Augmented Succinct Trie for Multi-Component Key Indexing
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Solution Overview
Problem
Data storage systems face challenges in efficiently storing indexes that use multi-component keys, as existing solutions like succinct tries can lead to errors and incorrect sorting, particularly in systems with column stores and row keys, and fail to accurately store and retrieve multi-component keys.
Innovation Solution
An augmented succinct trie (AST) is constructed by encoding boundary information between data components, using label, child, and level order unary degree sequence (LOUDS) information, and continuation bits to correctly sort and store multi-component keys, reducing storage space and improving query efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a traditional index structure is used to store multi-component keys, then data retrieval speed is improved, but storage space consumption increases significantly
Solution Approach 1:
The patent segments multi-component keys into individual components and stores them in a hierarchical trie structure where each level represents one component. This segmentation allows the index to store only necessary path information rather than complete key-value pairs, significantly reducing storage space while maintaining retrieval speed through the hierarchical navigation structure.
Solution Approach 2:
The patent implements a nested hierarchical structure where the index is organized as a trie of tries, with each level nesting within the previous level. This nested structure allows compact representation of multi-component keys by sharing common prefixes at higher levels and only storing unique portions at lower levels, thereby reducing overall storage requirements while preserving fast retrieval through level-by-level navigation.
2Volume of stationary object
If space reduction techniques are applied to the index, then storage space is reduced, but sorting accuracy and retrieval correctness deteriorate
Solution Approach 1:
The patent applies local quality by storing different types of information at different levels of the hierarchical trie structure. Higher levels store component separators and navigation information, while lower levels store actual data references. This localized specialization of storage content ensures that each part of the structure contributes optimally to both space efficiency and sorting accuracy, preventing the loss of critical sorting information that plagues uniform compression techniques.
Solution Approach 2:
The patent transforms the traditional flat key-value storage into a multi-dimensional hierarchical structure where keys are distributed across multiple levels representing different components. This dimensional transformation preserves sorting accuracy by maintaining the hierarchical ordering relationship among all key components, while the sparse representation at each level significantly reduces the total storage required compared to storing complete keys at a single level.
Data Source
AI summary
Mechanisms for constructing and querying a database are described. Constructing the database includes accessing the database comprising multi-component data and constructing an augmented succinct trie (AST) as an index of the database. The database includes sorted data blocks. Construction of the AST is based on the multi-component data. The AST includes indications of boundaries of the data components of the multi-component data. Querying the database includes accessing a key comprising multiple data components and augmenting the key data with data component boundary information. The AST is searched using the augmented key and a search result provided as a value corresponding to the key in the database.