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
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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
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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
更多文章可以访问http://www.sreguide.com/
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
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
