Database Query Caching Priority to Prevent Cache Pollution
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Solution Overview
Problem
Database caching systems suffer from cache pollution due to analytical workloads, leading to increased cache misses and slower query response times for end-user workloads, as analytical workloads often displace cached data needed for end-user queries.
Innovation Solution
Implement techniques that determine a caching priority for each query, allowing query results to be cached or not based on the determined priority, thereby reducing cache pollution and improving performance for end-user workloads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If analytical workloads are allowed to query the database, then analytical processing can be performed, but cache pollution occurs and end-user query performance deteriorates
Solution Approach 1:
The patent segments the database system into two distinct cache structures: a first cache for end-user workloads and a second cache for analytical workloads. This segmentation prevents analytical queries from polluting the end-user cache, thereby maintaining end-user query performance while still enabling analytical processing capabilities.
Solution Approach 2:
The patent introduces a workload classification mechanism that acts as an intermediary to route different types of queries to appropriate cache structures. By classifying workloads as either end-user or analytical, the system directs analytical queries to a dedicated second cache, preventing them from affecting the first cache used by end-user queries.
2Quantity of substance
If database cache size is increased to accommodate analytical workload data, then analytical queries can be served, but end-user query data is pushed out of the cache
Solution Approach 1:
The patent divides the cache resources into separate first and second cache structures, allocating specific capacity to each workload type. This ensures that increasing cache capacity for analytical workloads does not displace end-user data, as each cache structure operates independently with its own capacity allocation.
3Productivity
If query results are cached without discrimination, then cache hit ratio improves, but cache pollution from analytical workloads increases
Solution Approach 1:
The patent applies different caching policies to different workload types by maintaining separate cache structures. The first cache is optimized for end-user workloads with specific retention policies, while the second cache handles analytical workloads with different policies. This local differentiation allows each cache to achieve high hit ratios for its intended workload without causing pollution to the other.
Solution Approach 2:
The patent implements dynamic workload classification that determines cache usage based on the characteristics of each incoming query. By dynamically identifying whether a query is end-user or analytical in nature, the system routes it to the appropriate cache structure, ensuring optimal cache utilization and preventing pollution while maintaining high hit ratios.
Data Source
AI summary
Techniques for caching data in a database system include one or more non-transitory computer-readable media storing program instructions that, when executed, perform the method of receiving a request to access a database, determining a caching priority specified in the request, processing the request to generate query results, and after generating the query results, caching or not caching data from which the query results are generated based on the determined caching priority.