Dynamic Expression Cache for Online System Adaptability
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Solution Overview
Problem
Online systems face challenges in dynamically updating computations due to frequent changes in user interactions and system upgrades, which can be resource-intensive and complex, especially in social networking systems that need to continuously present relevant information to users.
Innovation Solution
The system dynamically incorporates expressions based on user attributes using a cache that selects the most efficient representation, such as postfix or tree representations, to evaluate computations efficiently, allowing for dynamic modifications without requiring system upgrades.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional systems use system upgrades to introduce changes in computations, then the system can adapt to new functionality, but the upgrade process becomes complex and resource-intensive
Solution Approach 1:
The system segments computation logic into separate, independently manageable expression components that can be modified without affecting the entire system. Expressions are stored as discrete units in a cache, allowing individual expressions to be updated, added, or removed without requiring system-wide upgrades.
Solution Approach 2:
The system creates and maintains copies of expression representations in a cache memory structure. These copied expressions can be evaluated repeatedly without modifying the original system code, enabling rapid adaptation through expression substitution rather than system upgrades.
2Adaptability or versatility
If system upgrades are performed frequently to incorporate new computations, then the system remains current with user needs, but significant resources are consumed during upgrades
Solution Approach 1:
Expressions are pre-compiled and stored in the cache in advance, with their representations prepared beforehand. When computation changes are needed, the system simply retrieves or updates expressions in the cache rather than performing resource-intensive compilation and system upgrades at runtime.
Solution Approach 2:
The system uses cached copies of expression representations that can be rapidly updated and re-evaluated without consuming the significant resources required for full system upgrades. This copying mechanism enables frequent adaptation with minimal resource expenditure.
3Manufacturing precision
If the system evaluates expressions multiple times using multiple entities, then comprehensive rankings can be generated, but computation time increases
Solution Approach 1:
Expression representations are pre-processed and cached in an optimized format before being applied to multiple entities. This preliminary preparation enables rapid evaluation across numerous entities without repeating the full computation each time, significantly reducing the time loss from multiple evaluations.
Data Source
AI summary
Online systems, for example, social networking systems evaluate expressions based on features describing relations between entities represented in the online system. These expressions are represented using an expression language. The expression language allows features to be specified as functions of attributes from user accounts. The expressions support use of variables to represent computations, for example, sub-expressions. The expressions are dynamic, since expressions can be specified and executed at call time. The same set of expressions is used many times, e.g., to compute the same function for multiple feature sets, for example, user accounts. Expressions are preferably represented using postfix representation. However some expressions, for example, expressions using variables are represented as trees. To optimize the expressions at runtime, the expressions are cached using a representation determined to be efficient for executing the expression. The cached representation of the expression is applied to multiple feature sets, for example, user accounts.