Tree-Based Data Storage Format for Scalable Node Management
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Solution Overview
Problem
Existing data storage systems face increased complexity and costs as data volumes grow, with existing data formats often requiring costly changes or redistribution when adding or removing storage locations, which can disrupt data locality and access performance.
Innovation Solution
A tree-based data storage format that organizes data into storage slabs, allowing for efficient redistribution and addition of new slabs without disrupting data locality, using a distribution scheme that maintains access performance by grouping commonly accessed data together and allowing for incremental changes in storage infrastructure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is organized in traditional storage formats, then data can be stored and accessed, but adding or removing storage locations requires costly redistribution of data that disrupts data locality and access performance
Solution Approach 1:
The patent segments data into fixed-size chunks and organizes them in a tree structure where each node represents a storage location. This segmentation allows individual chunks to be moved or added without requiring redistribution of entire data sets, enabling storage infrastructure changes while preserving data locality for accessed chunks.
Solution Approach 2:
The patent implements a nested tree structure where storage chunks are organized in hierarchical levels. Parent nodes contain metadata about child nodes, creating a nested arrangement that allows efficient navigation and access. This nesting enables selective access to specific data portions without touching other data, maintaining performance during storage changes.
2Speed
If data is redistributed to maintain locality or sorting formats, then data access performance may be optimized, but the cost and complexity of adding or reducing storage locations increases
Solution Approach 1:
The patent pre-organizes data into fixed-size chunks with metadata that identifies their location in the tree structure before storage changes occur. This preliminary organization allows the system to accommodate storage additions or reductions without requiring complex redistribution operations, as the chunk structure is already optimized for locality.
Solution Approach 2:
The tree structure automatically manages data chunk placement and metadata updates when storage locations change. The system self-adjusts by updating parent node metadata to reflect new child node locations without requiring external coordination or complex redistribution algorithms, reducing management complexity.
3Speed
If specialized data formats are implemented to optimize specific performance features, then access performance for certain operations improves, but the system becomes less adaptable and requires costly changes when needs change
Solution Approach 1:
The patent creates a universal tree-based storage format that can accommodate multiple access patterns and data types without requiring format changes. The hierarchical structure naturally supports sequential access, random access, and range queries, making the system multi-functional and adaptable to different performance needs without costly format conversions.
Data Source
AI summary
A tree-based format may be implemented for data stored in a data store. A table may be maintained across one or multiple storage nodes in storage slabs. Storage slabs may be mapped to different nodes of a tree. Each node of the tree may be assigned a different range of distribution scheme values which identify what portions of the table are stored in the storage slab. Storage slabs mapped to child nodes in the tree may be assigned portions of the range of distribution scheme values assigned to a parent. Storage nodes may be added or removed for storing the table. Storage slabs may be moved from one storage node to another in order to accommodate the addition or removal of storage nodes.