@Slf4j
@Component
public class MySimpleJob implements SimpleJob {

    //  @Scheduled(cron = "0 0/1 * * * ?")
    @Override
    public void execute(ShardingContext shardingContext) {
        log.info(String.format("Thread ID: %s, 作业分片总数: %s, " +
                        "当前分片项: %s.当前参数: %s," +
                        "作业名称: %s.作业自定义参数: %s",
                Thread.currentThread().getId(),
                shardingContext.getShardingTotalCount(),
                shardingContext.getShardingItem(),
                shardingContext.getShardingParameter(),
                shardingContext.getJobName(),
                shardingContext.getJobParameter()
        ));
        // 分片大致如下：根据配置的分片参数执行相应的逻辑
        switch (context.getShardingItem()) {
            case 0: 
                // do something by sharding item 0
                break;
            case 1: 
                // do something by sharding item 1
                break;
            case 2: 
                // do something by sharding item 2
                break;
            // case n: ...
        }
    }
}

@Configuration
public class MyJobConfig {

    // job 名称
    private static final String JOB_NAME = "MySimpleJob";

    // 定时器cron参数
    private static final String CRON = "0 0/1 * * * ?";

    // 定时器分片
    private static final int SHARDING_TOTAL_COUNT = 1;

    // 分片参数
    private static final String SHARDING_ITEM_PARAMETERS = "0=Beijing,1=Shanghai,2=Guangzhou";

    // 自定义参数
    private static final String JOB_PARAMETERS = "parameter";

    @Resource
    private ZookeeperRegistryCenter regCenter;

    @Resource
    private JobEventConfiguration jobEventConfiguration;


    @Bean(initMethod = "init")
    public JobScheduler mySimpleJobScheduler(final MySimpleJob mySimpleJob) {

        LiteJobConfiguration liteJobConfiguration = ElasticJobUtils
                .getLiteJobConfiguration(mySimpleJob.getClass(), JOB_NAME, CRON,
                        SHARDING_TOTAL_COUNT, SHARDING_ITEM_PARAMETERS, JOB_PARAMETERS);
        // 参数：1.定时器实例，2.注册中心类，3.LiteJobConfiguration，
        //     3.历史轨迹（不需要可以省略）
        return new SpringJobScheduler(mySimpleJob, regCenter, liteJobConfiguration, jobEventConfiguration);
    }

}

/**
     * 获取 {@link LiteJobConfiguration} 对象
     *
     * @param jobClass               定时器实现类
     * @param jobName                定时器名称
     * @param cron                   定时参数
     * @param shardingTotalCount     作业分片总数
     * @param shardingItemParameters 当前参数 可以为null
     * @param jobParameters          作业自定义参数 可以为null
     * @return {@link LiteJobConfiguration}
     */
  public static LiteJobConfiguration getLiteJobConfiguration(
      final Class<? extends SimpleJob> jobClass,
      final String jobName,
      final String cron,
      final int shardingTotalCount,
      final String shardingItemParameters,
      final String jobParameters) {
  ...
    return ...;
  }

@Configuration
public class PropertiesSimpleJobConfig {

    @Resource
    private SpringJobSchedulerFactory springJobSchedulerFactory;

    @Bean(initMethod = "init")
    public JobScheduler propertiesSimpleJobScheduler(final PropertiesSimpleJob job) {
        // 参数：1.定时器实例，2.配置名称，3.是否开启历史轨迹
        return springJobSchedulerFactory.getSpringJobScheduler(job,"PropertiesSimpleJob", true);
    }

}

@Slf4j
@ElasticJobScheduler(
        name = "AnnotationSimpleJob", // 定时器名称
        cron = "0/8 * * * * ?", // 定时器表达式
    	shardingTotalCount = 1, // 作业分片总数 默认为1
        shardingItemParameters = "0=Beijing,1=Shanghai,2=Guangzhou",  // 分片序列号和参数用等号分隔 不需要参数可以不加
        jobParameters = "123", // 作业自定义参数 不需要参数可以不加
    	isEvent = true // 是否开启数据记录 默认为true
)
public class AnnotationSimpleJob implements SimpleJob {

    @Override
    public void execute(ShardingContext shardingContext) {
        log.info(String.format("Thread ID: %s, 作业分片总数: %s, " +
                        "当前分片项: %s.当前参数: %s," +
                        "作业名称: %s.作业自定义参数: %s",
                Thread.currentThread().getId(),
                shardingContext.getShardingTotalCount(),
                shardingContext.getShardingItem(),
                shardingContext.getShardingParameter(),
                shardingContext.getJobName(),
                shardingContext.getJobParameter()
        ));
    }
}