- setNx和expire要做成原子性操作，否则，setNx成功，系统down，其他系统都无法获取这个锁
- 设置锁的时候，一定要setNx传入唯一的value，解锁的时候要校验这个value，来保证不要把别人的锁给清除（这种情况会出现在，锁定周期内的业务执行时间大于了锁的有效时间，当前client的锁都失效了，其他client已经获取到锁，这个时候，当前client如果不校验value的值直接del的话，就会把别人的锁给释放了）
- 在释放锁的时候，要保证判断value和del操作是一个原子操作，防止第一步和第二步之间有其他的client获取到锁，误删除其他client的锁
Correct implementation with a single instance
Before trying to overcome the limitation of the single instance setup described above, let’s check how to do it correctly in this simple case, since this is actually a viable solution in applications where a race condition from time to time is acceptable, and because locking into a single instance is the foundation we’ll use for the distributed algorithm described here.
To acquire the lock, the way to go is the following:
SET resource_name my_random_value NX PX 30000
The command will set the key only if it does not already exist (NX option), with an expire of 30000 milliseconds (PX option). The key is set to a value “myrandomvalue”. This value must be unique across all clients and all lock requests.
Basically the random value is used in order to release the lock in a safe way, with a script that tells Redis: remove the key only if it exists and the value stored at the key is exactly the one I expect to be. This is accomplished by the following Lua script:
if redis.call("get",KEYS[1]) == ARGV[1] then
return redis.call("del",KEYS[1])
else
return 0
end
This is important in order to avoid removing a lock that was created by another client. For example a client may acquire the lock, get blocked in some operation for longer than the lock validity time (the time at which the key will expire), and later remove the lock, that was already acquired by some other client. Using just DEL is not safe as a client may remove the lock of another client. With the above script instead every lock is “signed” with a random string, so the lock will be removed only if it is still the one that was set by the client trying to remove it.
What should this random string be? I assume it’s 20 bytes from /dev/urandom, but you can find cheaper ways to make it unique enough for your tasks. For example a safe pick is to seed RC4 with /dev/urandom, and generate a pseudo random stream from that. A simpler solution is to use a combination of unix time with microseconds resolution, concatenating it with a client ID, it is not as safe, but probably up to the task in most environments.
The time we use as the key time to live, is called the “lock validity time”. It is both the auto release time, and the time the client has in order to perform the operation required before another client may be able to acquire the lock again, without technically violating the mutual exclusion guarantee, which is only limited to a given window of time from the moment the lock is acquired.
So now we have a good way to acquire and release the lock. The system, reasoning about a non-distributed system composed of a single, always available, instance, is safe. Let’s extend the concept to a distributed system where we don’t have such guarantees.
上面说的原子操作通过redis的eval script来完成原子操作
Redis uses the same Lua interpreter to run all the commands. Also Redis guarantees that a script is executed in an atomic way: no other script or Redis command will be executed while a script is being executed. This semantic is similar to the one of MULTI / EXEC. From the point of view of all the other clients the effects of a script are either still not visible or already completed.
However this also means that executing slow scripts is not a good idea. It is not hard to create fast scripts, as the script overhead is very low, but if you are going to use slow scripts you should be aware that while the script is running no other client can execute commands.
