Elastic-job与SpringBoot集成demo

1.引入jar

    com.dangdang
    elastic-job-lite-core


    com.dangdang
    elastic-job-lite-spring

2.注册中心配置

package com.alen.entity.config;

import com.dangdang.ddframe.job.reg.zookeeper.ZookeeperConfiguration;
import com.dangdang.ddframe.job.reg.zookeeper.ZookeeperRegistryCenter;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.boot.autoconfigure.condition.ConditionalOnExpression;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;

/**
 * 注册中心配置
 * 用于注册和协调作业分布式行为的组件，目前仅支持Zookeeper。
 */
@Configuration
@ConditionalOnExpression("'${regCenter.serverList}'.length() > 0")
public class RegistryCenterConfig {
    
    @Bean(initMethod = "init")
    public ZookeeperRegistryCenter regCenter(@Value("${regCenter.serverList}") final String serverList, @Value("${regCenter.namespace}") final String namespace) {
        return new ZookeeperRegistryCenter(new ZookeeperConfiguration(serverList, namespace));
    }
}

 

/**
 * 如果想把作业运行的内容写到DB中，我们需要用到另一个构造器， * 同时定义自己的JobEventConfiguration， * 目前来说实现这个接口的只有一个类JobEventRdbConfiguration， * 通过这个可以将作业运行的痕迹进行持久化到DB的操作。
 */
@Configuration
public class JobEventConfig {
    @Resource
    private DataSource dataSource;

    @Bean
    public JobEventConfiguration jobEventConfiguration() {
        return new JobEventRdbConfiguration(dataSource);
    }
}

3.作业配置

简单Simple类型作业配置

package com.alen.entity.config;

import com.alen.entity.job.simple.SpringSimpleJob;
import com.dangdang.ddframe.job.api.simple.SimpleJob;
import com.dangdang.ddframe.job.config.JobCoreConfiguration;
import com.dangdang.ddframe.job.config.simple.SimpleJobConfiguration;
import com.dangdang.ddframe.job.event.JobEventConfiguration;
import com.dangdang.ddframe.job.lite.api.JobScheduler;
import com.dangdang.ddframe.job.lite.config.LiteJobConfiguration;
import com.dangdang.ddframe.job.lite.spring.api.SpringJobScheduler;
import com.dangdang.ddframe.job.reg.zookeeper.ZookeeperRegistryCenter;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;

import javax.annotation.Resource;

@Configuration
public class SimpleJobConfig {
    //  注册中心配置
    @Resource
    private ZookeeperRegistryCenter regCenter;

    //将作业运行的痕迹进行持久化到DB的操作配置
    @Resource
    private JobEventConfiguration jobEventConfiguration;
    
    @Bean
    public SimpleJob simpleJob() {
        return new SpringSimpleJob();
    }
    
    @Bean(initMethod = "init")
    public JobScheduler simpleJobScheduler(final SimpleJob simpleJob, @Value("${simpleJob.cron}") final String cron, @Value("${simpleJob.shardingTotalCount}") final int shardingTotalCount,
                                           @Value("${simpleJob.shardingItemParameters}") final String shardingItemParameters) {
        return new SpringJobScheduler(simpleJob, regCenter, getLiteJobConfiguration(simpleJob.getClass(), cron, shardingTotalCount, shardingItemParameters), jobEventConfiguration);
    }

   /* 作业配置
    作业配置分为3级，分别是JobCoreConfiguration，JobTypeConfiguration和LiteJobConfiguration。
    LiteJobConfiguration使用JobTypeConfiguration，JobTypeConfiguration使用JobCoreConfiguration，层层嵌套。
    JobTypeConfiguration根据不同实现类型分为SimpleJobConfiguration，DataflowJobConfiguration和ScriptJobConfiguration。*/
    private LiteJobConfiguration getLiteJobConfiguration(final Class jobClass, final String cron, final int shardingTotalCount, final String shardingItemParameters) {
        return LiteJobConfiguration.newBuilder(new SimpleJobConfiguration(JobCoreConfiguration.newBuilder(
                jobClass.getName(), cron, shardingTotalCount).shardingItemParameters(shardingItemParameters).build(), jobClass.getCanonicalName())).overwrite(true).build();
    }
}

 

流式任务配置

package com.alen.entity.config;

import com.alen.entity.job.dataflow.SpringDataflowJob;
import com.dangdang.ddframe.job.api.dataflow.DataflowJob;
import com.dangdang.ddframe.job.config.JobCoreConfiguration;
import com.dangdang.ddframe.job.config.dataflow.DataflowJobConfiguration;
import com.dangdang.ddframe.job.event.JobEventConfiguration;
import com.dangdang.ddframe.job.lite.api.JobScheduler;
import com.dangdang.ddframe.job.lite.config.LiteJobConfiguration;
import com.dangdang.ddframe.job.lite.spring.api.SpringJobScheduler;
import com.dangdang.ddframe.job.reg.zookeeper.ZookeeperRegistryCenter;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;

import javax.annotation.Resource;

/**
 * 流式任务配置
 */
@Configuration
public class DataflowJobConfig {
  //  注册中心配置
    @Resource
    private ZookeeperRegistryCenter regCenter;

    //将作业运行的痕迹进行持久化到DB的操作配置
    @Resource
    private JobEventConfiguration jobEventConfiguration;
    
    @Bean
    public DataflowJob dataflowJob() {
        return new SpringDataflowJob();
    }
    
    @Bean(initMethod = "init")
    public JobScheduler dataflowJobScheduler(final DataflowJob dataflowJob, @Value("${dataflowJob.cron}") final String cron, @Value("${dataflowJob.shardingTotalCount}") final int shardingTotalCount,
                                           @Value("${dataflowJob.shardingItemParameters}") final String shardingItemParameters) {
        return new SpringJobScheduler(dataflowJob, regCenter, getLiteJobConfiguration(dataflowJob.getClass(), cron, shardingTotalCount, shardingItemParameters), jobEventConfiguration);
    }

    /* 作业配置
    作业配置分为3级，分别是JobCoreConfiguration，JobTypeConfiguration和LiteJobConfiguration。
    LiteJobConfiguration使用JobTypeConfiguration，JobTypeConfiguration使用JobCoreConfiguration，层层嵌套。
    JobTypeConfiguration根据不同实现类型分为SimpleJobConfiguration，DataflowJobConfiguration和ScriptJobConfiguration。*/
    private LiteJobConfiguration getLiteJobConfiguration(final Class jobClass, final String cron, final int shardingTotalCount, final String shardingItemParameters) {
        return LiteJobConfiguration.newBuilder(new DataflowJobConfiguration(JobCoreConfiguration.newBuilder(
                jobClass.getName(), cron, shardingTotalCount).shardingItemParameters(shardingItemParameters).build(), jobClass.getCanonicalName(), true)).overwrite(true).build();
    }
}