Summary of the difference between Redis local lock and distributed lock

Redis local locks and distributed locks are significantly different in design purposes, implementation methods and application scenarios. Here are the detailed differences:

Redis local lock

1. Design Purpose:

Local locks are mainly used inside a single application instance, ensuring that only one thread or process can access a shared resource at the same time.
It is suitable for stand-alone environments or single instance applications, solving concurrent access problems.

2. Implementation method:

Local locks usually use the lock mechanism that comes with the language, such as in JavaReentrantLockorSynchronizedKeywords, in Pythonwait.
In Redis, it can be done bySETNXCommand (SET if Not eXists) to implement a basic local lock.

3. Application scenarios:

A single application instance needs to control access to shared resources, such as controlling access to local memory data structures or local files.
Not suitable for scenarios that span multi-instance and multi-server, because local locks cannot be synchronized in a distributed environment.

Redis distributed lock

1. Design Purpose:

Distributed locks are used in distributed systems to ensure that a shared resource can only be accessed by one instance at the same time between multiple application instances or servers.
It solves the problem of concurrent access to shared resources by multiple instances in a distributed environment.

2. Implementation method:

Redis distributed locks can be implemented by combining multiple Redis commands, for exampleSETCommand plusNXandPXOptions:SET resource_name my_random_value NX PX 30000。
You can also use the Redlock algorithm, which is an algorithm that implements distributed locking officially recommended by Redis. It requires the use of multiple Redis instances to ensure higher reliability.
Third-party libraries such as Redisson and Spring Data Redis also provide well-encapsulated distributed lock implementations.

3. Application scenarios:

Resource synchronization problems in distributed systems, such as distributed task scheduling, distributed transactions, and resource control across multiple microservices.
Suitable for scenarios where operations need to be coordinated across multiple instances or servers, for example, in a microservice architecture, multiple service instances require orderly operations on shared databases or distributed caches.

Sample code

Simple implementation of Redis local lock:

import redis

r = (host='localhost', port=6379, db=0)

def acquire_lock(lock_name, acquire_timeout=10):
    end_time = () + acquire_timeout
    while () < end_time:
        if (lock_name, 1):
            (lock_name, 10)
            return True
        (0.001)
    return False

def release_lock(lock_name):
    (lock_name)

Simple implementation of Redis distributed lock:

import redis
import uuid

r = (host='localhost', port=6379, db=0)

def acquire_lock(lock_name, acquire_timeout=10, lock_timeout=10):
    identifier = str(uuid.uuid4())
    end_time = () + acquire_timeout
    while () < end_time:
        if (lock_name, identifier, ex=lock_timeout, nx=True):
            return identifier
        (0.001)
    return False

def release_lock(lock_name, identifier):
    lock_value = (lock_name)
    if lock_value and lock_value.decode() == identifier:
        (lock_name)

Through the above comparison, there are obvious differences between Redis local locks and distributed locks in usage scenarios and implementation details.

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