分布式事务的21种武器 - 1

2023-04-14  本文已影响0人  DeepNoMind

在分布式系统中，事务的处理分布在不同组件、服务中，因此分布式事务的ACID保障面临着一些特殊难点。本系列文章介绍了21种分布式事务设计模式，并分析其实现原理和优缺点，在面对具体分布式事务问题时，可以选择合适的模式进行处理。原文: Exploring Solutions for Distributed Transactions (1)

Towfiqu barbhuiya @Unsplash

由于良好的可伸缩性和容错性，分布式系统现在变得越来越普遍，但在分布式系统中维护数据一致性可能非常困难，尤其是在在需要处理跨多个节点的事务时。接下来我们就来探讨那些可以确保分布式系统数据一致性的技术、模式和算法。

分布式事务涉及多个节点，它们一起工作以执行单个事务。确保所有节点对事务结果达成一致，同时保持数据一致性是一项具有挑战性的任务。传统事务的ACID(原子性、一致性、隔离性、持久性)属性在分布式环境中变得更加难以实现。

本文旨在全面介绍可用于维护分布式系统数据一致性的不同方法，讨论每种方法的优缺点，以及在什么场景下适用。

在不同业务场景下，可以有不同的解决方案，常见方法有:

  1. 阻塞重试(Blocking Retry)
  2. 二阶段和三阶段提交(Two-Phase Commit (2PC) and Three-Phase Commit (3PC))
  3. 基于后台队列的异步处理(Using Queues to Process Asynchronously in the Background)
  4. TCC补偿(TCC Compensation Matters)
  5. 本地消息表(异步保证)/发件箱模式(Local Message Table (Asynchronously Ensured)/Outbox Pattern)
  6. MQ事务(MQ Transaction)
  7. Saga模式(Saga Pattern)
  8. 事件驱动(Event Sourcing)
  9. 命令查询职责分离(Command Query Responsibility Segregation, CQRS)
  10. 原子提交(Atomic Commitment)
  11. 并行提交(Parallel Commits)
  12. 事务复制(Transactional Replication)
  13. 一致性算法(Consensus Algorithms)
  14. 时间戳排序(Timestamp Ordering)
  15. 乐观并发控制(Optimistic Concurrency Control)
  16. 拜占庭容错(Byzantine Fault Tolerance, BFT)
  17. 分布式锁(Distributed Locking)
  18. 分片(Sharding)
  19. 多版本并发控制(Multi-Version Concurrency Control, MVCC)
  20. 分布式快照(Distributed Snapshots)
  21. 主从复制(Leader-Follower Replication)

本文将介绍阻塞重试、2PC/3PC、后台队列三种模式。

1. 阻塞重试(Blocking Retry) 
import retrying

@retrying.retry(wait_fixed=1000, stop_max_delay=10000)
def my_function():
    # code to retry goes here
    # if this function throws an exception, it will be retried according to the parameters specified above

示例代码:

优点

缺点

适用场景

挑战

2. 二阶段和三阶段提交(Two-Phase Commit (2PC) and Three-Phase Commit (3PC)) 
# Coordinator code
def two_phase_commit(coordinator, participants, data):
    # Phase 1: Prepare phase
    prepare_ok = True
    for participant in participants:
        try:
            participant.prepare(data)
        except:
            prepare_ok = False
            break
    if not prepare_ok:
        # Phase 1b: Abort
        for participant in participants:
            participant.abort()
        return False
    else:
        # Phase 2: Commit phase
        commit_ok = True
        for participant in participants:
            try:
                participant.commit()
            except:
                commit_ok = False
                break
        if not commit_ok:
            # Phase 2b: Rollback
            for participant in participants:
                participant.rollback()
            return False
        else:
            return True

# Participant code
class Participant:
    def prepare(self, data):
        # Perform prepare operations on local data
        # If prepare fails, raise an exception
        pass

    def commit(self):
        # Perform commit operations on local data
        pass

    def rollback(self):
        # Perform rollback operations on local data
        pass

示例代码:

优点

缺点

适用场景

挑战

# Coordinator code
def three_phase_commit(coordinator, participants, data):
    # Phase 1: CanCommit phase
    can_commit_ok = True
    for participant in participants:
        try:
            participant.can_commit(data)
        except:
            can_commit_ok = False
            break
    if not can_commit_ok:
        # Phase 1b: Abort
        for participant in participants:
            participant.abort()
        return False
    else:
        # Phase 2: PreCommit phase
        pre_commit_ok = True
        for participant in participants:
            try:
                participant.pre_commit()
            except:
                pre_commit_ok = False
                break
        if not pre_commit_ok:
            # Phase 2b: Abort
            for participant in participants:
                participant.abort()
            return False
        else:
            # Phase 3: DoCommit phase
            do_commit_ok = True
            for participant in participants:
                try:
                    participant.do_commit()
                except:
                    do_commit_ok = False
                    break
            if not do_commit_ok:
                # Phase 3b: Rollback
                for participant in participants:
                    participant.rollback()
                return False
            else:
                return True

# Participant code
class Participant:
    def can_commit(self, data):
        # Determine if participant can commit
        # If participant cannot commit, raise an exception
        pass

    def pre_commit(self):
        # Perform pre-commit operations on local data
        pass

    def do_commit(self):
        # Perform commit operations on local data
        pass

    def rollback(self):
        # Perform rollback operations on local data
        pass

示例代码:

优点

缺点

适用场景

挑战

3. 基于后台队列的异步处理(Using Queues to Process Asynchronously in the Background) 
import multiprocessing

# Create a Queue
task_queue = multiprocessing.Queue()
result_queue = multiprocessing.Queue()

# Define a task function
def do_task(task):
    # Code to perform the task
    result = task.upper()
    # Store the result in the output queue
    result_queue.put(result)

# Add tasks to the queue
tasks = ['task1', 'task2', 'task3']
for task in tasks:
    task_queue.put(task)

# Create workers
num_workers = multiprocessing.cpu_count()
workers = [multiprocessing.Process(target=do_task, args=(task_queue,)) for i in range(num_workers)]

# Start workers
for worker in workers:
    worker.start()

# Retrieve tasks from the queue
while not task_queue.empty():
    task = task_queue.get()

# Process completed tasks
while not result_queue.empty():
    result = result_queue.get()
    print(result)

# Join workers
for worker in workers:
    worker.join()

# Clean up
task_queue.close()
result_queue.close()

示例代码

优点

缺点

适用场景

挑战

参考文献

Implementing Retry In Kafka Consumer

retry logic blocks the main consumer while its waiting for the retry in spring

Main Difference between 2PC and 3PC Protocols

Three-Phase Commit Protocol

Distributed DBMS - Commit Protocols

COMMIT Protocol in DBMS

Asynchronous Task Processing in Cloud

Asynchronous Task Queues

Asynchronous Messaging, Part 3: Backend Service

Async and Background Processing

Queue instruction-run an activity asynchronously

你好，我是俞凡，在Motorola做过研发，现在在Mavenir做技术工作，对通信、网络、后端架构、云原生、DevOps、CICD、区块链、AI等技术始终保持着浓厚的兴趣，平时喜欢阅读、思考，相信持续学习、终身成长，欢迎一起交流学习。
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