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Synchronization mechanism and performance bottleneck optimization solution in Golang
package main import ( "fmt" "sync" ) var ( count int lock sync.Mutex ) func increment() { lock.Lock() defer lock.Unlock() count++ } func main() { var wg sync.WaitGroup for i := 0; i < 1000; i++ { wg.Add(1) go func() { defer wg.Done() increment() }() } wg.Wait() fmt.Println(count) }
2.2 Condition variable (Cond)
Condition variable is used to communicate between coroutines and implement the waiting and wake-up mechanism of the coroutine . When a coroutine meets certain conditions, you can use condition variables to notify other coroutines. The following is a sample code using condition variables:
package main import ( "fmt" "sync" ) var ( ready bool cond *sync.Cond ) func init() { cond = sync.NewCond(&sync.Mutex{}) } func printNumbers() { cond.L.Lock() defer cond.L.Unlock() for !ready { cond.Wait() } fmt.Println("1 2 3 4 5") } func main() { go printNumbers() cond.L.Lock() ready = true cond.Signal() cond.L.Unlock() }
2.3 Read-write lock (RWMutex)
Read-write lock can further improve the performance of concurrent programs. In scenarios where there are many reads and few writes, using read-write locks can allow multiple coroutines to read shared resources at the same time, while only one coroutine can perform write operations. The following is a sample code using a read-write lock:
package main import ( "fmt" "sync" ) var ( count int lock sync.RWMutex ) func read() { lock.RLock() defer lock.RUnlock() fmt.Println(count) } func write() { lock.Lock() defer lock.Unlock() count++ } func main() { var wg sync.WaitGroup wg.Add(10) for i := 0; i < 5; i++ { go func() { defer wg.Done() read() }() go func() { defer wg.Done() write() }() } wg.Wait() }
3.1 Reduce the lock granularity
When using a mutex lock, you can minimize the lock granularity and only lock the necessary critical section code segments. This reduces lock contention. When using a read-write lock, you can choose a read lock or a write lock according to the actual situation to make full use of the characteristics of parallel reading.
3.2 Use lock-free data structures
For high-concurrency scenarios, you can consider using lock-free data structures, such as the atomic operation function in the atomic package. These functions provide some atomic operations without using locks to ensure data consistency. For example, use atomic.AddInt64() instead of a mutex to ensure consistent counting.
3.3 Use channels instead of mutex locks
Channels can be used as a synchronization mechanism to ensure the order and consistency of data access. In some scenarios, using channels can avoid explicit use of mutex locks, thereby reducing lock contention. However, attention needs to be paid to channel capacity and performance overhead to avoid blocking or memory leaks.
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