Global SQL Execution DAGs for Parallelism and Shuffle Visibility
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Solution Overview
Problem
Distributed computing systems like Apache Spark and Apache Flink lack comprehensive visual or graphical representations of execution plans and shuffle rules for SQL queries, leading to unclear execution processes and suboptimal performance optimization.
Innovation Solution
A system and method to create a global directed acyclic graph (DAG) of an execution plan that provides comprehensive information about parallelism and data-exchange strategies, enabling developers to visualize and optimize SQL query execution processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If distributed computing systems execute SQL queries without comprehensive visual representations, then system complexity is reduced, but execution process clarity and optimization capability deteriorate
Solution Approach 1:
The patent creates a visual copy (graphical representation) of the execution plan that mirrors the actual query execution process. This copy includes nodes representing operations and edges representing data flow, allowing developers to visualize the execution plan without adding physical complexity to the distributed computing system itself. The graphical representation serves as an information copy that preserves execution details while keeping the system architecture simple.
2Productivity
If comprehensive execution plan information is provided, then optimization capability improves, but information processing complexity increases
Solution Approach 1:
The execution plan is segmented into discrete nodes (representing operations like scan, filter, join, aggregate) and edges (representing data flow). This segmentation allows comprehensive information to be presented in a structured, manageable way. Each node can be independently analyzed for optimization opportunities, and the modular structure reduces the complexity of processing the overall execution plan information.
3Loss of information
If visual representation of execution plans is implemented, then execution process clarity improves, but system resource consumption increases
Solution Approach 1:
The patent introduces an intermediary component that generates and manages the graphical representation of execution plans. This intermediary translates the internal execution plan data structure into a visual format without requiring the distributed computing system itself to perform additional resource-intensive operations. The visual representation is generated as a separate layer that mediates between the execution engine and the developer, providing clarity without significantly increasing system resource consumption.
Data Source
AI summary
Creating a global directed acyclic graph (DAG) of an execution plan according to a logical plan derived from one or more Structured Query Language (SQL) queries. The logical plan comprises a set of SqlNodes, where each non-root SqlNode includes parent SqlNode information. The DAG comprises vertices connected by edges, wherein each vertex corresponds to a respective relational expression of a set of relational expressions and is labeled according to an operator of an execution engine, such as Spark, that has been mapped to the respective relational expression. The DAG may be displayed via a graphical user interface. In some implementations, one or more vertices includes information indicating a level of execution parallelism and/or cache enablement.