Weighted Navigational Index for XML Query Optimization
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Solution Overview
Problem
Current technologies lack efficient methods for storing, indexing, and retrieving XML data due to its hierarchical and unpredictable structure, which differs significantly from tabularized data handled by relational databases, necessitating a flexible and adaptive indexing scheme that can adjust to frequent query types.
Innovation Solution
A method and system that create a path index and weighted content index for XML documents, using a Document Object Model (DOM) tree to map nodes, identify keywords, and compute a-priori query probabilities, allowing for efficient querying and updating of indices based on query results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If relational database indexing methods are used for XML data, then tabular data retrieval is efficient, but XML hierarchical structure retrieval becomes inefficient
Solution Approach 1:
The patent segments the indexing process into two distinct components: a path index that captures the hierarchical structure of XML documents, and a content index that stores textual information. This segmentation allows each index to be optimized for its specific purpose, resolving the contradiction between handling hierarchical structure and achieving retrieval efficiency.
Solution Approach 2:
The patent introduces a new dimension to traditional indexing by creating a path index that operates on the hierarchical structure of XML documents. This path index adds a structural dimension to the conventional content-based indexing, enabling efficient navigation through hierarchical paths while maintaining content search capabilities.
2Adaptability or versatility
If a fixed indexing scheme is used, then implementation is simple, but adaptation to frequent query types is impossible
Solution Approach 1:
The patent implements a dynamic indexing scheme where the system monitors query frequencies and automatically adjusts the weighting of index entries based on observed usage patterns. This dynamic adaptation allows the indexing scheme to evolve with user needs, improving adaptability while maintaining manageable complexity through automated adjustment mechanisms.
Solution Approach 2:
The patent incorporates feedback mechanisms that track query frequencies and use this information to refine the indexing strategy. The system continuously monitors access patterns and adjusts index weights accordingly, creating a closed-loop system that adapts to changing query requirements without manual intervention.
3Reliability
If comprehensive indexing of all XML nodes is performed, then query coverage is complete, but indexing time and space consumption increase
Solution Approach 1:
The patent applies partial indexing by focusing computational resources on the most frequently accessed paths and content within XML documents. Rather than uniformly indexing all nodes, the system identifies and prioritizes critical paths based on query patterns, achieving sufficient query coverage with reduced indexing overhead.
Solution Approach 2:
The patent implements local quality optimization by applying different indexing strategies to different parts of the XML document structure. Frequently accessed regions receive more comprehensive indexing, while less critical regions use lighter indexing approaches, optimizing the balance between query coverage and resource consumption.
Data Source
AI summary
A technique for optimizing the archival and management of data stored as XML documents is capable of handling mixed data including highly structured data and unstructured data. The technique maps the structured data to a relational database while storing the unstructured data in its native XML format. The data is updated using a rules database that maps updating rules against attributes and classes of elements within the documents. A document checking/validation engine performs the updates based on rule verification. A search engine searches the documents using both a path index table and a weighted content index.