XXL-JOB是一个分布式任务调度平台,可以帮助我们实现定时任务的功能
在OJ挑战项目中,因为未完赛的竞赛在时时刻刻都会变成历史竞赛,所以我就引入XXL-JOB帮我实现一个任务,就是在每天的凌晨一天刷新一下redis中的未完赛的竞赛列表信息和完赛的竞赛列表信息
1.配置部署"调度中心"
1.1通过Docker镜像方式搭建调度中心
打开cmd,执行一下命令即可
docker pull xuxueli/xxl-job-admin:2.4.0
1.2初始化数据库
在MySQL执行下面的sql
sql
CREATE database if NOT EXISTS `xxl_job` default character set utf8mb4 collate utf8mb4_unicode_ci;
GRANT CREATE,DROP,SELECT, INSERT, UPDATE, DELETE ON xxl_job_dev.* TO 'ojtest'@'%';
use `xxl_job`;
SET NAMES utf8mb4;
CREATE TABLE `xxl_job_info`
(
`id` int(11) NOT NULL AUTO_INCREMENT,
`job_group` int(11) NOT NULL COMMENT '执行器主键ID',
`job_desc` varchar(255) NOT NULL,
`add_time` datetime DEFAULT NULL,
`update_time` datetime DEFAULT NULL,
`author` varchar(64) DEFAULT NULL COMMENT '作者',
`alarm_email` varchar(255) DEFAULT NULL COMMENT '报警邮件',
`schedule_type` varchar(50) NOT NULL DEFAULT 'NONE' COMMENT '调度类型',
`schedule_conf` varchar(128) DEFAULT NULL COMMENT '调度配置,值含义取决于调度类型',
`misfire_strategy` varchar(50) NOT NULL DEFAULT 'DO_NOTHING' COMMENT '调度过期策略',
`executor_route_strategy` varchar(50) DEFAULT NULL COMMENT '执行器路由策略',
`executor_handler` varchar(255) DEFAULT NULL COMMENT '执行器任务handler',
`executor_param` varchar(512) DEFAULT NULL COMMENT '执行器任务参数',
`executor_block_strategy` varchar(50) DEFAULT NULL COMMENT '阻塞处理策略',
`executor_timeout` int(11) NOT NULL DEFAULT '0' COMMENT '任务执行超时时间,单位秒',
`executor_fail_retry_count` int(11) NOT NULL DEFAULT '0' COMMENT '失败重试次数',
`glue_type` varchar(50) NOT NULL COMMENT 'GLUE类型',
`glue_source` mediumtext COMMENT 'GLUE源代码',
`glue_remark` varchar(128) DEFAULT NULL COMMENT 'GLUE备注',
`glue_updatetime` datetime DEFAULT NULL COMMENT 'GLUE更新时间',
`child_jobid` varchar(255) DEFAULT NULL COMMENT '子任务ID,多个逗号分隔',
`trigger_status` tinyint(4) NOT NULL DEFAULT '0' COMMENT '调度状态:0-停止,1-运行',
`trigger_last_time` bigint(13) NOT NULL DEFAULT '0' COMMENT '上次调度时间',
`trigger_next_time` bigint(13) NOT NULL DEFAULT '0' COMMENT '下次调度时间',
PRIMARY KEY (`id`)
) ENGINE = InnoDB
DEFAULT CHARSET = utf8mb4;
CREATE TABLE `xxl_job_log`
(
`id` bigint(20) NOT NULL AUTO_INCREMENT,
`job_group` int(11) NOT NULL COMMENT '执行器主键ID',
`job_id` int(11) NOT NULL COMMENT '任务,主键ID',
`executor_address` varchar(255) DEFAULT NULL COMMENT '执行器地址,本次执行的地址',
`executor_handler` varchar(255) DEFAULT NULL COMMENT '执行器任务handler',
`executor_param` varchar(512) DEFAULT NULL COMMENT '执行器任务参数',
`executor_sharding_param` varchar(20) DEFAULT NULL COMMENT '执行器任务分片参数,格式如 1/2',
`executor_fail_retry_count` int(11) NOT NULL DEFAULT '0' COMMENT '失败重试次数',
`trigger_time` datetime DEFAULT NULL COMMENT '调度-时间',
`trigger_code` int(11) NOT NULL COMMENT '调度-结果',
`trigger_msg` text COMMENT '调度-日志',
`handle_time` datetime DEFAULT NULL COMMENT '执行-时间',
`handle_code` int(11) NOT NULL COMMENT '执行-状态',
`handle_msg` text COMMENT '执行-日志',
`alarm_status` tinyint(4) NOT NULL DEFAULT '0' COMMENT '告警状态:0-默认、1-无需告警、2-告警成功、3-告警失败',
PRIMARY KEY (`id`),
KEY `I_trigger_time` (`trigger_time`),
KEY `I_handle_code` (`handle_code`),
KEY `I_jobid_jobgroup` (`job_id`,`job_group`),
KEY `I_job_id` (`job_id`)
) ENGINE = InnoDB
DEFAULT CHARSET = utf8mb4;
CREATE TABLE `xxl_job_log_report`
(
`id` int(11) NOT NULL AUTO_INCREMENT,
`trigger_day` datetime DEFAULT NULL COMMENT '调度-时间',
`running_count` int(11) NOT NULL DEFAULT '0' COMMENT '运行中-日志数量',
`suc_count` int(11) NOT NULL DEFAULT '0' COMMENT '执行成功-日志数量',
`fail_count` int(11) NOT NULL DEFAULT '0' COMMENT '执行失败-日志数量',
`update_time` datetime DEFAULT NULL,
PRIMARY KEY (`id`),
UNIQUE KEY `i_trigger_day` (`trigger_day`) USING BTREE
) ENGINE = InnoDB
DEFAULT CHARSET = utf8mb4;
CREATE TABLE `xxl_job_logglue`
(
`id` int(11) NOT NULL AUTO_INCREMENT,
`job_id` int(11) NOT NULL COMMENT '任务,主键ID',
`glue_type` varchar(50) DEFAULT NULL COMMENT 'GLUE类型',
`glue_source` mediumtext COMMENT 'GLUE源代码',
`glue_remark` varchar(128) NOT NULL COMMENT 'GLUE备注',
`add_time` datetime DEFAULT NULL,
`update_time` datetime DEFAULT NULL,
PRIMARY KEY (`id`)
) ENGINE = InnoDB
DEFAULT CHARSET = utf8mb4;
CREATE TABLE `xxl_job_registry`
(
`id` int(11) NOT NULL AUTO_INCREMENT,
`registry_group` varchar(50) NOT NULL,
`registry_key` varchar(255) NOT NULL,
`registry_value` varchar(255) NOT NULL,
`update_time` datetime DEFAULT NULL,
PRIMARY KEY (`id`),
UNIQUE KEY `i_g_k_v` (`registry_group`, `registry_key`, `registry_value`) USING BTREE
) ENGINE = InnoDB
DEFAULT CHARSET = utf8mb4;
CREATE TABLE `xxl_job_group`
(
`id` int(11) NOT NULL AUTO_INCREMENT,
`app_name` varchar(64) NOT NULL COMMENT '执行器AppName',
`title` varchar(12) NOT NULL COMMENT '执行器名称',
`address_type` tinyint(4) NOT NULL DEFAULT '0' COMMENT '执行器地址类型:0=自动注册、1=手动录入',
`address_list` text COMMENT '执行器地址列表,多地址逗号分隔',
`update_time` datetime DEFAULT NULL,
PRIMARY KEY (`id`)
) ENGINE = InnoDB
DEFAULT CHARSET = utf8mb4;
CREATE TABLE `xxl_job_user`
(
`id` int(11) NOT NULL AUTO_INCREMENT,
`username` varchar(50) NOT NULL COMMENT '账号',
`password` varchar(50) NOT NULL COMMENT '密码',
`role` tinyint(4) NOT NULL COMMENT '角色:0-普通用户、1-管理员',
`permission` varchar(255) DEFAULT NULL COMMENT '权限:执行器ID列表,多个逗号分割',
PRIMARY KEY (`id`),
UNIQUE KEY `i_username` (`username`) USING BTREE
) ENGINE = InnoDB
DEFAULT CHARSET = utf8mb4;
CREATE TABLE `xxl_job_lock`
(
`lock_name` varchar(50) NOT NULL COMMENT '锁名称',
PRIMARY KEY (`lock_name`)
) ENGINE = InnoDB
DEFAULT CHARSET = utf8mb4;
INSERT INTO `xxl_job_group`(`id`, `app_name`, `title`, `address_type`, `address_list`, `update_time`)
VALUES (1, 'xxl-job-executor-sample', '示例执行器', 0, NULL, '2018-11-03 22:21:31');
INSERT INTO `xxl_job_info`(`id`, `job_group`, `job_desc`, `add_time`, `update_time`, `author`, `alarm_email`,
`schedule_type`, `schedule_conf`, `misfire_strategy`, `executor_route_strategy`,
`executor_handler`, `executor_param`, `executor_block_strategy`, `executor_timeout`,
`executor_fail_retry_count`, `glue_type`, `glue_source`, `glue_remark`, `glue_updatetime`,
`child_jobid`)
VALUES (1, 1, '测试任务1', '2018-11-03 22:21:31', '2018-11-03 22:21:31', 'XXL', '', 'CRON', '0 0 0 * * ? *',
'DO_NOTHING', 'FIRST', 'demoJobHandler', '', 'SERIAL_EXECUTION', 0, 0, 'BEAN', '', 'GLUE代码初始化',
'2018-11-03 22:21:31', '');
INSERT INTO `xxl_job_user`(`id`, `username`, `password`, `role`, `permission`)
VALUES (1, 'admin', 'e10adc3949ba59abbe56e057f20f883e', 1, NULL);
INSERT INTO `xxl_job_lock` (`lock_name`)
VALUES ('schedule_lock');
commit;
1.3启动Docker中的XXL-JOB容器
打开cmd,执行下面的命令
注意下面的命令是一行的,如果直接复制下面的命令会报错,从第二行开始,每一行的开始位置按回车即可
docker run -e PARAMS="--spring.datasource.url=jdbc:mysql://172.17.0.2:3306/xxl_job?useUnicode=true&characterEncoding=UTF-8&autoReconnect=true&serverTimezone=Asia/Shanghai --spring.datasource.username=ojtest -spring.datasource.password=123456" -p
8080:8080 --name xxl-job-admin -d xuxueli/xxl-job-admin:2.4.0
1.4进入调度中心
成功启动容器上,即可进入任务调度中心
任务调度中心的地址: http://localhost:8080/xxl-job-admin/
默认的登录账号:admin
默认的登录密码:123456

1.5新增执行器

1.6新增任务

2.在项目中引入XXL-JOB
2.1 添加对应的依赖
XML
<dependency>
<groupId>com.xuxueli</groupId>
<artifactId>xxl-job-core</artifactId>
<version>2.4.0</version>
</dependency>
2.2 在配置文件中添加对应的配置
Matlab
xxl:
job:
admin:
addresses: http://localhost:8080/xxl-job-admin
accessToken: default_token
executor:
appname: ${spring.application.name}-executor
配置介绍:
xxl.job.admin.address是任务调度中心的地址
xxl.job.admin.accessToken是XXL-JOB用户执行器与调度中心之间的进行通信时的安全验证,它相当于一个密钥,用于确保只有合法的Executor才能与任务调度中心交互
xxl.job.admin.executor是上面添加的执行器的名称
2.3 在项目中创建一个配置类
java
import com.xxl.job.core.executor.impl.XxlJobSpringExecutor;
import lombok.extern.slf4j.Slf4j;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
@Configuration
@Slf4j
public class XxlJobConfig {
@Value("${xxl.job.admin.addresses}")
private String adminAddresses;
@Value("${xxl.job.accessToken}")
private String accessToken;
@Value("${xxl.job.executor.appname}")
private String appname;
@Bean
public XxlJobSpringExecutor xxlJobExecutor() {
log.info(">>>>>>>>>>> xxl-job config init.");
XxlJobSpringExecutor xxlJobSpringExecutor = new XxlJobSpringExecutor();
xxlJobSpringExecutor.setAdminAddresses(adminAddresses);
xxlJobSpringExecutor.setAppname(appname);
xxlJobSpringExecutor.setAccessToken(accessToken);
return xxlJobSpringExecutor;
}
}
2.4增加对应的Handler类
1.该类中有一个方法,该方法中包含了我们定时任务的内容
2.采用Bean的模式,每个定时任务对应一个方法
3.在对应的Handler方法上添加注解:@XxlJob(),注解有一个参数,就是在新增任务器时JobHandler,在新增任务器中JobHandler里填的值要和该方法名一样
4.使用上面的@XxlJob注解后,支持自动扫描任务并注入到Spring容器中
下面的代码是我在项目的定义的定时任务,看到这里的人可以自己实现一个逻辑,在examListOrganizeHandler方法里面写一个自己的逻辑即可,也可以写一个hello world
java
@Component
@Slf4j
public class ExamXxlJob {
@Autowired
private ExamMapper examMapper;
@Autowired
private RedisService redisService;
@XxlJob("examListOrganizeHandler")
public void examListOrganizeHandler() {
//统计哪些竞赛存入未完赛的列表 哪些竞赛应该存入历史竞赛 统计出来之后,在存入对应的缓存中
log.info("*** examListOrganizeHandler ***");
List<Exam> unFinishList = examMapper.selectList(new LambdaQueryWrapper<Exam>()
.select(Exam::getExamId, Exam::getTitle, Exam::getStartTime, Exam::getEndTime)
.gt(Exam::getEndTime, LocalDateTime.now())
.eq(Exam::getStatus, Constants.TRUE)
.orderByDesc(Exam::getCreateTime));
refreshCache(unFinishList,CacheConstants.EXAM_UNFINISHED_LIST);
List<Exam> historyList =examMapper.selectList(new LambdaQueryWrapper<Exam>()
.select(Exam::getExamId, Exam::getTitle, Exam::getStartTime, Exam::getEndTime)
.le(Exam::getEndTime, LocalDateTime.now())
.eq(Exam::getStatus, Constants.TRUE)
.orderByDesc(Exam::getCreateTime));
refreshCache(historyList,CacheConstants.EXAM_HISTORY_LIST);
}
public void refreshCache(List<Exam> examList,String examListLey) {
if (CollectionUtil.isEmpty(examList)) {
return;
}
Map<String, Exam> examMap = new HashMap<>();
List<Long> examIdList = new ArrayList<>();
for (Exam exam : examList) {
examMap.put(getDetailKey(exam.getExamId()), exam);
examIdList.add(exam.getExamId());
}
redisService.multiSet(examMap); //刷新详情缓存(竞赛基本信息) 批量插入缓存redis
redisService.deleteObject(examListLey); //将之前的缓存的key删掉,因为之前存的key可能会有问题,导致后面的插入有问题
redisService.rightPushAll(examListLey, examIdList); //刷新列表缓存
}
private String getDetailKey(Long examId) {
return CacheConstants.EXAM_DETAIL + examId;
}
}