In the optimistic concurrency model, updates to cached objects do not take locks. Instead, the cache client first reads the version of the object to be updated and then sends that version information together with the updated object to the cache for an update. The system only updates the object if the version sent matches the current version of the object. Every update to an object changes its version number, which prevents the update from overwriting someone else’s changes.

The example in this topic illustrates how optimistic concurrency maintains data consistency.

Example

In this example, two cache clients (cacheClientA and cacheClientB) on two separate application servers try to update the same cached object, which is named RadioInventory.

Time Zero: Both Clients Retrieve the Same Object

At time zero (T0), both cache clients instantiate a DataCacheItem class to capture the cached object that they intend to update, together with additional information associated with that cached object, such as version and tag information. This is illustrated in the following diagram and code example.

C#

VB

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//cacheClientA pulls the FM radio inventory from cache
DataCacheFactory clientACacheFactory = new DataCacheFactory();
DataCache cacheClientA = clientACacheFactory.GetCache("catalog");
DataCacheItem radioInventoryA = 
    cacheClientA.GetCacheItem("RadioInventory","electronics");

//cacheClientB pulls the same FM radio inventory from cache
DataCacheFactory clientBCacheFactory = new DataCacheFactory();
DataCache cacheClientB = clientBCacheFactory.GetCache("catalog");
DataCacheItem radioInventoryB= 
    cacheClientA.GetCacheItem("RadioInventory", "electronics");

Time One: The First Update Succeeds

At time one (T1), cacheClientA updates the cached object RadioInventory with a new value. When cacheClientA executes the Put method, the version associated with the RadioInventory cache item increments. At this time, cacheClientB has an out-of-date cache item. This is illustrated in the following diagram and code example.

C#

VB

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//at time T1, cacheClientA updates the FM radio inventory
int newRadioInventoryA = 155;

cacheClientA.Put("RadioInventory", newRadioInventoryA, 
    radioInventoryA.Version,"electronics");

Time Two: The Second Update Fails

At time two (T2), cacheClientB tries to update the RadioInventory cached object by using what is now an out-of-date version number. To prevent the changes from cacheClientA from being overwritten, the cacheClientB Put method call fails. This is illustrated in the following diagram and code example.

C#

VB

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//later, at time T2, cacheClientB tries to 
//update the FM radio inventory, triggers exception ERRCA001
int newRadioInventoryB = 130;

cacheClientB.Put("RadioInventory", newRadioInventoryB,
    radioInventoryB.Version,"electronics");

In the pessimistic locking model, the client explicitly locks objects to perform operations. Other operations that request locks are rejected (the system does not block requests) until the locks are released. When objects are locked, a lock handle is returned as an output parameter. The lock handle is required to unlock the object. In case the client application ends before freeing a locked object, timeouts are provided to release the locks. Locked objects are never expired, but they may expire immediately after they are unlocked if it is past their expiry time.

Note
Transactions spanning operations are not supported. The application that uses cache is responsible for determining the order of the locks and detecting deadlocks, if any.

Concepts

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