NoSQL Cache State Tracking Through Traffic Log Deduplication
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Solution Overview
Problem
Traditional SQL databases struggle with data storage and access requirements of modern applications due to their declarative language programming, necessitating specialty hardware and skilled administrators, while No-SQL databases face challenges in determining real-time caching states without impacting runtime performance.
Innovation Solution
Maintain a log table to reflect modifications in No-SQL databases during runtime, deduplicate it to remove stale entries, and generate a cost table without querying the database, allowing real-time caching state determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional SQL databases are used for data storage and access, then data can be stored and accessed with structured schema, but specialty hardware and skilled administrators are required, limiting horizontal scalability
Solution Approach 1:
The patent creates a cost table that copies and aggregates cost information from the noSQL database without requiring direct access to the actual data. This copying approach allows the system to analyze storage costs and optimize caching strategies while maintaining the simplicity and scalability of noSQL databases, eliminating the need for complex SQL database infrastructure.
2Productivity
If noSQL databases are used to handle large datasets with inexpensive hardware, then horizontal scalability is improved, but determining real-time caching states requires querying the database which impacts runtime performance
Solution Approach 1:
The patent pre-calculates and stores cost information for each property in a cost table before runtime queries are needed. By performing this cost analysis in advance and maintaining it separately from the operational noSQL database, the system can determine real-time caching states by querying the pre-computed cost table rather than analyzing actual database contents during runtime, thus avoiding performance impact.
Solution Approach 2:
The cost table serves as an intermediary structure that mediates between the operational noSQL database and the caching optimization process. Instead of directly querying the noSQL database to determine caching states, the system queries the cost table which contains pre-aggregated cost information, thereby isolating the optimization process from the operational database and eliminating performance impact.
3Reliability
If the noSQL database is queried to determine caching state during runtime, then accurate real-time information is obtained, but runtime operation is impacted
Solution Approach 1:
The system pre-computes cost information and stores it in the cost table before runtime operations. This preliminary action ensures that accurate cost and caching state information is available without requiring runtime queries to the noSQL database, thus maintaining both accuracy and operational performance.
Solution Approach 2:
The cost table contains copied and aggregated cost information from the noSQL database properties. This copying approach provides reliable caching state data for optimization decisions without requiring access to the actual operational database, ensuring accuracy while avoiding runtime impact.
Data Source
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AI summary
Database management techniques can gauge real-time caching states of no-schema-based (noSQL) databases (DBs) during runtime operation by maintaining a log table to reflect modifications to the noSQL DB. The log table is maintained by adding row entries to reflect modifications to the noSQL DB and therefore does not requiring querying the noSQL DB. The log table may then be deduplicated to remove stale entries and queried to generate a cost table reflecting a real-time caching state of the noSQL DB.