Database Query Executor Parallel Task Generation
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Solution Overview
Problem
Existing database management systems face challenges in reducing the total data read wait time during query execution, as they often require sequential access to storage devices and fail to optimize the sequence of data read requests effectively.
Innovation Solution
A database management system that includes a query interface, a query plan generator, and a query executor capable of generating and executing tasks in parallel, with an I/O optimizer that reorders data read requests based on priority and queue management to optimize data read time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If data read requests are processed sequentially in conventional database management systems, then the system structure remains simple, but the total data read time increases
Solution Approach 1:
The patent segments the database processing into multiple independent tasks that can be executed in parallel. Each task represents a discrete unit of work that accesses specific data, allowing the system to process multiple data read requests simultaneously rather than sequentially, thereby reducing total data read time while managing complexity through structured task segmentation
Solution Approach 2:
The patent implements dynamic task generation and elimination mechanisms where tasks are created when data access is needed and eliminated after completion. This dynamic approach allows the system to adapt the number of concurrent tasks based on actual processing needs, optimizing parallel execution while preventing excessive resource consumption and managing system complexity
2Productivity
If multiple tasks are executed in parallel to reduce data read time, then productivity improves, but the complexity of task management and coordination increases
Solution Approach 1:
The patent employs feedback mechanisms where the query executor monitors task execution status, data availability, and system resources. Based on this feedback, the system dynamically adjusts task generation, suspends tasks when conditions are not met, and coordinates parallel execution, thereby improving query execution speed while managing task coordination complexity through continuous monitoring and adaptive control
Solution Approach 2:
The patent performs preliminary actions by generating tasks in advance when data access patterns are predictable, and by pre-coordinating task execution plans. This allows the system to prepare for parallel execution before actual data processing begins, improving productivity while reducing the complexity of real-time task coordination through advance planning
3Loss of time
If the system generates a new task for each data access operation, then data read time is reduced through parallel execution, but the number of tasks and system resource consumption increases
Solution Approach 1:
The patent implements a task lifecycle management system where tasks are discarded (eliminated) after completion and can be recovered (regenerated) when needed. This allows the system to maintain a controlled number of concurrent tasks by eliminating completed ones and regenerating new tasks based on actual processing requirements, reducing data read wait time through parallel execution while preventing unbounded task proliferation and resource consumption
Data Source
AI summary
A database management system has a query interface for receiving a query and a query executor for executing the received query. The query executor dynamically generates a task, and executes a plurality of tasks in parallel. In execution of each task, each time data is required to be read from a database, the query executor generates a task for acquiring the data, and in execution of the generated task, issues a data read request for reading the data from the database, to thereby shorten a time taken to execute each task.