1. Windows Server AppFabric Cache
Patterns of use

2. Outline
Reference data
Activity data
Resource data
Priming
Batching

3. Classify your data When using the cache
Classification can help organize
Caches
Regions
Remember that availability, expiration, and eviction are set on a per cache basis
Reference
Activity
Resource
Primary Read Only
Read-Write Not shared
Read-Write, Shared
Catalog Data
Shopping Cart
Auction Data/Seat Assignment

4. Reference data Data that doesn’t change often (or at all)
List of countries, catalog items, descriptions, images
Excellent candidate for caching
Since it doesn’t change frequently also a good candidate for using with local cache
Think about turning off expiration and eviction

5. Activity Data Typically data relating to one client Important data
Shopping cart
Important data
Configure high availability (HA)
Can also use Session provider from ASP.NET

6. Resource data Data that is contentious Need to use locking
Seating assignment for flights or concerts
Need to use locking
Optimistic
Pessimistic

7. Using Optimistic concurrency
Clients must retrieve DataCacheItemVersion
Pass to overload of DataCache.Put
If newer version is already in the cache Put throws an exception
Use DataCache.GetCacheItem to retreive the DataCacheItemVersion
DataCache.Get does have overload with an out param
DataCache.GetIfNewer to avoid full round trip

8. Concurrency APIs
public DataCacheItemVersion Put(string key, object value, DataCacheItemVersion oldVersion);
public DataCacheItemVersion Put(string key, object value, DataCacheItemVersion oldVersion, string region);
public DataCacheItemVersion Put(string key, object value, DataCacheItemVersion oldVersion, TimeSpan timeout);
public DataCacheItemVersion Put(string key, object value, DataCacheItemVersion oldVersion, TimeSpan timeout,
string region);
Parameter
description
key
Key of item in the distributed cache
value
Value of object stored in the cache (serialized)
timeout
How long before the item should expire
oldVersion
DataCacheItemVersion held by client
region
Region to place item

9. Using optimistic concurrency
var version = cache.Add("NewKey", "NewValue");
try {
cache.Put("NewKey", "OtherValue", version); }
catch (DataCacheException ex)
Console.WriteLine(ex.ToString());
//some other process or thread
cache.Put("NewKey", "ChangedValue");

10. On demand This is the most typical pattern of cache usage
Application looks for cached data
If not found pulls from real data source
Puts the data in the cache
AKA Cache-aside pattern

11. On demand object data = null; var key = "DataKey";
data = cache.Get(key);
if (data == null) {
data = GetData();
cache.Add(key, data); }

12. Priming
Priming is a pattern where you pull data into the cache before the first request for it
Typically done on application start
Priming is especially useful with Reference data

13. Batching Batching in general is always more effective
Best used with reference data
Used with Tags or Regions in AppFabric Cache
DataCache.BulkGet
List<string> keys = GetKeys();
var batchItems = cache.BulkGet(keys, "BulkRegion");

14. Summary
You need to classify the data you are storing in the cache to be able to choose the correct features
DataCacheVersion enables optimistic concurrency pattern (resource data)

15. Questions?