开源基于docker的任务调度器pipeline，比`quartzs` 更强大的分布式任务调度器

本文主要是介绍开源基于docker的任务调度器pipeline，比`quartzs` 更强大的分布式任务调度器，对大家解决编程问题具有一定的参考价值，需要的程序猿们随着小编来一起学习吧！

pipeline 分布式任务调度器

目标：基于docker的布式任务调度器, 比quartzs,xxl-job 更强大的分布式任务调度器。

可以将要执行的任务打包为docker镜像，或者选择已有镜像，自定义脚本程序，通过pipeline框架来实现调度。

开源地址： https://github.com/jadepeng/docker-pipeline

架构

pipeline master 中心节点，管理和调度任务
pipeline agent 执行任务的节点，接收到任务后，调用docker执行pipeline任务

功能特性 && TODO List

分布式框架，高可用，服务注册与状态维护
Agent执行任务
rolling日志接口
运行老版本pipeline任务
支持定时执行任务(固定周期和cron表达式)
快速创建任务，支持python、node等脚本程序直接执行
- python、java等基础镜像
- 快速docker镜像任务API
- 快速创建脚本任务
根据资源配额（内存、CPU）调度任务, 运行任务需要指定资源配额
agent 增加label标识，调度时可以调度到指定label的agent，比如gpu=true
增加任务管理web, 管理提交任务、查询运行日志等
- 复用腾讯bk-job 网页
- 修改bk-job前端，适配pipeline

进展

2021.07.31

支持定时执行任务(固定周期和cron表达式)
增加分布式mongodb锁，多master时，同时只能有一个master schedule任务

2021.07.28

新增运行老版本pipeline任务能力
增加日志接口

2021.07.27

引入bk-job的ui，待修改

2021.07.21

Master 调用 agent执行任务
agnet 启动docker执行任务

2021.07.19

基于jhipster搭建框架
分布式实现

数据结构

一个pipeline 任务：

支持多个pipelineTask
一个pipelineTask 包含多个Step

@Data
public class Pipeline {

    @Id
    private String id;

    private String name;

    @JSONField(name = "pipeline")
    private List<PipelineTask> pipelineTasks = new ArrayList<>();

    private List<Network> networks = Lists.newArrayList(new Network());

    private List<Volume> volumes = Lists.newArrayList(new Volume());

    private String startNode;

    /**
     * 调度类型：
     *      1） CRON， 设置cronExpression
     *      2） FIX_RATE， 设置fixRateInSeconds
     */
    private ScheduleType scheduleType = ScheduleType.NONE;

    /**
     * CRON表达式，在scheduleType=CRON 时生效
     */
    private String cronExpression;

    /**
     * 固定周期运行，比如每隔多少s,在scheduleType=FIX_RATE 时生效
     */
    private int fixRateInSeconds;

    /**
     * 是否需要调度,为true时，才调度
     */
    @Indexed
    private boolean enableTrigger;

    private long lastTriggerTime;

    @Indexed
    private long nextTriggerTime;

    /**
     * 执行超时时间
     */
    private int executorTimeout;

    /**
     * 重试次数
     */
    private int executorFailRetryCount;

    /**
     * 内存限制
     */
    private String memory;

    /**
     * CPU 限制
     */
    private String cpu;

    @Data
    @Builder
    public static class PipelineTask {

        /**
         * 名称
         */
        String name;

        /**
         * 别名
         */
        String alias;

        /**
         * 依赖的pipelines，必须依赖的执行完成才能运行该PipelineTask
         */
        List<String> dependencies;

        /**
         * 任务步骤，顺序执行
         */
        List<Step> steps;
    }

    @Data
    public static class Network {
        String name = "pipeline_default";
        String driver = "bridge";
    }

    @Data
    public static class Volume {
        String name = "pipeline_default";
        String driver = "local";
    }

    @Data
    public static class StepNetwork {
        private String name;
        private List<String> aliases = Lists.newArrayList("default");

        public StepNetwork(String name) {
            this.name = name;
        }
    }

}

举例：

{
    "_id" : "29103d5e4a77409b9f6050eea8110bb3",
    "name" : "docker image pipeline",
    "pipelineTasks" : [ 
        {
            "name" : "docker image pipeline",
            "steps" : [ 
                {
                    "name" : "defaultJob",
                    "image" : "java-pipeline:1.0.1",
                    "workingDir" : "/workspace",
                    "environment" : {},
                    "networks" : [ 
                        {
                            "name" : "pipeline_default",
                            "aliases" : [ 
                                "default"
                            ]
                        }
                    ],
                    "onSuccess" : false,
                    "authConfig" : {}
                }
            ]
        }
    ],
    "networks" : [ 
        {
            "name" : "pipeline_default",
            "driver" : "bridge"
        }
    ],
    "volumes" : [ 
        {
            "name" : "pipeline_default",
            "driver" : "local"
        }
    ],
    "cronExpression" : "0 0 * * * ?",
    "fixRateInSeconds" : 0,
    "scheduleType" : "CRON",
    "enableTrigger" : true,
    "lastTriggerTime" : 1627744509047,
    "nextTriggerTime" : 1627747200000,
    "executorTimeout" : 0,
    "executorFailRetryCount" : 0,
    "isAvailable" : 1,
    "runningPipelines" : [],
    "finishedPipeliens" : [],
    "created_by" : "admin",
    "created_date" : "2021-07-20T04:33:16.477Z",
    "last_modified_by" : "system",
    "last_modified_date" : "2021-07-31T15:15:09.048Z"
}

使用说明

安装部署

编译

使用mvn编译

mvn package -DskipTests

部署master

根据需要，修改master的prod配置文件application-prod.yml。

包含kafka配置，server端口，mongodb地址,jwt secret配置。

mongodb 会自动新建collection和初始化数据，无需手动导入数据。

kafka:
    producer:
      bootstrap-servers: 127.0.0.1:9092
      retries: 3
      batch-size: 2000
      buffer-memory: 33554432
    consumer:
      group-id: consumer-pipeline
      auto-offset-reset: earliest
      enable-auto-commit: true
      bootstrap-servers: 172.31.161.38:9092

server:
  port: 8080

spring:
  data:
    mongodb:
      uri: mongodb://127.0.0.1:28017
      database: pipeline

jhipster:
  security:
    authentication:
      jwt:
        base64-secret:

注意master的jwt secret需要和agent的保持一致。

配置好后，启动：

nohup java -jar pipeline-master-$version.jar --spring.profiles.active=prod &

可以将application-prod.yml放在和jar包同一目录。

部署agent

根据需要，修改master的prod配置文件application-prod.yml。

包含：

eureka的defaultZone，配置master的地址
端口
docker地址
- docker-tls-verify: 是否启动tls验证
- docker-cert-path：启动tls验证的ca证书
- pipeline-log-path: 运行日志存储路径

eureka:
  instance:
    prefer-ip-address: true
  client:
    service-url:
      defaultZone: http://admin:${jhipster.registry.password}@127.0.0.1:8080/eureka/

server:
  port: 8081

application:
  docker-server: 
  docker-tls-verify: true
  docker-cert-path: /mnt/parastor/pipeline/ca/
  pipeline-log-path: /mnt/parastor/pipeline/logs/


jhipster:
  security:
    authentication:
      jwt:
        base64-secret:

执行老版本任务

POST /api/pipelines/exec-old


Body：

{
	"networks":[
		{
			"driver":"bridge",
			"name":"pipeline_network_3eac4b36209a41e58a5f22dd403fee50"
		}
	],
	"pipeline":[
		{
			"alias":"Word",
			"dependencies":[],
			"name":"pipeline_task_3eac4b36209a41e58a5f22dd403fee50_1",
			"nextPipelines":[],
			"steps":[
				{
					"alias":"Word",
					"auth_config":{},
					"command":[
						"echo $CI_SCRIPT | base64 -d | /bin/bash -e"
					],
					"entrypoint":[
						"/bin/bash",
						"-c"
					],
					"environment":{
						"CI_SCRIPT":"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"
					},
					"image":"registry.iflyresearch.com/aimind/java:v1.0.0",
					"name":"pipeline_task_3eac4b36209a41e58a5f22dd403fee50_1",
					"networks":[
						{
							"aliases":[
								"default"
							],
							"name":"pipeline_network_3eac4b36209a41e58a5f22dd403fee50"
						}
					],
					"on_success":true,
					"volumes":[
						"pipeline_default:/aimind",
						"/mnt/parastor/aimind/shared/:/share",
						"/mnt/parastor/aimind/pipeline-jobs/2021/07/26/3eac4b36209a41e58a5f22dd403fee50:/workspace",
						"/mnt/parastor/aimind/datavolumes/carmaster:/datavolume"
					],
					"working_dir":"/workspace"
				}
			]
		}
	],
	"volumes":[
		{
			"driver":"local",
			"name":"pipeline_default"
		}
	]
}

成功返回：

{
    "retcode": "000000",
    "desc": "成功",
    "data": {
        "id": "8137f344-f52d-4595-bdbb-425363847b61",
    }
}

可根据id获取日志。

获取job执行日志

GET /api/pipelines/jobLog/{jobid}/

结果：

{
    "retcode": "000000",
    "desc": "成功",
    "data": {
        "currentTask": null,
        "logs": [
            {
                "id": "e76a686f68b64c0783b7721b058be137",
                "jobId": "8137f344-f52d-4595-bdbb-425363847b61",
                "status": "FINISHED",
                "taskName": "pipeline_task_3eac4b36209a41e58a5f22dd403fee50_1",
                "exitedValue": 0,
                "logs": [
                    "proc \"pipeline_task_3eac4b36209a41e58a5f22dd403fee50_1\" started",
                    "pipeline_task_3eac4b36209a41e58a5f22dd403fee50_1:+ java -cp /datavolume/pdf_to_word/pdfbox_util-1.0-SNAPSHOT.jar com.iflytek.indexer.Runner --inputPDF /datavolume/extract/f92c2a75bae84bb0883205db3f2dae79/pdf/ec5c0b943d0b4f4293722a5ddc61e66d/HS7.pdf --outputWord /datavolume/extract/f92c2a75bae84bb0883205db3f2dae79/pdfToWord/ec5c0b943d0b4f4293722a5ddc61e66d/ --schemaInputPath /datavolume/extract/kbqa/f92c2a75bae84bb0883205db3f2dae79 --entityIndexPath /datavolume/extract/f92c2a75bae84bb0883205db3f2dae79/pdfToWord/entity --fieldIndexPath /datavolume/extract/f92c2a75bae84bb0883205db3f2dae79/pdfToWord/field --type lucene --output /datavolume/extract/f92c2a75bae84bb0883205db3f2dae79/pdfToWord/ec5c0b943d0b4f4293722a5ddc61e66d/entityInfo.txt",
                    "proc \"pipeline_task_3eac4b36209a41e58a5f22dd403fee50_1\" exited with status 0"
                ]
            }
        ],
        "exitedValue": 0,
        "status": "FINISHED",
        "pipelineJobSt": 1627477250599,
        "pipelineJobFt": 1627477274299
    }
}

周期任务

如果pipelien需要周期执行,需要配置enableTrigger为true，同时设置按照CRON或者’FIX_RATE` 运行:

FIX_RATE: 固定周期，通过fixRateInSeconds配置周期运行时间

示例：每360秒运行一次：

{
    // pipeline ...
    "pipelineTasks" : [ ],
    "fixRateInSeconds" : 360,
    "scheduleType" : "FIX_RATE",
    "enableTrigger" : true
}

CRON: 按照CRON表达式周期执行，通过cronExpression配置.

示例：每小时开始的时候运行一次：

{
    // pipeline ...
    "pipelineTasks" : [ ],
    "cronExpression" : "0 0 * * * ?",
    "scheduleType" : "CRON",
    "enableTrigger" : true
}

Docker容器

开源基于docker的任务调度器pipeline，比`quartzs` 更强大的分布式任务调度器

pipeline 分布式任务调度器

架构

功能特性 && TODO List

进展

2021.07.31

2021.07.28

2021.07.27

2021.07.21

2021.07.19

数据结构

使用说明

安装部署

编译

部署master

部署agent

执行老版本任务

获取job执行日志

周期任务

更多待解锁

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