Terracotta DB 10.2 | Ehcache API Developer Guide | Cache Usage Patterns
 
Cache Usage Patterns
There are several common access patterns when using a cache. Ehcache supports the following patterns:
*Cache-aside
*Cache-as-SoR
*Read-through
*Write-through
*Write-behind
Cache-aside
With the cache-aside pattern, application code uses the cache directly.
This means that application code which accesses the system-of-record (SoR) should consult the cache first, and if the cache contains the data, then return the data directly from the cache, bypassing the SoR. Otherwise, the application code must fetch the data from the system-of-record, store the data in the cache, and then return it. When data is written, the cache must be updated along with the system-of-record.
Pseudocode for reading values
v = cache.get(k)
if(v == null) {
v = sor.get(k)
cache.put(k, v)
}
Pseudocode for writing values
v = newV
sor.put(k, v)
cache.put(k, v)
Cache-as-SoR
The cache-as-SoR pattern implies using the cache as though it were the primary system-of-record (SoR).
The pattern delegates SoR reading and writing activities to the cache, so that application code is (at least directly) absolved of this responsibility. To implement the cache-as-SoR pattern, use a combination of the following read and write patterns:
*read-through
*write-through or write-behind
Advantages of using the cache-as-SoR pattern are:
*Less cluttered application code (improved maintainability through centralized SoR read/write operations)
*Choice of write-through or write-behind strategies on a per-cache basis
*Allows the cache to solve the thundering-herd problem
A disadvantage of using the cache-as-SoR pattern is:
*Less directly visible code-path
Read-through
Under the read-through pattern, the cache is configured with a loader component that knows how to load data from the system-of-record (SoR).
When the cache is asked for the value associated with a given key and such an entry does not exist within the cache, the cache invokes the loader to retrieve the value from the SoR, then caches the value, then returns it to the caller.
The next time the cache is asked for the value for the same key it can be returned from the cache without using the loader (unless the entry has been evicted or expired).
Write-through
Under the write-through pattern, the cache is configured with a writer component that knows how to write data to the system-of-record (SoR).
When the cache is asked to store a value for a key, the cache invokes the writer to store the value in the SoR, as well as updating the cache.
Write-behind
The write-behind pattern changes the timing of the write to the system-of-record. Rather than writing to the system-of-record while the thread making the update waits (as with write-through), write-behind queues the data for writing at a later time. This allows the user's thread to move along more quickly, at the cost of introducing some lag in time before the SoR is updated.

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