Dynamic Partition Layer for Database Table Management
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Solution Overview
Problem
As the amount of data stored in a database table increases, access efficiency decreases, leading to performance issues in storage systems, as existing methods fail to effectively manage and partition data efficiently.
Innovation Solution
A computer-implemented method and system that dynamically partitions data into subsets based on attributes, using a dynamic partition layer to transform insert, query, and delete statements, creating tables as needed and marking them active or on hold based on pre-configured thresholds to maintain efficient data storage and retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If data is stored in a single table, then data storage is simple, but data access efficiency decreases as data volume increases
Solution Approach 1:
The patent segments the single large table into multiple smaller partitioned tables based on data attributes (e.g., date ranges, customer categories). Each partition stores a subset of the total data, allowing queries to access only relevant partitions rather than scanning the entire table, thus maintaining storage simplicity while improving access efficiency.
2Speed
If data is partitioned into multiple tables, then data access efficiency improves, but system complexity increases
Solution Approach 1:
The patent introduces a partitioning layer as an intermediary between the application and the physical storage tables. This layer automatically manages table partitioning, routing, and merging operations, shielding the user from complexity while enabling efficient data access through intelligent partition management.
Solution Approach 2:
The patent implements dynamic partition management where tables can be automatically created, merged, or split based on data volume thresholds and access patterns. This dynamic adjustment optimizes performance without requiring manual intervention, balancing efficiency gains with operational simplicity.
3Manufacturing precision
If manual table partitioning is performed, then data organization is controlled, but maintenance effort increases
Solution Approach 1:
The patent implements self-service automation where the system automatically monitors data volumes, detects when partitioning thresholds are met, and executes table creation, splitting, or merging operations without manual intervention. This maintains precise data organization while eliminating the maintenance burden on users.
Data Source
AI summary
Methods, systems, and computer program products are included for defining a partitioning strategy corresponding to an attribute, creating tables and inserting data into the tables according to the partitioning strategy, detecting triggering events, and responsive to the triggering events, dynamically activating tables for storing data.