先上代碼,采用php腳本語言
<?php/* * Copyright (C) FatHong *//* 數(shù)據(jù)初始化,weight: 權重 */$hosts['a'] = array('weight' => 5, 'current_weight' => 0, 'count' => 0);$hosts['b'] = array('weight' => 3, 'current_weight' => 0, 'count' => 0);$hosts['c'] = array('weight' => 2, 'current_weight' => 0, 'count' => 0);$result = array();/* 模擬10次 */for ($i = 0; $i < 10; $i++) { round_robin($hosts, $result);}/* 輸出結果 */print_r($result);/* round robin 輪循 */function round_robin(&$hosts, &$result){ $total = 0; $best = null; foreach ($hosts as $key => $item) { $current = &$hosts[$key]; $weight = $current['weight']; $current['current_weight'] += $weight; $total += $weight; if ( ($best == null) || ($hosts[$best]['current_weight'] < $current['current_weight']) ) { $best = $key; } } $hosts[$best]['current_weight'] -= $total; $hosts[$best]['count']++; $result[] = $best;}
輸出結果:
Array
(
[0] => a
[1] => b
[2] => c
[3] => a
[4] => a
[5] => b
[6] => a
[7] => c
[8] => b
[9] => a
)
負載均衡的服務器中,其實現(xiàn)算法有種是round-robin權重輪循,就是后端的服務器列表中,給每個服務器標上權重,代表它被采用的機率。
這段代碼把最簡潔的流程剝離出來,沒考慮后端掛起等情況,可以知道它是怎么實現(xiàn)的,僅供參考。
-----------------------------------------------
小編hx注解:
附執(zhí)行時,每個key的變化,就比較好理解了。
每次執(zhí)行時current_weight加上weight,如果當前current_weight>=weight則命中,把命中的減去所有weight(本例中是10),然后不斷循環(huán)。
Array
(
[a] => Array
(
[weight] => 5
[current_weight] => -5
[count] => 1
)
[b] => Array
(
[weight] => 3
[current_weight] => 3
[count] => 0
)
[c] => Array
(
[weight] => 2
[current_weight] => 2
[count] => 0
)
)
Array
(
[a] => Array
(
[weight] => 5
[current_weight] => 0
[count] => 1
)
[b] => Array
(
[weight] => 3
[current_weight] => -4
[count] => 1
)
[c] => Array
(
[weight] => 2
[current_weight] => 4
[count] => 0
)
)
Array
(
[a] => Array
(
[weight] => 5
[current_weight] => 5
[count] => 1
)
[b] => Array
(
[weight] => 3
[current_weight] => -1
[count] => 1
)
[c] => Array
(
[weight] => 2
[current_weight] => -4
[count] => 1
)
)
Array
(
[a] => Array
(
[weight] => 5
[current_weight] => 0
[count] => 2
)
[b] => Array
(
[weight] => 3
[current_weight] => 2
[count] => 1
)
[c] => Array
(
[weight] => 2
[current_weight] => -2
[count] => 1
)
)
Array
(
[a] => Array
(
[weight] => 5
[current_weight] => -5
[count] => 3
)
[b] => Array
(
[weight] => 3
[current_weight] => 5
[count] => 1
)
[c] => Array
(
[weight] => 2
[current_weight] => 0
[count] => 1
)
)
Array
(
[a] => Array
(
[weight] => 5
[current_weight] => 0
[count] => 3
)
[b] => Array
(
[weight] => 3
[current_weight] => -2
[count] => 2
)
[c] => Array
(
[weight] => 2
[current_weight] => 2
[count] => 1
)
)
Array
(
[a] => Array
(
[weight] => 5
[current_weight] => -5
[count] => 4
)
[b] => Array
(
[weight] => 3
[current_weight] => 1
[count] => 2
)
[c] => Array
(
[weight] => 2
[current_weight] => 4
[count] => 1
)
)
Array
(
[a] => Array
(
[weight] => 5
[current_weight] => 0
[count] => 4
)
[b] => Array
(
[weight] => 3
[current_weight] => 4
[count] => 2
)
[c] => Array
(
[weight] => 2
[current_weight] => -4
[count] => 2
)
)
Array
(
[a] => Array
(
[weight] => 5
[current_weight] => 5
[count] => 4
)
[b] => Array
(
[weight] => 3
[current_weight] => -3
[count] => 3
)
[c] => Array
(
[weight] => 2
[current_weight] => -2
[count] => 2
)
)
Array
(
[a] => Array
(
[weight] => 5
[current_weight] => 0
[count] => 5
)
[b] => Array
(
[weight] => 3
[current_weight] => 0
[count] => 3
)
[c] => Array
(
[weight] => 2
[current_weight] => 0
[count] => 2
)
)
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