Right-to-Left Piecewise Scheduling for Multi-Child Query Operators
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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, particularly when handling large volumes of data.
Innovation Solution
Implementing a database system with a parallelized architecture that includes a parallelized data input, storage, retrieval, and processing sub-systems, along with a query and response system, utilizing a piecewise scheduling strategy for query execution to optimize query plans and execute them across multiple nodes and processing core resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional sequential query execution is used, then system complexity remains low, but processing speed and productivity deteriorate when handling large volumes of data
Solution Approach 1:
The patent divides the query execution process into multiple independent child operators that can be executed in parallel. Each child operator processes a portion of the query independently, allowing simultaneous execution across multiple processing core resources. This segmentation transforms a single sequential execution path into multiple parallel execution paths, directly improving query processing speed while managing system complexity through modular design.
Solution Approach 2:
The patent introduces a new dimension of parallel execution by utilizing multiple processing core resources simultaneously. Instead of executing operators sequentially in a single thread, the system distributes child operators across multiple cores, adding a spatial dimension to the execution architecture. This dimensional expansion enables concurrent processing without fundamentally complicating the core execution logic.
2Productivity
If parallel execution architecture is implemented, then processing efficiency improves, but system complexity and coordination overhead increase
Solution Approach 1:
The patent introduces a parent operator as an intermediary that coordinates child operator execution. The parent operator manages the parallel execution by distributing tasks to child operators, collecting their results, and maintaining execution state. This intermediary structure simplifies coordination overhead by centralizing control logic in the parent operator, allowing child operators to execute independently without direct communication between them.
Solution Approach 2:
The patent implements feedback mechanisms where child operators report their execution status and results back to the parent operator. The parent operator uses this feedback to manage resource allocation, handle dependencies, and coordinate the overall execution flow. This feedback loop enables efficient parallel execution by allowing the system to dynamically adjust to execution conditions while maintaining structured coordination.
3Loss of time
If more processing core resources are utilized, then execution time reduces, but hardware cost and system complexity increase
Solution Approach 1:
The patent implements dynamic resource allocation where the system can adaptively utilize available processing core resources based on query requirements and system conditions. The parallel execution architecture allows flexible scaling from single-core to multi-core environments without requiring fundamental architectural changes. This dynamic capability enables the system to optimize execution time by utilizing more cores when available, while automatically falling back to fewer cores when resources are constrained, thereby managing hardware cost and complexity effectively.
Data Source
AI summary
A database system is operable to execute a set of multi-child operators of a query operator execution flow of a corresponding query in conjunction with applying a right-to-left piecewise scheduling strategy. Each multi-child operator is executed based on, in response to detecting when a right input threshold condition has been met after processing at least some of a stream of right input data of right input, triggering execution of at least one leaf operator of a set of leaf operators included in a corresponding left child branch. In response to processing all right input and receiving corresponding left input rows in a stream of left input data, corresponding multi-child operator output is generated as a stream output data based on processing the left input rows.