Distributed MySQL Routing Table for Shard Management
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Solution Overview
Problem
Conventional MySQL databases face challenges in handling the rapidly increasing demand of internet users, requiring improved storage capability and performance.
Innovation Solution
A distributed MySQL database system is implemented, where a large table is divided into partitioned tables stored across sub-databases, with a routing table used to determine the target sub-database based on a shard key for efficient data processing requests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a conventional MySQL database is used, then the system structure is simple, but the storage capability and performance cannot fulfill the requirements of rapidly increasing internet demands
Solution Approach 1:
The patent divides a large relational database into multiple sub-databases, each containing partitioned tables with shards. This segmentation allows the system to distribute data across multiple storage units, thereby increasing storage capability and handling capacity while maintaining manageable system complexity through modular architecture.
Solution Approach 2:
The patent introduces a routing table as an additional dimensional layer that maps data processing requests to appropriate sub-databases. This routing dimension enables efficient navigation across the distributed database structure, allowing the system to scale storage capability without proportionally increasing query complexity.
2Productivity
If a conventional MySQL database is used, then the system structure is simple, but the query efficiency deteriorates with increasing data volume
Solution Approach 1:
By segmenting the database into sub-databases with partitioned tables and shards, the system can route queries to specific subsets of data rather than scanning entire databases. This segmentation improves query efficiency by reducing the search space while maintaining a structured approach to complexity management.
Solution Approach 2:
The routing table acts as an intermediary that receives data processing requests, determines the appropriate target sub-database based on routing rules, and directs queries efficiently. This intermediary layer improves query performance by preventing full-database scans while adding a manageable layer of complexity for routing logic.
3Quantity of substance
If data is distributed across sub-databases, then storage capability is improved, but the complexity of data management increases
Solution Approach 1:
The patent organizes distributed data into a hierarchical structure with sub-databases, partitioned tables, and shards. This segmentation approach increases storage capacity by allowing horizontal scaling while managing complexity through a systematic organization that enables localized data management within each sub-database.
Solution Approach 2:
The routing table serves multiple functions: it stores structure information of the distributed database, determines target sub-databases for data processing requests, and manages the mapping between logical data access and physical storage locations. This multi-functionality reduces data management complexity by consolidating routing and management operations in a single structure.
Data Source
AI summary
Embodiments of the present disclosure disclose a data processing method, apparatus, and system. The method provided in the embodiments of the present disclosure includes receiving a data processing request sent by a client and obtaining a routing table according to the data processing request. The routing table stores structure information of a relational database. The relational database includes a plurality of sub-databases. The sub-database includes a plurality of partitioned tables, and the partitioned table includes a plurality of shards. The method also includes determining a target sub-database according to the data processing request and the routing table. The method further includes sending the data processing request to the target sub-database, so that the target sub-database performs an operation according to the data processing request.