Stream Listening Cache Updater for Data Freshness
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Solution Overview
Problem
Service providers face challenges in providing timely data to consumers due to the spiky nature of consumer demand, leading to increased burden on storage systems and potential serving of stale data, which can result in consumer dissatisfaction.
Innovation Solution
Implementing a method that involves receiving and storing data in an application cache, monitoring data streams for changes, and using machine-learning models to predict user interactions and prepopulate caches, thereby refreshing TTL values and ensuring timely data delivery while reducing the processing burden on storage systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If longer TTL values are used, then data freshness is improved, but the chance of serving stale data increases
Solution Approach 1:
The system performs preliminary actions by prepopulating the cache with data from multiple sources (data store and data streams) before consumer requests arrive. This ensures that when consumers access data, fresh information is already available in the cache without requiring long TTL values, thus preventing stale data service while maintaining data freshness.
Solution Approach 2:
The system maintains continuous operation by simultaneously listening to data streams and updating the cache in real-time. This continuous updating mechanism ensures that cache data remains fresh without requiring extended TTL values, resolving the contradiction between data freshness and stale data prevention.
2Reliability
If shorter TTL values are used, then data freshness is improved, but the processing burden on storage systems increases
Solution Approach 1:
The system prepopulates the cache with data from both the data store and data streams before consumer requests arrive. This preliminary caching action reduces the frequency and burden of queries to the data store, allowing shorter TTL values to be used without increasing storage system processing burden, as the cache is continuously updated from multiple sources.
Solution Approach 2:
The system introduces data streams as an intermediary source that continuously provides updates to the cache. This intermediary mechanism reduces the direct processing burden on the data store by filtering and pre-processing data through the stream listener, enabling shorter TTL values without overwhelming the storage system.
3Loss of time
If cache is refreshed based on data streams, then data timeliness is improved, but system complexity increases
Solution Approach 1:
The system segments the caching functionality into distinct components: a data store for persistent storage, a data stream listener for real-time updates, and a cache for fast access. This segmentation allows each component to handle specific tasks independently, improving data timeliness through stream-based refreshing while managing complexity through modular architecture.
Solution Approach 2:
The cache serves multiple functions simultaneously: it stores data from the data store, receives real-time updates from data streams, and provides fast access to consumers. This multi-functionality improves data timeliness through comprehensive refreshing mechanisms while the unified cache structure avoids the complexity of multiple separate systems.
Data Source
AI summary
A system, process, and computer-readable medium for updating an application cache using a stream listening service is described. A stream listening service may monitor one or more data streams for content relating to a user. The stream listening service may forward the content along with time-to-live values to an application cache. A user may use an application to obtain information regarding the user's account, where the application obtains information from a data store and/or cached information from the application cache. The stream listening service, by forwarding current account information, obtained from listening to one or more streams, to the application cache, reduces traffic at the data store by providing current information from the data stream to the application cache.