Module: Concurrent Documentation for concurrent-ruby 1 2.0

Get_groups_list and get_channels_list method implementations are potentially non-thread safe, and there is no simple way to validate it. You could check out the method’s implementation details but in a typical Ruby project it’s turtles all the way down, with the usual excess of external dependencies. The code passed on the block will run in parallel and we can query the state of the future on the main thread without blocking it.

It had a few API calls, some DB requests and finally an action that was performed on all the data that was aggregated. Contrary to the previous approaches, Typhoeus does not spawn Ruby threads but instead uses a cURL multithreading capabilities. Another scenario when depleting the pool can happen is using threads when handling a request in a Puma server. Due to its multithreaded nature, Puma works similarly to Sidekiq. Number of Puma worker threads competing for a database connection can easily exceed the available pool, crashing your Rails production servers.

You may recognise these properties from database transactions. Of course, another potentially viable alternative, depending on your operational requirements and constraints would be to employ background jobs. A number of Ruby Gems exist to support background processing (i.e., saving jobs in a queue and processing them later without blocking the current thread). Notable examples include Sidekiq, Resque, Delayed Job, and Beanstalkd.

Additional Project Details

Dataflow allows you to create a task that will be scheduled when all of its data dependencies are available. The dataflow task itself is also a Future value, so you can build up a graph of these tasks, each of which is run when all the data and other tasks it depends on are available or completed. Specific thread safety guarantees are documented with each abstraction. We can reuse a connection pool as a pool of tokens for accessing Redis.

• Inspired by Erlang, Clojure, Go, JavaScript, actors, and classic concurrency patterns.
• We first create a fiber for each subset of the numbers we want to check if even or odd.
• These features are under active development and may change frequently.
• Although threads are lighter than processes, requiring less overhead, you can still run out of resources if you start too many threads concurrently.

In the next section, we’re going to take a look at Fiber as a mechanism for improving the performance of IO-heavy apps. We then pushed the IDs of the mailers to the job queue and created our pool of 10 worker threads. In the above code, we started by creating a jobs queue for the jobs that need to be performed. We used Queue for this purpose since it’s thread-safe which avoids the need for a more complicated implementation requiring the use of a mutex. A key configuration parameter for a thread pool is typically the number of threads in the pool.

Thread Pooling

Fortunately, there is a better way; namely, thread pooling. This tutorial provides a practical treatment of the various techniques and approaches that are available for concurrency and parallelism in Ruby. When disabled it will be the application programmer’s responsibility to ensure that the handlers are shutdown properly prior to application exit by calling AtExit.run method.

There are many libraries and services that allow you to implement background jobs in your applications. Some popular tools include database-backed job frameworks and message queues. On Windows the Win32 API will be queried for the NumberOfCores from Win32_Processor.

.use_stdlib_logger(level = Logger::FATAL, output = $stderr) ⇒ Object

Probably the safest solution would be to stick with concurrency only on the layer of the HTTP requests. Unless necessary, you should always avoid spawning new threads within Sidekiq jobs. Usually, a better approach might be to spawn more fine-tuned jobs, than to spawn threads inside a How to Run a Successful 1-on-1 Meeting with a Developer job. This is the eBook that I wish existed when I was first tasked with moving the Heroku database to AWS as a developer with limited dev ops experience. The behavior will be different for JRuby and Rubinius because they don’t use GIL, but we’ll focus solely on MRI in this tutorial.

Immutable struct where values are set at construction and cannot be changed later. Sign up to get free protection for your applications and to get access to all the features. Check out my step-by-step guide on tuning the performance of a Rails application. There’s no way of knowing if some gem down the call stack https://bitcoin-mining.biz/ uses a shared mutable state, or a mutex that can cause a deadlock. Occasionally Slack API responded slower than usual, accounting for most of the endpoint’s execution time. Slack requires bot users backend APIs to respond within a maximum of three seconds, so it was necessary to optimize the faulty endpoints.

By using these async methods we can prevent IO operations from blocking our fiber-based code. A case when the pool exhaustion scenario is highly probably is parallelizing code execution within Sidekiq jobs. A single Sidekiq process usually executes jobs in a couple of threads.

This method is responsible for stopping the current fiber and allowing another one to resume. Below is the implementation of a tiny API that accepts a number and responds as plain text if the number provided is even odd. Not everyone uses concurrency directly, but we all use it indirectly via tools like Sidekiq.

Number of processors seen by the OS and used for process scheduling. This option should be needed only because of at_exit ordering issues which may arise when running some of the testing frameworks. Minitest’s test-suite runs itself in at_exit callback which executes after the pools are already terminated. Raised when an object with a start/stop lifecycle has been started an excessive number of times. Often used in conjunction with a restart policy or strategy.

Using threads allows our IO heavy programs to run much faster, but they’re also tough to get right. The error in our results above is caused by a race condition in the handle_response method. A race condition happens when two threads manipulate the same data. This is possible because the Ruby VM allows other threads to run while one is waiting during IO. Even if a program has to make dozens of requests, if we use concurrency, the requests will be made at virtually the same time. Concurrency is most often used for applications that are IO heavy.

C Extensions for MRI

Understanding Ruby concurrency won’t just help you build your own solutions; it will help you understand and troubleshoot existing ones. Raised by an `Executor` when it is unable to process a given task, possibly because of a reject policy or other internal error. High concurrency is not only achievable in Ruby, but is also simpler than you might think. Thanks to the Ruby Gem ecosystem, much of the complexity of multithreading is neatly encapsulated in a number of easy-to-use Ruby Gems out-of-the-box. Well, in the MRI , the unfortunate answer is that you’re basically stuck and there’s very little that multithreading can do for you.

Forking, threading, and background processing are all viable alternatives. The decision as to which one to use depends on the nature of your application, your operational environment, and requirements. Hopefully this tutorial has provided a useful introduction to the options available. Multiple threads within a single process have considerably less overhead than a corresponding number of processes since they share address space and memory.

Before we look into Ruby multithreading options, let’s explore the easier path of spawning multiple processes. One of the drawbacks of this approach is that all the futures start, and then most of them immediately block on their dependencies. We know that there’s no point executing those futures until their dependencies are ready, so let’s not execute each future until all their dependencies are ready.