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README
Apache-2.0

LTS用户文档

LTS(light-task-scheduler)主要用于解决分布式任务调度问题,支持实时任务,定时任务和Cron任务。有较好的伸缩性,扩展性,健壮稳定性而被多家公司使用,同时也希望开源爱好者一起贡献。

---> 底部有招人帖

项目地址

github地址: https://github.com/ltsopensource/light-task-scheduler

oschina地址: http://git.oschina.net/hugui/light-task-scheduler

例子: https://github.com/ltsopensource/lts-examples

文档地址(正在更新中,后面以这个为准): https://www.gitbook.com/book/qq254963746/lts/details

这两个地址都会同步更新。感兴趣,请加QQ群:109500214 (加群密码: hello world)一起探讨、完善。越多人支持,就越有动力去更新,喜欢记得右上角star哈。

1.7.2-SNAPSHOT(master)变更主要点

  1. 优化JobContext中的BizLogger,由原来的去掉了threadlocal,解决taskTracker多线程的问题, 去掉LtsLoggerFactory.getLogger()用法

框架概况

LTS 有主要有以下四种节点:

  • JobClient:主要负责提交任务, 并接收任务执行反馈结果。
  • JobTracker:负责接收并分配任务,任务调度。
  • TaskTracker:负责执行任务,执行完反馈给JobTracker。
  • LTS-Admin:(管理后台)主要负责节点管理,任务队列管理,监控管理等。

其中JobClient,JobTracker,TaskTracker节点都是无状态的。 可以部署多个并动态的进行删减,来实现负载均衡,实现更大的负载量, 并且框架采用FailStore策略使LTS具有很好的容错能力。

LTS注册中心提供多种实现(Zookeeper,redis等),注册中心进行节点信息暴露,master选举。(Mongo or Mysql)存储任务队列和任务执行日志, netty or mina做底层通信, 并提供多种序列化方式fastjson, hessian2, java等。

LTS支持任务类型:

  • 实时任务:提交了之后立即就要执行的任务。
  • 定时任务:在指定时间点执行的任务,譬如 今天3点执行(单次)。
  • Cron任务:CronExpression,和quartz类似(但是不是使用quartz实现的)譬如 0 0/1 * * * ?

支持动态修改任务参数,任务执行时间等设置,支持后台动态添加任务,支持Cron任务暂停,支持手动停止正在执行的任务(有条件),支持任务的监控统计,支持各个节点的任务执行监控,JVM监控等等.

架构图

LTS architecture

概念说明

节点组

  1. 英文名称 NodeGroup,一个节点组等同于一个小的集群,同一个节点组中的各个节点是对等的,等效的,对外提供相同的服务。
  2. 每个节点组中都有一个master节点,这个master节点是由LTS动态选出来的,当一个master节点挂掉之后,LTS会立马选出另外一个master节点,框架提供API监听接口给用户。

FailStore

  1. 顾名思义,这个主要是用于失败了存储的,主要用于节点容错,当远程数据交互失败之后,存储在本地,等待远程通信恢复的时候,再将数据提交。
  2. FailStore主要用户JobClient的任务提交,TaskTracker的任务反馈,TaskTracker的业务日志传输的场景下。
  3. FailStore目前提供几种实现:leveldb,rocksdb,berkeleydb,mapdb,ltsdb,用于可以自由选择使用哪种,用户也可以采用SPI扩展使用自己的实现。

流程图

下图是一个标准的实时任务执行流程。

LTS progress

LTS-Admin新版界面预览

LTS Admin 目前后台带有由ztajy提供的一个简易的认证功能. 用户名密码在auth.cfg中,用户自行修改.

特性

1、Spring支持

LTS可以完全不用Spring框架,但是考虑到很用用户项目中都是用了Spring框架,所以LTS也提供了对Spring的支持,包括Xml和注解,引入lts-spring.jar即可。

2、业务日志记录器

在TaskTracker端提供了业务日志记录器,供应用程序使用,通过这个业务日志器,可以将业务日志提交到JobTracker,这些业务日志可以通过任务ID串联起来,可以在LTS-Admin中实时查看任务的执行进度。

3、SPI扩展支持

SPI扩展可以达到零侵入,只需要实现相应的接口,并实现即可被LTS使用,目前开放出来的扩展接口有

  1. 对任务队列的扩展,用户可以不选择使用mysql或者mongo作为队列存储,也可以自己实现。
  2. 对业务日志记录器的扩展,目前主要支持console,mysql,mongo,用户也可以通过扩展选择往其他地方输送日志。

4、故障转移

当正在执行任务的TaskTracker宕机之后,JobTracker会立马将分配在宕机的TaskTracker的所有任务再分配给其他正常的TaskTracker节点执行。

5、节点监控

可以对JobTracker,TaskTracker节点进行资源监控,任务监控等,可以实时的在LTS-Admin管理后台查看,进而进行合理的资源调配。

6、多样化任务执行结果支持

LTS框架提供四种执行结果支持,EXECUTE_SUCCESSEXECUTE_FAILEDEXECUTE_LATEREXECUTE_EXCEPTION,并对每种结果采取相应的处理机制,譬如重试。

  • EXECUTE_SUCCESS: 执行成功,这种情况,直接反馈客户端(如果任务被设置了要反馈给客户端)。
  • EXECUTE_FAILED:执行失败,这种情况,直接反馈给客户端,不进行重试。
  • EXECUTE_LATER:稍后执行(需要重试),这种情况,不反馈客户端,重试策略采用1min,2min,3min的策略,默认最大重试次数为10次,用户可以通过参数设置修改这个重试次数。
  • EXECUTE_EXCEPTION:执行异常, 这种情况也会重试(重试策略,同上)

7、FailStore容错

采用FailStore机制来进行节点容错,Fail And Store,不会因为远程通信的不稳定性而影响当前应用的运行。具体FailStore说明,请参考概念说明中的FailStore说明。

项目编译打包

项目主要采用maven进行构建,目前提供shell脚本的打包。 环境依赖:Java(jdk1.6+) Maven

用户使用一般分为两种:

1、Maven构建

可以通过maven命令将lts的jar包上传到本地仓库中。在父pom.xml中添加相应的repository,并用deploy命令上传即可。具体引用方式可以参考lts中的例子即可。

2、直接Jar引用

需要将lts的各个模块打包成单独的jar包,并且将所有lts依赖包引入。具体引用哪些jar包可以参考lts中的例子即可。

JobTracker和LTS-Admin部署

提供(cmd)windows(shell)linux两种版本脚本来进行编译和部署:

  1. 运行根目录下的sh build.shbuild.cmd脚本,会在dist目录下生成lts-{version}-bin文件夹

  2. 下面是其目录结构,其中bin目录主要是JobTracker和LTS-Admin的启动脚本。jobtracker 中是 JobTracker的配置文件和需要使用到的jar包,lts-admin是LTS-Admin相关的war包和配置文件。 lts-{version}-bin的文件结构

-- lts-${version}-bin
    |-- bin
    |   |-- jobtracker.cmd
    |   |-- jobtracker.sh
    |   |-- lts-admin.cmd
    |   |-- lts-admin.sh
    |   |-- lts-monitor.cmd
    |   |-- lts-monitor.sh
    |   |-- tasktracker.sh
    |-- conf
    |   |-- log4j.properties
    |   |-- lts-admin.cfg
    |   |-- lts-monitor.cfg
    |   |-- readme.txt
    |   |-- tasktracker.cfg
    |   |-- zoo
    |       |-- jobtracker.cfg
    |       |-- log4j.properties
    |       |-- lts-monitor.cfg
    |-- lib
    |   |-- *.jar
    |-- war
        |-- jetty
        |   |-- lib
        |       |-- *.jar
        |-- lts-admin.war
  1. JobTracker启动。如果你想启动一个节点,直接修改下conf/zoo下的配置文件,然后运行 sh jobtracker.sh zoo start即可,如果你想启动两个JobTracker节点,那么你需要拷贝一份zoo,譬如命名为zoo2,修改下zoo2下的配置文件,然后运行sh jobtracker.sh zoo2 start即可。logs文件夹下生成jobtracker-zoo.out日志。
  2. LTS-Admin启动.修改conf/lts-monitor.cfgconf/lts-admin.cfg下的配置,然后运行bin下的sh lts-admin.shlts-admin.cmd脚本即可。logs文件夹下会生成lts-admin.out日志,启动成功在日志中会打印出访问地址,用户可以通过这个访问地址访问了。

JobClient(部署)使用

需要引入lts的jar包有lts-jobclient-{version}.jarlts-core-{version}.jar 及其它第三方依赖jar。

API方式启动

JobClient jobClient = new RetryJobClient();
jobClient.setNodeGroup("test_jobClient");
jobClient.setClusterName("test_cluster");
jobClient.setRegistryAddress("zookeeper://127.0.0.1:2181");
jobClient.start();

// 提交任务
Job job = new Job();
job.setTaskId("3213213123");
job.setParam("shopId", "11111");
job.setTaskTrackerNodeGroup("test_trade_TaskTracker");
// job.setCronExpression("0 0/1 * * * ?");  // 支持 cronExpression表达式
// job.setTriggerTime(new Date()); // 支持指定时间执行
Response response = jobClient.submitJob(job);

Spring XML方式启动

<bean id="jobClient" class="com.github.ltsopensource.spring.JobClientFactoryBean">
    <property name="clusterName" value="test_cluster"/>
    <property name="registryAddress" value="zookeeper://127.0.0.1:2181"/>
    <property name="nodeGroup" value="test_jobClient"/>
    <property name="masterChangeListeners">
        <list>
            <bean class="com.github.ltsopensource.example.support.MasterChangeListenerImpl"/>
        </list>
    </property>
    <property name="jobFinishedHandler">
        <bean class="com.github.ltsopensource.example.support.JobFinishedHandlerImpl"/>
    </property>
    <property name="configs">
        <props>
            <!-- 参数 -->
            <prop key="job.fail.store">leveldb</prop>
        </props>
    </property>
</bean>

Spring 全注解方式

@Configuration
public class LTSSpringConfig {

    @Bean(name = "jobClient")
    public JobClient getJobClient() throws Exception {
        JobClientFactoryBean factoryBean = new JobClientFactoryBean();
        factoryBean.setClusterName("test_cluster");
        factoryBean.setRegistryAddress("zookeeper://127.0.0.1:2181");
        factoryBean.setNodeGroup("test_jobClient");
        factoryBean.setMasterChangeListeners(new MasterChangeListener[]{
                new MasterChangeListenerImpl()
        });
        Properties configs = new Properties();
        configs.setProperty("job.fail.store", "leveldb");
        factoryBean.setConfigs(configs);
        factoryBean.afterPropertiesSet();
        return factoryBean.getObject();
    }
}

TaskTracker(部署使用)

需要引入lts的jar包有lts-tasktracker-{version}.jarlts-core-{version}.jar 及其它第三方依赖jar。

定义自己的任务执行类

public class MyJobRunner implements JobRunner {
    @Override
    public Result run(JobContext jobContext) throws Throwable {
        try {
            // TODO 业务逻辑
            // 会发送到 LTS (JobTracker上)
            jobContext.getBizLogger().info("测试,业务日志啊啊啊啊啊");

        } catch (Exception e) {
            return new Result(Action.EXECUTE_FAILED, e.getMessage());
        }
        return new Result(Action.EXECUTE_SUCCESS, "执行成功了,哈哈");
    }
}

API方式启动

TaskTracker taskTracker = new TaskTracker();
taskTracker.setJobRunnerClass(MyJobRunner.class);
taskTracker.setRegistryAddress("zookeeper://127.0.0.1:2181");
taskTracker.setNodeGroup("test_trade_TaskTracker");
taskTracker.setClusterName("test_cluster");
taskTracker.setWorkThreads(20);
taskTracker.start();

Spring XML方式启动

<bean id="taskTracker" class="com.github.ltsopensource.spring.TaskTrackerAnnotationFactoryBean" init-method="start">
    <property name="jobRunnerClass" value="com.github.ltsopensource.example.support.MyJobRunner"/>
    <property name="bizLoggerLevel" value="INFO"/>
    <property name="clusterName" value="test_cluster"/>
    <property name="registryAddress" value="zookeeper://127.0.0.1:2181"/>
    <property name="nodeGroup" value="test_trade_TaskTracker"/>
    <property name="workThreads" value="20"/>
    <property name="masterChangeListeners">
        <list>
            <bean class="com.github.ltsopensource.example.support.MasterChangeListenerImpl"/>
        </list>
    </property>
    <property name="configs">
        <props>
            <prop key="job.fail.store">leveldb</prop>
        </props>
    </property>
</bean>

Spring注解方式启动

@Configuration
public class LTSSpringConfig implements ApplicationContextAware {
    private ApplicationContext applicationContext;
    @Override
    public void setApplicationContext(ApplicationContext applicationContext) throws BeansException {
        this.applicationContext = applicationContext;
    }
	@Bean(name = "taskTracker")
    public TaskTracker getTaskTracker() throws Exception {
        TaskTrackerAnnotationFactoryBean factoryBean = new TaskTrackerAnnotationFactoryBean();
        factoryBean.setApplicationContext(applicationContext);
        factoryBean.setClusterName("test_cluster");
        factoryBean.setJobRunnerClass(MyJobRunner.class);
        factoryBean.setNodeGroup("test_trade_TaskTracker");
        factoryBean.setBizLoggerLevel("INFO");
        factoryBean.setRegistryAddress("zookeeper://127.0.0.1:2181");
        factoryBean.setMasterChangeListeners(new MasterChangeListener[]{
                new MasterChangeListenerImpl()
        });
        factoryBean.setWorkThreads(20);
        Properties configs = new Properties();
        configs.setProperty("job.fail.store", "leveldb");
        factoryBean.setConfigs(configs);

        factoryBean.afterPropertiesSet();
//        factoryBean.start();
        return factoryBean.getObject();
    }
}

参数说明

参数说明

使用建议

一般在一个JVM中只需要一个JobClient实例即可,不要为每种任务都新建一个JobClient实例,这样会大大的浪费资源,因为一个JobClient可以提交多种任务。相同的一个JVM一般也尽量保持只有一个TaskTracker实例即可,多了就可能造成资源浪费。当遇到一个TaskTracker要运行多种任务的时候,请参考下面的 "一个TaskTracker执行多种任务"。

一个TaskTracker执行多种任务

有的时候,业务场景需要执行多种任务,有些人会问,是不是要每种任务类型都要一个TaskTracker去执行。我的答案是否定的,如果在一个JVM中,最好使用一个TaskTracker去运行多种任务,因为一个JVM中使用多个TaskTracker实例比较浪费资源(当然当你某种任务量比较多的时候,可以将这个任务单独使用一个TaskTracker节点来执行)。那么怎么才能实现一个TaskTracker执行多种任务呢。下面是我给出来的参考例子。

/**
 * 总入口,在 taskTracker.setJobRunnerClass(JobRunnerDispatcher.class)
 * JobClient 提交 任务时指定 Job 类型  job.setParam("type", "aType")
 */
public class JobRunnerDispatcher implements JobRunner {

    private static final ConcurrentHashMap<String/*type*/, JobRunner>
            JOB_RUNNER_MAP = new ConcurrentHashMap<String, JobRunner>();

    static {
        JOB_RUNNER_MAP.put("aType", new JobRunnerA()); // 也可以从Spring中拿
        JOB_RUNNER_MAP.put("bType", new JobRunnerB());
    }

    @Override
    public Result run(JobContext jobContext) throws Throwable {
        Job job = jobContext.getJob();
        String type = job.getParam("type");
        return JOB_RUNNER_MAP.get(type).run(job);
    }
}

class JobRunnerA implements JobRunner {
    @Override
    public Result run(JobContext jobContext) throws Throwable {
        //  TODO A类型Job的逻辑
        return null;
    }
}

class JobRunnerB implements JobRunner {
    @Override
    public Result run(JobContext jobContext) throws Throwable {
        // TODO B类型Job的逻辑
        return null;
    }
}

TaskTracker的JobRunner测试

一般在编写TaskTracker的时候,只需要测试JobRunner的实现逻辑是否正确,又不想启动LTS进行远程测试。为了方便测试,LTS提供了JobRunner的快捷测试方法。自己的测试类集成com.github.ltsopensource.tasktracker.runner.JobRunnerTester即可,并实现initContextnewJobRunner方法即可。如lts-examples中的例子:

public class TestJobRunnerTester extends JobRunnerTester {

    public static void main(String[] args) throws Throwable {
        //  Mock Job 数据
        Job job = new Job();
        job.setTaskId("2313213");

        JobContext jobContext = new JobContext();
        jobContext.setJob(job);

        JobExtInfo jobExtInfo = new JobExtInfo();
        jobExtInfo.setRetry(false);

        jobContext.setJobExtInfo(jobExtInfo);

        // 运行测试
        TestJobRunnerTester tester = new TestJobRunnerTester();
        Result result = tester.run(jobContext);
        System.out.println(JSON.toJSONString(result));
    }

    @Override
    protected void initContext() {
        // TODO 初始化Spring容器
    }

    @Override
    protected JobRunner newJobRunner() {
        return new TestJobRunner();
    }
}

Spring Quartz Cron任务无缝接入

对于Quartz的Cron任务只需要在Spring配置中增加一下代码就可以接入LTS平台

<bean class="com.github.ltsopensource.spring.quartz.QuartzLTSProxyBean">
    <property name="clusterName" value="test_cluster"/>
    <property name="registryAddress" value="zookeeper://127.0.0.1:2181"/>
    <property name="nodeGroup" value="quartz_test_group"/>
</bean>

Spring Boot 支持

@SpringBootApplication
@EnableJobTracker       // 启动JobTracker
@EnableJobClient        // 启动JobClient
@EnableTaskTracker      // 启动TaskTracker
@EnableMonitor          // 启动Monitor
public class Application {
    public static void main(String[] args) {
        SpringApplication.run(Application.class, args);
    }
}

剩下的就只是在application.properties中添加相应的配置就行了, 具体见lts-example中的com.github.ltsopensource.examples.springboot包下的例子

多网卡选择问题

当机器有内网两个网卡的时候,有时候,用户想让LTS的流量走外网网卡,那么需要在host中,把主机名称的映射地址改为外网网卡地址即可,内网同理。

关于节点标识问题

如果在节点启动的时候设置节点标识,LTS会默认设置一个UUID为节点标识,可读性会比较差,但是能保证每个节点的唯一性,如果用户能自己保证节点标识的唯一性,可以通过 setIdentity 来设置,譬如如果每个节点都是部署在一台机器(一个虚拟机)上,那么可以将identity设置为主机名称

SPI扩展说明

支持JobLogger,JobQueue等等的SPI扩展

和其它解决方案比较

LTS-Admin使用jetty启动(默认),不定期挂掉解决方案

issue#389

招人!!!

工作年限 三年以上

学历要求 本科

期望层级 P6(资深Java工程师)/P7(技术专家)

岗位描述

会员平台,负责阿里巴巴集团的用户体系,支持集团内各线业务线用户类需求,支持集团对外合作的用户通和业务通。 包括各个端的用户登录&授权、Session体系、注册、账户管理、账户安全等功能,底层的用户信息服务,会话和凭证管理等等,是集团最核心的产品线之一,每天承载千亿次调用量、峰值千万QPS、以及分布全球的混合云架构等等。

作为软件工程师,你将会在我们的核心产品上工作,这些产品为我们的商业基础设施提供关键功能, 取决于你的兴趣和经验,你可以在如下的一个或多个领域工作:全球化,用户体验,数据安全,机器学习,系统高可用性等等。

  1. 独立完成中小型项目的系统分析、设计,并主导完成详细设计和编码的任务,确保项目的进度和质量;
  2. 能够在团队中完成code review的任务,确保相关代码的有效性和正确性,并能够通过code review提供相关性能以及稳定性的建议;
  3. 参与建设通用、灵活、智能的业务支撑平台,支撑上层多场景的复杂业务。 岗位要求
  4. 扎实的java编程基础,熟悉常用的Java开源框架;
  5. 具有基于数据库、缓存、分布式存储开发高性能、高可用数据应用的实际经验,熟练掌握LINUX操作系统;
  6. 具备良好的识别和设计通用框架及模块的能力;
  7. 热爱技术,工作认真、严谨,对系统质量有近乎苛刻的要求意识,善于沟通与团队协作;
  8. 具备大型电子商务网站或金融行业核心系统开发、设计工作经验者优先;
  9. 具备大数据处理、算法、机器学习类工作经验优先。 感兴趣,可以发简历到 hugui.hg@alibaba-inc.com 欢迎投递
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简介

分布式任务调度框架, 支持 实时任务;支持定时任务 (如:3天之后执行);CronExpression 任务(如:0 0/1 * * * ?) 展开 收起
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