I have 2 applications, which using the same database. The first app can write and read from database. The second app only read from database.
I include second-level hibernate cache with read-write strategy. And now, when I change data from the first app, I don't see this changes at the second app.
How to resolve this issue?
Disclaimer: I am not an hibernate expert, maybe somebody else can give a more cripsy answer...
This is the same question on SO:
Hibernate 2nd level cache invalidation when another process modifies the database However it seems fairly outdated.
You need to look for a distributed or replicated cache and follow the documentation of the respective product. Examples:
Using Infinispan as JPA second level cache provider
Using EHCache and hibernate
Some blog articles about it:
http://codespot.net/2014/02/03/hibernate-caching-strategies
http://vladmihalcea.com/how-does-hibernate-store-second-level-cache-entries
If one application directly writes to the database you need to properly invalidate the second level caches by yourself.
Related
I use technologies like spring boot, jpa and java 8. I have a question, how can I check if the cache is empty and I should send a query to the database to reload it (how to check that I need to reload the cache)?
As your question is not clear about regarding what type of cache you are using ??
JPA uses the first level of caching is the persistence context.
The Entity Manager guarantees that within a single Persistence Context, for any particular database row, there will be only one object instance. However the same entity could be managed in another User's transaction, so you should use either optimistic or pessimistic locking.
If you mean 2nd level cache ,This level of cache came due to performance reasons.this 2nd level cache sits between Entity Manager and the database. Persistence context shares the cache, making the second level cache available throughout the application. Database traffic is reduced considerably because entities are loaded in to the shared cache and made available from there. So actually laying you dont need to worry about reloading of data from database if cache miss happens.
Now if you are implementing your own logic to implement the cache , then you need to do more research on how actually caching works and different algorithms for caching like LRU,MRU etc. (which I would personally not recommend as you can use existing available providers like ehcache, redis,hazelcast just few names for 2nd level caching )
I have a search bar, and as soon as user types in he must be shown suggestions by querying the database. But if he tries to enter those same characters in sequence I want a way to cache the previous suggestions and return back to him without querying DB. I can use a hashmap but I need a much better implementation. I'm using hibernate as an ORM.
You can plug a cache into your ORM (I'd suggest EHCache, here's the corresponding manual section)
Or you can use a programmatic cache on the application layer. Here, I'd suggest a Guava Cache.
If you use Spring, then both of these are also available through Spring's own Cache abstraction
I am currently working on a project that uses JPA (Toplink, currently) for its persistence. Currently, we are running a single application server, but, for redundancy, we would like to add a load balancer and another application sever (and possibly more as it grows).
First, I'm running into the issue of JPA caching. Since two processes will be updating the same database, the JPA cache returns the cached value rather than going to the database. I see how to turn that off, and the database itself implements a level of caching. Is turning off the cache completely the way to go here? I see the ways to tell JPA to always get from the database at a query level, but in a multi-server environment, it seems that you'll always want that to happen.
Along with this specific question, I'm interested in anyone out there who has implemented a JPA solution with multiple application servers and what problems arose during the implementation (and any suggestions you have).
Thanks much.
As you have found, you can disable the shared cache, see http://wiki.eclipse.org/EclipseLink/Examples/JPA/Caching or http://wiki.eclipse.org/EclipseLink/FAQ/How_to_disable_the_shared_cache%3F
There are also other options available in EclipseLink depending on your data and requirements.
A list of option include:
Disable shared cache
Enable cache coordination (see, http://www.eclipse.org/eclipselink/api/2.1/org/eclipse/persistence/config/PersistenceUnitProperties.html#COORDINATION_PROTOCOL)
Set a cache invalidation timeout (see, http://www.eclipse.org/eclipselink/api/2.1/org/eclipse/persistence/annotations/Cache.html#expiry%28%29)
Enable optimistic locking, this will ensure that any stale object cannot be updated, when an update on stale data occurs it will fail, and EclipseLink will automatically invalidate the object in the cache.
Investigate the Oracle TopLink integration of EclipseLink and Oracle Coherence to provide a distributed cache.
See also, http://en.wikibooks.org/wiki/Java_Persistence/Caching#Caching_in_a_Cluster
There is no perfect solution, the solution used normally depend on the data/class, normally an application has a set of read-only classes, read-mostly classes and write mostly classes. Personally I would enable the cache for the read-only with a 1 day timeout, enable the cache with cache coordination for the read-mostly, and disable the cache for the write mostly.
We are looking at implementing a caching framework for our application to help improve the overall performance of our site.
We are running on Websphere 6.1, Spring, Hibernate and Oracle. The focus currently is on the static data or data that changes very little through out the day but is used a lot.
So any info would be great. I have started my google search and reading but wanted to get a feel for what has worked for members of the community. One of the things that we are interested in is the ability to have the system invalidate the cache when a change does happen in the underlining data.
Thanks
Update:
I came across an article on the IBM web site where it says that Hibernate's Cluster aware caches in conjunction with WebSphere Application Server has not been determined yet; therefore, is is not yet determined whether or not their use is supported.
Thoughts on that? We are running in a clustered environment.
Well the hibernate cache system does just that, I used ehCache effectively and easily with Hibernate (and the second level cache system).
Lucene could be an option too depending on the situation. Hibernate Search or Compass could help with that (although it might take some major work).
Replication using Terracotta could also be an option although I've never done it.
Hibernate has first and second level caching built in. You can configure it to use EhCache, OSCache, SwarmCache, or C3P0 - your choice.
You can also leverage WebSphere's default cache i.e. DynaCache to implement the second level cache. This will allow you to administer, monitor and configure your cache leveraging WebSphere caching infrastructure
I've used ehCache and OSCache and found OSCache to be easier to configure and use.
One of the things that we are
interested in is the ability to have
the system invalidate the cache when a
change does happen in the underlining
data.
From what I can see, Hibernate doesn't actually do the above - from Hibernate's docs:
Be careful. Caches are never aware of
changes made to the persistent store
by another application (though they
may be configured to regularly expire
cached data).
Obviously what it means is that a cache doesn't have ESP, and can't tell if an app not in the cluster has called straight DML on the database - but I am guessing that what you want is an ability to expose a service for legacy apps to hook in and invalidate the cache when they do update that data. And there isn't, to my knowledge, a suggestion about how this might be done.
Our design has one jvm that is a jboss/webapp (read/write) that is used to maintain the data via hibernate (using jpa) to the db. The model has 10-15 persistent classes with 3-5 levels of depth in the relationships.
We then have a separate jvm that is the server using this data. As it is running continuously we just have one long db session (read only).
There is currently no intra-jvm cache involved - so we manually signal one jvm from the other.
Now when the webapp changes some data, it signals the server to reload the changed data. What we have found is that we need to tell hibernate to purge the data and then reload it. Just doing a fetch/merge with the db does not do the job - mainly in respect of the objects several layers down the hierarchy.
Any thoughts on whether there is anything fundamentally wrong with this design or if anyone is doing this and has had better luck with working with hibernate on the reloads.
Thanks,
Chris
A Hibernate session loads all data it reads from the DB into what they call the first-level cache. Once a row is loaded from the DB, any subsequent fetches for a row with the same PK will return the data from this cache. Furthermore, Hibernate gaurentees reference equality for objects with the same PK in a single Session.
From what I understand, your read-only server application never closes its Hibernate session. So when the DB gets updated by the read-write application, the Session on read-only server is unaware of the change. Effectively, your read-only application is loading an in-memory copy of the database and using that copy, which gets stale in due course.
The simplest and best course of action I can suggest is to close and open Sessions as needed. This sidesteps the whole problem. Hibernate Sessions are intended to be a window for a short-lived interaction with the DB. I agree that there is a performance gain by not reloading the object-graph again and again; but you need to measure it and convince yourself that it is worth the pains.
Another option is to close and reopen the Session periodically. This ensures that the read-only application works with data not older than a given time interval. But there definitely is a window where the read-only application works with stale data (although the design guarantees that it gets the up-to-date data eventually). This might be permissible in many applications - you need to evaluate your situation.
The third option is to use a second level cache implementation, and use short-lived Sessions. There are various caching packages that work with Hibernate with relative merits and demerits.
Chris, I'm a little confused about your circumstances. If I understand correctly, you have a both a web app (read/write) a standalone application (read-only?) using Hibernate to access a shared database. The changes you make with the web app aren't visible to the standalone app. Is that right?
If so, have you considered using a different second-level cache implementation? I'm wondering if you might be able to use a clustered cache that is shared by both the web application and the standalone application. I believe that SwarmCache, which is integrated with Hibernate, will allow this, but I haven't tried it myself.
In general, though, you should know that the contents of a given cache will never be aware of activity by another application (that's why I suggest having both apps share a cache). Good luck!
From my point of view, you should change your underline Hibernate cache to that one, which supports clustered mode. It could be a JBoss Cache or a Swarm Cache. The first one has a better support of data synchronization (replication and invalidation) and also supports JTA.
Then you will able to configure cache synchronization between webapp and server. Also look at isolation level if you will use JBoss Cache. I believe you should use READ_COMMITTED mode if you want to get new data on a server from the same session.
The most used practice is to have a Container-Managed Entity Manager so that two or more applications in the same container (ie Glassfish, Tomcat, Websphere) can share the same caches.
But if you don't use an Application container, because you use Play! for instance, then I would build some webservices in the primary Application to read/write consistently in the cache.
I think using stale data is an open door for disaster. Just like Singletons become Multitons, read-only applications are often a write sometimes.
Belt and braces :)