Hierarchical Query Compliance Checks for Faster Data Policy Screening
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Solution Overview
Problem
Existing query compliance checks in database systems are inefficient, taking a long time due to high computational resource utilization, particularly when organization rule checks are complex and resource-intensive, leading to delayed query execution and correction.
Innovation Solution
Implement a query processing system that first performs data flow policy checks on identified data items, only executing organization rule checks if the data flow policy check fails, thereby reducing unnecessary computational overhead and improving resource utilization efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If organization rule check is executed for all queries, then compliance accuracy is improved, but computational resource utilization efficiency deteriorates
Solution Approach 1:
The compliance check process is segmented into two distinct stages: data flow policy check (first stage) and organization rule check (second stage). This segmentation allows the system to filter queries at the first stage using simpler rules, avoiding the need to execute resource-intensive organization rule checks on all queries, thereby improving computational efficiency while maintaining compliance accuracy for queries that require it.
Solution Approach 2:
The data flow policy check is performed as a preliminary action before executing the organization rule check. This preliminary filtering mechanism identifies and eliminates queries that violate data flow policies early in the process, preventing unnecessary execution of complex organization rule checks and reducing overall computational resource consumption.
2Reliability
If organization rule check is executed for all queries, then compliance accuracy is improved, but query execution time deteriorates
Solution Approach 1:
The compliance verification process is divided into two sequential segments: data flow policy check followed by organization rule check. This segmentation enables early termination for queries failing the first segment, reducing the time loss associated with executing the more time-consuming organization rule check on all queries while ensuring compliance accuracy is maintained for queries that proceed to the second segment.
Solution Approach 2:
The data flow policy check serves as a preliminary action that quickly filters out non-compliant queries before they reach the organization rule check stage. This preliminary filtering significantly reduces the average query execution time by avoiding unnecessary processing of queries that would fail compliance checks anyway, while still ensuring thorough compliance verification for queries that pass the initial filter.
3Reliability
If computational resources are allocated for comprehensive compliance checks, then compliance accuracy is improved, but resource utilization efficiency deteriorates
Solution Approach 1:
Compliance checking resources are allocated segmentally rather than uniformly. The system dedicates appropriate computational resources to each stage: sufficient resources for the data flow policy check to effectively filter queries, and then resources for organization rule checks are allocated only to queries that pass the first stage. This segmented resource allocation improves overall resource utilization efficiency while maintaining compliance accuracy.
Solution Approach 2:
The data flow policy check acts as a preliminary resource-filtering mechanism that prevents wasteful allocation of computational resources to queries that will ultimately fail compliance checks. By performing this preliminary check with moderate resource investment, the system avoids the much larger resource expenditure that would be required to execute comprehensive organization rule checks on all queries, thereby improving resource utilization efficiency while preserving compliance accuracy.
Data Source
AI summary
To improve resource utilization efficiency of query compliance check, which is check as to whether a query complies with a restriction imposed on data. The query compliance check is roughly divided into data flow policy check as to whether a data flow policy that defines a restriction on data transfer within a county or between countries is complied with, and organization rule check as to whether an organization rule that defines a restriction on sharing outside an organization is complied with, which are hierarchically configured. By analyzing a received query, a system identifies one or more data items as target input/output (I/O) data according to the query, and executes the data flow policy check on the identified one or more data items. When a result of the data flow policy check is false, the system returns a result that the query is compliance violation without executing the organization rule check.