本篇文章为你整理了基于雪花算法的增强版ID生成器(基于雪花算法的增强版id生成器怎么用)的详细内容,包含有基于雪花算法的增强版id生成器是什么 基于雪花算法的增强版id生成器怎么用 雪花算法生成id原理 雪花算法生成id长度可控吗 基于雪花算法的增强版ID生成器,希望能帮助你了解 基于雪花算法的增强版ID生成器。
public Sequence sequence() {
SequenceConfig sequenceConfig = new SimpleSequenceConfig();
return new Sequence(sequenceConfig);
使用序列器生成ID
@Autowired
private Sequence sequence;
public long generateId() {
return sequence.nextId();
目前提供两个配置类
io.github.mocreates.config.DefaultSequenceConfig
io.github.mocreates.config.SimpleSequenceConfig
前者需要显式地指定 workerId、datacenterId,可以结合数据库来使用,后者是利用网卡信息进行自适应
`node_info` varchar(512) NOT NULL,
`gmt_create` datetime NOT NULL DEFAULT CURRENT_TIMESTAMP,
`gmt_modify` datetime NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT=DB WorkerID Assigner for UID Generator;
配置 (利用主键自增来分配workerId, 解决分布式环境下手动指定workerId的痛点)
@Bean
public Sequence sequence(WorkerNodeMapper workerNodeMapper) throws UnknownHostException {
WorkerNode workerNode = new WorkerNode();
InetAddress localHost = InetAddress.getLocalHost();
workerNode.setNodeInfo(localHost.toString());
workerNodeMapper.insertSelective(workerNode);
DefaultSequenceConfig defaultSequenceConfig = new DefaultSequenceConfig();
defaultSequenceConfig.setWorkerId(workerNode.getId());
return new Sequence(defaultSequenceConfig);
使用序列器生成ID
@Autowired
private Sequence sequence;
public long generateId() {
return sequence.nextId();
JMH 性能测试
测试机硬件情况
MacBook Pro (13-inch, M1, 2020) 8C 16G
Sequence 配置参数
private static final DefaultSequenceConfig SEQUENCE_CONFIG = new DefaultSequenceConfig();
static {
SEQUENCE_CONFIG.setSequenceBits(22);
SEQUENCE_CONFIG.setWorkerIdBits(0);
SEQUENCE_CONFIG.setDatacenterIdBits(0);
SEQUENCE_CONFIG.setTwepoch(System.currentTimeMillis());
SEQUENCE_CONFIG.setWorkerId(0L);
SEQUENCE_CONFIG.setDatacenterId(0L);
private static final Sequence SEQUENCE = new Sequence(SEQUENCE_CONFIG);
JMH参数
@BenchmarkMode(Mode.Throughput)
@Threads(10)
@Warmup(iterations = 3, time = 10, timeUnit = TimeUnit.SECONDS)
@Measurement(iterations = 10, time = 10, timeUnit = TimeUnit.SECONDS)
@State(value = Scope.Benchmark)
@Fork(1)
@OutputTimeUnit(TimeUnit.SECONDS)
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