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#GOSYNC MAP CODE#

What happens if you return a non-nil newValue with store = false?) I expected to see at least methods Modify and DeleteOrStore on sync.Map What did you see instead? I don't know good use cases for LoadOrCompute and DeleteOrCompute, though, unlike for Modify and DeleteOrStore. Likewise, a DeleteOrCompute is potentially useful. This could be useful if computing a new value is expensive for some reason. Here, we will launch a bunch of goroutines that will add and retrieve values from our map concurrently.M.Modify(key, func(value interface) Note: Range does not necessarily correspond to any consistent snapshot of the Map's contents. If f returns false, the range stops the iteration.

Range(f func(key, value any) bool) calls f sequentially for each key and value present in the map.

Store(key, value any) sets the value for a key.

The loaded result is true if the value was loaded, and false if stored. Otherwise, it stores and returns the given value.

LoadOrStore(key, value any) returns the existing value for the key if present.

The loaded result reports whether the key was present.

LoadAndDelete(key any) deletes the value for a key, returning the previous value if any.

Load(key any) returns the value stored in the map for a key, or nil if no value is present.

A Map must not be copied after first use. In these two cases, the use of a sync.Map may significantly reduce lock contention compared to a Go map paired with a separate Mutex or RWMutex.

When multiple goroutines read, write, and overwrite entries for disjoint sets of keys.

When the entry for a given key is only ever written once but read many times, as in caches that only grow.The Map type is optimized for two common use cases:

#GOSYNC MAP CODE#

Most code should use a plain Go map instead, with separate locking or coordination, for better type safety and to make it easier to maintain other invariants along with the map content. Loads, stores, and deletes are spread over constant time. Map is like the standard mapany but is safe for concurrent use by multiple goroutines without additional locking or coordination. It can be seen that the sync.Pool is strictly a temporary object pool, which is suitable for storing some temporary objects that will be shared among goroutines. Notice how we did type assertion when we call Get. Now, we can simply use the RLock and RUnlock methods so that readers don't have to wait for each other. We will also change sync.Mutex to sync.RWMutex. Let's add a GetValue method which will read the counter value. Notice how RWMutex has additional RLock and RUnlock methods compared to Mutex. RLock() acquires or holds the read lock.Similar to sync.Mutex, we can use sync.RWMutex using the following methods: Sync.RWMutex is thus preferable for data that is mostly read, and the resource that is saved compared to a sync.Mutex is time. They only have to wait for writers holding the lock. In other words, readers don't have to wait for each other. The lock can be held by an arbitrary number of readers or a single writer. RWMutexĪn RWMutex is a reader/writer mutual exclusion lock. Note: Similar to WaitGroup a Mutex must not be copied after first use. Looks like we solved our issue and the output looks correct as well. Wait() blocks the program until all the goroutines specified by Add() have invoked Done() from within.Īdding 25 to 14 Adding 10 to 39 Result is 49.Done() is called within the goroutine to signal that the goroutine has successfully executed.This must be called before we execute a goroutine.

Add(delta int) takes in an integer value which is essentially the number of goroutines that the WaitGroup has to wait for.

We can use the sync.WaitGroup using the following methods: At the same time, Wait can be used to block until all goroutines have finished. Then each of the goroutines runs and calls Done when finished. The main goroutine calls Add to set the number of goroutines to wait for. WaitGroupĪ WaitGroup waits for a collection of goroutines to finish. The sync package provides useful primitives. As we learned earlier, goroutines run in the same address space, so access to shared memory must be synchronized.