Indexed Query Modification for Non-Indexed Hierarchical Terms
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Solution Overview
Problem
Existing query execution systems face inefficiencies when dealing with non-indexed query terms, leading to increased computational expense and complexity, especially in hierarchal data sets.
Innovation Solution
The system modifies queries by adding indexed node properties to include terms associated with indexed data, using machine learning to identify relevant terms and applying node routines to derive or inherit non-indexed properties, thereby reducing computational expense.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If queries include non-indexed query terms, then query completeness and accuracy are improved, but computational expense and execution time increase significantly
Solution Approach 1:
The query execution is segmented into two phases: first execute the indexed portion to retrieve a candidate subset, then apply the non-indexed term filtering to this reduced set. This segmentation allows the system to benefit from both indexed and non-indexed query terms without paying the full computational cost of processing all terms equally.
Solution Approach 2:
The indexed query terms are processed in advance to pre-filter the data set before applying the more computationally expensive non-indexed term filtering. This preliminary action reduces the search space early in the execution process, minimizing overall computational expense.
2Loss of information
If queries search through all nodes in a hierarchal data set, then query completeness is improved, but execution time increases
Solution Approach 1:
The hierarchal data set traversal is segmented using the indexed terms to identify and process only relevant subsets of nodes. This allows the system to maintain query completeness for the indexed portion while avoiding unnecessary traversal of unrelated nodes.
Solution Approach 2:
The system performs partial action by executing the indexed query terms on a subset of nodes rather than all nodes. This partial execution is sufficient to retrieve relevant results when combined with the non-indexed term filtering, avoiding the excessive action of processing every node in the hierarchal structure.
3Adaptability or versatility
If the system processes non-indexed query terms without modification, then query functionality is maintained, but system complexity increases
Solution Approach 1:
The system introduces an intermediary processing layer that translates non-indexed query terms into operations that can be efficiently applied after indexed term execution. This intermediary layer maintains full query functionality while managing complexity by providing a structured approach to handling both indexed and non-indexed terms.
Data Source
AI summary
Techniques for modifying a query based on a data index of nodes in a data set are disclosed. A system modifies queries based on query terms associated with indexed data. The system modifies queries to include query terms based on indexed data or to obtain values for query terms that are not associated with indexed node properties. The system adds query terms, that reference indexed data, to a query in response to determining that none of a query's terms reference indexed data. The system derives values for query terms that are not associated with indexed node properties using a logical or mathematical formula. The system traverses parent nodes of a child node to identify values for query terms that are not associated with the child node in a data index, but are inherited from a parent node.