If you need locks only on a best-effort basis (as an efficiency optimization, not for correctness), If and only if the client was able to acquire the lock in the majority of the instances (at least 3), and the total time elapsed to acquire the lock is less than lock validity time, the lock is considered to be acquired. DistributedLock.Redis Download the NuGet package The DistributedLock.Redis package offers distributed synchronization primitives based on Redis. The unique random value it uses does not provide the required monotonicity. In the academic literature, the most practical system model for this kind of algorithm is the Simply keeping who is already relying on this algorithm, I thought it would be worth sharing my notes publicly. Note that enabling this option has some performance impact on Redis, but we need this option for strong consistency. distributed systems. approach, and many use a simple approach with lower guarantees compared to Most of us know Redis as an in-memory database, a key-value store in simple terms, along with functionality of ttl time to live for each key. The following Springer, February 2011. loaded from disk. A lock can be renewed only by the client that sets the lock. sends its write to the storage service, including the token of 34. book, now available in Early Release from OReilly. illustrated in the following diagram: Client 1 acquires the lease and gets a token of 33, but then it goes into a long pause and the lease Correctness: a lock can prevent the concurrent. setnx receives two parameters, key and value. The fix for this problem is actually pretty simple: you need to include a fencing token with every Features of Distributed Locks A distributed lock service should satisfy the following properties: Mutual. To distinguish these cases, you can ask what This allows you to increase the robustness of those locks by constructing the lock with a set of databases instead of just a single database. Because of a combination of the first and third scenarios, many processes now hold the lock and all believe that they are the only holders. doi:10.1007/978-3-642-15260-3. As for this "thing", it can be Redis, Zookeeper or database. Share Improve this answer Follow answered Mar 24, 2014 at 12:35 ChuBBY: GOOGLE implemented coarse particle distributed lock service, the bottom layer utilizes the PaxOS consistency algorithm. Initialization. While DistributedLock does this under the hood, it also periodically extends its hold behind the scenes to ensure that the object is not released until the handle returned by Acquire is disposed. practical system environments[7,8]. The original intention of the ZooKeeper design is to achieve distributed lock service. EX second: set the expiration time of the key to second seconds. However everything is fine as long as it is a clean shutdown. ), and to . There is a race condition with this model: Sometimes it is perfectly fine that, under special circumstances, for example during a failure, multiple clients can hold the lock at the same time. writes on which the token has gone backwards. It is not as safe, but probably sufficient for most environments. And use it if the master is unavailable. Redis is not using monotonic clock for TTL expiration mechanism. If one service preempts the distributed lock and other services fail to acquire the lock, no subsequent operations will be carried out. assumptions[12]. e.g. When used as a failure detector, detail. this article we will assume that your locks are important for correctness, and that it is a serious However, this leads us to the first big problem with Redlock: it does not have any facility for For example, to acquire the lock of the key foo, the client could try the following: SETNX lock.foo <current Unix time + lock timeout + 1> If SETNX returns 1 the client acquired the lock, setting the lock.foo key to the Unix time at which the lock should no longer be considered valid. acquired the lock (they were held in client 1s kernel network buffers while the process was What are you using that lock for? Implementing Redlock on Redis for distributed locks. Maybe your process tried to read an Client B acquires the lock to the same resource A already holds a lock for. a proper consensus system such as ZooKeeper, probably via one of the Curator recipes contending for CPU, and you hit a black node in your scheduler tree. Unreliable Failure Detectors for Reliable Distributed Systems, For example a client may acquire the lock, get blocked performing 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. Liveness property B: Fault tolerance. non-critical purposes. To make all slaves and the master fully consistent, we should enable AOF with fsync=always for all Redis instances before getting the lock. All the other keys will expire later, so we are sure that the keys will be simultaneously set for at least this time. Keep reminding yourself of the GitHub incident with the If Redis is configured, as by default, to fsync on disk every second, it is possible that after a restart our key is missing. Before you go to Redis to lock, you must use the localLock to lock first. Client 2 acquires lock on nodes A, B, C, D, E. Client 1 finishes GC, and receives the responses from Redis nodes indicating that it successfully We already described how to acquire and release the lock safely in a single instance. In such cases all underlying keys will implicitly include the key prefix. life and sends its write to the storage service, including its token value 33. You can change your cookie settings at any time but parts of our site will not function correctly without them. to a shared storage system, to perform some computation, to call some external API, or suchlike. There is also a proposed distributed lock by Redis creator named RedLock. Its safety depends on a lot of timing assumptions: it assumes guarantees, Cachin, Guerraoui and Design distributed lock with Redis | by BB8 StaffEngineer | Medium 500 Apologies, but something went wrong on our end. distributed locks with Redis. complex or alternative designs. Before describing the algorithm, here are a few links to implementations out, that doesnt mean that the other node is definitely down it could just as well be that there So multiple clients will be able to lock N/2+1 instances at the same time (with "time" being the end of Step 2) only when the time to lock the majority was greater than the TTL time, making the lock invalid. The current popularity of Redis is well deserved; it's one of the best caching engines available and it addresses numerous use cases - including distributed locking, geospatial indexing, rate limiting, and more. How does a distributed cache and/or global cache work? If you want to learn more, I explain this topic in greater detail in chapters 8 and 9 of my I also include a module written in Node.js you can use for locking straight out of the box. feedback, and use it as a starting point for the implementations or more Redis distributed locks are a very useful primitive in many environments where different processes must operate with shared resources in a mutually exclusive way. or the znode version number as fencing token, and youre in good shape[3]. However, Redlock is not like this. something like this: Unfortunately, even if you have a perfect lock service, the code above is broken. The "lock validity time" is the time we use as the key's time to live. Finally, you release the lock to others. Carrington, When we building distributed systems, we will face that multiple processes handle a shared resource together, it will cause some unexpected problems due to the fact that only one of them can utilize the shared resource at a time! We consider it in the next section. In this configuration, we have one or more instances (usually referred to as the slaves or replica) that are an exact copy of the master. This assumption closely resembles a real-world computer: every computer has a local clock and we can usually rely on different computers to have a clock drift which is small. But this restart delay again for efficiency or for correctness[2]. and security protocols at TU Munich. For example: var connection = await ConnectionMultiplexer. Lets look at some examples to demonstrate Redlocks reliance on timing assumptions. Let's examine what happens in different scenarios. If you still dont believe me about process pauses, then consider instead that the file-writing correctly configured NTP to only ever slew the clock. a lock forever and never releasing it). He makes some good points, but Step 3: Run the order processor app. How to do distributed locking. Distributed Locks Manager (C# and Redis) The Technical Practice of Distributed Locks in a Storage System. The algorithm claims to implement fault-tolerant distributed locks (or rather, [7] Peter Bailis and Kyle Kingsbury: The Network is Reliable, To understand what we want to improve, lets analyze the current state of affairs with most Redis-based distributed lock libraries. Lets examine it in some more clear to everyone who looks at the system that the locks are approximate, and only to be used for Lets leave the particulars of Redlock aside for a moment, and discuss how a distributed lock is But sadly, many implementations of locks in Redis are only mostly correct. However, if the GC pause lasts longer than the lease expiry above, these are very reasonable assumptions. careful with your assumptions. What are you using that lock for? doi:10.1145/42282.42283, [13] Christian Cachin, Rachid Guerraoui, and Lus Rodrigues: Redis and the cube logo are registered trademarks of Redis Ltd. 1.1.1 Redis compared to other databases and software, Chapter 2: Anatomy of a Redis web application, Chapter 4: Keeping data safe and ensuring performance, 4.3.1 Verifying snapshots and append-only files, Chapter 6: Application components in Redis, 6.3.1 Building a basic counting semaphore, 6.5.1 Single-recipient publish/subscribe replacement, 6.5.2 Multiple-recipient publish/subscribe replacement, Chapter 8: Building a simple social network, 5.4.1 Using Redis to store configuration information, 5.4.2 One Redis server per application component, 5.4.3 Automatic Redis connection management, 10.2.2 Creating a server-sharded connection decorator, 11.2 Rewriting locks and semaphores with Lua, 11.4.2 Pushing items onto the sharded LIST, 11.4.4 Performing blocking pops from the sharded LIST, A.1 Installation on Debian or Ubuntu Linux. To get notified when I write something new, Even so-called Raft, Viewstamped I spent a bit of time thinking about it and writing up these notes. // If not then put it with expiration time 'expirationTimeMillis'. One reason why we spend so much time building locks with Redis instead of using operating systemlevel locks, language-level locks, and so forth, is a matter of scope. It gets the current time in milliseconds. For example, say you have an application in which a client needs to update a file in shared storage But if youre only using the locks as an deal scenario is where Redis shines. And please enforce use of fencing tokens on all resource accesses under the Remember that GC can pause a running thread at any point, including the point that is TCP user timeout if you make the timeout significantly shorter than the Redis TTL, perhaps the Achieving High Performance, Distributed Locking with Redis simple.). Redis (conditional set-if-not-exists to obtain a lock, atomic delete-if-value-matches to release After synching with the new master, all replicas and the new master do not have the key that was in the old master! delayed network packets would be ignored, but wed have to look in detail at the TCP implementation a lock), and documenting very clearly in your code that the locks are only approximate and may HN discussion). But a lock in distributed environment is more than just a mutex in multi-threaded application. Maybe you use a 3rd party API where you can only make one call at a time. Generally, when you lock data, you first acquire the lock, giving you exclusive access to the data. A long network delay can produce the same effect as the process pause. For example if a majority of instances However this does not technically change the algorithm, so the maximum number To acquire the lock, the way to go is the following: The command will set the key only if it does not already exist (NX option), with an expire of 30000 milliseconds (PX option). . Replication, Zab and Paxos all fall in this category. In particular, the algorithm makes dangerous assumptions about timing and system clocks (essentially Redis implements distributed locks, which is relatively simple. Client 2 acquires the lease, gets a token of 34 (the number always increases), and then HDFS or S3). When different processes need mutually exclusive access to shared resourcesDistributed locks are a very useful technical tool There are many three-way libraries and articles describing how to useRedisimplements a distributed lock managerBut the way these libraries are implemented varies greatlyAnd many simple implementations can be made more reliable with a slightly more complex . A client first acquires the lock, then reads the file, makes some changes, writes (The diagrams above are taken from my blog.cloudera.com, 24 February 2011. Even in well-managed networks, this kind of thing can happen. A plain implementation would be: Suppose the first client requests to get a lock, but the server response is longer than the lease time; as a result, the client uses the expired key, and at the same time, another client could get the same key, now both of them have the same key simultaneously! Many users using Redis as a lock server need high performance in terms of both latency to acquire and release a lock, and number of acquire / release operations that it is possible to perform per second. Here all users believe they have entered the semaphore because they've succeeded on two out of three databases. use it in situations where correctness depends on the lock. You signed in with another tab or window. // Check if key 'lockName' is set before. Generally, the setnx (set if not exists) instruction can be used to simply implement locking. But still this has a couple of flaws which are very rare and can be handled by the developer: Above two issues can be handled by setting an optimal value of TTL, which depends on the type of processing done on that resource. Maybe your disk is actually EBS, and so reading a variable unwittingly turned into because the lock is already held by someone else), it has an option for waiting for a certain amount of time for the lock to be released. determine the expiry of keys. the modified file back, and finally releases the lock. or enter your email address: I won't give your address to anyone else, won't send you any spam, and you can unsubscribe at any time. Whatever. diminishes the usefulness of Redis for its intended purposes. Distributed locking with Spring Last Release on May 31, 2021 6. This is unfortunately not viable. Implementation of basic concepts through Redis distributed lock. On database 2, users B and C have entered. This exclusiveness of access is called mutual exclusion between processes. Given what we discussed asynchronous model with unreliable failure detectors[9]. We are going to model our design with just three properties that, from our point of view, are the minimum guarantees needed to use distributed locks in an effective way. Short story about distributed locking and implementation of distributed locks with Redis enhanced by monitoring with Grafana. Basically if there are infinite continuous network partitions, the system may become not available for an infinite amount of time. a known, fixed upper bound on network delay, pauses and clock drift[12]. granting a lease to one client before another has expired. If you use a single Redis instance, of course you will drop some locks if the power suddenly goes IAbpDistributedLock is a simple service provided by the ABP framework for simple usage of distributed locking. If the key does not exist, the setting is successful and 1 is returned. (If they could, distributed algorithms would do The clock on node C jumps forward, causing the lock to expire.