整合Elastic-Job(支持动态任务)
最近公司的项目需要用到分布式任务调度，在结合xxl-job，elastic-job，quartz多款开源框架后决定使用当当的Elastic-job。不知道大家有没有这样的需求，就是动态任务。之前比较了xxl-job和elastic-job发现，都只是支持注解或者配置以及后台添加现有的任务，不支持动态添加。比如：类似订单半小时后自动取消的场景。
xxl-job理论上来说是可以支持的，但是需要高度整合admin端的程序，然后开放对应的接口才可以给其他服务调用，这样本质直接改源码对后期的升级十分不便，最后放弃了xxl-job。elastic-job在移交Apache后的版本规划中，有提到API的开放，但是目前还没有稳定版，所以只能使用之前的2.1.5的版本来做。在Github搜了很多整合方案，最后决定选择下面的来实现。
因为底层本质上还是用elastic-job的东西。下面引入elastic-job坐标
com.dangdang
elastic-job-lite-spring
2.1.5
com.dangdang
elastic-job-lite-lifecycle
2.1.5
这是Github找到的集成方案，把代码clone下来，然后修改一下。github地址：https://github.com/xjzrc/elastic-job-lite-spring-boot-starter。因为要做的是动态的，所以这里没有直接使用maven坐标引入，直接将源码全部接入项目来使用并修改成自己想要的，这样比较灵活。项目采用的是SpringBoot，为简介代码，使用了Lombok。
先引入Zookeeper配置类
/**
* Zookeeper配置
* @author Nil
* @date 2020/9/14 11:24
*/
@Setter
@Getter
public class ZookeeperRegistryProperties {
/**
* 连接Zookeeper服务器的列表
* 包括IP地址和端口号
* 多个地址用逗号分隔
* 如: host1:2181,host2:2181
*/
private String serverLists;
/**
* Zookeeper的命名空间
*/
private String namespace;
/**
* 等待重试的间隔时间的初始值
* 单位：毫秒
*/
private int baseSleepTimeMilliseconds = 1000;
/**
* 等待重试的间隔时间的最大值
* 单位：毫秒
*/
private int maxSleepTimeMilliseconds = 3000;
/**
* 最大重试次数
*/
private int maxRetries = 3;
/**
* 连接超时时间
* 单位：毫秒
*/
private int connectionTimeoutMilliseconds = 15000;
/**
* 会话超时时间
* 单位：毫秒
*/
private int sessionTimeoutMilliseconds = 60000;
/**
* 连接Zookeeper的权限令牌
* 缺省为不需要权限验
*/
private String digest;
}引入Elastic-Job配置类，这个类主要是为了可以支持配置式的任务
/**
* 任务配置类
* @author Nil
* @date 2020/9/14 17:25
*/
@Getter
@Setter
@RefreshScope
@ConfigurationProperties(prefix = "spring.elasticjob")
public class ElasticJobProperties {
/**
* 注册中心
*/
private ZookeeperRegistryProperties zookeeper;
/**
* 简单作业配置(String为任务名)
*/
private Map simples = new LinkedHashMap<>(16);
/**
* 流式作业配置(String为任务名)
*/
private Map dataflows = new LinkedHashMap<>(16);
/**
* 脚本作业配置(String为任务名)
*/
private Map scripts = new LinkedHashMap<>(16);
@Getter
@Setter
public static class SimpleConfiguration extends JobConfiguration {
/**
* 作业类型
*/
private final JobType jobType = JobType.SIMPLE;
}
@Getter
@Setter
public static class ScriptConfiguration extends JobConfiguration {
/**
* 作业类型
*/
private final JobType jobType = JobType.SCRIPT;
/**
* 脚本型作业执行命令行
*/
private String scriptCommandLine;
}
@Getter
@Setter
public static class DataflowConfiguration extends JobConfiguration {
/**
* 作业类型
*/
private final JobType jobType = JobType.DATAFLOW;
/**
* 是否流式处理数据
* 如果流式处理数据, 则fetchData不返回空结果将持续执行作业
* 如果非流式处理数据, 则处理数据完成后作业结束
*/
private boolean streamingProcess = false;
}
@Getter
@Setter
public static class JobConfiguration {
/**
* 作业实现类，需实现ElasticJob接口
*/
private String jobClass;
/**
* 注册中心Bean的引用，需引用reg:zookeeper的声明
*/
private String registryCenterRef = ElasticJobAutoConfiguration.DEFAULT_REGISTRY_CENTER_NAME;
/**
* cron表达式，用于控制作业触发时间
*/
private String cron;
/**
* 作业分片总数
*/
private int shardingTotalCount = 1;
/**
* 分片序列号和参数用等号分隔，多个键值对用逗号分隔
* 分片序列号从0开始，不可大于或等于作业分片总数
* 如：0=a,1=b,2=c
*/
private String shardingItemParameters = "0=A";
/**
* 作业实例主键，同IP可运行实例主键不同, 但名称相同的多个作业实例
*/
private String jobInstanceId;
/**
* 作业自定义参数
* 作业自定义参数，可通过传递该参数为作业调度的业务方法传参，用于实现带参数的作业
* 例：每次获取的数据量、作业实例从数据库读取的主键等
*/
private String jobParameter;
/**
* 监控作业运行时状态
* 每次作业执行时间和间隔时间均非常短的情况，建议不监控作业运行时状态以提升效率。
* 因为是瞬时状态，所以无必要监控。请用户自行增加数据堆积监控。并且不能保证数据重复选取，应在作业中实现幂等性。
* 每次作业执行时间和间隔时间均较长的情况，建议监控作业运行时状态，可保证数据不会重复选取。
*/
private boolean monitorExecution = true;
/**
* 作业监控端口
* 建议配置作业监控端口, 方便开发者dump作业信息。
* 使用方法: echo “dump” | nc 127.0.0.1 9888
*/
private int monitorPort = -1;
/**
* 最大允许的本机与注册中心的时间误差秒数
* 如果时间误差超过配置秒数则作业启动时将抛异常
* 配置为-1表示不校验时间误差
*/
private int maxTimeDiffSeconds = -1;
/**
* 是否开启失效转移
*/
private boolean failover = false;
/**
* 是否开启错过任务重新执行
*/
private boolean misfire = true;
/**
* 作业分片策略实现类全路径
* 默认使用平均分配策略
* 详情参见：作业分片策略http://elasticjob.io/docs/elastic-job-lite/02-guide/job-sharding-strategy
*/
private String jobShardingStrategyClass;
/**
* 作业描述信息
*/
private String description;
/**
* 作业是否禁止启动
* 可用于部署作业时，先禁止启动，部署结束后统一启动
*/
private boolean disabled = false;
/**
* 本地配置是否可覆盖注册中心配置
* 如果可覆盖，每次启动作业都以本地配置为准
*/
private boolean overwrite = true;
/**
* 扩展异常处理类
*/
private String jobExceptionHandler = DefaultJobExceptionHandler.class.getCanonicalName();
/**
* 扩展作业处理线程池类
*/
private String executorServiceHandler = DefaultExecutorServiceHandler.class.getCanonicalName();
/**
* 修复作业服务器不一致状态服务调度间隔时间，配置为小于1的任意值表示不执行修复
* 单位：分钟
*/
private int reconcileIntervalMinutes = 10;
/**
* 作业事件追踪的数据源Bean引用
*/
private String eventTraceRdbDataSource = "dataSource";
/**
* 监听器
*/
private Listener listener;
@Getter
@Setter
public static class Listener {
/**
* 每台作业节点均执行的监听
* 若作业处理作业服务器的文件，处理完成后删除文件，可考虑使用每个节点均执行清理任务。
* 此类型任务实现简单，且无需考虑全局分布式任务是否完成，请尽量使用此类型监听器。
*
* 注意：类必须继承com.dangdang.ddframe.job.lite.api.listener.ElasticJobListener
*/
String listenerClass;
/**
* 分布式场景中仅单一节点执行的监听
* 若作业处理数据库数据，处理完成后只需一个节点完成数据清理任务即可。
* 此类型任务处理复杂，需同步分布式环境下作业的状态同步，提供了超时设置来避免作业不同步导致的死锁，请谨慎使用。
*
* 注意：类必须继承com.dangdang.ddframe.job.lite.api.listener.AbstractDistributeOnceElasticJobListener
*/
String distributedListenerClass;
/**
* 最后一个作业执行前的执行方法的超时时间
* 单位：毫秒
*/
Long startedTimeoutMilliseconds = Long.MAX_VALUE;
/**
* 最后一个作业执行后的执行方法的超时时间
* 单位：毫秒
*/
Long completedTimeoutMilliseconds = Long.MAX_VALUE;
}
}
} 创建自动配置类
/**
* elastic-job配置
* @author Nil
* @date 2020/9/14 11:24
*/
@Configuration
@RequiredArgsConstructor
@EnableConfigurationProperties(ElasticJobProperties.class)
public class ElasticJobAutoConfiguration {
public static final String DEFAULT_REGISTRY_CENTER_NAME = "elasticJobRegistryCenter";
private final ElasticJobProperties elasticJobProperties;
/**
* 初始化Zookeeper
* @return
*/
@Bean(name = DEFAULT_REGISTRY_CENTER_NAME, initMethod = "init")
@ConditionalOnMissingBean
public ZookeeperRegistryCenter regCenter() {
ZookeeperRegistryProperties zookeeperRegistryProperties = elasticJobProperties.getZookeeper();
ZookeeperConfiguration zookeeperConfiguration = new ZookeeperConfiguration(zookeeperRegistryProperties.getServerLists(), zookeeperRegistryProperties.getNamespace());
zookeeperConfiguration.setBaseSleepTimeMilliseconds(zookeeperRegistryProperties.getBaseSleepTimeMilliseconds());
zookeeperConfiguration.setConnectionTimeoutMilliseconds(zookeeperRegistryProperties.getConnectionTimeoutMilliseconds());
zookeeperConfiguration.setMaxSleepTimeMilliseconds(zookeeperRegistryProperties.getMaxSleepTimeMilliseconds());
zookeeperConfiguration.setSessionTimeoutMilliseconds(zookeeperRegistryProperties.getSessionTimeoutMilliseconds());
zookeeperConfiguration.setMaxRetries(zookeeperRegistryProperties.getMaxRetries());
zookeeperConfiguration.setDigest(zookeeperRegistryProperties.getDigest());
return new ZookeeperRegistryCenter(zookeeperConfiguration);
}
/**
* 初始化简单任务
* @return
*/
@Bean(initMethod = "init")
@ConditionalOnMissingBean
public SimpleJobInitialization simpleJobInitialization() {
return new SimpleJobInitialization(elasticJobProperties.getSimples());
}
/**
* 流式任务初始化
* @return
*/
@Bean(initMethod = "init")
@ConditionalOnMissingBean
public DataflowJobInitialization dataflowJobInitialization() {
return new DataflowJobInitialization(elasticJobProperties.getDataflows());
}
/**
* 脚本任务初始化
* @return
*/
@Bean(initMethod = "init")
@ConditionalOnMissingBean
@ConditionalOnBean(ZookeeperRegistryCenter.class)
public ScriptJobInitialization scriptJobInitialization() {
return new ScriptJobInitialization(elasticJobProperties.getScripts());
}
/**
* 动态任务初始化
* @return
*/
@Bean(initMethod = "init")
@ConditionalOnMissingBean
public DynamicJobInitialization dynamicJobInitialization() {
return new DynamicJobInitialization(this.regCenter());
}
}AbstractJobInitialization核心基类，主要用作初始化任务的操作
/**
* 任务初始化抽象类
* @author Nil
* @date 2020/9/14 19:24
*/
public abstract class AbstractJobInitialization implements ApplicationContextAware {
protected ApplicationContext applicationContext;
@Override
public void setApplicationContext(ApplicationContext applicationContext) {
this.applicationContext = applicationContext;
}
/**
* 初始化任务
* @param jobName 任务名
* @param jobType 任务类型
* @param configuration 配置
*/
protected void initJob(String jobName, JobType jobType, ElasticJobProperties.JobConfiguration configuration) {
//向spring容器中注册作业任务
ElasticJob elasticJob = registerElasticJob(jobName, configuration.getJobClass(), jobType);
//获取注册中心
ZookeeperRegistryCenter regCenter = getZookeeperRegistryCenter(configuration.getRegistryCenterRef());
//构建核心配置
JobCoreConfiguration jobCoreConfiguration = getJobCoreConfiguration(jobName, configuration);
//获取作业类型配置
JobTypeConfiguration jobTypeConfiguration = getJobTypeConfiguration(jobName, jobType, jobCoreConfiguration);
//获取Lite作业配置
LiteJobConfiguration liteJobConfiguration = getLiteJobConfiguration(jobTypeConfiguration, configuration);
//获取作业事件追踪的数据源配置
JobEventRdbConfiguration jobEventRdbConfiguration = getJobEventRdbConfiguration(configuration.getEventTraceRdbDataSource());
//获取作业监听器
ElasticJobListener[] elasticJobListeners = creatElasticJobListeners(configuration.getListener());
//注册作业
if (null == jobEventRdbConfiguration) {
new SpringJobScheduler(elasticJob, regCenter, liteJobConfiguration, elasticJobListeners).init();
} else {
new SpringJobScheduler(elasticJob, regCenter, liteJobConfiguration, jobEventRdbConfiguration, elasticJobListeners).init();
}
}
/**
* 获取作业类型配置
* @param jobName 任务名称
* @param jobType 任务类型
* @param jobCoreConfiguration 任务核心配置
* @return JobTypeConfiguration
*/
public abstract JobTypeConfiguration getJobTypeConfiguration(String jobName, JobType jobType, JobCoreConfiguration jobCoreConfiguration);
/**
* 获取作业任务实例
* @param jobName 任务名称
* @param jobType 任务类型
* @param strClass 任务类全路径
* @return ElasticJob
*/
private ElasticJob registerElasticJob(String jobName, String strClass, JobType jobType) {
switch (jobType) {
case SIMPLE:
return registerBean(jobName, strClass, SimpleJob.class);
case DATAFLOW:
return registerBean(jobName, strClass, DataflowJob.class);
default:
return null;
}
}
/**
* 获取注册中心
* @param registryCenterRef 注册中心引用
* @return ZookeeperRegistryCenter
*/
protected ZookeeperRegistryCenter getZookeeperRegistryCenter(String registryCenterRef) {
if (StringUtils.isBlank(registryCenterRef)) {
registryCenterRef = ElasticJobAutoConfiguration.DEFAULT_REGISTRY_CENTER_NAME;
}
if (!applicationContext.containsBean(registryCenterRef)) {
throw new ServiceException("not exist ZookeeperRegistryCenter [" + registryCenterRef + "] !");
}
return applicationContext.getBean(registryCenterRef, ZookeeperRegistryCenter.class);
}
/**
* 获取作业事件追踪的数据源配置
* @param eventTraceRdbDataSource 作业事件追踪的数据源Bean引用
* @return JobEventRdbConfiguration
*/
private JobEventRdbConfiguration getJobEventRdbConfiguration(String eventTraceRdbDataSource) {
if (StringUtils.isBlank(eventTraceRdbDataSource)) {
return null;
}
if (!applicationContext.containsBean(eventTraceRdbDataSource)) {
throw new ServiceException("not exist datasource [" + eventTraceRdbDataSource + "] !");
}
DataSource dataSource = (DataSource) applicationContext.getBean(eventTraceRdbDataSource);
return new JobEventRdbConfiguration(dataSource);
}
/**
* 构建Lite作业
* @param jobTypeConfiguration 任务类型
* @param jobConfiguration 任务配置
* @return LiteJobConfiguration
*/
private LiteJobConfiguration getLiteJobConfiguration(JobTypeConfiguration jobTypeConfiguration, ElasticJobProperties.JobConfiguration jobConfiguration) {
//构建Lite作业
return LiteJobConfiguration.newBuilder(Objects.requireNonNull(jobTypeConfiguration))
.monitorExecution(jobConfiguration.isMonitorExecution())
.monitorPort(jobConfiguration.getMonitorPort())
.maxTimeDiffSeconds(jobConfiguration.getMaxTimeDiffSeconds())
.jobShardingStrategyClass(jobConfiguration.getJobShardingStrategyClass())
.reconcileIntervalMinutes(jobConfiguration.getReconcileIntervalMinutes())
.disabled(jobConfiguration.isDisabled())
.overwrite(jobConfiguration.isOverwrite()).build();
}
/**
* 构建任务核心配置
* @param jobName 任务执行名称
* @param jobConfiguration 任务配置
* @return JobCoreConfiguration
*/
protected JobCoreConfiguration getJobCoreConfiguration(String jobName, ElasticJobProperties.JobConfiguration jobConfiguration) {
JobCoreConfiguration.Builder builder = JobCoreConfiguration.newBuilder(jobName, jobConfiguration.getCron(), jobConfiguration.getShardingTotalCount())
.shardingItemParameters(jobConfiguration.getShardingItemParameters())
.jobParameter(jobConfiguration.getJobParameter())
.failover(jobConfiguration.isFailover())
.misfire(jobConfiguration.isMisfire())
.description(jobConfiguration.getDescription());
if (StringUtils.isNotBlank(jobConfiguration.getJobExceptionHandler())) {
builder.jobProperties(JobProperties.JobPropertiesEnum.JOB_EXCEPTION_HANDLER.getKey(), jobConfiguration.getJobExceptionHandler());
}
if (StringUtils.isNotBlank(jobConfiguration.getExecutorServiceHandler())) {
builder.jobProperties(JobProperties.JobPropertiesEnum.EXECUTOR_SERVICE_HANDLER.getKey(), jobConfiguration.getExecutorServiceHandler());
}
return builder.build();
}
/**
* 获取监听器
* @param listener 监听器配置
* @return ElasticJobListener[]
*/
private ElasticJobListener[] creatElasticJobListeners(ElasticJobProperties.JobConfiguration.Listener listener) {
if (null == listener) {
return new ElasticJobListener[0];
}
List elasticJobListeners = new ArrayList<>(16);
//注册每台作业节点均执行的监听
ElasticJobListener elasticJobListener = registerBean(listener.getListenerClass(), listener.getListenerClass(), ElasticJobListener.class);
if (null != elasticJobListener) {
elasticJobListeners.add(elasticJobListener);
}
//注册分布式监听者
AbstractDistributeOnceElasticJobListener distributedListener = registerBean(listener.getDistributedListenerClass(), listener.getDistributedListenerClass(),
AbstractDistributeOnceElasticJobListener.class, listener.getStartedTimeoutMilliseconds(), listener.getCompletedTimeoutMilliseconds());
if (null != distributedListener) {
elasticJobListeners.add(distributedListener);
}
if (CollUtil.isEmpty(elasticJobListeners)) {
return new ElasticJobListener[0];
}
//集合转数组
ElasticJobListener[] elasticJobListenerArray = new ElasticJobListener[elasticJobListeners.size()];
for (int i = 0; i < elasticJobListeners.size(); i++) {
elasticJobListenerArray[i] = elasticJobListeners.get(i);
}
return elasticJobListenerArray;
}
/**
* 向spring容器中注册bean
* @param beanName bean名字
* @param strClass 类全路径
* @param tClass 类类型
* @param constructorArgValue 构造函数参数
* @param 泛型
* @return T
*/
protected T registerBean(String beanName, String strClass, Class tClass, Object... constructorArgValue) {
//判断是否配置了监听者
if (StringUtils.isBlank(strClass)) {
return null;
}
if (StringUtils.isBlank(beanName)) {
beanName = strClass;
}
//判断监听者是否已经在spring容器中存在
if (applicationContext.containsBean(beanName)) {
return applicationContext.getBean(beanName, tClass);
}
//不存在则创建并注册到Spring容器中
BeanDefinitionBuilder beanDefinitionBuilder = BeanDefinitionBuilder.rootBeanDefinition(strClass);
beanDefinitionBuilder.setScope(BeanDefinition.SCOPE_PROTOTYPE);
//设置参数
for (Object argValue : constructorArgValue) {
beanDefinitionBuilder.addConstructorArgValue(argValue);
}
getDefaultListableBeanFactory().registerBeanDefinition(beanName, beanDefinitionBuilder.getBeanDefinition());
return applicationContext.getBean(beanName, tClass);
}
/**
* 获取beanFactory
* @return DefaultListableBeanFactory
*/
private DefaultListableBeanFactory getDefaultListableBeanFactory() {
return (DefaultListableBeanFactory) ((ConfigurableApplicationContext) applicationContext).getBeanFactory();
}
} 分别初始化简单任务，流式任务，脚本任务
/**
* 流式任务初始化
* @author Nil
* @date 2020/9/14 19:15
*/
public class DataflowJobInitialization extends AbstractJobInitialization {
private Map dataflowConfigurationMap;
public DataflowJobInitialization(Map dataflowConfigurationMap) {
this.dataflowConfigurationMap = dataflowConfigurationMap;
}
public void init() {
if (CollUtil.isNotEmpty(dataflowConfigurationMap)) {
dataflowConfigurationMap.forEach((k, v) -> {
ElasticJobProperties.DataflowConfiguration configuration = dataflowConfigurationMap.get(k);
super.initJob(k, configuration.getJobType(), configuration);
});
}
}
@Override
public JobTypeConfiguration getJobTypeConfiguration(String jobName, JobType jobType, JobCoreConfiguration jobCoreConfiguration) {
ElasticJobProperties.DataflowConfiguration configuration = dataflowConfigurationMap.get(jobName);
return new DataflowJobConfiguration(jobCoreConfiguration, configuration.getJobClass(), configuration.isStreamingProcess());
}
} /**
* 简单任务初始化
* @author Nil
* @date 2020/9/14 19:14
*/
public class SimpleJobInitialization extends AbstractJobInitialization {
private Map simpleConfigurationMap;
public SimpleJobInitialization(Map simpleConfigurationMap) {
this.simpleConfigurationMap = simpleConfigurationMap;
}
public void init() {
if (CollUtil.isNotEmpty(simpleConfigurationMap)) {
simpleConfigurationMap.forEach((k, v) -> {
ElasticJobProperties.SimpleConfiguration configuration = simpleConfigurationMap.get(k);
super.initJob(k, configuration.getJobType(), configuration);
});
}
}
@Override
public JobTypeConfiguration getJobTypeConfiguration(String jobName, JobType jobType, JobCoreConfiguration jobCoreConfiguration) {
ElasticJobProperties.SimpleConfiguration configuration = simpleConfigurationMap.get(jobName);
return new SimpleJobConfiguration(jobCoreConfiguration, configuration.getJobClass());
}
} /**
* 脚本任务初始化
* @author Nil
* @date 2020/9/14 20:45
*/
public class ScriptJobInitialization extends AbstractJobInitialization {
private Map scriptConfigurationMap;
public ScriptJobInitialization(final Map scriptConfigurationMap) {
this.scriptConfigurationMap = scriptConfigurationMap;
}
public void init() {
if (CollUtil.isNotEmpty(scriptConfigurationMap)) {
scriptConfigurationMap.forEach((k, v) -> {
ElasticJobProperties.ScriptConfiguration configuration = scriptConfigurationMap.get(k);
super.initJob(k, configuration.getJobType(), configuration);
});
}
}
@Override
public JobTypeConfiguration getJobTypeConfiguration(String jobName, JobType jobType, JobCoreConfiguration jobCoreConfiguration) {
ElasticJobProperties.ScriptConfiguration configuration = scriptConfigurationMap.get(jobName);
return new ScriptJobConfiguration(jobCoreConfiguration, configuration.getScriptCommandLine());
}
} 下面就是核心部分，用来做动态任务的添加修改和删除，同时支持自动启动初始化任务，就可以满足大部分场景了。代码如下
/**
* 动态任务初始化(支持简单、流式任务)
* @author Nil
* @date 2020/9/14 19:22
*/
@Slf4j
public class DynamicJobInitialization extends AbstractJobInitialization {
private JobStatisticsAPI jobStatisticsAPI;
private JobSettingsAPI jobSettingsAPI;
public DynamicJobInitialization(ZookeeperRegistryCenter zookeeperRegistryCenter) {
this.jobStatisticsAPI = new JobStatisticsAPIImpl(zookeeperRegistryCenter);
this.jobSettingsAPI = new JobSettingsAPIImpl(zookeeperRegistryCenter);
}
public void init() {
Collection allJob = jobStatisticsAPI.getAllJobsBriefInfo();
if (CollUtil.isNotEmpty(allJob)) {
allJob.forEach(jobInfo -> {
// 已下线的任务
if (JobBriefInfo.JobStatus.CRASHED.equals(jobInfo.getStatus())) {
try {
Date currentDate = new Date();
CronExpression cronExpression = new CronExpression(jobInfo.getCron());
Date nextValidTimeAfter = cronExpression.getNextValidTimeAfter(currentDate);
// 表达式还生效的任务
if (ObjectUtil.isNotNull(nextValidTimeAfter)) {
this.initJobHandler(jobInfo.getJobName());
}
} catch (ParseException e) {
log.error(e.getMessage(), e);
}
}
});
}
}
/**
* 初始化任务操作
* @param jobName 任务名
*/
private void initJobHandler(String jobName) {
try {
JobSettings jobSetting = jobSettingsAPI.getJobSettings(jobName);
if (ObjectUtil.isNotNull(jobSetting)) {
String jobCode = StrUtil.subBefore(jobSetting.getJobName(), StrUtil.UNDERLINE, false);
JobClassEnum jobClassEnum = JobClassEnum.convert(jobCode);
if (ObjectUtil.isNotNull(jobClassEnum)) {
ElasticJobProperties.JobConfiguration configuration = new ElasticJobProperties.JobConfiguration();
configuration.setCron(jobSetting.getCron());
configuration.setJobParameter(jobSetting.getJobParameter());
configuration.setShardingTotalCount(jobSetting.getShardingTotalCount());
configuration.setDescription(jobSetting.getDescription());
configuration.setShardingItemParameters(jobSetting.getShardingItemParameters());
configuration.setJobClass(jobClassEnum.getClazz().getCanonicalName());
super.initJob(jobName, JobType.valueOf(jobSetting.getJobType()), configuration);
}
}
} catch (Exception e) {
log.error("初始化任务操作失败: {}", e.getMessage(), e);
}
}
/**
* 保存/更新任务
* @param job
* @param jobClass
*/
public void addOrUpdateJob(Job job, Class jobClass) {
ElasticJobProperties.JobConfiguration configuration = new ElasticJobProperties.JobConfiguration();
configuration.setCron(job.getCron());
configuration.setJobParameter(job.getJobParameter());
configuration.setShardingTotalCount(job.getShardingTotalCount());
configuration.setShardingItemParameters(job.getShardingItemParameters());
configuration.setJobClass(jobClass.getCanonicalName());
super.initJob(job.getJobName(), JobType.valueOf(job.getJobType()), configuration);
}
@Override
public JobTypeConfiguration getJobTypeConfiguration(String jobName, JobType jobType, JobCoreConfiguration jobCoreConfiguration) {
String jobCode = StrUtil.subBefore(jobName, StrUtil.UNDERLINE, false);
JobClassEnum jobClassEnum = JobClassEnum.convert(jobCode);
if (ObjectUtil.isNotNull(jobClassEnum)) {
if (JobType.SIMPLE.equals(jobType)) {
return new SimpleJobConfiguration(jobCoreConfiguration, jobClassEnum.getClazz().getCanonicalName());
} else if (JobType.DATAFLOW.equals(jobType)) {
return new DataflowJobConfiguration(jobCoreConfiguration, jobClassEnum.getClazz().getCanonicalName(), false);
}
}
return null;
}
}
在ElasticJobAutoConfiguration类中初始化动态任务
/**
* 动态任务初始化
* @return
*/
@Bean(initMethod = "init")
@ConditionalOnMissingBean
public DynamicJobInitialization dynamicJobInitialization() {
return new DynamicJobInitialization(this.regCenter());
}为什么是这样的实现？我发现每次重新发布服务后，现在的未执行的任务都会变成“已下线”，这可能跟Zookeeper有关，需要重新初始化才行，对于注解和配置式的，会自动初始化，但是动态添加的不会自动初始化。所以必须自己初始化，之前有个思路是自己建张表来维护定时，每次启动时进行初始化，但是这样太麻烦，后来实现使用elastic-job现有的API来实现，即启动时，遍历Zookeeper已有的节点，然后判断Cron表达式是否过期，如果还没有过期，则重新初始化任务，初始化时配置设置了会覆盖原来的配置，所以不会有影响。然后外层可以通过MQ来新增任务，在通过服务调用去指定对应的定时逻辑即可。
(不知道大家有没有更好的实现方案，可以初始化动态任务的)
而配置式的，可以直接在配置文件指定并实现即可
spring:
elasticjob:
#注册中心配置
zookeeper:
server-lists: 127.0.0.1:6181
namespace: elastic-job-spring-boot-stater-demo
#简单作业配置
simples:
#spring简单作业示例配置
spring-simple-job:
#配置简单作业，必须实现com.dangdang.ddframe.job.api.simple.SimpleJob
job-class: com.zen.spring.boot.demo.elasticjob.job.SpringSimpleJob
cron: 0/2 * * * * ?
sharding-total-count: 3
sharding-item-parameters: 0=Beijing,1=Shanghai,2=Guangzhou
#配置监听器
listener:
#配置每台作业节点均执行的监听，必须实现com.dangdang.ddframe.job.lite.api.listener.ElasticJobListener
listener-class: com.zen.spring.boot.demo.elasticjob.listener.MyElasticJobListener
#流式作业配置
dataflows:
#spring简单作业示例配置
spring-dataflow-job:
#配置简单作业，必须实现com.dangdang.ddframe.job.api.dataflow.DataflowJob
job-class: com.zen.spring.boot.demo.elasticjob.job.SpringDataflowJob
cron: 0/2 * * * * ?
sharding-total-count: 3
sharding-item-parameters: 0=Beijing,1=Shanghai,2=Guangzhou
streaming-process: true
#配置监听器
listener:
#配置分布式场景中仅单一节点执行的监听，必须实现com.dangdang.ddframe.job.lite.api.listener.AbstractDistributeOnceElasticJobListener
distributed-listener-class: com.zen.spring.boot.demo.elasticjob.listener.MyDistributeElasticJobListener
started-timeout-milliseconds: 5000
completed-timeout-milliseconds: 10000
#脚本作业配置
scripts:
#脚本作业示例配置
script-job:
cron: 0/2 * * * * ?
sharding-total-count: 3
sharding-item-parameters: 0=Beijing,1=Shanghai,2=Guangzhou
script-command-line: youPath/spring-boot-starter-demo/elastic-job-spring-boot-starter-demo/src/main/resources/script/demo.bat 以上整合基本可以满足现在的使用，如果大家有更好的整合方案也可以一起交流一下。比较期待移交Apache后的3的版本，这样可以有更多API的支持，而不用自己造轮子。