintaining manageable complexity through structured task distribution and coordination mechanisms
Data Source
AI summary
According to one aspect, a computer system configured to access distributed data is provided. The system comprising a memory including a plurality of data sources, a plurality of processors, and a pattern matching component executed by at least one processor of the plurality of processors and configured to execute a query execution plan using a first processor of the plurality of processors concurrently with a second processor of the plurality of processors, wherein the first processor processes a first data source of the plurality of data sources identified in the query execution plan and the second processor processes a second data source of the plurality of data sources identified in the query execution plan.