Distributed Database Query Processing with Multidimensional Result Cursors
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Solution Overview
Problem
Existing database querying technologies face delays when dealing with distributed data sets, as the final query response is dependent on data from multiple locations, leading to delayed computation and inefficient processing.
Innovation Solution
The method generates multiple cursors to traverse and process data across interrelated data sets, enabling concurrent processing and deductive closure in distributed database environments, particularly using a query engine with components like a cursor generator and result set compiler to handle multi-dimensional data sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is distributed across multiple databases in different geographic or network locations, then data storage capacity and accessibility are improved, but query processing time and computational efficiency deteriorate
Solution Approach 1:
The patent divides the distributed database system into multiple autonomous data nodes that can be independently queried. Each node maintains local data and can process queries autonomously, eliminating the need to wait for data from all distributed locations. The system segments the monolithic query processing task into parallel operations across multiple nodes.
Solution Approach 2:
The patent implements pre-computation of deductive closures for individual data nodes before queries are executed. By pre-processing and storing derived data relationships at each node, the system eliminates runtime computation delays when combining results from distributed databases, allowing immediate query response without waiting for data synchronization.
2Reliability
If the final query response depends on data sets received from distributed databases at different times, then data completeness is improved, but computational efficiency and query response time deteriorate
Solution Approach 1:
The patent segments the query processing into independent node-level operations that can proceed concurrently. Each data node processes its local data and generates results independently without waiting for other nodes, allowing the system to return partial results immediately while continuing to process remaining data sources in parallel.
Solution Approach 2:
The patent implements a feedback mechanism where the query processing system continuously monitors results from distributed nodes and dynamically adjusts processing based on received data quality and quantity. This allows the system to determine when sufficient data has been received to provide a meaningful response, eliminating unnecessary waiting for complete data sets from all locations.
3Speed
If multiple cursors are generated to traverse distributed data sets concurrently, then query processing speed is improved, but system complexity and resource requirements worsen
Solution Approach 1:
The patent implements a universal cursor interface that can operate across different data node types and distributed database systems. This single multi-functional cursor mechanism handles traversal, result compilation, and synchronization tasks uniformly, reducing system complexity compared to implementing separate specialized cursors for each data source and operation type.
Data Source
AI summary
A method comprises selecting at least a first data set and a second data set on which to apply a query. The method also comprises causing generating of a first cursor based and a second cursor based on a first application of the query on the first data set and a second cursor based on a second application of the query on the second data set. A third cursor based on a combination of a result set returned by the first cursor and second cursor is then generated in response to the query.