Created
January 29, 2019 17:25
-
-
Save lrita/674294a65c06f893d8db9b5492e09d60 to your computer and use it in GitHub Desktop.
分布式存储系统可靠性-注解
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
package main | |
import ( | |
"fmt" | |
"math" | |
) | |
func C(N, K int64) float64 { | |
a, b := 1.0, 1.0 | |
if N == 0 { | |
panic(fmt.Sprint("N ", N)) | |
} | |
if K == 0 { | |
return 1.0 | |
} | |
for i := N; i > N-K; i-- { | |
a *= float64(i) | |
} | |
for i := int64(1); i <= K; i++ { | |
b = b * float64(i) | |
} | |
return a / b | |
} | |
// 在N块盘的系统内,坏K块盘时,命中copyset的概率 | |
func pK(N, K, R, S int64) float64 { | |
var ( | |
sum float64 | |
n = K / R | |
) | |
for i := int64(1); i <= n; i++ { | |
sum += C(S, i) * C(N-i*R, K-i*R) | |
} | |
return sum / C(N, K) | |
} | |
// returns n! | |
func Factorial(n int64) float64 { | |
sum := 1.0 | |
for i := int64(1); i < n+1; i++ { | |
sum *= float64(i) | |
} | |
return sum | |
} | |
// 计算泊松分布概率 | |
func Poisson(lambda, T float64, K int64) float64 { | |
lambda *= T | |
return math.Pow(lambda, float64(K)) * | |
math.Pow(math.E, -1*lambda) / Factorial(K) | |
} | |
// 将N块磁盘的年故障率转换为每小时内的故障概率 | |
func ARF2Lambda(N int64, ARF float64) float64 { | |
return float64(N) * ARF / (365.0 * 24.0) | |
} | |
// P(N(T)=K) : N 个磁盘存储系统中T时间同时损坏K块盘的概率,年故障率ARF | |
func DiskFailRateOfK(N, T, K int64, ARF float64) float64 { | |
return Poisson(ARF2Lambda(N, ARF), float64(T), K) | |
} | |
// 副本数R的N 个磁盘存储系统中T时间内造成数据丢失的概率 | |
// 只统计 [R,2R-1]个副本情况下的丢失数据概率(大于R个情况下,在一遍情况下对结果影响比较小) | |
func LossDataInT(N, S, R, T int64, ARF float64) float64 { | |
sum := 0.0 | |
for K := R; K <= R*2; K++ { | |
sum += DiskFailRateOfK(N, T, K, ARF) * pK(N, K, R, S) | |
} | |
return sum | |
} | |
// 恢复故障时间为T时(单位:小时),一年内丢数据的概率 | |
func LossDataRate(N, S, R, T int64, ARF float64) float64 { | |
return 1.0 - math.Pow(1.0-LossDataInT(N, S, R, T, ARF), 365.0*24.0/float64(T)) | |
} | |
func main() { | |
println(LossDataInT(7200, 1376256, 3, 1, 0.04)) // -> 1.310834e-010 一小时内丢数据的概率 | |
println(LossDataRate(7200, 1376256, 3, 1, 0.04)) // -> 1.148291e-006 一年内丢数据的概率 | |
} |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment