What happens if the Redis master goes down? SETNX key val SETNX is the abbreviation of SET if Not eXists. Offers distributed Redis based Cache, Map, Lock, Queue and other objects and services for Java. reliable than they really are. We propose an algorithm, called Redlock, Client A acquires the lock in the master. Client 2 acquires the lease, gets a token of 34 (the number always increases), and then By Peter Baumgartner on Aug. 11, 2020 As you start scaling an application out horizontally (adding more servers/instances), you may run into a problem that requires distributed locking.That's a fancy term, but the concept is simple. And use it if the master is unavailable. There is also a proposed distributed lock by Redis creator named RedLock. This is especially important for processes that can take significant time and applies to any distributed locking system. the algorithm safety is retained as long as when an instance restarts after a 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 It is not as safe, but probably sufficient for most environments. clear to everyone who looks at the system that the locks are approximate, and only to be used for Complete source code is available on the GitHub repository: https://github.com/siahsang/red-utils. period, and the client doesnt realise that it has expired, it may go ahead and make some unsafe Because the SETNX command needs to set the expiration time in conjunction with exhibit, the execution of a single command in Redis is atomic, and the combination command needs to use Lua to ensure atomicity. 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. This is an essential property of a distributed lock. For the rest of A simpler solution is to use a UNIX timestamp with microsecond precision, concatenating the timestamp with a client ID. Suppose there are some resources which need to be shared among these instances, you need to have a synchronous way of handling this resource without any data corruption. at 7th USENIX Symposium on Operating System Design and Implementation (OSDI), November 2006. So, we decided to move on and re-implement our distributed locking API. A process acquired a lock, operated on data, but took too long, and the lock was automatically released. [6] Martin Thompson: Java Garbage Collection Distilled, Warlock: Battle-hardened distributed locking using Redis Now that we've covered the theory of Redis-backed locking, here's your reward for following along: an open source module! guarantees.) // ALSO THERE MAY BE RACE CONDITIONS THAT CLIENTS MISS SUBSCRIPTION SIGNAL, // AT THIS POINT WE GET LOCK SUCCESSFULLY, // IN THIS CASE THE SAME THREAD IS REQUESTING TO GET THE LOCK, https://download.redis.io/redis-stable/redis.conf, Source Code Management for GitOps and CI/CD, Spring Cloud: How To Deal With Microservice Configuration (Part 2), How To Run a Docker Container on the Cloud: Top 5 CaaS Solutions, Distributed Lock Implementation With Redis. The effect of SET key value EX second is equivalent to that of set key second value. manner while working on the shared resource. posted a rebuttal to this article (see also doi:10.1145/74850.74870. Using the IAbpDistributedLock Service. What are you using that lock for? a DLM (Distributed Lock Manager) with Redis, but every library uses a different A distributed lock service should satisfy the following properties: Mutual exclusion: Only one client can hold a lock at a given moment. 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. for at least a bit more than the max TTL we use. [1] Cary G Gray and David R Cheriton: The lock has a timeout But in the messy reality of distributed systems, you have to be very I will argue in the following sections that it is not suitable for that purpose. If you are concerned about consistency and correctness, you should pay attention to the following topics: If you are into distributed systems, it would be great to have your opinion / analysis. Generally, when you lock data, you first acquire the lock, giving you exclusive access to the data. Its safety depends on a lot of timing assumptions: it assumes If you find my work useful, please Before You Begin Before you begin, you are going to need the following: Postgres or Redis A text editor or IDE of choice. non-critical purposes. HBase and HDFS: Understanding filesystem usage in HBase, at HBaseCon, June 2013. maximally inconvenient for you (between the last check and the write operation). Design distributed lock with Redis | by BB8 StaffEngineer | Medium 500 Apologies, but something went wrong on our end. In that case we will be having multiple keys for the multiple resources. We were talking about sync. several nodes would mean they would go out of sync. This prevents the client from remaining blocked for a long time trying to talk with a Redis node which is down: if an instance is not available, we should try to talk with the next instance ASAP. Also, with the timeout were back down to accuracy of time measurement again! I think the Redlock algorithm is a poor choice because it is neither fish nor fowl: it is Once the first client has finished processing, it tries to release the lock as it had acquired the lock earlier. enough? Martin Kleppman's article and antirez's answer to it are very relevant. a proper consensus system such as ZooKeeper, probably via one of the Curator recipes 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? RedisRedissentinelmaster . (e.g. 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. This post is a walk-through of Redlock with Python. Ethernet and IP may delay packets arbitrarily, and they do[7]: in a famous At the t1 time point, the key of the distributed lock is resource_1 for application 1, and the validity period for the resource_1 key is set to 3 seconds. As soon as those timing assumptions are broken, Redlock may violate its safety properties, A client acquires the lock in 3 of 5 instances. However, Redis has been gradually making inroads into areas of data management where there are distributed systems. That work might be to write some data For example a safe pick is to seed RC4 with /dev/urandom, and generate a pseudo random stream from that. If Redis is configured, as by default, to fsync on disk every second, it is possible that after a restart our key is missing. This bug is not theoretical: HBase used to have this problem[3,4]. occasionally fail. Redis is so widely used today that many major cloud providers, including The Big 3 offer it as one of their managed services. set sku:1:info "OK" NX PX 10000. for efficiency or for correctness[2]. Terms of use & privacy policy. In plain English, this means that even if the timings in the system are all over the place EX second: set the expiration time of the key to second seconds. restarts. For learning how to use ZooKeeper, I recommend Junqueira and Reeds book[3]. complicated beast, due to the problem that different nodes and the network can all fail unnecessarily heavyweight and expensive for efficiency-optimization locks, but it is not a counter on one Redis node would not be sufficient, because that node may fail. a lock extension mechanism. Implementing Redlock on Redis for distributed locks | by Syafdia Okta | Level Up Coding Write Sign up Sign In 500 Apologies, but something went wrong on our end. You should implement fencing tokens. In our first simple version of a lock, well take note of a few different potential failure scenarios. Therefore, two locks with the same name targeting the same underlying Redis instance but with different prefixes will not see each other. and it violates safety properties if those assumptions are not met. for generating fencing tokens (which protect a system against long delays in the network or in Because Redis expires are semantically implemented so that time still elapses when the server is off, all our requirements are fine. that is, it might suddenly jump forwards by a few minutes, or even jump back in time (e.g. In Redis, a client can use the following Lua script to renew a lock: if redis.call("get",KEYS[1]) == ARGV[1] then return redis . (If they could, distributed algorithms would do For example, say you have an application in which a client needs to update a file in shared storage Is the algorithm safe? 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. Instead, please use Co-Creator of Deno-Redlock: a highly-available, Redis-based distributed systems lock manager for Deno with great safety and liveness guarantees. Thus, if the system clock is doing weird things, it Therefore, exclusive access to such a shared resource by a process must be ensured. But a lock in distributed environment is more than just a mutex in multi-threaded application. Well, lets add a replica! [7] Peter Bailis and Kyle Kingsbury: The Network is Reliable, (The diagrams above are taken from my This no big Short story about distributed locking and implementation of distributed locks with Redis enhanced by monitoring with Grafana. In the next section, I will show how we can extend this solution when having a master-replica. 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. above, these are very reasonable assumptions. The sections of a program that need exclusive access to shared resources are referred to as critical sections. stronger consistency and durability expectations which worries me, because this is not what Redis We assume its 20 bytes from /dev/urandom, but you can find cheaper ways to make it unique enough for your tasks. 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. already available that can be used for reference. A long network delay can produce the same effect as the process pause. For example, you can use a lock to: . Well instead try to get the basic acquire, operate, and release process working right. Client 1 acquires lock on nodes A, B, C. Due to a network issue, D and E cannot be reached. Distributed Operating Systems: Concepts and Design, Pradeep K. Sinha, Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems,Martin Kleppmann, https://curator.apache.org/curator-recipes/shared-reentrant-lock.html, https://etcd.io/docs/current/dev-guide/api_concurrency_reference_v3, https://martin.kleppmann.com/2016/02/08/how-to-do-distributed-locking.html, https://www.alibabacloud.com/help/doc-detail/146758.htm. [9] Tushar Deepak Chandra and Sam Toueg: It's often the case that we need to access some - possibly shared - resources from clustered applications.In this article we will see how distributed locks are easily implemented in Java using Redis.We'll also take a look at how and when race conditions may occur and . A similar issue could happen if C crashes before persisting the lock to disk, and immediately The only purpose for which algorithms may use clocks is to generate timeouts, to avoid waiting Replication, Zab and Paxos all fall in this category. is a large delay in the network, or that your local clock is wrong. Alturkovic/distributed Lock. 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. 5.2.7 Lm sao chn ng loi lock. A distributed lock manager (DLM) runs in every machine in a cluster, with an identical copy of a cluster-wide lock database. During the time that the majority of keys are set, another client will not be able to acquire the lock, since N/2+1 SET NX operations cant succeed if N/2+1 keys already exist. It violet the mutual exclusion. We can use distributed locking for mutually exclusive access to resources. Designing Data-Intensive Applications, has received Three core elements implemented by distributed locks: Lock redis command. The code might look The client will later use DEL lock.foo in order to release . doi:10.1145/3149.214121, [11] Maurice P Herlihy: Wait-Free Synchronization, The lock prevents two clients from performing To understand what we want to improve, lets analyze the current state of affairs with most Redis-based distributed lock libraries. For example, imagine a two-count semaphore with three databases (1, 2, and 3) and three users (A, B, and C). crash, the system will become globally unavailable for TTL (here globally means Features of Distributed Locks A distributed lock service should satisfy the following properties: Mutual. 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. An important project maintenance signal to consider for safe_redis_lock is that it hasn't seen any new versions released to PyPI in the past 12 months, and could be considered as a discontinued project, or that which . translate into an availability penalty. What about a power outage? What are you using that lock for? The value value of the lock must be unique; 3. several minutes[5] certainly long enough for a lease to expire. ( A single redis distributed lock) To protect against failure where our clients may crash and leave a lock in the acquired state, well eventually add a timeout, which causes the lock to be released automatically if the process that has the lock doesnt finish within the given time. However, Redis has been gradually making inroads into areas of data management where there are stronger consistency and durability expectations - which worries me, because this is not what Redis is designed for. Implements Redis based Transaction, Redis based Spring Cache, Redis based Hibernate Cache and Tomcat Redis based Session Manager. So now we have a good way to acquire and release the lock. paused). diminishes the usefulness of Redis for its intended purposes. Arguably, distributed locking is one of those areas. RSS feed. Let's examine it in some more detail. trick. assumes that delays, pauses and drift are all small relative to the time-to-live of a lock; if the A process acquired a lock for an operation that takes a long time and crashed. If you want to learn more, I explain this topic in greater detail in chapters 8 and 9 of my For example if the auto-release time is 10 seconds, the timeout could be in the ~ 5-50 milliseconds range. use smaller lock validity times by default, and extend the algorithm implementing correctness, most of the time is not enough you need it to always be correct. algorithm might go to hell, but the algorithm will never make an incorrect decision. 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. (At the very least, use a database with reasonable transactional If a client takes too long to process, during which the key expires, other clients can acquire lock and process simultaneously causing race conditions. This paper contains more information about similar systems requiring a bound clock drift: Leases: an efficient fault-tolerant mechanism for distributed file cache consistency. Maybe your disk is actually EBS, and so reading a variable unwittingly turned into I also include a module written in Node.js you can use for locking straight out of the box. In this scenario, a lock that is acquired can be held as long as the client is alive and the connection is OK. We need a mechanism to refresh the lock before the lease expiration. There are two ways to use the distributed locking API: ABP's IAbpDistributedLock abstraction and DistributedLock library's API. makes the lock safe. The queue mode is adopted to change concurrent access into serial access, and there is no competition between multiple clients for redis connection. See how to implement Extending locks' lifetime is also an option, but dont assume that a lock is retained as long as the process that had acquired it is alive. But timeouts do not have to be accurate: just because a request times sends its write to the storage service, including the token of 34. a lock forever and never releasing it). case where one client is paused or its packets are delayed. Control concurrency for shared resources in distributed systems with DLM (Distributed Lock Manager) that a lock in a distributed system is not like a mutex in a multi-threaded application. However there is another consideration around persistence if we want to target a crash-recovery system model. What we will be doing is: Redis provides us a set of commands which helps us in CRUD way. Redis based distributed MultiLock object allows to group Lock objects and handle them as a single lock. No partial locking should happen. who is already relying on this algorithm, I thought it would be worth sharing my notes publicly. In the following section, I show how to implement a distributed lock step by step based on Redis, and at every step, I try to solve a problem that may happen in a distributed system. Basic property of a lock, and can only be held by the first holder. Throughout this section, well talk about how an overloaded WATCHed key can cause performance issues, and build a lock piece by piece until we can replace WATCH for some situations. The clock on node C jumps forward, causing the lock to expire. detector. Liveness property A: Deadlock free. timeouts are just a guess that something is wrong. forever if a node is down. Consensus in the Presence of Partial Synchrony, I spent a bit of time thinking about it and writing up these notes. We will need a central locking system with which all the instances can interact. Basically, In addition to specifying the name/key and database(s), some additional tuning options are available. All the other keys will expire later, so we are sure that the keys will be simultaneously set for at least this time. dedicated to the project for years, and its success is well deserved. of the Redis nodes jumps forward? relies on a reasonably accurate measurement of time, and would fail if the clock jumps. Lets examine it in some more 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. If one service preempts the distributed lock and other services fail to acquire the lock, no subsequent operations will be carried out. own opinions and please consult the references below, many of which have received rigorous work, only one actually does it (at least only one at a time). Remember that GC can pause a running thread at any point, including the point that is They basically protect data integrity and atomicity in concurrent applications i.e. 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. timing issues become as large as the time-to-live, the algorithm fails. ACM Queue, volume 12, number 7, July 2014. storage. 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. a synchronous network request over Amazons congested network. wrong and the algorithm is nevertheless expected to do the right thing. Redis Redis . It is efficient for both coarse-grained and fine-grained locking. For example: The RedisDistributedLock and RedisDistributedReaderWriterLock classes implement the RedLock algorithm. Redis is commonly used as a Cache database. delayed network packets would be ignored, but wed have to look in detail at the TCP implementation 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 But this is not particularly hard, once you know the Salvatore has been very Maybe your process tried to read an But sadly, many implementations of locks in Redis are only mostly correct. of five-star reviews. We are going to use Redis for this case. While using a lock, sometimes clients can fail to release a lock for one reason or another. Liveness property B: Fault tolerance. 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. Nu bn c mt cm ZooKeeper, etcd hoc Redis c sn trong cng ty, hy s dng ci c sn p ng nhu cu . Many libraries use Redis for distributed locking, but some of these good libraries haven't considered all of the pitfalls that may arise in a distributed environment. distributed locks with Redis. In theory, if we want to guarantee the lock safety in the face of any kind of instance restart, we need to enable fsync=always in the persistence settings. And if youre feeling smug because your programming language runtime doesnt have long GC pauses, Second Edition. Other clients will think that the resource has been locked and they will go in an infinite wait. Some Redis synchronization primitives take in a string name as their name and others take in a RedisKey key. Redis distributed locks are a very useful primitive in many environments where different processes must operate with shared resources in a mutually exclusive way. Each RLock object may belong to different Redisson instances. over 10 independent implementations of Redlock, asynchronous model with unreliable failure detectors, straightforward single-node locking algorithm, database with reasonable transactional And its not obvious to me how one would change the Redlock algorithm to start generating fencing However this does not technically change the algorithm, so the maximum number leases[1]) on top of Redis, and the page asks for feedback from people who are into any system in which the clients may experience a GC pause has this problem. Only one thread at a time can acquire a lock on shared resource which otherwise is not accessible. There are several resources in a system that mustn't be used simultaneously by multiple processes if the program operation must be correct. Keeping counters on We already described how to acquire and release the lock safely in a single instance. 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. After synching with the new master, all replicas and the new master do not have the key that was in the old master! This is Theme borrowed from 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. Before trying to overcome the limitation of the single instance setup described above, lets 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 well use for the distributed algorithm described here. One should follow all-or-none policy i.e lock all the resource at the same time, process them, release lock, OR lock none and return. that no resource at all will be lockable during this time). Featured Speaker for Single Sprout Speaker Series: After we have that working and have demonstrated how using locks can actually improve performance, well address any failure scenarios that we havent already addressed. So you need to have a locking mechanism for this shared resource, such that this locking mechanism is distributed over these instances, so that all the instances work in sync. To ensure that the lock is available, several problems generally need to be solved: I will argue that if you are using locks merely for efficiency purposes, it is unnecessary to incur If Hazelcast nodes failed to sync with each other, the distributed lock would not be distributed anymore, causing possible duplicates, and, worst of all, no errors whatsoever. Raft, Viewstamped This is the time needed This happens every time a client acquires a lock and gets partitioned away before being able to remove the lock. ISBN: 978-3-642-15259-7, some transient, approximate, fast-changing data between servers, and where its not a big deal if Redis distributed lock Redis is a single process and single thread mode. the lock). The original intention of the ZooKeeper design is to achieve distributed lock service. Refresh the page, check Medium 's site status, or find something. The RedisDistributedSemaphore implementation is loosely based on this algorithm. glance as though it is suitable for situations in which your locking is important for correctness. On the other hand, the Redlock algorithm, with its 5 replicas and majority voting, looks at first Basically the client, if in the middle of the Here, we will implement distributed locks based on redis. The key is set to a value my_random_value. granting a lease to one client before another has expired. Journal of the ACM, volume 32, number 2, pages 374382, April 1985. ported to Jekyll by Martin Kleppmann. A lock can be renewed only by the client that sets the lock. If you need locks only on a best-effort basis (as an efficiency optimization, not for correctness), In the latter case, the exact key will be used. of a shared resource among different instances of the applications. Otherwise we suggest to implement the solution described in this document. ISBN: 978-1-4493-6130-3. network delay is small compared to the expiry duration; and that process pauses are much shorter If this is the case, you can use your replication based solution. . Redis based distributed lock for some operations and features of Redis, please refer to this article: Redis learning notes . Thank you to Kyle Kingsbury, Camille Fournier, Flavio Junqueira, and Are you sure you want to create this branch? if the I would recommend sticking with the straightforward single-node locking algorithm for For Redis single node distributed locks, you only need to pay attention to three points: 1. of the time this is known as a partially synchronous system[12]. However, the key was set at different times, so the keys will also expire at different times. We could find ourselves in the following situation: on database 1, users A and B have entered. every time a client acquires a lock. As part of the research for my book, I came across an algorithm called Redlock on the seconds[8]. the storage server a minute later when the lease has already expired. request may get delayed in the network before reaching the storage service. 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. what can be achieved with slightly more complex designs. This is accomplished by the following Lua script: This is important in order to avoid removing a lock that was created by another client. support me on Patreon Basically to see the problem here, lets assume we configure Redis without persistence at all. The lock that is not added by yourself cannot be released. Since there are already over 10 independent implementations of Redlock and we dont know In this case simple locking constructs like -MUTEX,SEMAPHORES,MONITORS will not help as they are bound on one system. 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. (i.e. Those nodes are totally independent, so we don't use replication or any other implicit coordination system. Step 3: Run the order processor app. 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. But every tool has elsewhere. Let's examine what happens in different scenarios. In a reasonably well-behaved datacenter environment, the timing assumptions will be satisfied most Normally,