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Mutex Lock Targeting: A Closer Examination
In multi-threaded environments, mutexes play a crucial role in coordinating access to shared resources, ensuring data integrity and preventing race conditions. However, understanding how a mutex determines which variables it locks can be a pivotal step in mastering concurrency.
Consider the following example code:
<code class="go">var state = make(map[int]int) var mutex = &sync.Mutex{} var readOps uint64 var writeOps uint64 // Start 100 goroutines to perform repeated reads on state for r := 0; r < 100; r++ { go func() { total := 0 for { key := rand.Intn(5) mutex.Lock() total += state[key] mutex.Unlock() atomic.AddUint64(&readOps, 1) time.Sleep(time.Millisecond) } }() }</code>
Despite its simplicity, this code raises questions about how the mutex knows which variables to lock. Traditionally, mutexes are associated with locking specific variables, but in this example, there seems to be a disconnect between the mutex and the underlying data it protects.
The key to understanding this behavior lies in recognizing that a mutex locks access to a resource, not a variable. This means that any goroutine attempting to access the resource protected by the mutex must first acquire the lock.
In the example code, the mutex synchronizes access to the state map. Since the goroutines are reading and modifying the state map, they must acquire the mutex before performing any operations on it. The acquisition of the mutex ensures that only one goroutine can access the state map at any given time, preventing concurrent modifications and maintaining data integrity.
Therefore, while mutexes do not directly lock specific variables, they provide a mechanism to control access to resources, including shared variables like maps or data structures. By acquiring the mutex before accessing a shared resource, programmers can effectively prevent race conditions and ensure the consistency of their code.
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