Database Tree Enumeration via Concurrent Level-by-Level Traversal
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Solution Overview
Problem
Hierarchically organized data in database environments faces performance bottlenecks due to inefficient enumeration of tree structures, particularly as database deployments scale, leading to complex data access patterns and the need for optimized traversal methods.
Innovation Solution
The implementation of a database acceleration system that performs concurrent level-by-level traversal of multiple tree structures, utilizing a tree traversal engine to optimize data fetches and support features like child node synthesis and error checking, allowing for efficient enumeration and data access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional enumeration methods are used for hierarchically organized data in database environments, then the implementation is simple, but the processing speed and scalability deteriorate as database deployments increase in size
Solution Approach 1:
The patent segments the enumeration process into distinct phases: vector generation phase, vector processing phase, and result aggregation phase. Each phase operates on discrete data structures (vectors representing nodes at specific hierarchical levels), allowing for optimized processing at each stage and reducing overall complexity despite improved speed.
Solution Approach 2:
The patent transforms the traditional tree traversal approach by organizing data into level-based vectors rather than sequential node references. This dimensional reorganization allows parallel processing of nodes at the same hierarchical level across multiple trees, improving enumeration speed while managing complexity through structured data representation.
2Productivity
If level-by-level processing of multiple tree structures is implemented, then data access patterns are optimized, but the system complexity increases
Solution Approach 1:
The patent merges multiple tree structure enumerations into a unified level-by-level processing framework. Nodes from different trees at the same hierarchical level are processed together using shared vector structures, improving productivity by eliminating redundant operations while managing complexity through standardized processing routines.
Solution Approach 2:
The vector processing mechanism serves multiple functions: it represents nodes at any hierarchical level, stores node attributes and relationships, and enables both sequential and parallel processing modes. This universal data structure reduces system complexity by providing a single framework that handles various enumeration scenarios.
3Loss of time
If concurrent enumeration of multiple primary trees is performed, then processing time is reduced, but the data access patterns become more complex
Solution Approach 1:
The patent performs preliminary organization of tree nodes into level-based vectors before actual enumeration processing. This pre-processing step groups nodes by hierarchical level across all trees, enabling efficient concurrent access during enumeration while reducing the complexity of data access patterns during the actual processing phase.
Data Source
AI summary
Methods and systems are disclosed for enumeration of trees in a database environment. Temporary copies of trees are stored in a database accelerator environment, for efficient access by software programs operating within the database layer. Multiple trees can be enumerated concurrently using level-by-level traversal. Nodes are assigned sortable indices through which a tree structure is maintained. Enumeration supports linking from a node of a parent tree to a child tree stored separately. Enumeration supports synthesizing child nodes in order to satisfy constraints on a parent node. Filtering and sorting are supported. The disclosed technology provides unexpectedly superior results, and can be applied in many fields. Variants are disclosed.