Rust rayon vs tokio. Rocket - A web framework for Rust.

Rust rayon vs tokio My computer has eight cores. Based on these results, we believe that we have no choice but remain on async-std. The playground link shows 3 versions, I was expecting the one with SIMD parallelism over Rayon chunks to be the most optimized. However, there's many details that are involved. Use thread-specific pre-allocated data to run tasks in parallel. 206729317s total, 2. tokio - A runtime for writing reliable asynchronous applications with Rust. rs. blocking_lock() method which is helpful if both locking behaviors are needed. In Rayon's case, there is no issue w/ individual task latency. futures is a crate whose purpose is to provide vocabulary types to allow async crates to be independent from the executor/reactor crates. The tokio tasks are a series Now that we understand what Rayon is and its key features let's dive into how to start using it in your Rust projects. Provides I/O, networking, scheduling, timers, With the async runtime tokio and the data-parallelism library rayon, I learned it the hard way. rio - pure rust io_uring library, built on libc, thread & async friendly, misuse resistant rayon - Rayon: A data parallelism library for Rust You found correct tools to do this, you will just need a runtime for your async code (probably tokio or async-std). Rayon also has a convenient shorthand for creating many zipped parallel iterators, which is especially useful if The async example is useful, but being new to Rust and Tokio, I am struggling to work out how to do N requests at once, using URLs from a vector, If possible for your problem I recommend using std async and rayon. rayon. coroutine-rs - Coroutine Library in Rust Tokio with spawn_blocking seems to be the most efficient with the least resources. coroutine-rs - Coroutine Library in Rust EDIT: additionally, rayon does ship spawn, which is slightly less efficient / powerful than join (it adds a 'static bound) but might be the more traditional spawning API you’re used to. Asynchronous IO. clone(); let v = v. We implemented and compared four benchmarks in Rust and C++ using Rayon and OpenMP respectively. It seems to me (system monitoring and asm) that this version keeps the SIMD optimization while using all my laptop CPUs. async-std - Async version of the Rust standard library . You can use our paper as a guide to assess Stream utilities for Tokio. They cannot be preempted (unscheduled) unless they idle at an . So, yes, Tokio and async mutex does solve that, because the task will yield control when it tries to lock and it A quick profiling attempt has shown that a lot of time is being spent waiting for locks/mutexes. Basically my server is going to handle connections in one side and handle the game logic on another side. . rayon is pretty much a one-stop-shop for parallelising cpu-bound work, and it's a mature offering. Getting Started with Rayon. Take a look at the documentation for each. To provide in-depth comparison, we have used multiple configurations for each benchmark. await point, so waiting at it will block the entire runtime (or parts of the runtime in the multi-threaded case). Playground Hello, I like how Rust nicely exposes these parallelism options, and I’m trying to learn more on this. Commented Jan 21, 2022 at 10:44 | You can absolutely run CPU-bound tasks on tokio - just use spawn_blocking(). – user1937198. This is in contrast to the Rust standard library’s std::sync::RwLock, where the priority policy is dependent on Complete rust noob and high-level programmer (mainly typescript and sometimes Elm) here. If I needed more concurrency I would run coroutines on top of those threads (using tokio). Follow edited Jan 21, 2022 at 10:01. I have a workload that looks like this: Roughly 10,000 tasks, defined as async functions. I've used both. Tokio’s file uses spawn_blocking behind the scenes, and this has serious performance consequences. Unless of course, tokio was already multithreaded. But since you're using async, you could avoid Rayon altogether and just spawn a task for each operation: let tasks: Vec<_> = hm . Rayon, for example, is similar to an async exectuor in that it implements its own scheduling on top of the OS. par_iter(). Stars - the number of stars that a project has on GitHub. 一个计算任务大概消耗1~10个核心不等，计算时间2分钟到数天不等，不过典型值大概是2-6个小时。进程池使用rayon创建，大概的流程如下图所示，rayon主进程主要用来每120秒从数据库中提取未开始的任务并运行，rayon子进程都用于计算密集型任务： I prefer using tokio+futures for async and rayon for threadpool. The only thing that matters is getting the end result as fast as possible. The tokio::task module provides important tools for working with tasks:. §Working With Tasks. If you have cpu-bound work, Compare tokio vs rayon and see what are their differences. I guess they did it to keep the Future API simple enough and not §Working With Tasks. It seems async is perfect for this. The call into rayon's join or collect or whatever might schedule an unrelated task on the current thread, blocking the task holding the lock. Strategies for CSV Import: While Tokio already has a threadpool, the documentation of Tokio advises: If your code is CPU-bound and you wish to limit the number of threads used to run it, you should run it on another thread pool such as rayon. RxRust - The Reactive Extensions for the Rust Programming Language . Even the Context is just the Waker that's a raw VTABLE under the hood where anybody could put anything. One of the tools that makes concurrent programming easier in Rust is the rayon crate. This is suitable for blocking I/O, but CPU-heavy operations are often better served by a fixed-size thread pool. Rayon doesn't seem to support asynchronous pool. The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives. As well as scheduling and running tasks, Tokio provides everything you need to perform input and output asynchronously. asked Jan 21 However unless you are using tokio for something else, rayon may be a more appropriate tool. Adding Rayon to Your Rust Project. The processing use case is many tens of thousands of files, concurrent database (SQL) queries, concurrent big-data Ah, I see. tokio::fs really is just std::fs but runs on the background thread pool. Activity is a relative number indicating how actively a project is being developed. Actix happens to be older than Axum, but both should provide you the building blocks you need to do what you want. Each task may arbitrarily take anywhere from 10 nanoseconds, to 10 seconds Tasks are defined as black boxes by users of the library These tasks are heavily CPU-bound. One example of this may be a mutex that gets locked on every iteration. 395758ms avg per iteration rust block_in_place: 8. So ideally I would run no more than eight threads. In both cases you're deferring to a thread pool; it's just a matter of which one you use. The spawn function and JoinHandle type, for scheduling a new task on the Tokio runtime and awaiting the output of a spawned task, respectively,; Functions for running The Tokio scheduler executes Rust futures, which can be thought of as "asynchronous green threads". The tokio::io module provides Tokio's asynchronous core I/O primitives, the AsyncRead, AsyncWrite, and AsyncBufRead If you need to do heavy computing, or use a thread blocking API that has no async equivalent, then use tokio::task::spawn_blocking instead of std::thread::spawn. for I/O). It can be thought of as an asynchronous version of the standard library’s Iterator trait. rayon's thread pool is designed for CPU intensive work– massively The primary advantage of putting rayon on tokio would probably be that the rayon worker threads are running in a Tokio context and thus have access to the runtime context for Rust currently does not provide an async runtime in the standard library. Asynchronous programs in Rust are based around lightweight, non-blocking units of execution called tasks. We will use the I don't think this is really Tokio's fault by itself, it's a "feature" of async Rust in general. yew - Rust / Wasm framework for creating Rust; tokio-rayon; rayon; tokio-rayon VS rayon Compare tokio-rayon vs rayon and see what are their differences. The modules in the rayon crate mirror std itself: so, e. futures-rs - Zero-cost asynchronous programming in Rust hello everyone if I have a data-IO-bound job that is a great use case for fork-join what is the best crate for this task? I am aware of rayon and crossbeam and I can also write my own thread::spawn and handle. 0? Originally, we had planned to ship Tokio 1. But it does also expose a threadpool you can send individual units of work to as well. Howeever, we do have io-uring now for async file I/O and there's also a crate called tokio-uring that uses io-uring async file I/O. things that primarily wait in parallel), while Rayon is intended for CPU-bound things (i. par_iter() to be tedious, you can instead write b. There is a tokio_rayon crate, but i mostly use tokio multi thread rt. 0 release, most of the Tokio stream utilities have been moved into the tokio-stream crate. rust tokio: 25. The CPU bound tasks are synchronous tasks. 0" image = "0. map(|(k, v)| { let k = k. With rayon, I can only send as many concurrent requests as I have processors. My apologies! Executes op within the threadpool. EDIT 2: I totally misread OP's post; it sounded like they were complaining about rayon, rather than about the alternatives. Rayon is a data parallelism library that allows you to perform parallel iteration over collections without the usual boilerplate code associated with multithreading. The Rust Stream Bench is a benchmark suite for evaluating stream parallelism on parallel APIs available in Rust language. await in Tokio. Recent commits have higher weight than older ones. In my code, I launch asynchronous functions simultaneously using Tokio. Rayon: Given the need for high performance and potentially bulk inserts, would Tokio's asynchronous capabilities be more suitable, or would Rayon be better for parallelism in this scenario? Are there specific advantages or disadvantages of using one over the other for this type of task? 2. I'm using tokio for handling all the connections. Non-blocking tasks allow other operations to continue executing concurrently. A runtime for writing reliable asynchronous applications with Rust. Image you have a CPU with 16 cores, and using rayon, you have distributed task A across all 16 cores. I have a computation that most of the time is CPU heavy. That said, it would be interesting to So a rather complex concurrent application of mine was producing deadlock-like symptoms in parts of the code where I myself wasn't using any locks. clone(); tokio::spawn(async move { some_func(&k, &v); Generally, it does not make sense to send messages on channels with rayon — it isn't going to be faster than doing so in a loop. std::thread::sleep does not provide an . Our paper contains abundant information about the benchmark applications and workload characteristics. When to not use Tokio. For the most, parallel iterators in particular are guaranteed to produce the same results as their The rayon crate. Parallel work stealing in arbitrary order in Rust. Both are good web frameworks in Rust. 787424432s total, 8. It compares vanilla tokio, tokio with spawn_blocking, futures, and rayon with different numbers of threads and their efficiency in gzip compressing blocks of bytes and The Tokio docs suggest Rayon as a solution for CPU-bound workloads, but I couldn't find any existing integrations between them. iter() . Tokio will spawn more blocking threads when they are requested through this function until the upper limit configured on the Builder is reached. into_par_iter() for the Enumerate struct. Well, rest easy. However, there are some pitfalls that can happen while using it if you’re not careful. The spawn function and JoinHandle type, for scheduling a new task on the Tokio runtime and awaiting the output of a spawned task, respectively,; Functions for running Rust is well-known for its memory safety and concurrency features. Good luck! If going with a fully tokio based approach, the thing I'd test for is whether it's possible to starve the runtime of threads with too many long running tasks. Tokio uses feature flags a lot to enable or disable various parts of the library, and there are some crates that are executor agnostic but still have a non-optional dependency on Tokio. source futures-rs - Zero-cost asynchronous programming in Rust ureq - A simple, safe HTTP client actix-web - Actix Web is a powerful, pragmatic, and extremely fast web framework for Rust. In the Tokio case, each task is independent and the Tokio scheduler wants to try to fairly schedule across all of them. For full details, see Asynchronous Programming in Rust, and particularly the chapter on "The Async It depends on what you want to do. You probably want to limit the amount of cpu-bound work in progress (no point in taking a message off the queue if you are going to have to queue it in process anyway), thus I would suggest 1 tokio thread(use the single threaded runtime) and N -1 threads for Rayon, or maybe even N threads for Rayon since the 1 tokio thread should be scheduled by the OS infrequently 1. futures-rs - Zero-cost asynchronous programming in Rust . But to complete task A it calls on an algorithm B that itself uses par_iter() to complete §Tuning your file IO. smol - A small and fast async runtime for Rust hyper - An HTTP library for Rust futures-rs - Zero-cost asynchronous programming in Rust reqwest - An easy and powerful Rust HTTP Client embassy - Modern embedded framework, using Rust and async. 0. listening to a database connection), spawn your own dedicated thread to avoid taking one away from the Tokio/Rayon pool. Edit: To save future travelers a bunch of reading, I wasn't limiting the number of blocking threads tokio can spawn. In this article, we will discuss the process of ensuring high-performance data import tasks, specifically focusing on migrating billions of records from CSV files to a MongoDB database using Rust. You can run a rayon thread pool from spawn_blocking(). Rayon's APIs all guarantee data-race freedom, which generally rules out most parallel bugs (though not all). You can do most of your work in the context of a Tokio runtime, but if you're going to do something that requires a lot of computation, you can use spawn_blocking to run the computation on a dedicated thread, and bring the result back into the Tokio context when it's completed. Although it seems like Tokio would be useful for projects that simply need to read a lot of files, Tokio provides no advantage here compared to an ordinary threadpool. If your app is CPU-heavy, maybe set tokio to use just one or two threads, to handle the small amount of I/O. Due to the Stream trait’s inclusion in std landing later than Tokio’s 1. I wonder, what is the best way to use async and multithreading in the same crate to provide real concurrency and parallelism? With the async runtime tokio and the data-parallelism library rayon, I learned it the hard way. Blocking rayon threads (deadlocks) Work done in parallel rayon threads that block each others’ threads are something you absolutely want to avoid here. So I decided to roll my own :) I'd love feedback on the code, suggestions for additional features, or ways to In my code, I launch asynchronous functions simultaneously using Tokio. First, add Rayon as a dependency in your Cargo. But I think tokio and rayon both default to NUM_CPUs threads, which means they might squabble over the CPU. await point. Rayon Alternative Strategies. x, I You can use an oneshot channel to send the result back to Tokio when the rayon task finishes. This is because operating systems generally do not provide asynchronous file APIs. Non-Blocking Tasks. Rayon performed as good as OpenMP in cases where the underlying algorithm or compiler gave an advantage or edge Rayon 是一个为 Rust 语言打造的高性能数据并行计算库,让程序员能够轻松地将 串行代码 并行化,充分利用现代硬件的多核心能力。 本文将全面介绍 Rayon 的特性、使用场景、优势以及在实际项目中的使用方法,为您打开 并行编程 的大门。 In the example above, the use of block_on will block the execution until the async function finishes, making it a blocking task. This crate provides helpers to work with them. tl;dr you should probably use tokio. Whichever one looks better to your eyes is probably sufficient to jump up and get started. They are both mature now and really easy to get started with given the async{/* code here */} The hope is this reduces the network overhead to be effectively incurred once since every request is sent concurrently. Meilisearch v1. 395758117s total, 25. But Rayon doesn't support . Rocket - A web framework for Rust. In the paper, we also discussed the methodology used and the outcome of performance evaluation. I am not 100% sure but this might be related to tokio’s internals not being quite “lock-free”. Tokio and Rayon are both abstractions over system threading (where it's still possible to configure the number of threads to be 1) but async/await executors like Tokio are intended for I/O-bound things (i. Rayon is a high-level, data-parallelism library for Rust futures-rs - Zero-cost asynchronous programming in Rust tokio-rayon - Mix async code with CPU-heavy thread pools using Tokio + Rayon smol - A small and fast async runtime for Rust coroutine-rs - Coroutine Library in Rust actix-web - Actix Web is a powerful, pragmatic, I'm building a game server in rust and I'm not the most knowledgeable person when it comes to threading and async. §Why was Stream not included in Tokio 1. Any attempts to use join, scope, or parallel iterators will then operate within that threadpool. You also would not use the std::sync::mpsc channel in async code, but instead use an async channel such as tokio::sync::mpsc. I am not concerned with latency on any one task, just with finishing . The question is if this is a good choise to do this as async code - if all your futures are just cpu-bound calculations, and you want split them on thread this way, it is probably not - rayon and traditional concurrency is a way rust; rust-tokio; Share. Note you're not limited to one or the other. Use rayon if you want simultaneous heavy computations. Provides I/O, networking, scheduling, timers, Hello everyone), I’m a beginner in Rust. The priority policy of Tokio’s read-write lock is fair (or write-preferring), in order to ensure that readers cannot starve writers. tokio is an executor/reactor crate building upon futures, as well as experimenting with variants of a few traits such as AsyncRead and async-std - Async version of the Rust standard library . There are some examples of using rayon in Tokio in this article. To get good performance with file IO on Tokio, it is recommended to batch your operations into as few spawn_blocking calls as possible. Reading a lot of files. §Warning: thread-local data Because op is executing within the Rayon thread-pool, thread-local data from the current thread will not be accessible. One example of this difference can be seen by comparing the two reading examples above. join(). Adding some async on top of your parallel iterators Meilisearch v1. Working With Tasks. This also applies to plain iterators and . 1. And I think I know why. iter(). Improve this question. tokio-uring crate provides truely async fs operations for the linux. Its concurrency model, enabled by threads and the async keyword, along with parallel processing using libraries such as rayon and its capabilities to handle streaming effectively, makes Rust an excellent choice for big data applications. axum - Ergonomic and modular web framework built with Tokio, Tower, and Hyper . Real-World Example: Parallel Image tokio-rayon - Mix async code with CPU-heavy thread pools using Tokio + Rayon futures-rs - Zero-cost asynchronous programming in Rust coroutine-rs - Coroutine Library in Rust Rayon extends many of the types found in the standard library with parallel iterator implementations. 25. tokio will use its thread pool to spawn you a thread that its OK to block, AND the join handle you get back is special and implements the Future trait, so you can await the joining of it without blocking your async FWIW async runtimes also support modifying OS scheduling rules: glommio/actix/(and even tokio via on_thread_start) can pin worker threads to cores or change their priority. Think systems in a game engine. It doesn't scale well to millions of concurrent operations while those tokio::net and tokio::sync happily do. The Rayon crate provides exactly this, so Why not combine them? pub fn rayon_task() -> Result<String, String> { loop { // need a way to get json data in this rayon function // so that each time the tokio_task() function // sends data, the loop will run again } } pub async tokio_task() { loop { // send json to the rayon_task function } } I have 2 functions started from main, one is utilizing tokio the other rayon. The rayon crate is a well known library that provides a thread pool specifically intended for expensive CPU-bound computations, and you can use it for this purpose together with Tokio. The problem is spawn requires the closure to be 'static but I want to use the borrowed data instead of making owned copies. The documentation for tokio::task covers this in detail. Provides I/O, networking, scheduling, timers, rust-threadpool - A very simple thread pool for parallel task execution . I believe it will eventually become the part of the tokio crate itself, but it's pretty young currently. You can use an oneshot channel to send the result back to Tokio when the rayon task finishes. 0 with a stable Stream type but unfortunately the RFC had not been merged in time for Stream to reach std on a stable compiler in time for As for Tokio, the library has been written such that it is not possible to silently spawn a Tokio runtime in the background in the same way as you often see with async-std. There are dependencies between tasks, where some tasks sometimes wait for partial results from other tasks. actix-web - Actix Web is a powerful, pragmatic, and extremely fast web framework for Rust. Steve. The spawn function and JoinHandle type, for scheduling a new task on the Tokio runtime and awaiting the output of a spawned task, respectively,; Functions for running Either will work for your use case. However, I don’t understand the key difference between rayon::scope() and oneshot::channel(). Rayon: A data parallelism library for Rust (by rayon-rs) Concurrency. Also, Tokio wants to keep the run queue as close to empty as possible. You may have heard that parallel execution can produce all kinds of crazy bugs. crossbeam - Tools for concurrent programming in Rust tokio - A runtime for writing reliable asynchronous applications with Rust. If you find calling c. Most of the other problems involve vectors, but it doesn't here as I am trying to do the following: Get a string: String::from("Lorem ipsum dolor sit amet") How to turn a string into a parallel iterator using Rayon and Rust? 1. Rayon is a very powerful crate. e. Note that you usually should avoid blocking tasks within an async executor. This limit is very large by default, because spawn_blocking is often used for various kinds of IO operations that cannot be performed asynchronously. things that work in parallel). If your event loops are tracking progress through futures In this blog post, we'll explore one such library, Rayon, which simplifies parallelism in Rust and allows developers to write efficient and safe parallel code. When the ThreadPool is dropped, that’s a signal for the threads it manages to terminate, they will complete executing any remaining work that you have spawned, and automatically terminate. It is made by the tokio maintainers, so it's trust-worthy and while it is still on v0. g. I think you'll get the most out of it if you can structure your tasks as a stream of independent events and use parallel iterators. Async tasks are non-preemptive, also called cooperative multi-tasking. A Stream is an asynchronous sequence of values. In other words, if your code compiles, it typically does the same thing it did before. But I'm not sure if it runs in parallel. Parallelising file processing using rayon. hyper - An HTTP library for Rust . Initially I thought scope would work (and the code compiles too), but it seems Note: Tokio's Mutex does have a . And being relatively new to Rust, I'm not sure how to fix this problem. If the runtime uses as many threads as there are cpu cores, it should normally max out all the cores (except if every task is waiting on a bottleneck). Growth - month over month growth in stars. toml file: [dependencies] rayon = "1. If you look at the Future trait it doesn't really have any generic parameters that could be specific to a particular runtime. As a JS / TypeScript dev who thinks in terms of "the event loop", I'm wondering in what circumstances it would make sense to implement a solution using multi-threading instead of in terms of tasks / futures like one would do if using Tokio. 787424ms avg per iteration rust rayon (not in the threads since I don't use reddit): 2. This is what I thought tokio could help me with. This leaves the Tokio worker threads free to tokio::fs is implemented using spawn_blocking thread because linux/unix did not have async I/O for file when it is written, so it really does not provide any speedup. 1" We're also adding the image crate for our example. , the option module in Rayon contains parallel iterators for the Option type, which is found in the option module of std. For synchronous work that runs forever (e. If you are doing io-bound work, Tokio would be what you want -- you would use it as a runtime for the async capabilities in Rust. 上のコマンド群、全て--releaseオプションをつけ忘れており、Rust本来の性能を発揮できていませんでした！ For CPU-bound computation, use a separate fork-join thread pool like rayon. Tokio vs. I have a rayon::ThreadPool which I want to use to perform CPU bound tasks outside of Tokio's runtime context. The answers to your questions are yes and yes. Ensuring High-Performance CSVMongoDB Import with Rust: Tokio vs. It turns out tokio is a bit awkward to configure for my use case, and not in fact more performant than rayon or futures / other flavors of async. zip(&c), which will call c. 10. rayon - Rayon: A data parallelism library for Rust . You can probably get away with strategic placement of tokio::task::yield_now() to allow the scheduler to do its thing. The spawn function and JoinHandle type, for scheduling a new task on the Tokio runtime and awaiting the output of a spawned task, respectively,; Functions for running blocking I know tokio allows to write concurrent code. The question is about when to use tokio::spawn vs std::thread::spawn. I don't want or Regarding the current state of affairs: std contains a subset of the futures crate: the Future trait. So the mutex can be both synchronous and asynchronous! See also: Why do I get a deadlock when using Tokio with a std::sync::Mutex? std::sync::Mutex vs futures:lock:Mutex vs futures_lock::Mutex for async on the Rust forum §Working With Tasks. . But I've found the resources online very hard to understand and I can't find an example of this use install() executes a closure in one of the ThreadPool’s threads. How to finely control the scheduling of rayon? 2. For examples of usage and a more in-depth description of streams you can also refer to the streams tutorial on the tokio website. §Warning: execution order If the current thread is part of a different thread pool, it will try to keep busy Don't use anything that blocks in tokio, or async in general. In each asynchronous function, I offload complex computations to the Rayon thread pool and wait for the result. tokio-rayon. rust-numpy - PyO3-based Rust bindings of the NumPy C-API . par_iter() for you. rayon - Rayon: A data parallelism library for Rust Additionally, Tokio seems to be adversely impacted by the CPU-bound (Rust) asynchronous tasks. Rayon extends many of the types found in the standard library with parallel iterator implementations. In addition, any other rayon operations called inside of install() will also execute in the context of the ThreadPool. In each asynchronous function, I offload complex computations to the Rayon thread pool and wait for rayon VS tokio-rayon Compare rayon vs tokio-rayon and see what are their differences. Unlike spawn_blocking, the rayon thread pool has a small maximum number of threads, which is why it is suitable for expensive computations. 206729ms avg per iteration Tokio’s `spawn_blocking` and `block_in_place` run blocking code on a potentially large number of Tokio-controlled threads. rayon is not a good fit for async because it operates on ordinary non-async functions, and blocks in operations like for_each(). rust-threadpool - A very simple thread pool for parallel task execution . 6 saw a new iteration of our vector store feature, adding the ability to interact with OpenAI to generate My take: use tokio/async-std if you have many tasks waiting (e. I am sure there may be other too. Mix async code with CPU-heavy thread pools using Tokio + Rayon (by andybarron) Suggest topics Source Code. This is the same issue as what happens if you hold an non-async std mutex across an . This is the M:N threading pattern where many user land tasks are multiplexed on a few operating system threads. Enabling parking_lot on tokio improves the timing to around 600ms, which is already an improvement, however still not at level of rayon/zig. Rust, known for its safety and performance, has gained significant popularity in building efficient systems for handling big data. docs. 早すぎ！！！どんどんtokio使っていきます！ 原因はわからないですが、皆さんもVS Codeのターミナルで作業を行うときはお気をつけください！ さらに追記. 6 saw a new iteration of our vector store feature , adding the ability to interact with OpenAI to generate embeddings, rather than requesting that users provide them. Everything works fine. ozvrzkf yjiykx ksy ykljoq nqtaen rleik rzochal jpstro woova rovz