基于环状队列和迭代器实现分布式任务RR分配策略

Java框架

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2019-7-4

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背景

分布式任务分配

在很多运维场景下,我们都会执行一些长时间的任务,比如装机、部署环境、打包镜像等长时间任务, 而通常我们的任务节点数量通常是有限的(排除基于k8s的hpa、或者knative等自动伸缩场景)。

那么当我们有一个任务如何根据当前的worker和corrdinator和任务来进行合理的分配,分配其实也比较复杂,往复杂里面做,可以根据当前系统的负载、每个任务的执行资源消耗、当前集群的任务数量等, 这里我们就搞一个最简单的,基于任务和当前worker的RR算法

系统架构

在worker和任务队列之间,添加一层协调调度层Coordinator, 由它来根据当前集群任务的状态来进行任务的分配,同时感知当前集群worker和task的状态,协调整个集群任务的执行、终止等操作

单机实现

整体设计

members: 表示当前集群中所有的worker tasks: 就是当前的任务 Coordinator: 就是我们的协调者, 负责根据members和tasks进行任务的分配 result: 就是分配的结果

CircularIterator

CircularIterator就是我们的环状对立迭代器, 拥有两个方法, 一个是add添加member, 一个Next返回基于rr的下一个member

// CircularIterator 环状迭代器
type CircularIterator struct {
	list []interface{}    // 保存所有的成员变量
	next int
}
// Next 返回下一个元素
func (c *CircularIterator) Next() interface{} {
	item := c.list[c.next]
	c.next = (c.next + 1) % len(c.list)
	return item
}

// Add 添加任务
func (c *CircularIterator) Add(v interface{}) bool {
	for _, item := range c.list {
		if v == item {
			return false
		}
	}
	c.list = append(c.list, v)
	return true
}

Member&Task

Member就是负责执行任务的worker, 有一个AddTask方法和Execute方法负责任务的执行和添加任务 Task标识一个任务

// Member 任务组成员
type Member struct {
	id    int
	tasks []*Task
}

// ID 返回当前memberID
func (m *Member) ID() int {
	return m.id
}

// AddTask 为member添加任务
func (m *Member) AddTask(t *Task) bool {
	for _, task := range m.tasks {
		if task == t {
			return false
		}
	}
	m.tasks = append(m.tasks, t)
	return true
}

// Execute 执行任务
func (m *Member) Execute() {
	for _, task := range m.tasks {
		fmt.Printf("Member %d run task %s\n", m.ID(), task.Execute())
	}
}

// Task 任务
type Task struct {
	name string
}

// Execute 执行task返回结果
func (t *Task) Execute() string {
	return "Task " + t.name + " run success"
}

Coordinator

Coordinator是协调器,负责根据 Member和task进行集群任务的协调调度

// Task 任务
type Task struct {
	name string
}

// Execute 执行task返回结果
func (t *Task) Execute() string {
	return "Task " + t.name + " run success"
}

// Coordinator 协调者
type Coordinator struct {
	members []*Member
	tasks   []*Task
}

// TaskAssignments 为member分配任务
func (c *Coordinator) TaskAssignments() map[int]*Member {
	taskAssignments := make(map[int]*Member)

	// 构建迭代器
	memberIt := c.getMemberIterator()
	for _, task := range c.tasks {
		member := memberIt.Next().(*Member)

		_, err := taskAssignments[member.ID()]
		if err == false {
			taskAssignments[member.ID()] = member
		}
		member.AddTask(task)
	}

	return taskAssignments
}

func (c *Coordinator) getMemberIterator() *CircularIterator {
	// 通过当前成员, 构造成员队列
	members := make([]interface{}, len(c.members))
	for index, member := range c.members {
		members[index] = member
	}

	return NewCircularIterftor(members)
}

// AddMember 添加member组成员
func (c *Coordinator) AddMember(m *Member) bool {
	for _, member := range c.members {
		if member == m {
			return false
		}
	}
	c.members = append(c.members, m)
	return true
}

// AddTask 添加任务
func (c *Coordinator) AddTask(t *Task) bool {
	for _, task := range c.tasks {
		if task == t {
			return false
		}
	}
	c.tasks = append(c.tasks, t)
	return true
}

测试

我们首先创建一堆member和task, 然后调用coordinator进行任务分配,执行任务结果

	coordinator := NewCoordinator()
	for i := 0; i < 10; i++ {
		m := &Member{id: i}
		coordinator.AddMember(m)
	}

	for i := 0; i < 30; i++ {
		t := &Task{name: fmt.Sprintf("task %d", i)}
		coordinator.AddTask(t)
	}

	result := coordinator.TaskAssignments()
	for _, member := range result {
		member.Execute()
	}

结果

可以看到每个worker均匀的得到任务分配

Member 6 run task Task task 6 run success
Member 6 run task Task task 16 run success
Member 6 run task Task task 26 run success
Member 8 run task Task task 8 run success
Member 8 run task Task task 18 run success
Member 8 run task Task task 28 run success
Member 0 run task Task task 0 run success
Member 0 run task Task task 10 run success
Member 0 run task Task task 20 run success
Member 3 run task Task task 3 run success
Member 3 run task Task task 13 run success
Member 3 run task Task task 23 run success
Member 4 run task Task task 4 run success
Member 4 run task Task task 14 run success
Member 4 run task Task task 24 run success
Member 7 run task Task task 7 run success
Member 7 run task Task task 17 run success
Member 7 run task Task task 27 run success
Member 9 run task Task task 9 run success
Member 9 run task Task task 19 run success
Member 9 run task Task task 29 run success
Member 1 run task Task task 1 run success
Member 1 run task Task task 11 run success
Member 1 run task Task task 21 run success
Member 2 run task Task task 2 run success
Member 2 run task Task task 12 run success
Member 2 run task Task task 22 run success
Member 5 run task Task task 5 run success
Member 5 run task Task task 15 run success
Member 5 run task Task task 25 run success

完整代码

package main

import "fmt"

// CircularIterator 环状迭代器
type CircularIterator struct {
	list []interface{}
	next int
}

// Next 返回下一个元素
func (c *CircularIterator) Next() interface{} {
	item := c.list[c.next]
	c.next = (c.next + 1) % len(c.list)
	return item
}

// Add 添加任务
func (c *CircularIterator) Add(v interface{}) bool {
	for _, item := range c.list {
		if v == item {
			return false
		}
	}
	c.list = append(c.list, v)
	return true
}

// Member 任务组成员
type Member struct {
	id    int
	tasks []*Task
}

// ID 返回当前memberID
func (m *Member) ID() int {
	return m.id
}

// AddTask 为member添加任务
func (m *Member) AddTask(t *Task) bool {
	for _, task := range m.tasks {
		if task == t {
			return false
		}
	}
	m.tasks = append(m.tasks, t)
	return true
}

// Execute 执行任务
func (m *Member) Execute() {
	for _, task := range m.tasks {
		fmt.Printf("Member %d run task %s\n", m.ID(), task.Execute())
	}
}

// Task 任务
type Task struct {
	name string
}

// Execute 执行task返回结果
func (t *Task) Execute() string {
	return "Task " + t.name + " run success"
}

// Coordinator 协调者
type Coordinator struct {
	members []*Member
	tasks   []*Task
}

// TaskAssignments 为member分配任务
func (c *Coordinator) TaskAssignments() map[int]*Member {
	taskAssignments := make(map[int]*Member)

	// 构建迭代器
	memberIt := c.getMemberIterator()
	for _, task := range c.tasks {
		member := memberIt.Next().(*Member)

		_, err := taskAssignments[member.ID()]
		if err == false {
			taskAssignments[member.ID()] = member
		}
		member.AddTask(task)
	}

	return taskAssignments
}

func (c *Coordinator) getMemberIterator() *CircularIterator {
	// 通过当前成员, 构造成员队列
	members := make([]interface{}, len(c.members))
	for index, member := range c.members {
		members[index] = member
	}

	return NewCircularIterftor(members)
}

// AddMember 添加member组成员
func (c *Coordinator) AddMember(m *Member) bool {
	for _, member := range c.members {
		if member == m {
			return false
		}
	}
	c.members = append(c.members, m)
	return true
}

// AddTask 添加任务
func (c *Coordinator) AddTask(t *Task) bool {
	for _, task := range c.tasks {
		if task == t {
			return false
		}
	}
	c.tasks = append(c.tasks, t)
	return true
}

// NewCircularIterftor 返回迭代器
func NewCircularIterftor(list []interface{}) *CircularIterator {
	iterator := CircularIterator{}
	for _, item := range list {
		iterator.Add(item)
	}
	return &iterator
}

// NewCoordinator 返回协调器
func NewCoordinator() *Coordinator {
	c := Coordinator{}
	return &c
}

func main() {
	coordinator := NewCoordinator()
	for i := 0; i < 10; i++ {
		m := &Member{id: i}
		coordinator.AddMember(m)
	}

	for i := 0; i < 30; i++ {
		t := &Task{name: fmt.Sprintf("task %d", i)}
		coordinator.AddTask(t)
	}

	result := coordinator.TaskAssignments()
	for _, member := range result {
		member.Execute()
	}
}

总结

任务协调是一个非常复杂的事情, 内部的任务平台,虽然实现了基于任务的组合和app化,但是任务调度分配着一块,仍然没有去做,只是简单的根据树形任务去简单的做一些分支任务的执行,未来有时间再做吧,要继续研究下一个模块了

这个调度思想来源于kafka connect的DistributedHerder里面的WorkerCoordinator,感兴趣的可以看看,未完待续

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作者:8小时