Distributed Graph Query Processing With Dynamic Concurrency Control
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Solution Overview
Problem
Distributed graph database systems face inefficiencies in query processing due to storage node service overload, leading to retries that waste resources and fail to meet user expectations, especially when handling complex queries.
Innovation Solution
A query processing method that analyzes the type of retrieval request and adjusts concurrency based on the complexity, allowing for differentiated handling of simple and complex queries, including adjusting concurrency levels and implementing flow control to optimize resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the system processes complex queries by splitting them into multiple sub-queries and sending them to storage nodes, then the query processing capability is improved, but the storage node service becomes overloaded and response time increases
Solution Approach 1:
The system dynamically adjusts the concurrency level of query processing based on real-time monitoring of storage node service status. When service overload is detected, the system reduces concurrency to prevent further overload; when service capacity is available, it increases concurrency to improve processing throughput. This dynamic adaptation resolves the contradiction between processing capability and response time.
Solution Approach 2:
The system implements a feedback mechanism that continuously monitors storage node service status and uses this information to adjust query processing concurrency. The feedback loop ensures that the system responds to changing service conditions, preventing overload while maximizing processing efficiency under normal conditions.
2Reliability
If the system retries queries when storage node service is overloaded, then query completion is attempted, but resource wastage increases and does not meet user expectations
Solution Approach 1:
The system performs preliminary monitoring of storage node service status before initiating query processing. By detecting service overload conditions in advance, the system can preemptively adjust concurrency levels or queue queries, preventing futile retry cycles and resource wastage while maintaining reliable query completion through alternative routing or load balancing.
3Device complexity
If the system handles all queries with the same concurrency level, then the processing logic is simple, but resource utilization is not optimized
Solution Approach 1:
The system applies different concurrency handling strategies to different query types and storage nodes based on local conditions. Complex queries to overloaded nodes receive different treatment than simple queries to healthy nodes, optimizing resource utilization while maintaining manageable processing logic through condition-based differentiation.
Data Source
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AI summary
The present disclosure provides a query processing method and apparatus, an electronic device and a storage medium, and relates to the field of technologies, such as cloud computing technologies, big data technologies, or the like. An implementation includes: analyzing (S101) a type of a received retrieval request; and performing (S102) a query processing operation on the retrieval request based on the type of the retrieval request. The technology according to the present disclosure may effectively improve a query efficiency.