ZooKeeper comparison of Redis implementation of distributed locks

With the rapid development of Internet technology, distributed systems have been widely used in modern applications, especially in large Internet companies. However, in a distributed system, it is very difficult to maintain consistency between nodes, so the distributed lock mechanism has become one of the foundations to solve this problem. In the implementation of distributed locks, Redis and ZooKeeper are both popular tools. This article will compare and analyze them.

1. Redis implements distributed locks

Redis is an open source in-memory data storage system that can be used as a database, cache and message middleware. Redis's distributed lock mechanism is implemented through SETNX. The SETNX command can atomically set the value of a key, but it is only set successfully when the key does not exist. Therefore, we can implement distributed locks through SETNX.

Suppose we want to implement a lock named Lock and need to lock a shared variable. You can use the following sample code:

def acquire_lock(conn, lockname, acquire_timeout=10):
    identifier = str(uuid.uuid4())
    end = time.time() + acquire_timeout
    while time.time() < end:
        if conn.setnx(lockname, identifier):
            return identifier
        time.sleep(0.001)
    return False

In the above code, the acquire_lock function generates a random value through uuid The identifier, and operates on lockname through setnx, and returns the identifier if the operation is successful. Returns False if the lock is not acquired.

But there is a problem here: if a client has obtained the lock, but crashes or hangs before releasing the lock, then other clients will never be able to obtain the lock, which causes a deadlock problem. To avoid this, we can add a timeout to automatically release the lock. The following is the code to release the lock:

def release_lock(conn, lockname, identifier):
    pip = conn.pipeline(True)
    while True:
        try:
            # watch the lock name to ensure that no one else has acquired the lock
            pip.watch(lockname)
            if pip.get(lockname) == identifier:
                pip.multi()
                pip.delete(lockname)
                pip.execute()
                return True
            pip.unwatch()
            break
        except redis.exceptions.WatchError:
            pass
    return False

The above example code is relatively simple and can be used directly. However, in actual use, the distributed lock scenario is more complex and requires a more complete solution. Let's take a look at how ZooKeeper implements distributed locks.

2. ZooKeeper implements distributed locks

ZooKeeper is a distributed coordination service that can be used to coordinate the status of different nodes in a distributed system. It is used by many distributed systems. Go to ZooKeeper to coordinate various nodes. In ZooKeeper, distributed locks are also a very useful mechanism.

The basic process of ZooKeeper implementing distributed locks is as follows:

(1) Create a mutex node (Mutex Node)

First, the client needs to create a mutual lock on ZooKeeper The lock node is used as the identifier of the lock. You can use the create command to create a node. If the node already exists, the creation will fail. When creating a node, you need to specify the node type. Distributed locks generally use short-lived ordered nodes, that is, appending a set of numbers after the node name to ensure the uniqueness of the node name.

(2) Obtaining the lock

The process of acquiring the lock is the process of locking the mutex lock node. The order in which locks are acquired is determined by the numerical order in the node names. If the client successfully creates a mutex node, then it owns the lock. If the node is not successfully created, you need to wait for other clients to release the lock before trying again.

(3) Release the lock

When the client no longer needs to lock the resource, it needs to release the lock. Releasing the lock requires deleting the mutex lock node. After the lock is released, other clients will immediately receive the lock release message through the Watcher mechanism.

ZooKeeper is more expensive than Redis and requires starting services and installing and maintaining ZooKeeper clusters. Therefore, the frequency of using ZooKeeper to implement distributed locks in distributed systems is relatively low. However, ZooKeeper is relatively more stable and secure, and is more suitable than Redis for some critical systems.

Overall, Redis and ZooKeeper are very practical distributed lock implementation solutions. When choosing which solution to use, you need to make a choice based on the actual situation and make trade-offs in terms of performance, stability, security, etc. to achieve the best results.

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