Query Assistant Batch Processing Optimization
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Solution Overview
Problem
Current computing systems face inefficiencies in batch query processing due to the first-come first-served approach, which does not optimize query order, leading to suboptimal use of data sources and caching systems.
Innovation Solution
A method involving a query assistant that accumulates queries, separates them into partitions based on accessed storage tables, orders these partitions and queries within them, and processes them in a specific order to improve efficiency, leveraging caching and buffering systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If queries are processed in first-come first-served fashion, then simplicity of processing is maintained, but query processing efficiency deteriorates
Solution Approach 1:
The system performs preliminary actions by accumulating queries in a query holding area before processing, and pre-ordering them based on partitioning and from-type analysis. This allows the system to optimize query execution order in advance, improving efficiency without adding complexity during actual query execution.
Solution Approach 2:
The system segments accumulated queries into multiple partitions based on from-type (combination of storage tables accessed). Each partition is then independently ordered and processed. This segmentation allows parallel processing of different query types while maintaining overall efficiency optimization.
2Productivity
If queries are reordered for optimal processing, then query processing efficiency is improved, but system complexity increases
Solution Approach 1:
The query assistant performs preliminary ordering of queries based on from-type and partitioning before execution. By analyzing the from-type (combination of storage tables) of each query in advance and establishing an optimal execution order, the system achieves efficiency improvement without requiring complex real-time decision-making during query processing.
Solution Approach 2:
The query assistant acts as an intermediary component between query submission and execution. It introduces a query holding area and ordering mechanism that mediates between incoming queries and the processing system, optimizing the execution sequence without modifying the underlying data source or query structure.
3Productivity
If queries are accumulated in batch mode, then processing efficiency is improved, but query response time increases
Solution Approach 1:
The system performs preliminary ordering and partitioning of queries while they are being accumulated in the query holding area. This preliminary processing prepares the queries for efficient batch execution without requiring additional time after accumulation, as the ordering work is completed in advance during the accumulation phase.
Data Source
AI summary
A system and method of batch query processing includes accumulating data queries in a query holding area of a query assistant running in a computer server, separating the accumulated data queries into a plurality of partitions, ordering the partitions, ordering the accumulated data queries within each of the partitions, and processing the accumulated data queries in an order based on the ordering of the partitions and the ordering of the data queries within each of the partitions. Each of the partitions includes data queries with a respective from-type. Each respective from-type is associated with a combination of storage tables accessed by each of the data queries in a corresponding partition. In some examples, ordering the accumulated data queries within each of the partitions includes processing the data queries in each partition against a test data set and ordering the data queries based on results of the processing.