Home > Article > Backend Development > Understanding sync.Cond in Go: Synchronizing Goroutines in Producer-Consumer Scenarios
In concurrent programming, synchronization is key to preventing data races and ensuring threads or goroutines operate in a coordinated manner. Imagine you have a problem to coordinate multiple producers and consumers accessing a shared resource, such as a buffer or queue. This classic concurrency challenge is known as the producer-consumer problem. In this scenario, synchronization is essential to ensure that producers do not overwrite data and consumers do not read invalid or stale data. Synchronisation is necessary, because without proper synchronization, simultaneous access to shared data can lead to race conditions, data corruption, or crashes. Producers need to wait if the buffer is full, and consumers need to wait if the buffer is empty. There might be scenarios where you have a bounded buffer with a fixed size, and you need to manage access to it among multiple producers and consumers.
sync.Cond in Go is a signaling mechanism that allows goroutines to wait until a specific condition is met. It’s particularly useful for coordinating complex workflows where some goroutines need to pause execution and wait until other goroutines complete certain actions. The ideas behind the sync.Cond are pretty simple and easy to understand:
Imagine you have a buffer (or queue) with a fixed size. Multiple producers generate items and add them to the buffer, while multiple consumers remove items from it. The challenge is to:
Here’s the initial code structure:
package main import ( "fmt" "sync" "time" ) const bufferSize = 5 type Buffer struct { data []int mu sync.Mutex cond *sync.Cond } func (b *Buffer) produce(item int) { // Producer logic to add item to the buffer } func (b *Buffer) consume() int { // Consumer logic to remove item from the buffer return 0 } func main() { buffer := &Buffer{data: make([]int, 0, bufferSize)} buffer.cond = sync.NewCond(&buffer.mu) var wg sync.WaitGroup // Start producer goroutines for i := 1; i <= 3; i++ { wg.Add(1) go func(id int) { defer wg.Done() for j := 0; j < 5; j++ { // Each producer creates 5 items buffer.produce(id*10 + j) // Produce unique items based on id and j time.Sleep(100 * time.Millisecond) } }(i) } // Start consumer goroutines for i := 1; i <= 3; i++ { wg.Add(1) go func(id int) { defer wg.Done() for j := 0; j < 5; j++ { // Each consumer consumes 5 items item := buffer.consume() fmt.Printf("Consumer %d consumed item %d\n", id, item) time.Sleep(150 * time.Millisecond) } }(i) } wg.Wait() fmt.Println("All producers and consumers finished.") }
Our task, as an engineer, is to implement produce and consume methods to achieve these requirements. The the produce method adds items to the buffer and notifies consumers when an item is added. The consume method removes items from the buffer and notifies producers when an item is removed. This problem can be seamlessly solved using sync.Cond to wait and signal when the buffer is full or empty.
Here’s a breakdown of how sync.Cond is used in the produce and consume methods:
Initialization:
buffer.cond = sync.NewCond(&buffer.mu)
Producer Method (produce):
func (b *Buffer) produce(item int) { b.mu.Lock() defer b.mu.Unlock() // Wait if the buffer is full for len(b.data) == bufferSize { b.cond.Wait() // Release lock and wait until signaled } // Add item to the buffer b.data = append(b.data, item) fmt.Printf("Produced item %d\n", item) // Signal a consumer that an item is available b.cond.Signal() }
Consumer Method (consume):
func (b *Buffer) consume() int { b.mu.Lock() defer b.mu.Unlock() // Wait if the buffer is empty for len(b.data) == 0 { b.cond.Wait() // Release lock and wait until signaled } // Remove item from the buffer item := b.data[0] b.data = b.data[1:] fmt.Printf("Consumed item %d\n", item) // Signal a producer that space is available b.cond.Signal() return item }
In this example:
This coordination allows the producers and consumers to share the buffer without interference or deadlock, efficiently managing access based on the buffer’s state.
Imagine you have tasks where multiple goroutines need to wait for a specific condition before proceeding, such as:
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