Prediction-Based Caching System for Search Latency Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional search systems experience latency in returning search results, which can slow down the search process and frustrate users, as they often require two seconds to display results after a search term is submitted, during which time users may continue typing ahead.
Innovation Solution
A prediction-based caching system that simultaneously searches a cache and a source for current requested information and predicts future requests, storing predicted results in the cache for faster retrieval, allowing for instant search results to be displayed while the user is still inputting characters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional search systems wait for user submission before returning results, then server load is reduced, but search latency increases and user experience deteriorates
Solution Approach 1:
The system performs preliminary actions by predicting future search queries based on current user input and proactively caching the results before they are actually requested. This allows the system to prepare search results in advance, reducing latency when users submit their searches while distributing the computational load over time rather than concentrating it all at once when queries are submitted.
Solution Approach 2:
The caching system serves itself by automatically identifying which search results to cache based on prediction algorithms, eliminating the need for manual curation. The system monitors user input patterns, predicts upcoming searches, and autonomously caches relevant results, thereby reducing server load and improving response times without requiring additional human intervention or resources.
2Speed
If search results are cached proactively, then retrieval speed increases, but cache memory usage increases
Solution Approach 1:
The system dynamically changes the parameter of cache content by storing complete search results (including images, descriptions, and metadata) rather than just basic query identifiers. This parameter change in what is cached enables faster and more comprehensive result delivery while the prediction algorithm ensures that only relevant future searches are cached, optimizing memory utilization.
Solution Approach 2:
The system applies partial action by caching only the top N predicted search results for each predicted query rather than caching all possible results. This selective caching approach balances memory constraints with the need for fast retrieval, storing enough information to satisfy anticipated user needs without unnecessarily consuming cache space.
3Measurement precision
If prediction algorithms analyze user input in real-time, then search accuracy improves, but computing resource consumption increases
Solution Approach 1:
The system uses inexpensive, lightweight prediction models that can be rapidly executed and discarded after each prediction cycle. Rather than relying on complex, resource-intensive algorithms, the system employs simple pattern-matching and frequency-based prediction methods that consume minimal computing resources while still providing adequate accuracy for caching decisions.
Solution Approach 2:
The prediction algorithm serves multiple functions simultaneously: it analyzes user input patterns, predicts future searches, determines which results to cache, and prioritizes caching decisions. This multi-functionality reduces the need for separate specialized algorithms, thereby lowering overall computing resource consumption while maintaining prediction accuracy.
Data Source
AI summary
Example embodiments provide a prediction-based caching system. The caching system receives an application program interface (API) request from a component of the client device. The request indicates a parameter for current requested information. The caching system causes a search of both a cache and a source for the current requested information based on the parameter. The caching system causes retrieval of the current requested information from one of the cache or the source. The caching system then transmits the current requested information to the component of the client device. The caching system also predicts a future request for information (or receives a predicted request for future information). The caching system retrieves predicted results based on the predicted request from the source, and stores the predicted results in a cache for faster retrieval.