Infinispan will be configured via new fluent API using builders, hence the call to  .build() method at the end. We need to configure aspects related to  transactions and cache loaders. The configuration API for cache loaders  is likely going to be changed in not-so-far future. It should be fluent  and more intuitive, generally easier to use than current one. 

I purposely do not show XML configuration. Configuration examples can be found at https://github.com/infinispan/infinispan/blob/master/core/src/main/resources/config-samples/sample.xml. In order to configure transactions and cache loaders, look for tags called  <transaction> and <loaders> and modify that sample file according to below configuration. Tag names and attribute names are very similar for both XML and Java configuration. If that is not enough, there is always a schema in Infinispan distribution.

The configuration of Infinispan is as follows: 

Lines marked with red are different in other containers/configurations, as you’ll see in a minute. The code above implies that we need to specify proper TransactionManagerLookup implementation which is, in this case, GenericTransactionManagerLookup. We  also need to say: "Hey, I wanna use ManagedConnectionFactory as a connectionFactoryClass". OK, here we go. I should, as well, explain how to configure a datasource properly, right? In JBoss AS 7, this is configured as a subsystem in $JBOSS_HOME/standalone/configuration/standalone.xml:

The usage of transactions is very simple as we can obtain a transaction object by injection.

Sources: https://github.com/mgencur/infinispan-examples/blob/master/carmart-tx-jdbc/src/jbossas/java/org/infinispan/examples/carmart/session/CarManager.java

Quite easy, isn’t it …​if you know how to do it. The only problem is that it does not work (at least not completely) :-) If you deploy the app, you find out that when storing a key-value pair in  the cache, an exception is thrown. This exception indicates that the operation with DB (and JDBC cache store) failed. The exception says:

A complete stack trace looks similar to https://gist.github.com/2777348 There’s still an open issue in JIRA (ISPN-604) and it is being worked on. 

But how do we cope with this inconvenience for now…​ By not using a managed datasource but rather a third party library called c3p0 (JDBC3  Connection and Statement Pooling, more information at http://www.mchange.com/projects/c3p0/index.html) Infinispan allows you to use this library for connecting to the database. If you really want to use it, you need to choose a different connectionFactoryClass which is, in this case, PooledConnectionFactory.

Infinispan configuration looks like this:

Transactions are accessible in the same way as in the previous use case. Now let’s look at configuration for Tomcat servlet container. 

Tomcat does not have any Transaction Manager in it so we have to bundle one with the application. For the purpose of this exercise, we choose JBoss Transactions (http://www.jboss.org/jbosstm). See dependencies at the end.

Cache manager and cache configuration is in this form:

For Tomcat, we need to specify a different transactionManagerLookup implementation and datasourceJndiLocation. Tomcat simply places objects  under a bit different JNDI locations. The datasource is defined in context.xml file which has to be on classpath. This file might look like this:

How do we get the transaction manager in the application then? Lets obtain  it directly from a cache. 

Infinispan knows how to find the manager and we need to know how to obtain it from Infinispan.

Sources: https://github.com/mgencur/infinispan-examples/blob/master/carmart-tx-jdbc/src/tomcat/java/org/infinispan/examples/carmart/session/CarManager.java The transaction manager provides standard methods for transactions, such as begin(), commit() and rollback(). 

So…​which dependencies do we always need when using Infinispan with JDBC cache stores and transactions? These are infinspan-core, infinispan-cachestore-jdbc and javax.transaction.jta. The scope for jta dependency, as defined in Maven, is different for JBossAS and Tomcat.

Common dependencies for JBossAS and Tomcat

Of course, our application needs a few more dependencies but these are not directly related to Infinispan. Let’s ignore them in this article. JBoss AS 7 provides managed datasource that is accessible from Infinispan. The only specific dependency (related to transactions or Infinispan) is JTA.

Dependencies specific to JBossAS - using managed Datasource (managed by the server)

Dependencies specific to JBossAS - using c3p0

Yes, you need to bundle also MySQL connector. On the other hand, for Tomcat use case and JBossAS with managed datasource, this jar file needs do be deployed to the server separately. For Tomcat, do this simply by copying the jar file to $TOMCAT_HOME/lib.  For JBoss AS 7, copy the jar file into $JBOSS_HOME/standalone/deployments.

Dependencies specific to Tomcat - using JBoss Transactions

That’s it. I hope you’ve found this article helpful. Any feedback is welcome, especially the positive one :-) If you find any problem with the  application, feel free to comment here or participate in Infinispan forums (http://www.jboss.org/infinispan/forums).

Martin

Don’t be scared the name, use1PcForAutoCommitTransactions is a new feature (5.1.CR1) that does quite a cool thing: increases your transactions’s performance. Let me explain. Before Infinispan 5.1 you could access the cache both transactional and non-transactional. Naturally the non-transactional access is faster and offers less consistency guarantees.But we don’t support mixed access in Infinispan 5.1, so what what’s to be done when you need the speed of non-transactional access and you are ready to trade some consistency guarantees for it? Well here is where use1PcForAutoCommitTransactions helps you. What is does is forces an induced (autoCommit=true) transaction to commit in a single phase. So only 1 RPC instead of 2RPCs as in the case of a full 2 Phase Commit (2PC).

You might end up with inconsistent data if multiple transactions modify the same key concurrently. But if you know that’s not the case, or you can live with it then use1PcForAutoCommitTransactions will help your performance considerably.

Let’s say you do a simple put operation outside the scope of a transaction:

Now let’s see how this would behave if the cache has several different transaction configurations:

Short version: if you use transactions that concurrently write to the same keys, this improvement significantly increases your system' throughput.

Long version: If you’re using Infinispan with transactions that modify the same key(s) concurrently then you can easily end up in a deadlock. A deadlock can also occur if two transaction modify the same key at the same time - which is both inefficient and counter-intuitive. Such a deadlock means that at one transaction(or both) eventually rollback but also the lock on the key is held for the duration of a lockAquistionTimout config option (defaults to 10 seconds). These deadlocks reduces the throughput significantly as transactions threads are held inactive during deadlock time. On top of that, other transactions that want to operate on that key are also delayed, potentially resulting in a cascade effect.

The only encountered performance penalty is during cluster topology changes. At that point the cluster needs to perform some additional computation (no RPC involved) to fail-over the acquired locks from previous to new owners. Another noticeable aspect is that locks are now being released asynchronously, after the transaction commits. This doesn’t add any burden to the transaction duration, but it means that locks are being held slightly longer. That’s not something to be concerned about if you’re not using transactions that compete for same locks though. We plan to benchmark this feature using Radargun benchmark tool - we’ll report back!

You can read the single lock owner design wiki or/and follow the JIRA JIRA discussions.

It’s up to you as an user to decide weather you want to define a cache as transactional or not. By default, infinispan caches are non transactional. A cache can be made transactional by changing the transactionMode attribute:

transactionMode can only take two values: TRANSACTIONAL and NON_TRANSACTIONAL. Same thing can be also achieved programatically:

Important:for transactional caches it is required to configure a TransactionManagerLookup.

The autoCommit attribute was added in order to assure backward compatibility. If a cache is transactional and autoCommit is enabled (defaults to true) then any call that is performed outside of a transaction’s scope is transparently wrapped within a transaction. In other words Infinispan adds the logic for starting a transaction before the call and committing it after the call. So if your code accesses a cache both transactionally and non-transactionally, all you have to do when migrating to Infinispan 5.1 is mark the cache as transactional and enable autoCommit (that’s actually enabled by default, so just don’t disable it :) The autoCommit feature can be managed through configuration:

or programatically:

With optimistic transactions locks are being acquired at transaction prepare time and are only being held up to the point the transaction commits (or rollbacks). This is different from the 5.0 default locking model where local locks are being acquire on writes and cluster locks are being acquired during prepare time. Optimistic transactions can be enabled in the configuration file:

or programatically:

By default, a transactional cache is optimistic.

From a lock acquisition perspective, pessimistic transactions obtain locks on keys at the time the key is written. E.g.

When cache.put(k1,v1) returns k1 is locked and no other transaction running anywhere in the cluster can write to it. Reading k1 is still possible. The lock on k1 is released when the transaction completes (commits or rollbacks).

Pessimistic transactions can be enabled in the configuration file:

or programatically:

From a use case perspective, optimistic transactions should be used when there’s not a lot of contention between multiple transactions running at the same time. That is because the optimistic transactions rollback if data has changed between the time it was read and the time it was committed (writeSkewCheck). On the other hand, pessimistic transactions might be a better fit when there is high contention on the keys and transaction rollbacks are less desirable. Pessimistic transactions are more costly by their nature: each write operation potentially involves a RPC for lock acquisition.

This major transaction rework has opened the way for several other transaction related improvements:

Stay tuned! Mircea