Caching Design Pattern example
Let’s create a simple C++ program that demonstrates caching. In this example, we’ll implement a function to calculate the nth Fibonacci number, and we’ll use caching to optimize repeated calculations.
Problem Statement
Calculate the nth Fibonacci number using caching to improve performance.
Explanation
We will create a caching mechanism to store previously calculated Fibonacci numbers so that we don’t need to recalculate them. This will reduce time complexity of our program for repeated calculation.
Below is the implementation of the above example:
C++
#include <iostream> #include <unordered_map> // Define a cache to store calculated Fibonacci numbers std::unordered_map< int , long long > fibCache; // Function to calculate the nth Fibonacci number with // caching long long fibonacciWithCache( int n) { // Check if the result is already in the cache if (fibCache.find(n) != fibCache.end()) { return fibCache[n]; } // Base case: Fibonacci(0) and Fibonacci(1) are 0 and 1, // respectively if (n == 0) { return 0; } else if (n == 1) { return 1; } // Recursive case: Calculate Fibonacci(n) by summing // Fibonacci(n-1) and Fibonacci(n-2) long long result = fibonacciWithCache(n - 1) + fibonacciWithCache(n - 2); // Cache the result for future use fibCache[n] = result; return result; } int main() { int n = 4; // Calculate and print the nth Fibonacci number using // caching long long result = fibonacciWithCache(n); std::cout << "Fibonacci(" << n << ") = " << result << std::endl; return 0; } |
Fibonacci(4) = 3
This example illustrates a simple use case of caching to optimize recursive calculations. However, keep in mind that for Fibonacci numbers, an iterative solution or more optimized algorithm would be more efficient than a purely recursive approach. The caching mechanism becomes particularly beneficial when dealing with more complex and time-consuming calculations.
Caching Design Pattern
In today’s digital world, speed and efficiency matter a lot. When we use apps and websites, we want things to happen quickly. But making applications run fast is a bit tricky. That’s where the caching design pattern comes in.
Imagine caching as a fast storage trick. It stores important data from apps in a special place so that the app doesn’t need to do the hard work repeatedly. Caching design patterns are clever ways to use this storage trick. They make apps quicker in various ways.
Important Topics for the Caching Design Pattern
- Understanding Caching
- Caching Design Pattern
- Caching Design Patterns
- Advantages of the Caching Design Pattern
- Disadvantages of the Caching Design Pattern
- Use Cases of Caching
- Caching Design Pattern example
- Conclusion