Graph Query Early Pruning for Distributed Network Latency
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Solution Overview
Problem
Graph database query execution in distributed systems is hindered by network latencies and inefficiencies, as existing techniques do not adequately optimize the exploration of potential solution paths, leading to suboptimal performance and increased resource usage.
Innovation Solution
Implement early pruning of potential solution paths in graph queries by utilizing expression-specific intermediate results to discard paths whose property values cannot affect the final query results, specifically using prunable functions like MIN, MAX, SUM, and DISTINCT to reduce the number of paths explored.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If graph queries are executed by exploring all potential solution paths in distributed systems, then complete query results are obtained, but network latency and query response time increase significantly
Solution Approach 1:
The system performs preliminary evaluation of path properties during query execution to determine early whether a path can satisfy the query conditions. By assessing intermediate results and comparing them against query requirements before complete path exploration, the system eliminates unpromising paths ahead of time, reducing unnecessary network communication and processing time while maintaining result completeness.
2Measurement precision
If all potential solution paths are explored to ensure accurate query results, then query accuracy is maintained, but hardware and energy costs increase
Solution Approach 1:
The system applies partial action by exploring only the necessary portion of solution paths required to achieve accurate query results.通过使用prunable functions (MIN, MAX, SUM, DISTINCT), the system determines early whether continuing path exploration would change the final result. When intermediate evaluations show that further exploration cannot affect the outcome, the system stops exploring that path, consuming minimal energy while preserving accuracy.
3Reliability
If comprehensive path exploration is performed to capture all query solutions, then query completeness is achieved, but network congestion increases
Solution Approach 1:
The system performs preliminary assessment of path viability using intermediate evaluation results before committing to complete path exploration and network communication. By evaluating path properties early and comparing them against query requirements, the system prunes unpromising paths before they generate network traffic, thereby reducing network congestion while ensuring that only relevant paths are fully explored and included in results.
Data Source
AI summary
Techniques are described herein for early pruning of potential graph query results. Specifically, based on determining that property values of a path through graph data cannot affect results of a query, the path is pruned from a set of potential query solutions prior to fully exploring the path. Early solution pruning is performed on prunable queries that project prunable functions including MIN, MAX, SUM, and DISTINCT, the results of which are not tied to a number of paths explored for query execution. A database system implements early solution pruning for a prunable query based on intermediate results maintained for the query during query execution. Specifically, when a system determines that property values of a given potential solution path cannot affect the query results reflected in intermediate results maintained for the query, the path is discarded from the set of possible query solutions without further exploration of the path.