How Clojure is multi-threaded

Multi-threaded refers to a program’s ability to execute multiple threads concurrently, allowing parallel processing for increased efficiency and performance.

Emphasis on immutability

At the heart of Clojure’s approach to multi-threaded programming is its emphasis on immutability. In Clojure, data structures are immutable by default. This means that once a data structure is created, it cannot be modified. Instead, operations that would traditionally modify a data structure return a new version of the structure with the change applied. This fundamental principle drastically reduces the complexity of concurrent programming because it eliminates the need for locks or other synchronization mechanisms to prevent concurrent modification errors. When data cannot change, multiple threads can safely operate on the same data without stepping on each other’s toes.

Persistent data structures

Closely related to immutability is Clojure’s use of persistent data structures. These are not merely immutable but are also designed to be efficient when shared across threads. When a modification is made, the resulting data structure shares as much of its structure as possible with the original. This sharing reduces the overhead and memory footprint of creating “new” versions of data structures and makes the process highly efficient, even in highly concurrent applications.

Software transactional memory (STM)

Clojure offers a powerful abstraction called software transactional memory (STM) for scenarios where a mutable state is unavoidable. STM allows developers to define transactions that encapsulate multiple state changes. These transactions behave like database transactions, providing atomicity, consistency, isolation, and durability (ACID) properties. If a transaction conflicts with another (for example, two transactions attempt to modify the same piece of state concurrently), one will be retried until it can be completed without conflict. This model simplifies the reasoning about concurrent updates to shared state, as the STM system handles the complexity of managing synchronization.

Agents and atoms

Clojure provides other concurrency primitives, such as agents and atoms, to manage state changes in a multi-threaded context. Agents allow asynchronous operations on state, with changes queued and applied in a single thread, ensuring that each change is applied consistently without blocking the submitting thread. Atoms provide a way to manage change synchronously but lock-free, suitable for situations where state changes must be immediate and consistent but are relatively simple and fast.

Code example

Let’s look at a code example for better understanding.

(ns clojure-examples.core
  (:gen-class))
(defn increment-counter [counter-atom]
  "Function to increment the value of the given counter atom"
  (swap! counter-atom inc))
(defn -main []
  "Main function"
  (let [counter (atom 0)] ;; Initialize counter atom with value 0
    (println "Initial counter value:" @counter) ;; Print initial counter value
    
    ;; Create 10 threads to increment the counter
    (doseq [n (range 10)]
      ;; Define thread body to increment counter 100 times
      (let [t (Thread. #(do (dotimes [_ 100] (increment-counter counter))
                            ;; Print thread number
                            (println "Incremented by thread" n)))]
        (.start t) ;; Start the thread
        (.join t))) ;; Wait for the thread to finish before proceeding
    
    (println "Final counter value:" @counter))) ;; Print final counter value
(-main) ;; Execute the main function

Code explanation

The code above demonstrates how Clojure’s atom ensures thread safety by allowing only one thread to modify its state at a time, even in a multi-threaded environment:

Line 4: The increment-counter function takes an atom counter-atom and increments its value using swap!.
Line 8: In the -main function:
- Line 10: An atom named counter is initialized with a value of 0.
- Line 11: The initial value of the counter is printed.
- Line 14: A loop creates 10 threads, increasing the counter 100 times.
- Line 19: Each thread is started with (.start t) and then joined with (.join t) to ensure they are complete before proceeding.
- Line 22: After all threads have finished, the final value of the counter is printed.
Line 24: We exit the -main function.

`core.async` for communicating sequential processes (CSP)

Inspired by the communicating sequential processes (CSP) model, Clojure’s core.async library offers a different angle on concurrencyConcurrency refers to the execution of multiple tasks simultaneously, enabling better resource utilization and efficiency by overlapping task execution.. It enables the expression of asynchronous workflows as sequences of operations on channels through which threads can communicate and synchronize. This model is particularly powerful for event-driven or stream-processing applications, allowing for clean separation of concerns and backpressure management.

Conclusion

Clojure’s approach to multi-threaded programming, rooted in immutability and complemented by a suite of concurrency primitives, addresses the complexities of modern software development. By providing a range of tools—from persistent data structures and STM to agents, atoms, and core.async—Clojure enables developers to build robust, concurrent applications with less effort and lower risk of errors. Its philosophy not only makes concurrent programming more accessible but also encourages a shift in how developers think about managing state and synchronization in a multi-threaded environment.

Free Resources