Distributed Device Order Data Storage for Faster Queries
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Solution Overview
Problem
Existing data storage methods struggle with data bottlenecks and inefficiencies in data retrieval, particularly when dealing with large volumes of data, leading to storage limitations and challenges in real-time data analysis.
Innovation Solution
A device order data storage method utilizing hash modulo operations and a snowflake algorithm to distribute data across multiple servers and databases based on user identifiers, device identifiers, and timestamps, ensuring efficient storage and retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If data is stored in a single table or classified by data attributes (generation date, source, type), then data storage is simple and easy to implement, but data bottlenecks occur and query efficiency deteriorates when data volume grows large
Solution Approach 1:
The patent segments data storage by creating multiple data tables divided into different data regions based on user identifiers. Each data region contains multiple data tables, and each table stores data for specific users. This segmentation allows data to be distributed across multiple tables and regions, preventing single-table bottlenecks while enabling efficient queries by directing access to specific regions based on user ID hashing.
2Ease of manufacture
If data is classified and stored by data attributes such as generation date or source, then data organization is straightforward, but real-time data retrieval becomes difficult and inconvenient
Solution Approach 1:
The patent introduces a user identifier as an intermediary key that bridges data organization and retrieval. User identifiers are hashed to determine both the data region and specific table where user data is stored. This intermediary mechanism enables straightforward data organization by user while allowing rapid retrieval by hashing the user ID to directly locate the relevant data region and table, eliminating the need to search through all classified data.
3Quantity of substance
If hardware resources are continuously increased to accommodate growing data volume, then data storage capacity is sufficient, but costs increase and data reading remains difficult
Solution Approach 1:
The patent adds dimensional organization to data storage by creating a hierarchical structure with data regions, tables, and user-level partitioning. Instead of simply adding more storage capacity in a single dimension, the system organizes data across multiple dimensions (region → table → user records), allowing efficient utilization of existing hardware resources and enabling scalable storage without proportionally increasing hardware complexity.
Data Source
AI summary
Provided are device order data storage method and apparatus, and device order data query method and apparatus. The device order data storage method includes: acquiring target user identifier, target device identifier, device order information and software detail information corresponding to target device order data; for the device order information and the software detail information respectively, performing first hash modulo operation according to the target user identifier, to position target server; according to server identifier, current timestamp, the target device identifier and snowflake algorithm, generating information identifier corresponding to current information; performing second hash modulo operation on digit at specified bit in the information identifier, to position target database; according to the category of the current information and the current timestamp, positioning, from multiple information tables of the target database, target information table corresponding to target month for information storage; and storing multiple identifiers into specified database in associated manner.