Read through Scheme in Replicated Cache with berkely db

Question

Hi i have a 20 gb of data, while restarting the server i need to populate all the data in to coherence cache.if i create a pre load java class hadrly it will take 30 mins to 1 hour to load the data in to cache, while loading time if any request came means how can give the response to the request. i have gone through the Read through scheme its good. But i dont know how to implement with replicated cahce. is it possible to implement the read through+replicated cache+berkeley. if yes menas please post the sample code with full reference. thanks in advance
Edited by: 875786 on Dec 5, 2011 8:10 PM

Answer 1

If you read the documentation for the replicated scheme configuration here: http://docs.oracle.com/cd/E24290_01/coh.371/e22837/appendix_cacheconfig.htm#BABGHEJE ans specifically the part about the <backing-map> configutation you will see...
http://docs.oracle.com/cd/E24290_01/coh.371/e22837/appendix_cacheconfig.htm#BABGHEJE:
To ensure cache coherence, the backing-map of a replicated cache must not use a read-through pattern to load cache entries. Either use a cache-aside pattern from outside the cache service, or switch to the distributed-scheme, which supports read-through clustered caching.So it would appear that you cannot do read-through with a replicated cache - which makes sense really when you think about it.
As I already asked - why are you trying to put 20GB in a replicated cache?
Presumably you do not have JVMs with heaps well over 20GB to hold all that data, or do you - in which case you must have tuned GC very well. You say you are bothered about NFRs and network latency yet you are building a system that will require either very big heaps, and hence at some point there will be long GCs or you cannot hold all the data in memory so you have to configure expiry and then you have the latency of reading the data from the DB.
If you are using read-through then presumably your use-case does not require all the data to be in the cache - i.e. all you data access is using a get by key and you do not do any filter queries. If this is the case then use a distributed cache where you can store all the data or use read-through. If all you access is using key based gets then you do not need to co-locate the caches and your application in a single JVM - have separate cache server JVMs to hold the data and configure near-caches in your application.
There are various ways to hold 20GB of data that would be much more efficient than you are suggesting with a replicated cache.
JK