Let’s build a concurrent non-blocking cache Concurrent Data Structure Design in Go 

Hi, I’m Konrad 

Server Get Service 

Server Cache Get Service func Get(key string, f Func) Result 

Server Cache Get Service func Get(key string, f Func) Result 

Why bother? 

queue := deque.NewDeque() queue.Append(1) queue.Append(2) queue.Append(3) queue.Shift().(int) + 1 // needs type assertion 

queue := deque.NewDeque() queue.Append(1) queue.Append(2) queue.Append(3) item, ok := queue.Shift().(int) if !ok { // handle error } 

type User struct { username string `json:"username"` email string `json:"email"` deque deque.Deque `json:"deque"` } // {"username":"konrad", "email":"[email protected]"} 

type User struct { username string `json:"username"` email string `json:"email"` deque deque.Deque `json:"deque"` } // {"username":"konrad", "email":"[email protected]"} type Deque struct { sync.RWMutex container *list.List // unexported fields capacity int } 

Cache func Get(key string, f Func) Result Get Service 

Blocking Cache If a cache request results in a miss, the cache must wait for the result of the slow function, until then it is blocked. Non-blocking Cache A non-blocking cache has the ability to work on other requests while waiting for the result of the function. 

Recap ● Use -race to uncover data races, does not guarantee the absence of those and is best of your Continuous Integration chain ● Monitor-based synchronization uses sync.Mutex or sync.RWMutex to protect the critical section ● Duplicate suppression by using a signal-only channel to broadcast ready condition ● Alternative design: confine map to monitor goroutine using channels ● Different use of concurrency design can make your solution more expressive 

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