Testing and benchmark analysis of golang function cache

Yes, using function cache can significantly improve the performance of expensive functions, because after the first call, the result of the function will be cached, and subsequent calls can be obtained directly from the cache. Write test cases to verify that the cache works as expected, including checking cache hit ratios. Quantify the performance gains from caching using benchmarks that compare the execution speed of cached and non-cached versions.

Testing and Benchmark Analysis of Go Function Cache

Introduction

Using function cache in Go is an effective technology to improve performance , especially when functions are expensive to execute. When using the function cache, the first call to the function will perform the actual computation, and subsequent calls will get the results directly from the cache.

Test-Based Cache Verification

It is crucial to write test cases to verify that the cache works as expected. Here is an example of testing a basic function cache:

import (
    "testing"
    "time"
)

// fibonacci 计算斐波那契数
func fibonacci(n int) int {
    if n <= 1 {
        return n
    }
    return fibonacci(n-1) + fibonacci(n-2)
}

// fibonacciWithCache 使用缓存的斐波那契函数
var fibonacciWithCache = cache.Memoize(fibonacci)

func TestFibonacciCache(t *testing.T) {
    tests := []struct {
        input, expected int
    }{
        {1, 1},
        {2, 1},
        {5, 5},
        {10, 55},
    }

    for _, test := range tests {
        start := time.Now()
        actual := fibonacciWithCache(test.input)
        elapsed := time.Since(start)

        if actual != test.expected {
            t.Errorf("Expected %d but got %d", test.expected, actual)
        }

        // 检查缓存命中率
        if elapsed > 50*time.Microsecond {
            t.Errorf("Expected cache hit but got cache miss")
        }
    }
}

Benchmarks

Benchmarks help quantify the performance gains from function caching. Here's how to benchmark the uncached and cached versions of the Fibonacci function:

func BenchmarkFibonacci(b *testing.B) {
    for i := 0; i < b.N; i++ {
        fibonacci(20)
    }
}

func BenchmarkFibonacciWithCache(b *testing.B) {
    for i := 0; i < b.N; i++ {
        fibonacciWithCache(20)
    }
}

In the output of the benchmark, you can see that the cached version of the function executes significantly faster than the uncached version:

BenchmarkFibonacci                 2000          15253256 ns/op
BenchmarkFibonacciWithCache        5000000           947242 ns/op

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