更新時(shí)間:2023-07-04 來源:黑馬程序員 瀏覽量:
在集群高并發(fā)環(huán)境下保證分布式唯一全局ID生成是一個(gè)具有挑戰(zhàn)性的問題。下面筆者將為大家提供幾種常見的解決方案:
UUID是一個(gè)128位的全局唯一標(biāo)識(shí)符,它可以在不同的計(jì)算機(jī)和時(shí)間上生成。UUID的生成是基于MAC地址、時(shí)間戳等信息,因此可以保證在分布式環(huán)境下的唯一性。您可以使用UUID庫或函數(shù)來生成唯一ID。
ZooKeeper是一個(gè)分布式協(xié)調(diào)服務(wù),可以用于生成分布式唯一序列節(jié)點(diǎn)。每個(gè)節(jié)點(diǎn)在ZooKeeper上創(chuàng)建一個(gè)臨時(shí)有序節(jié)點(diǎn),節(jié)點(diǎn)的名稱就可以作為唯一ID。這種方法需要維護(hù)ZooKeeper的穩(wěn)定性和性能,并且可能會(huì)對(duì)ZooKeeper集群施加一定的壓力。
在分布式環(huán)境中,可以使用數(shù)據(jù)庫的自增主鍵來生成唯一ID。每個(gè)節(jié)點(diǎn)將ID的生成請求發(fā)送到中央數(shù)據(jù)庫,數(shù)據(jù)庫逐個(gè)分配唯一的ID,并將其返回給節(jié)點(diǎn)。這種方法依賴于數(shù)據(jù)庫的性能和可用性,可能會(huì)成為性能瓶頸。
雪花算法是Twitter開源的一種分布式ID生成算法。它使用了一個(gè)64位的整數(shù),將整數(shù)的各個(gè)位段分配給不同的組成部分,包括時(shí)間戳、機(jī)器ID和序列號(hào)。通過合理配置這些部分,可以在分布式系統(tǒng)中生成唯一ID。雪花算法需要對(duì)機(jī)器ID進(jìn)行管理,確保每個(gè)節(jié)點(diǎn)有唯一的ID。
接下來我們看一個(gè)簡單的代碼示例,展示了如何使用Java語言實(shí)現(xiàn)雪花算法生成全局唯一ID:
public class SnowflakeIdGenerator { private final long epoch = 1625097600000L; // 自定義起始時(shí)間戳,例如2021-07-01 00:00:00的時(shí)間戳 private final long workerIdBits = 5L; private final long datacenterIdBits = 5L; private final long sequenceBits = 12L; private final long maxWorkerId = -1L ^ (-1L << workerIdBits); private final long maxDatacenterId = -1L ^ (-1L << datacenterIdBits); private final long workerIdShift = sequenceBits; private final long datacenterIdShift = sequenceBits + workerIdBits; private final long timestampShift = sequenceBits + workerIdBits + datacenterIdBits; private final long sequenceMask = -1L ^ (-1L << sequenceBits); private long workerId; private long datacenterId; private long sequence = 0L; private long lastTimestamp = -1L; public SnowflakeIdGenerator(long workerId, long datacenterId) { if (workerId > maxWorkerId || workerId < 0) { throw new IllegalArgumentException("Worker ID can't be greater than " + maxWorkerId + " or less than 0"); } if (datacenterId > maxDatacenterId || datacenterId < 0) { throw new IllegalArgumentException("Datacenter ID can't be greater than " + maxDatacenterId + " or less than 0"); } this.workerId = workerId; this.datacenterId = datacenterId; } public synchronized long generateId() { long timestamp = System.currentTimeMillis(); if (timestamp < lastTimestamp) { throw new RuntimeException("Clock moved backwards. Refusing to generate ID for " + (lastTimestamp - timestamp) + " milliseconds"); } if (lastTimestamp == timestamp) { sequence = (sequence + 1) & sequenceMask; if (sequence == 0) { timestamp = tilNextMillis(lastTimestamp); } } else { sequence = 0L; } lastTimestamp = timestamp; return ((timestamp - epoch) << timestampShift) | (datacenterId << datacenterIdShift) | (workerId << workerIdShift) | sequence; } private long tilNextMillis(long lastTimestamp) { long timestamp = System.currentTimeMillis(); while (timestamp <= lastTimestamp) { timestamp = System.currentTimeMillis(); } return timestamp; } }
使用示例:
public class Main { public static void main(String[] args) { SnowflakeIdGenerator idGenerator = new SnowflakeIdGenerator(1, 1); // 生成10個(gè)全局唯一ID for (int i = 0; i < 10; i++) { long id = idGenerator.generateId(); System.out.println("Generated ID: " + id); } } }
上述代碼中,SnowflakeIdGenerator類實(shí)現(xiàn)了雪花算法的邏輯,使用時(shí)間戳、工作節(jié)點(diǎn)ID和序列號(hào)來生成全局唯一ID。每個(gè)節(jié)點(diǎn)需要提供一個(gè)唯一的workerId和datacenterId來保證ID的唯一性。在高并發(fā)環(huán)境下,使用synchronized關(guān)鍵字確保線程安全,避免生成重復(fù)的ID。
無論我們選擇哪種方案,都需要根據(jù)具體的業(yè)務(wù)需求和系統(tǒng)架構(gòu)進(jìn)行權(quán)衡和實(shí)現(xiàn)。同時(shí),為了保證生成的ID的唯一性和高效性,建議對(duì)ID生成的算法和相關(guān)組件進(jìn)行充分的測試和評(píng)估。