conductor服务编排http任务安排
conductor服务编排http任务安排测试
# 编排
1.定义任务：http://localhost:8080/api/metadata/taskdefs
[{
"name": "user_task",
"retryCount": 3,
"timeoutSeconds": 1200,
"inputKeys": [
"type"
],
"outputKeys": [
"id",
"name"
],
"timeoutPolicy": "TIME_OUT_WF",
"retryLogic": "FIXED",
"retryDelaySeconds": 600,
"responseTimeoutSeconds": 3600
},
{
"name": "group_task",
"retryCount": 3,
"timeoutSeconds": 1200,
"inputKeys": [
"id",
"name"
],
"outputKeys": [
"response",
"result"
],
"timeoutPolicy": "TIME_OUT_WF",
"retryLogic": "FIXED",
"retryDelaySeconds": 600,
"responseTimeoutSeconds": 3600
}
]
name 任务类型 唯一
retryCount 任务标记为失败时尝试重试的次数 -
retryLogic 重试机制
timeoutSeconds 以毫秒为单位的时间，在此之后，如果在转换到IN_PROGRESS状态后未完成任务，则将任务标记为TIMED_OUT 如果设置为0，则不会超时
timeoutPolicy 任务的超时策略
responseTimeoutSeconds 如果大于0，则在此时间之后未更新状态时，将重新安排任务。当work轮询任务但由于错误/网络故障而无法完成时很有用。 -
outputKeys 任务输出的键集。用于记录任务的输出
2.定义工作流：http://localhost:8080/api/metadata/workflow
{
"name": "user_and_group",
"description": "Encodes a file and deploys to CDN",
"version": 1,
"tasks": [
{
"name": "user_task",
"taskReferenceName": "user",
"inputParameters": {
"http_request": {
"method": "POST",
"uri": "http://localhost:8000/user/getUser",
"body": {
"type": "${workflow.input.type}"
}
}
},
"type": "HTTP"
},
{
"name": "group_task",
"taskReferenceName": "group",
"inputParameters": {
"http_request": {
"method": "POST",
"uri": "http://localhost:8010/group/getGroup",
"body": {
"id": "${user.output.response.body.id}",
"name": "${user.output.response.body.name}"
}
}
},
"type": "HTTP"
}
],
"outputParameters": {
"response": "${group.output.response.body.response}",
"result": "${group.output.response.body.result}"
},
"schemaVersion": 2
}
3.任务执行：http://localhost:8080/api/workflow/{workname}
在body中定义参数：
{
"type":"1"
}
4.根据上一步返回的id获取任务信息：http://localhost:8080/api/workflow/{workid}:
输出内容：
{
"output": {
"response": [
"1",
"2",
"3",
"4"
],
"result": "李四gaga"
}
}
#### 安装node.js
curl --silent --location https://rpm.nodesource.com/setup_8.x | bash -
sudo yum install -y nodejs
node -v
#### gradle 安装
wget http://downloads.gradle.org/distributions/gradle-4.8-bin.zip
unzip gradle-4.8-bin.zip
配置环境变量
打开profile 文件
vim /etc/profile
export GRADLE_HOME=/root/proess/gradle48
export PATH=$GRADLE_HOME/bin:$PATH
source /etc/profile
gradle -v
#### 环境启动conductor
git clone https://github.com/Netflix/conductor.git
cd conductor/server
../gradlew server
cd ui
npm install gulp --save-dev
npm install --save-dev
gulp watch
#### 例子一 conductor服务编排http任务安排
# 文档
http://wiki.ttxit.com/pages/viewpage.action?pageId=25919490
# 编排
1.定义任务：http://localhost:8080/api/metadata/taskdefs
[{
"name": "user_task",
"retryCount": 3,
"timeoutSeconds": 1200,
"inputKeys": [
"type"
],
"outputKeys": [
"id",
"name"
],
"timeoutPolicy": "TIME_OUT_WF",
"retryLogic": "FIXED",
"retryDelaySeconds": 600,
"responseTimeoutSeconds": 3600
},
{
"name": "group_task",
"retryCount": 3,
"timeoutSeconds": 1200,
"inputKeys": [
"id",
"name"
],
"outputKeys": [
"response",
"result"
],
"timeoutPolicy": "TIME_OUT_WF",
"retryLogic": "FIXED",
"retryDelaySeconds": 600,
"responseTimeoutSeconds": 3600
}
]
name 任务类型 唯一
retryCount 任务标记为失败时尝试重试的次数 -
retryLogic 重试机制
timeoutSeconds 以毫秒为单位的时间，在此之后，如果在转换到IN_PROGRESS状态后未完成任务，则将任务标记为TIMED_OUT 如果设置为0，则不会超时
timeoutPolicy 任务的超时策略
responseTimeoutSeconds 如果大于0，则在此时间之后未更新状态时，将重新安排任务。当work轮询任务但由于错误/网络故障而无法完成时很有用。 -
outputKeys 任务输出的键集。用于记录任务的输出
2.定义工作流：http://localhost:8080/api/metadata/workflow
{
"name": "user_and_group",
"description": "Encodes a file and deploys to CDN",
"version": 1,
"tasks": [
{
"name": "user_task",
"taskReferenceName": "user",
"inputParameters": {
"http_request": {
"method": "POST",
"uri": "http://localhost:8000/user/getUser",
"body": {
"type": "${workflow.input.type}"
}
}
},
"type": "HTTP"
},
{
"name": "group_task",
"taskReferenceName": "group",
"inputParameters": {
"http_request": {
"method": "POST",
"uri": "http://localhost:8010/group/getGroup",
"body": {
"id": "${user.output.response.body.id}",
"name": "${user.output.response.body.name}"
}
}
},
"type": "HTTP"
}
],
"outputParameters": {
"response": "${group.output.response.body.response}",
"result": "${group.output.response.body.result}"
},
"schemaVersion": 2
}
3.任务执行：http://localhost:8080/api/workflow/{workname}
在body中定义参数：
{
"type":"1"
}
4.根据上一步返回的id获取任务信息：http://localhost:8080/api/workflow/{workid}:
输出内容：
{
"output": {
"response": [
"1",
"2",
"3",
"4"
],
"result": "李四gaga"
}
}
#### 例子二 创建任务（Metadata Management）
参考：深入浅出Netflix Conductor使用
https://www.jianshu.com/p/4eae1af8afa8
http://192.168.13.183:8080/index.html#/
定义位置：post /metadata/taskdefs Create new task definition(s)
查看结果：http://192.168.13.183:3000/#/workflow/metadata/tasks?_k=dkzgv2
[
{
"name": "leaderRatify",
"retryCount": 3,
"timeoutSeconds": 1200,
"inputKeys": [
"staffName",
"staffDepartment"
],
"outputKeys": [
"leaderAgree",
"leaderDisagree"
],
"timeoutPolicy": "TIME_OUT_WF",
"retryLogic": "FIXED",
"retryDelaySeconds": 600,
"responseTimeoutSeconds": 800
},
{
"name": "managerRatify",
"retryCount": 3,
"timeoutSeconds": 1200,
"inputKeys": [
"managerName",
"managerDeparment"
],
"outputKeys": [
"managerAgree",
"managerDisagree"
],
"timeoutPolicy": "TIME_OUT_WF",
"retryLogic": "FIXED",
"retryDelaySeconds": 600,
"responseTimeoutSeconds": 800
}
]
#### 创建工作流
http://192.168.13.183:8080/index.html#/
定义位置：post /metadata/taskdefs Create new task definition(s)
查看结果：http://192.168.13.183:3000/#/workflow/metadata/Leave%20process/1?_k=te80nu
[{
"updateTime": 1540448903202,
"name": "Leave process",
"description": "a demo for workflow",
"version": 1,
"tasks": [{
"name": "leaderRatify",
"taskReferenceName": "node1",
"inputParameters": {
"staffName": "${workflow.input.staffName}",
"staffDepartment": "${workflow.input.staffDepartment}"
},
"type": "SIMPLE",
"startDelay": 0
},
{
"name": "managerRatify",
"taskReferenceName": "node2",
"inputParameters": {
"managerName": "${node1.output.leaderName}",
"managerDepartment": "${node1.output.leaderDepartment}"
},
"type": "SIMPLE",
"startDelay": 0
}
],
"outputParameters": {
"leaderName": "${node1.output.leaderName}",
"leaderDepartment": "${node1.output.leaderDepartment}",
"managerAgree": "${node2.output.managerAgree}",
"managerDisagree": "${node2.output.managerDisagree}"
},
"restartable": true,
"schemaVersion": 2
}]
#### 创建任务worker
class LeaderRatifyWorker implements Worker {
private String taskDefName;
public SampleWorker(String taskDefName) {
this.taskDefName = taskDefName;
}
@Override
public String getTaskDefName() {
return taskDefName;
}
@Override
public TaskResult execute(Task task) {
System.out.printf("Executing %s%n", taskDefName);
System.out.println("staffName:" + task.getInputData().get("staffName"));
System.out.println("staffDepartment:" + task.getInputData().get("staffDepartment"));
TaskResult result = new TaskResult(task);
result.setStatus(TaskResult.Status.COMPLETED);
//Register the output of the task
result.getOutputData().put("outputKey1", "value");
result.getOutputData().put("oddEven", 1);
result.getOutputData().put("mod", 4);
result.getOutputData().put("leaderAgree", "yes");
result.getOutputData().put("leaderDisagree", "no");
return result;
}
}
class ManagerRatifyWorker implements Worker {
private String taskDefName;
public SampleWorker2(String taskDefName) {
this.taskDefName = taskDefName;
}
@Override
public String getTaskDefName() {
return taskDefName;
}
@Override
public TaskResult execute(Task task) {
System.out.printf("Executing %s\n", taskDefName);
System.out.println("managerName:" + task.getInputData().get("managerName"));
System.out.println("managerDepartment:" + task.getInputData().get("managerDepartment"));
TaskResult result = new TaskResult(task);
result.setStatus(TaskResult.Status.COMPLETED);
//Register the output of the task
result.getOutputData().put("managerAgree", String.valueOf(task.getInputData().get("managerName")));
result.getOutputData().put("managerDisagree", String.valueOf(task.getInputData().get("managerDepartment")));
return result;
}
}
//在main方法中创建工作Worker以及设置需要访问的Conductor Server端api地址，并将流程进入初始化
public static void main(String[] args) {
TaskClient taskClient = new TaskClient();
taskClient.setRootURI("http://localhost:8080/api/"); //Point this to the server API
int threadCount = 2; //number of threads used to execute workers. To avoid starvation, should be same or more than number of workers
Worker worker1 = new LeaderRatifyWorker("leaderRatify");
Worker worker2 = new ManagerRatifyWorker("managerRatify");
//Create WorkflowTaskCoordinator
WorkflowTaskCoordinator.Builder builder = new WorkflowTaskCoordinator.Builder();
WorkflowTaskCoordinator coordinator = builder.withWorkers(worker1, worker2).withThreadCount(threadCount).withTaskClient(taskClient).build();
//Start for polling and execution of the tasks
coordinator.init();
}