Batched Query Processing with Psi Operators for Resource Contention
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Solution Overview
Problem
Conventional database management systems (DBMSs) face challenges in optimizing and efficiently processing multiple queries concurrently due to a lack of theoretical foundation for query optimization, leading to resource contention and suboptimal performance under high query loads.
Innovation Solution
A system model, referred to as PsiDB, generates a single algebraic expression based on equivalence rules to combine multiple database queries into a global relation, utilizing ψ-operators to optimize query processing and reduce resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple queries are processed independently in conventional DBMS, then each query can be optimized separately, but resource contention increases and overall performance deteriorates under high query loads
Solution Approach 1:
The patent merges multiple independent queries into a single batched query processing operation. By combining multiple queries that access the same database relations into one unified processing task, the system eliminates redundant operations and reduces resource contention. The batched approach allows the database engine to process all queries in a single pass through the data, significantly improving throughput while reducing overall resource consumption compared to processing each query independently.
2Productivity
If batched query processing is implemented, then resource consumption is reduced and performance improves, but the system complexity increases due to need for query optimization techniques
Solution Approach 1:
The patent applies preliminary action by performing query optimization and transformation before the actual query execution. The system pre-processes multiple queries to identify common subexpressions, relations, and optimization opportunities, then combines them into a unified batched processing plan. This preliminary optimization phase, which includes generating equivalent algebraic expressions and identifying shared computational paths, reduces the complexity during actual execution and enables significant performance improvements.
3Loss of time
If conventional one-query-at-a-time processing is used, then query optimization is simpler, but processing time increases significantly under high query loads
Solution Approach 1:
The patent uses copying by creating equivalent algebraic expressions that represent the same query semantics in different forms. By generating multiple equivalent representations of queries and identifying common subexpressions across these copies, the system can share computational work across multiple queries. This approach allows the batched processing to recognize and exploit redundancies that would be invisible in the original query formulations, significantly reducing processing time while managing complexity through systematic transformation rules.
Data Source
AI summary
Disclosed are various embodiments for batched query processing and optimization in database management systems. A single algebraic expression is generated based at least in part on applying equivalence rules to algebraic expressions for a plurality of database queries of a database comprising a set of relations. The equivalence rules involve relational operators comprising Psi (ψ) operators. The database can be queried using a single database query to create a result that is equivalent to the plurality of database queries.