Software Product Event Tables with Metadata-Based Column Sharing
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Solution Overview
Problem
Existing event data analysis systems face performance degradation due to the large number of columns required to store event attributes, leading to inefficient data storage and retrieval.
Innovation Solution
A method and apparatus that determine column information for event attributes in a target table based on metadata, allowing different cells in a column to store different event attributes, reducing the number of columns needed and improving system performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If columns are associated with event attributes (one attribute per column), then data storage is straightforward and simple, but the number of columns increases significantly when there are many event attributes, reducing system performance
Solution Approach 1:
The patent applies universality by making columns capable of storing multiple different event attributes. Instead of dedicating one column per attribute, a single column can hold values for different attributes across different rows. This is achieved through metadata that maps attribute names to column positions, allowing the same column to serve multiple attribute types dynamically, thereby reducing the total number of columns while maintaining data integrity.
2Productivity
If the number of columns is reduced by allowing different cells in a column to store different event attributes, then system performance is improved, but determining column information becomes more complex
Solution Approach 1:
The patent introduces metadata as an intermediary layer between the physical table structure and the logical event attributes. The metadata stores the mapping relationships between attribute names and column positions, acting as a mediator that translates between the reduced-column physical structure and the multi-attribute logical structure. This intermediary simplifies the determination of column information by providing a lookup mechanism rather than requiring complex real-time analysis.
Solution Approach 2:
The patent applies preliminary action by pre-establishing the metadata that defines the mapping between event attributes and column positions before data storage operations occur. This pre-computed mapping information is stored and reused, eliminating the need to determine column information dynamically during each storage or query operation, thereby reducing complexity while maintaining performance benefits.
Data Source
AI summary
The present application discloses a method for data processing for a software product. The method includes: obtaining event data to be stored, wherein the event data to be stored includes a software product identifier, an event identifier, and at least one event attribute; determining column information of each event attribute of the at least one event attribute in a target table; and storing, into the target table, the event data to be stored, based on the column information of each event attribute in the target table. In the embodiments of the present application, the target table includes a plurality of columns, the plurality of columns include at least a target column, and event attributes carried in at least two of cells included in the target column are different.