Database Query Processing with Shared IO Pipelines for CNF Predicates
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Solution Overview
Problem
Existing database systems face limitations in processing speed due to hardware constraints, data storage methods, and restricted co-processing options, leading to inefficiencies in query execution.
Innovation Solution
Implementing a database system that utilizes a disjunction of conjunctive normal form (CNF) predicates to optimize IO pipelines, allowing for parallel execution and shared IO elements across multiple predicates, thereby enhancing query processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional query processing methods are used, then hardware constraints and data storage methods limit processing speed, but implementing CNF predicate optimization increases system complexity
Solution Approach 1:
The query processing system segments the query into disjunctions of conjunctive normal form predicates, allowing parallel execution of independent predicate evaluations. This segmentation enables the system to process complex queries by dividing them into manageable, executable units that can run simultaneously across multiple processing cores.
Solution Approach 2:
The system dynamically adjusts the query execution plan based on the parsed CNF predicates, creating flexible execution paths that optimize performance. The query planner dynamically determines the best execution strategy by analyzing the predicate structure and generating optimized execution plans that leverage parallel processing capabilities.
2Productivity
If parallel execution is implemented to improve query processing speed, then hardware resources are consumed more intensively, but this increases the difficulty of resource management
Solution Approach 1:
Multiple predicate evaluations that can execute in parallel are merged into a unified query processing framework. The system combines independent predicate executions while managing shared resources through a centralized query planner, allowing parallel processing without proportionally increasing management complexity.
Solution Approach 2:
The query processing system implements a universal executor that handles multiple types of predicates and execution patterns through a single framework. This multi-functional approach allows the system to manage diverse parallel execution tasks using standardized resource management mechanisms, reducing overall system complexity.
3Speed
If data is stored in traditional formats, then storage is simple, but this limits the speed of exception and query processing
Solution Approach 1:
The data storage system applies different organization strategies to different data structures based on their access patterns and query requirements. Critical data accessed frequently in queries is organized for optimal retrieval speed, while less frequently accessed data uses simpler storage structures, balancing performance and complexity across the dataset.
Data Source
AI summary
A database system is operable to determine a query for execution. A disjunction of a plurality of conjunctive normal form (CNF) filtering predicates is determined based on filtering predicates of the query. An IO pipeline is generated based on the disjunction of the plurality of CNF filtering predicates that includes, based on applying at least one type of optimization, at least one shared IO element common to multiple ones of plurality of the CNF filtering predicates. The IO pipeline is executed in accordance with execution of the query to generate a filtered subset of a plurality of rows that each meet at least one of the plurality of CNF filtering predicates.