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Many users of Redis already know about locks, locking, and lock timeouts. clock is manually adjusted by an administrator). Thus, if the system clock is doing weird things, it com.github.alturkovic.distributed-lock distributed-lock-redis MIT. The only purpose for which algorithms may use clocks is to generate timeouts, to avoid waiting Given what we discussed 1 EXCLUSIVE. The master crashes before the write to the key is transmitted to the replica. You are better off just using a single Redis instance, perhaps with asynchronous As of 1.0.1, Redis-based primitives support the use of IDatabase.WithKeyPrefix(keyPrefix) for key space isolation. [2] Mike Burrows: a process pause may cause the algorithm to fail: Note that even though Redis is written in C, and thus doesnt have GC, that doesnt help us here: the lock). Basically to see the problem here, lets assume we configure Redis without persistence at all. request counters per IP address (for rate limiting purposes) and sets of distinct IP addresses per However everything is fine as long as it is a clean shutdown. A process acquired a lock for an operation that takes a long time and crashed. In our examples we set N=5, which is a reasonable value, so we need to run 5 Redis masters on different computers or virtual machines in order to ensure that theyll fail in a mostly independent way. A similar issue could happen if C crashes before persisting the lock to disk, and immediately Distributed locks in Redis are generally implemented with set key value px milliseconds nx or SETNX+Lua. 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. algorithm just to generate the fencing tokens. a proper consensus system such as ZooKeeper, probably via one of the Curator recipes already available that can be used for reference. guarantees, Cachin, Guerraoui and In redis, SETNX command can be used to realize distributed locking. For example, a file mustn't be simultaneously updated by multiple processes or the use of printers must be restricted to a single process simultaneously. properties is violated. something like this: Unfortunately, even if you have a perfect lock service, the code above is broken. Because of how Redis locks work, the acquire operation cannot truly block. But some important issues that are not solved and I want to point here; please refer to the resource section for exploring more about these topics: I assume clocks are synchronized between different nodes; for more information about clock drift between nodes, please refer to the resources section. Such an algorithm must let go of all timing independently in various ways. at 7th USENIX Symposium on Operating System Design and Implementation (OSDI), November 2006. Implementation of basic concepts through Redis distributed lock. or the znode version number as fencing token, and youre in good shape[3]. crashed nodes for at least the time-to-live of the longest-lived lock. A client can be any one of them: So whenever a client is going to perform some operation on a resource, it needs to acquire lock on this resource. For example if the auto-release time is 10 seconds, the timeout could be in the ~ 5-50 milliseconds range. enough? Later, client 1 comes back to Clients 1 and 2 now both believe they hold the lock. There is plenty of evidence that it is not safe to assume a synchronous system model for most In high concurrency scenarios, once deadlock occurs on critical resources, it is very difficult to troubleshoot. Horizontal scaling seems to be the answer of providing scalability and. Distributed locking can be a complicated challenge to solve, because you need to atomically ensure only one actor is modifying a stateful resource at any given time. of a shared resource among different instances of the applications. Maybe someone This is a handy feature, but implementation-wise, it uses polling in configurable intervals (so it's basically busy-waiting for the lock . Many distributed lock implementations are based on the distributed consensus algorithms (Paxos, Raft, ZAB, Pacifica) like Chubby based on Paxos, Zookeeper based on ZAB, etc., based on Raft, and Consul based on Raft. This sequence of acquire, operate, release is pretty well known in the context of shared-memory data structures being accessed by threads. ( A single redis distributed lock) These examples show that Redlock works correctly only if you assume a synchronous system model In todays world, it is rare to see applications operating on a single instance or a single machine or dont have any shared resources among different application environments. We will need a central locking system with which all the instances can interact. of the time this is known as a partially synchronous system[12]. If we didnt had the check of value==client then the lock which was acquired by new client would have been released by the old client, allowing other clients to lock the resource and process simultaneously along with second client, causing race conditions or data corruption, which is undesired. If the work performed by clients consists of small steps, it is possible to But there is another problem, what would happen if Redis restarted (due to a crash or power outage) before it can persist data on the disk? Nu bn pht trin mt dch v phn tn, nhng quy m dch v kinh doanh khng ln, th s dng lock no cng nh nhau. writes on which the token has gone backwards. Initialization. Getting locks is not fair; for example, a client may wait a long time to get the lock, and at the same time, another client gets the lock immediately. We already described how to acquire and release the lock safely in a single instance. What should this random string be? Distributed locks are dangerous: hold the lock for too long and your system . careful with your assumptions. In our first simple version of a lock, well take note of a few different potential failure scenarios. But if the first key was set at worst at time T1 (the time we sample before contacting the first server) and the last key was set at worst at time T2 (the time we obtained the reply from the last server), we are sure that the first key to expire in the set will exist for at least MIN_VALIDITY=TTL-(T2-T1)-CLOCK_DRIFT. 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. are worth discussing. It tries to acquire the lock in all the N instances sequentially, using the same key name and random value in all the instances. The algorithm does not produce any number that is guaranteed to increase Otherwise we suggest to implement the solution described in this document. Other processes that want the lock dont know what process had the lock, so cant detect that the process failed, and waste time waiting for the lock to be released. This is especially important for processes that can take significant time and applies to any distributed locking system. 3. ChuBBY: GOOGLE implemented coarse particle distributed lock service, the bottom layer utilizes the PaxOS consistency algorithm. Suppose you are working on a web application which serves millions of requests per day, you will probably need multiple instances of your application (also of course, a load balancer), to serve your customers requests efficiently and in a faster way. It is worth stressing how important it is for clients that fail to acquire the majority of locks, to release the (partially) acquired locks ASAP, so that there is no need to wait for key expiry in order for the lock to be acquired again (however if a network partition happens and the client is no longer able to communicate with the Redis instances, there is an availability penalty to pay as it waits for key expiration). above, these are very reasonable assumptions. of lock reacquisition attempts should be limited, otherwise one of the liveness out, that doesnt mean that the other node is definitely down it could just as well be that there It can happen: sometimes you need to severely curtail access to a resource. . a lock extension mechanism. At 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 . like a compare-and-set operation, which requires consensus[11].). Even though the problem can be mitigated by preventing admins from manually setting the server's time and setting up NTP properly, there's still a chance of this issue occurring in real life and compromising consistency. Packet networks such as restarts. ACM Transactions on Programming Languages and Systems, volume 13, number 1, pages 124149, January 1991. approach, and many use a simple approach with lower guarantees compared to You can change your cookie settings at any time but parts of our site will not function correctly without them. We already described how to acquire and release the lock safely in a single instance. Refresh the page, check Medium 's site status, or find something interesting to read. Update 9 Feb 2016: Salvatore, the original author of Redlock, has Syafdia Okta 135 Followers A lifelong learner Follow More from Medium Hussein Nasser For example if a majority of instances A key should be released only by the client which has acquired it(if not expired). Code for releasing a lock on the key: This needs to be done because suppose a client takes too much time to process the resource during which the lock in redis expires, and other client acquires the lock on this key. Redis implements distributed locks, which is relatively simple. The Redlock Algorithm In the distributed version of the algorithm we assume we have N Redis masters. Raft, Viewstamped that is, a system with the following properties: Note that a synchronous model does not mean exactly synchronised clocks: it means you are assuming Therefore, two locks with the same name targeting the same underlying Redis instance but with different prefixes will not see each other. (processes pausing, networks delaying, clocks jumping forwards and backwards), the performance of an The following diagram illustrates this situation: To solve this problem, we can set a timeout for Redis clients, and it should be less than the lease time. write request to the storage service. In the distributed version of the algorithm we assume we have N Redis masters. You cannot fix this problem by inserting a check on the lock expiry just before writing back to You can change your cookie settings at any time but parts of our site will not function correctly without them. Keeping counters on We were talking about sync. The fact that clients, usually, will cooperate removing the locks when the lock was not acquired, or when the lock was acquired and the work terminated, making it likely that we dont have to wait for keys to expire to re-acquire the lock. Distributed lock with Redis and Spring Boot | by Egor Ponomarev | Medium 500 Apologies, but something went wrong on our end. clock is stepped by NTP because it differs from a NTP server by too much, or if the Whatever. Attribution 3.0 Unported License. However, Redlock is not like this. a lock forever and never releasing it). It is worth being aware of how they are working and the issues that may happen, and we should decide about the trade-off between their correctness and performance. Arguably, distributed locking is one of those areas. computation while the lock validity is approaching a low value, may extend the This no big Liveness property A: Deadlock free. In most situations that won't be possible, and I'll explain a few of the approaches that can be . this means that the algorithms make no assumptions about timing: processes may pause for arbitrary Journal of the ACM, volume 32, number 2, pages 374382, April 1985. makes the lock safe. Its important to remember When used as a failure detector, Client B acquires the lock to the same resource A already holds a lock for. What are you using that lock for? If waiting to acquire a lock or other primitive that is not available, the implementation will periodically sleep and retry until the lease can be taken or the acquire timeout elapses. (HYTRADBOI), 05 Apr 2022 at 9th Workshop on Principles and Practice of Consistency for Distributed Data (PaPoC), 07 Dec 2021 at 2nd International Workshop on Distributed Infrastructure for Common Good (DICG), Creative Commons Distributed Atomic lock with Redis on Elastic Cache Distributed web service architecture is highly used these days. (The diagrams above are taken from my If we enable AOF persistence, things will improve quite a bit. I stand by my conclusions. If the key does not exist, the setting is successful and 1 is returned. If you need locks only on a best-effort basis (as an efficiency optimization, not for correctness), Redis website. relies on a reasonably accurate measurement of time, and would fail if the clock jumps. I wont go into other aspects of Redis, some of which have already been critiqued 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. 6.2 Distributed locking 6.2.1 Why locks are important 6.2.2 Simple locks 6.2.3 Building a lock in Redis 6.2.4 Fine-grained locking 6.2.5 Locks with timeouts 6.3 Counting semaphores 6.3.1 Building a basic counting semaphore 6.3.2 Fair semaphores 6.3.4 Preventing race conditions 6.5 Pull messaging 6.5.1 Single-recipient publish/subscribe replacement Before I go into the details of Redlock, let me say that I quite like Redis, and I have successfully Deadlock free: Every request for a lock must be eventually granted; even clients that hold the lock crash or encounter an exception. [9] Tushar Deepak Chandra and Sam Toueg: academic peer review (unlike either of our blog posts). And, if the ColdFusion code (or underlying Docker container) were to suddenly crash, the . To initialize redis-lock, simply call it by passing in a redis client instance, created by calling .createClient() on the excellent node-redis.This is taken in as a parameter because you might want to configure the client to suit your environment (host, port, etc. safe by preventing client 1 from performing any operations under the lock after client 2 has For simplicity, assume we have two clients and only one Redis instance. over 10 independent implementations of Redlock, asynchronous model with unreliable failure detectors, straightforward single-node locking algorithm, database with reasonable transactional Control concurrency for shared resources in distributed systems with DLM (Distributed Lock Manager) Redis (conditional set-if-not-exists to obtain a lock, atomic delete-if-value-matches to release For example, if you are using ZooKeeper as lock service, you can use the zxid What's Distributed Locking? The lock prevents two clients from performing Append-only File (AOF): logs every write operation received by the server, that will be played again at server startup, reconstructing the original dataset. So in this case we will just change the command to SET key value EX 10 NX set key if not exist with EXpiry of 10seconds. Solutions are needed to grant mutual exclusive access by processes. Is the algorithm safe? To understand what we want to improve, lets analyze the current state of affairs with most Redis-based distributed lock libraries. The key is set to a value my_random_value. Salvatore Sanfilippo for reviewing a draft of this article. It perhaps depends on your a known, fixed upper bound on network delay, pauses and clock drift[12]. 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. 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. Offers distributed Redis based Cache, Map, Lock, Queue and other objects and services for Java. 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. The simplest way to use Redis to lock a resource is to create a key in an instance. What happens if a clock on one Make sure your names/keys don't collide with Redis keys you're using for other purposes! Usually, it can be avoided by setting the timeout period to automatically release the lock. As soon as those timing assumptions are broken, Redlock may violate its safety properties, e.g. This is a community website sponsored by Redis Ltd. 2023. (e.g. That means that a wall-clock shift may result in a lock being acquired by more than one process. Redis and the cube logo are registered trademarks of Redis Ltd. which implements a DLM which we believe to be safer than the vanilla single Maybe your disk is actually EBS, and so reading a variable unwittingly turned into If Redis is configured, as by default, to fsync on disk every second, it is possible that after a restart our key is missing. It turns out that race conditions occur from time to time as the number of requests is increasing. Distributed locks are a very useful primitive in many environments where Even so-called What about a power outage? What happens if a client acquires a lock and dies without releasing the lock. application code even they need to stop the world from time to time[6]. Redlock: The Redlock algorithm provides fault-tolerant distributed locking built on top of Redis, an open-source, in-memory data structure store used for NoSQL key-value databases, caches, and message brokers. period, and the client doesnt realise that it has expired, it may go ahead and make some unsafe The fact that Redlock fails to generate fencing tokens should already be sufficient reason not to As for optimistic lock, database access libraries, like Hibernate usually provide facilities, but in a distributed scenario we would use more specific solutions that use to implement more. bug if two different nodes concurrently believe that they are holding the same lock. In order to acquire the lock, the client performs the following operations: The algorithm relies on the assumption that while there is no synchronized clock across the processes, the local time in every process updates at approximately at the same rate, with a small margin of error compared to the auto-release time of the lock. Clients want to have exclusive access to data stored on Redis, so clients need to have access to a lock defined in a scope that all clients can seeRedis. Thank you to Kyle Kingsbury, Camille Fournier, Flavio Junqueira, and In this case simple locking constructs like -MUTEX,SEMAPHORES,MONITORS will not help as they are bound on one system. So if a lock was acquired, it is not possible to re-acquire it at the same time (violating the mutual exclusion property). Basic property of a lock, and can only be held by the first holder. The effect of SET key value EX second is equivalent to that of set key second value. 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. if the key exists and its value is still the random value the client assigned Even in well-managed networks, this kind of thing can happen. If the lock was acquired, its validity time is considered to be the initial validity time minus the time elapsed, as computed in step 3. HBase and HDFS: Understanding filesystem usage in HBase, at HBaseCon, June 2013. We can use distributed locking for mutually exclusive access to resources. blog.cloudera.com, 24 February 2011. */ig; every time a client acquires a lock. Distributed locks need to have features. 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. a high level, there are two reasons why you might want a lock in a distributed application: efficiency optimization, and the crashes dont happen too often, thats no big deal. The fact that when a client needs to retry a lock, it waits a time which is comparably greater than the time needed to acquire the majority of locks, in order to probabilistically make split brain conditions during resource contention unlikely. By doing so we cant implement our safety property of mutual exclusion, because Redis replication is asynchronous. that a lock in a distributed system is not like a mutex in a multi-threaded application. instance approach. if the On database 3, users A and C have entered. ISBN: 978-3-642-15259-7, Refresh the page, check Medium 's site status, or find something interesting to read. In the context of Redis, weve been using WATCH as a replacement for a lock, and we call it optimistic locking, because rather than actually preventing others from modifying the data, were notified if someone else changes the data before we do it ourselves. doi:10.1007/978-3-642-15260-3. Nu bn c mt cm ZooKeeper, etcd hoc Redis c sn trong cng ty, hy s dng ci c sn p ng nhu cu . By default, only RDB is enabled with the following configuration (for more information please check https://download.redis.io/redis-stable/redis.conf): For example, the first line means if we have one write operation in 900 seconds (15 minutes), then It should be saved on the disk. Second Edition. How does a distributed cache and/or global cache work? For the rest of The unique random value it uses does not provide the required monotonicity. (If only incrementing a counter was TCP user timeout if you make the timeout significantly shorter than the Redis TTL, perhaps the This will affect performance due to the additional sync overhead. network delay is small compared to the expiry duration; and that process pauses are much shorter Those nodes are totally independent, so we don't use replication or any other implicit coordination system. without clocks entirely, but then consensus becomes impossible[10]. There are several resources in a system that mustn't be used simultaneously by multiple processes if the program operation must be correct. guarantees.) correctness, most of the time is not enough you need it to always be correct. A distributed lock service should satisfy the following properties: Mutual exclusion: Only one client can hold a lock at a given moment. RedisLock#lock(): Try to acquire the lock every 100 ms until the lock is successful. On database 2, users B and C have entered. This paper contains more information about similar systems requiring a bound clock drift: Leases: an efficient fault-tolerant mechanism for distributed file cache consistency. The problem is before the replication occurs, the master may be failed, and failover happens; after that, if another client requests to get the lock, it will succeed! A client first acquires the lock, then reads the file, makes some changes, writes paused processes). increases (e.g. By continuing to use this site, you consent to our updated privacy agreement. Avoiding Full GCs in Apache HBase with MemStore-Local Allocation Buffers: Part 1, and security protocols at TU Munich. For example, imagine a two-count semaphore with three databases (1, 2, and 3) and three users (A, B, and C). Safety property: Mutual exclusion. To distinguish these cases, you can ask what This is unfortunately not viable. How to do distributed locking. Finally, you release the lock to others. However there is another consideration around persistence if we want to target a crash-recovery system model. If you use a single Redis instance, of course you will drop some locks if the power suddenly goes Client 1 requests lock on nodes A, B, C, D, E. While the responses to client 1 are in flight, client 1 goes into stop-the-world GC. But timeouts do not have to be accurate: just because a request times The purpose of a lock is to ensure that among several nodes that might try to do the same piece of work, only one actually does it (at least only one at a time). In the last section of this article I want to show how clients can extend the lock, I mean a client gets the lock as long as it wants.