Simple caching with a TTL

Spring's cache abstraction framework is hugely useful for declarative caching as outlined in previous posts. As we start to use more caches, an inherent requirement that arises is periodic and on-demand purging. For the first kind of purge, you require a Time To Live (TTL) to be associated with your cache. External solutions like ehcache provide configuration to be able to do this. There are host of other parameters, like writing to disk, disk location, buffer sizes, max limits that can be configured using the configuration. However, what if your requirement is simpler and don't want to marry into ehcache just yet.

Spring's ConcurrentMapCacheFactoryBean has been made nicely pluggable where you can plug in any backing store that you want to use for the concurrent map based caching. So, here we can plug in our own TTLAwareConcurrentMap. But, I don't want to write TTL logic myself, right? Sure, just use the constructs available from guava. Guava gives a TTL backed map with a CacheBuilder which looks as simple as:

return CacheBuilder.newBuilder().expireAfterWrite(duration, unit).build().asMap();

All we need to do now is create a FactoryBean in Spring that will be injected with the duration (and unit of the duration) of the TTL and it will vend out the store that will be used by Spring's caching framework. Sample FactoryBean isTTLAwareConcurrentMapFactoryBean.

For on-demand spring cache flushes, we can have a JMX operation defined on a custom CacheManager that is injected with the Spring caches at startup. On invocation, the specific cache or all caches may be flushed by invoking the Cache.clear() method. Due credit to this SO question.

Hope this helps!

References:

• http://docs.spring.io/spring/docs/3.2.2.RELEASE/spring-framework-reference/html/cache.html
• http://stackoverflow.com/questions/8181768/can-i-set-a-ttl-for-cacheable
• http://docs.guava-libraries.googlecode.com/git/javadoc/com/google/common/cache/CacheBuilder.html
• http://docs.spring.io/spring/docs/3.1.x/javadoc-api/org/springframework/cache/concurrent/ConcurrentMapCacheFactoryBean.html
• https://github.com/kilokahn/spring-testers/tree/master/spring-cache-tester

More fun with @Cacheable

I am assuming the audience has already got themselves familiar with the previous post where vanilla cache operations were demonstrated. The scope of this post will be:

• Using multiple cache managers in a context
• Using aspectj to cache self calls
• Using cache:advice to cache non-owned calls

Using multiple cache managers in a context

So continuing from the fibonacci example from before, let's say that I wish to use both the simple cache manager as well as the ehcache cache manager? As with the pitfalls in using tx:annotation-driven, only one manager can effectively parade the annotations in the desired way. In tx:annotation-driven, we specify the transaction manager to use in the annotation itself, whereas such a thing is not available in the cache:annotation-driven (yet). Hence, when two cache managers wish to operate in tandem, enter org.springframework.cache.support.CompositeCacheManager. This specifies the list of cache managers that need to be used.

    <bean id="compositeCacheManager" class="org.springframework.cache.support.CompositeCacheManager">
        <property name="cacheManagers">
            <array>
                <ref bean="ehcacheManager" />
                <ref bean="concurrentMapCacheManager" />
            </array>
        </property>
    </bean>

The directive to process the annotation will refer to this compositeCacheManager as the sole manager

    <cache:annotation-driven cache-manager="compositeCacheManager" proxy-target-class="true"
        />

The output can be verified as showing each of the two cache managers operating without treading on each other's toes.

[ 2013-01-18 15:28:36,226 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.ConcurrentMapFibonacciServiceImpl$$EnhancerByCGLIB$$a3241f9a took 7.586 seconds
[ 2013-01-18 15:28:36,227 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.ConcurrentMapFibonacciServiceImpl$$EnhancerByCGLIB$$a3241f9a took 0.001 seconds
[ 2013-01-18 15:28:36,227 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.ConcurrentMapFibonacciServiceImpl$$EnhancerByCGLIB$$a3241f9a took 0.0 seconds
[ 2013-01-18 15:28:36,227 [main] driver.ConcurrentMapFibonacciServiceImpl.flushFibonacciCache():30  INFO ]: Royal ConcurrentMap flush
[ 2013-01-18 15:28:43,797 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.ConcurrentMapFibonacciServiceImpl$$EnhancerByCGLIB$$a3241f9a took 7.569 seconds
[ 2013-01-18 15:28:43,797 [main] driver.ConcurrentMapFibonacciServiceImpl.flushFibonacciCache():30  INFO ]: Royal ConcurrentMap flush
[ 2013-01-18 15:28:51,247 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.EhcacheFibonacciServiceImpl$$EnhancerByCGLIB$$73a5e038 took 7.449 seconds
[ 2013-01-18 15:28:51,247 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.EhcacheFibonacciServiceImpl$$EnhancerByCGLIB$$73a5e038 took 0.0 seconds
[ 2013-01-18 15:28:51,247 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.EhcacheFibonacciServiceImpl$$EnhancerByCGLIB$$73a5e038 took 0.0 seconds
[ 2013-01-18 15:28:51,253 [main] driver.EhcacheFibonacciServiceImpl.flushFibonacciCache():30  INFO ]: Royal Ehcache flush
[ 2013-01-18 15:28:58,850 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.EhcacheFibonacciServiceImpl$$EnhancerByCGLIB$$73a5e038 took 7.597 seconds
[ 2013-01-18 15:28:58,853 [main] driver.EhcacheFibonacciServiceImpl.flushFibonacciCache():30  INFO ]: Royal Ehcache flush

Using aspectj to cache self calls

Now let's get into some AspectJ magic! It would be worthwhile to spend a few minutes knowing how load time weaving (LTW) lends itself to processing annotations. There is anentire section in the Spring documentation that outlines the interactions in detail. In a nutshell, contrasting with the proxy based approach, the logic before/after/around a call is embedded in the bytecode of the class as the class is being loaded into the JVM. The JVM provides hook-ins via the java.lang.instrument.ClassFileTransformers route which can be configured per classloader. Since this logic is now part of the bytecode loaded in the JVM itself, any and all calls will have access to the logic coded for before/after/around calls. We will discover more as we take the tour. In our example for the concurrent map and ehcache based cached services, we were only storing the results for the fibonacci with index 45 and not the ones preceding it - and we gave the reason as the mode being proxy which doesn't support self calls (recursive or public/private/protected). Let's say we do want to achieve the benefits of the intermediate fetches as well, we should switch over to using the aspectj mode. Here are the set of steps you need to do and why:

Add maven dependencies for spring-aspects (which pulls in aspectj related jars)

        <!-- for mode aspectj -->
        <dependency>
            <groupId>org.springframework</groupId>
            <artifactId>spring-aspects</artifactId>
            <version>${spring.version}</version>
        </dependency>
        <dependency>
            <groupId>org.aspectj</groupId>
            <artifactId>aspectjweaver</artifactId>
            <version>1.6.11</version>
            <scope>runtime</scope>
        </dependency>
    <cache:annotation-driven cache-manager="compositeCacheManager" mode="aspectj" />

Informs Spring that we need to use aspectj for processing the annotations.

    <context:load-time-weaver/>

Inform spring to load time weave the bytecode for the beans that have been annotated. IMHO, specifying #2 should have automatically caused #3, but it is not - so we live with it.

-javaagent:/u/baigm/winnt/.m2/repository/org/springframework/spring-instrument/3.1.3.RELEASE/spring-instrument-3.1.3.RELEASE.jar

Specify the javaagent that will do the actual work of instrumenting the bytecode. From Java 5 onwards, java has built in support for agents that can help with instrumentation related activities which come out-of-the-box in most JEE containers. If you are not running in a JEE container (like Tomcat) or running a standalone java application, Spring provides a lightweight instrumentation jar that provides the implementation of a LoadTimeWeaver (viz. InstrumentationLoadTimeWeaver). So you need to add this to your launch configuration in your eclipse or to your invocation if outside eclipse.

And you are all set! Run the driver to see that the initial run itself now finishes in much under a second.

[ 2013-01-18 16:05:10,306 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.ConcurrentMapFibonacciServiceImpl took 0.074 seconds
[ 2013-01-18 16:05:10,306 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.ConcurrentMapFibonacciServiceImpl took 0.0 seconds
[ 2013-01-18 16:05:10,306 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.ConcurrentMapFibonacciServiceImpl took 0.0 seconds
[ 2013-01-18 16:05:10,313 [main] driver.ConcurrentMapFibonacciServiceImpl.flushFibonacciCache_aroundBody2():30  INFO ]: Royal ConcurrentMap flush
[ 2013-01-18 16:05:10,317 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.ConcurrentMapFibonacciServiceImpl took 0.004 seconds
[ 2013-01-18 16:05:10,317 [main] driver.ConcurrentMapFibonacciServiceImpl.flushFibonacciCache_aroundBody2():30  INFO ]: Royal ConcurrentMap flush
[ 2013-01-18 16:05:10,354 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.EhcacheFibonacciServiceImpl took 0.037 seconds
[ 2013-01-18 16:05:10,355 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.EhcacheFibonacciServiceImpl took 0.001 seconds
[ 2013-01-18 16:05:10,355 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.EhcacheFibonacciServiceImpl took 0.0 seconds
[ 2013-01-18 16:05:10,387 [main] driver.EhcacheFibonacciServiceImpl.flushFibonacciCache_aroundBody2():30  INFO ]: Royal Ehcache flush
[ 2013-01-18 16:05:10,397 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.EhcacheFibonacciServiceImpl took 0.008 seconds
[ 2013-01-18 16:05:10,400 [main] driver.EhcacheFibonacciServiceImpl.flushFibonacciCache_aroundBody2():30  INFO ]: Royal Ehcache flush

The call after the flush however returns faster than the first call - which may be due the the instrumentation stuff bootstrapping and subsequent calls reusing cached instrumented code.

Using cache:advice to cache non-owned calls

The annotation route is good when we are owning the services that need caching. If you don't own the services that vend out the data, you are forced to wrap it in a facade and place your annotation on this facade. The other route may be to use the cache:advice directive. This is similar to the tx:advice which we use to wrap calls around certain pointcuts based on fully qualified classnames, methods, arguments and argument types. So first off, we define a separate concurrent cache to be used for this external service.

    <bean id="externalConcurrentMapFibonacci"
        class="org.springframework.cache.concurrent.ConcurrentMapCacheFactoryBean" />
    <bean id="externalConcurrentMapFibonacciCacheManager"
        class="org.springframework.cache.support.SimpleCacheManager">
        <property name="caches">
            <set>
                <ref bean="externalConcurrentMapFibonacci" />
            </set>
        </property>
    </bean>

Then we define a cache advice (pointcut) with the cache manager to be used and defining which methods need to be cached and which backing cache store is to be used.

    <cache:advice id="externalFibonacciCacheAdvice" cache-manager="externalConcurrentMapFibonacciCacheManager">
        <cache:caching>
            <cache:cacheable method="*" cache="externalConcurrentMapFibonacci" />
        </cache:caching>
    </cache:advice>

Here we are asking Spring to cache all methods (via *) using the externalConcurrentMapFibonacciCacheManager cache manager and to use the externalConcurrentMapFibonacci cache as the underlying store.

    <aop:config proxy-target-class="true">
        <aop:pointcut id="externalFibonacciCacheOperation" expression="execution(* com.kilo.external..*.*(..))"/>
        <aop:advisor advice-ref="externalFibonacciCacheAdvice" pointcut-ref="externalFibonacciCacheOperation"/>
    </aop:config>

Now, we ask aop to to bind the pointcut to work on all beans of package com.kilo.external and use the advice defined before. We have to give the proxy-target-class="true" to use CGLIB based proxies (we can choose to use aspectj mode for reasons mentioned before).

You may verify the working via the output:

[ 2013-01-18 17:20:50,374 [main] driver.SpringCacheTesterDriver.doHeavyLifting():55  INFO ]: com.kilo.driver.SimpletonFibonacciServiceImpl took 7.248 seconds
[ 2013-01-18 17:20:57,615 [main] driver.SpringCacheTesterDriver.doHeavyLifting():55  INFO ]: com.kilo.driver.SimpletonFibonacciServiceImpl took 7.241 seconds
[ 2013-01-18 17:21:04,863 [main] driver.SpringCacheTesterDriver.doHeavyLifting():55  INFO ]: com.kilo.driver.SimpletonFibonacciServiceImpl took 7.247 seconds
[ 2013-01-18 17:21:04,863 [main] driver.SimpletonFibonacciServiceImpl.flushFibonacciCache():27  INFO ]: No-op
[ 2013-01-18 17:21:12,119 [main] driver.SpringCacheTesterDriver.doHeavyLifting():55  INFO ]: com.kilo.driver.SimpletonFibonacciServiceImpl took 7.255 seconds
[ 2013-01-18 17:21:12,119 [main] driver.SimpletonFibonacciServiceImpl.flushFibonacciCache():27  INFO ]: No-op
[ 2013-01-18 17:21:12,161 [main] driver.SpringCacheTesterDriver.doHeavyLifting():55  INFO ]: com.kilo.driver.ConcurrentMapFibonacciServiceImpl took 0.042 seconds
[ 2013-01-18 17:21:12,161 [main] driver.SpringCacheTesterDriver.doHeavyLifting():55  INFO ]: com.kilo.driver.ConcurrentMapFibonacciServiceImpl took 0.0 seconds
[ 2013-01-18 17:21:12,161 [main] driver.SpringCacheTesterDriver.doHeavyLifting():55  INFO ]: com.kilo.driver.ConcurrentMapFibonacciServiceImpl took 0.0 seconds
[ 2013-01-18 17:21:12,167 [main] driver.ConcurrentMapFibonacciServiceImpl.flushFibonacciCache_aroundBody2():30  INFO ]: Royal ConcurrentMap flush
[ 2013-01-18 17:21:12,172 [main] driver.SpringCacheTesterDriver.doHeavyLifting():55  INFO ]: com.kilo.driver.ConcurrentMapFibonacciServiceImpl took 0.004 seconds
[ 2013-01-18 17:21:12,172 [main] driver.ConcurrentMapFibonacciServiceImpl.flushFibonacciCache_aroundBody2():30  INFO ]: Royal ConcurrentMap flush
[ 2013-01-18 17:21:12,210 [main] driver.SpringCacheTesterDriver.doHeavyLifting():55  INFO ]: com.kilo.driver.EhcacheFibonacciServiceImpl took 0.038 seconds
[ 2013-01-18 17:21:12,211 [main] driver.SpringCacheTesterDriver.doHeavyLifting():55  INFO ]: com.kilo.driver.EhcacheFibonacciServiceImpl took 0.0 seconds
[ 2013-01-18 17:21:12,211 [main] driver.SpringCacheTesterDriver.doHeavyLifting():55  INFO ]: com.kilo.driver.EhcacheFibonacciServiceImpl took 0.0 seconds
[ 2013-01-18 17:21:12,242 [main] driver.EhcacheFibonacciServiceImpl.flushFibonacciCache_aroundBody2():30  INFO ]: Royal Ehcache flush
[ 2013-01-18 17:21:12,250 [main] driver.SpringCacheTesterDriver.doHeavyLifting():55  INFO ]: com.kilo.driver.EhcacheFibonacciServiceImpl took 0.008 seconds
[ 2013-01-18 17:21:12,253 [main] driver.EhcacheFibonacciServiceImpl.flushFibonacciCache_aroundBody2():30  INFO ]: Royal Ehcache flush
[ 2013-01-18 17:21:19,873 [main] driver.SpringCacheTesterDriver.doHeavyLifting():55  INFO ]: com.kilo.external.ExternalFibonacciServiceImpl$$EnhancerByCGLIB$$6337baf took 7.62 seconds
[ 2013-01-18 17:21:19,874 [main] driver.SpringCacheTesterDriver.doHeavyLifting():55  INFO ]: com.kilo.external.ExternalFibonacciServiceImpl$$EnhancerByCGLIB$$6337baf took 0.0 seconds
[ 2013-01-18 17:21:19,874 [main] driver.SpringCacheTesterDriver.doHeavyLifting():55  INFO ]: com.kilo.external.ExternalFibonacciServiceImpl$$EnhancerByCGLIB$$6337baf took 0.0 seconds
[ 2013-01-18 17:21:19,874 [main] external.ExternalFibonacciServiceImpl.flushFibonacciCache():28  INFO ]: No-op
[ 2013-01-18 17:21:19,874 [main] driver.SpringCacheTesterDriver.doHeavyLifting():55  INFO ]: com.kilo.external.ExternalFibonacciServiceImpl$$EnhancerByCGLIB$$6337baf took 0.0 seconds

Hope this helps!

There is one gotcha with the cache mapping that I will try to cover in a new post.

References:

• http://static.springsource.org/spring/docs/3.1.0.M1/spring-framework-reference/html/aop.html#aop-aj-ltw
• http://www.eclipse.org/aspectj/doc/released/devguide/ltw.html
• http://stackoverflow.com/questions/8658789/using-spring-cache-annotation-in-multiple-modules
• Test bed available at https://github.com/kilokahn/spring-testers/tree/master/spring-cache-tester

Fun with @Cacheable

From Spring 3.1.0.RELEASE onwards the @Cacheable annotation has been added to the spring-context jar. We will go through the motions of demonstrating how it can be leveraged through a contrived example of calculating the fibonacci numbers. We will have a service interface that is supposed to get the fibonacci number given an index over and over.

public interface FibonacciService {
    long getFibonacci(int index);
}

We will have three different service implementations. One will be a simpleton who will plainly calculate the number - called SimpletonFibonacciServiceImpl.

    public long getFibonacci(int index) {

        if (index == 0 || index == 1) {
            return 1;
        }

        long fiboMinusOne = getFibonacci(index - 1);
        long fiboMinusTwo = getFibonacci(index - 2);

        return fiboMinusOne + fiboMinusTwo;
    }

Our driver will make it go through its paces by making it calculate the 45th number of the fibonacci series.

    private static void doWorkWithFiboService(FibonacciService fibonacciService) {
        // First one
        doHeavyLifting(fibonacciService);
        // Some more
        doHeavyLifting(fibonacciService);
        // Come on... one last
        doHeavyLifting(fibonacciService);
        // Now flush
        fibonacciService.flushFibonacciCache();
        // Do some more
        doHeavyLifting(fibonacciService);
        // Be polite - clean out at the end - flush!
        fibonacciService.flushFibonacciCache();
    }

    private static void doHeavyLifting(FibonacciService fibonacciService) {
        StopWatch sw = new StopWatch();
        sw.start();
        fibonacciService.getFibonacci(45);
        sw.stop();

        LOG.info(fibonacciService.getClass().getCanonicalName() + " took "
                + sw.getTotalTimeSeconds() + " seconds");
    }

It roughly takes 7 seconds on a stock host to perform each computation (measured via org.springframework.util.StopWatch which is a good tool for poor man's benchmarking if you've not used it already).

[ 2013-01-18 10:49:04,006 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.SimpletonFibonacciServiceImpl took 7.212 seconds
[ 2013-01-18 10:49:11,236 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.SimpletonFibonacciServiceImpl took 7.23 seconds
[ 2013-01-18 10:49:18,465 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.SimpletonFibonacciServiceImpl took 7.229 seconds
[ 2013-01-18 10:49:18,466 [main] driver.SimpletonFibonacciServiceImpl.flushFibonacciCache():27  INFO ]: No-op
[ 2013-01-18 10:49:25,695 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.SimpletonFibonacciServiceImpl took 7.229 seconds
[ 2013-01-18 10:49:25,695 [main] driver.SimpletonFibonacciServiceImpl.flushFibonacciCache():27  INFO ]: No-op

To demonstrate the use of cache, we will have the second guy will use a concurrent map as the backing store for caching numbers once they are computed.

    @Cacheable("concurrentMapFibonacci")
    public long getFibonacci(int index) {

        if (index == 0 || index == 1) {
            return 1;
        }

        long fiboMinusOne = getFibonacci(index - 1);
        long fiboMinusTwo = getFibonacci(index - 2);

        return fiboMinusOne + fiboMinusTwo;
    }

The service has been annotated with the @Cacheable annotation. The annotation needs to be provided with the name of the backing cache store. The cache store definition (viz. concurrentMapFibonacci) is defined in the Spring context file as

    <bean id="concurrentMapFibonacci"
        class="org.springframework.cache.concurrent.ConcurrentMapCacheFactoryBean" />
    <bean id="concurrentMapCacheManager" class="org.springframework.cache.support.SimpleCacheManager">
        <property name="caches">
            <set>
                <ref bean="concurrentMapFibonacci" />
            </set>
        </property>
    </bean>

To enable the processing of the annotation, we need to specify the directive:

    <cache:annotation-driven proxy-target-class="true" cache-manager="concurrentMapCacheManager" />

This is very similar to the tx:annotation-driven directive that we use to enable processing for the @Transactional annotation. Here we ask Spring to process all beans in the container for the @Cacheable annotation and use the bean named "concurrentMapCacheManager" to act as the CacheManager (which is of type SimpleCacheManager). The processing can be done via proxies or aspectj byte code weaving. For simple use cases, we prefer using proxies which is the default mode (we will cover the aspectj angle in the next post). In using proxies, by default JDK proxies are created which fail if the bean to be proxied doesn't implement any interface. In contrast CGLIB based proxies work on POJO's with the exception of final classes and non-default constructor classes (because they work by subclassing the POJO). We ask it to use CGLIB based proxies by specifying the proxy-target-class="true" switch.

[ 2013-01-18 11:17:24,707 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.ConcurrentMapFibonacciServiceImpl$$EnhancerByCGLIB$$5ea80813 took 7.595 seconds
[ 2013-01-18 11:17:24,708 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.ConcurrentMapFibonacciServiceImpl$$EnhancerByCGLIB$$5ea80813 took 0.001 seconds
[ 2013-01-18 11:17:24,708 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.ConcurrentMapFibonacciServiceImpl$$EnhancerByCGLIB$$5ea80813 took 0.0 seconds
[ 2013-01-18 11:17:24,709 [main] driver.ConcurrentMapFibonacciServiceImpl.flushFibonacciCache():30  INFO ]: Royal ConcurrentMap flush
[ 2013-01-18 11:17:32,283 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.ConcurrentMapFibonacciServiceImpl$$EnhancerByCGLIB$$5ea80813 took 7.574 seconds
[ 2013-01-18 11:17:32,283 [main] driver.ConcurrentMapFibonacciServiceImpl.flushFibonacciCache():30  INFO ]: Royal ConcurrentMap flush

The first call takes the full time to calculate the fibonacci number, but the subsequent calls just fetch the numbers from the cache and hence finish instantaneously. Let's now explore the flushing or eviction of entries from the cache. The cache manager that we have used here is a SimpleCacheManager which provides a no-frills management (we will see fancy controls in management via EhCacheCacheManager later on). To evict entries from a cache on a particular call, we have the @CacheEvict annotation.

    @CacheEvict(allEntries = true, beforeInvocation = true, value = "concurrentMapFibonacci")
    public void flushFibonacciCache() {
        LOG.info("Royal ConcurrentMap flush");
    }

In this annotation we have asked Spring to evict all entries in the cache named "concurrentMapFibonacci" before said method is invoked. We can choose to evict bespoke keys via the keys directive (using SpEL). If the method has any arguments, those are used as keys for the entries to be evicted (ofcourse, in the absence of allEntries = true). So as expected, when the flush call is made, the cache goes cold, and the subsequent fetch again takes the full 7 odd seconds. It is important to note that though we are making recursive calls, the only key-value that got cached is the final one and not the intermediate ones. The reason being the mode that we chose. Proxy based solutions will only intercept calls that are being made from one spring bean to another and self calls are not processed (recursive or private/protected/public calls to the same class). In the next post, we will use aspectj to get a real live and kicking cache that will also house the intermediate entries and observe the improvement empirically.

The previous eviction policy was somewhat straight-jacketed. Who wants to call a method to flush caches periodically? Not me, because frankly it can be handled by a better cache store and an intelligent manager. Here is where ehcache comes in.

    @Cacheable("fibonacciEhcache")
    public long getFibonacci(int index) {

        if (index == 0 || index == 1) {
            return 1;
        }

        long fiboMinusOne = getFibonacci(index - 1);
        long fiboMinusTwo = getFibonacci(index - 2);

        return fiboMinusOne + fiboMinusTwo;
    }

To ask Spring to use ehcache as the underlying store, we specify so in the Spring context file:

    <bean id="fibonacciEhcache"
        class="org.springframework.cache.ehcache.EhCacheManagerFactoryBean">
        <property name="configLocation" value="ehcache.xml" />
    </bean>
    <bean id="ehcacheManager" class="org.springframework.cache.ehcache.EhCacheCacheManager">
        <property name="cacheManager" ref="fibonacciEhcache"/>
    </bean>

We ask it to create a cache store named fibonacciEhcache who is managed by the EhCacheCacheManager.

    <cache:annotation-driven cache-manager="ehcacheManager" proxy-target-class="true"/>

Further configuration for the cache is available in the ehcache config file named "ehcache.xml" available on the classpath which looks something like:

<?xml version="1.0" encoding="UTF-8"?>
<!-- To know more about the available configuration. Refer http://ehcache.org/ehcache.xml -->
<ehcache xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xsi:noNamespaceSchemaLocation="ehcache.xsd" monitoring="autodetect"
    updateCheck="false" dynamicConfig="false">

    <diskStore path="java.io.tmpdir" />

    <cache name="fibonacciEhcache" maxEntriesLocalHeap="10000"
        maxEntriesLocalDisk="1000" eternal="false"
        diskSpoolBufferSizeMB="20" timeToIdleSeconds="300"
        timeToLiveSeconds="600" memoryStoreEvictionPolicy="LFU"
        transactionalMode="off">
        <persistence strategy="localTempSwap" />
    </cache>

    <defaultCache
        maxElementsInMemory="10000"
        eternal="false"
        timeToIdleSeconds="120"
        timeToLiveSeconds="120"
        overflowToDisk="true"
        diskSpoolBufferSizeMB="30"
        maxElementsOnDisk="1000"
        diskPersistent="false"
        diskExpiryThreadIntervalSeconds="120"
        memoryStoreEvictionPolicy="LRU" />

</ehcache>

The cache named fibonacciEhcache is has been thus configured to keeping the backing disk store on the java.io.tmpdir location (by default /tmp on linux) and have the cache purged every 10 minutes (via the timeToLiveSeconds="600"). Other explanations can be found in the documentation of the sample ehcache.xml file.

[ 2013-01-18 11:38:12,689 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.EhcacheFibonacciServiceImpl$$EnhancerByCGLIB$$a1d7290c took 7.598 seconds
[ 2013-01-18 11:38:12,690 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.EhcacheFibonacciServiceImpl$$EnhancerByCGLIB$$a1d7290c took 0.001 seconds
[ 2013-01-18 11:38:12,690 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.EhcacheFibonacciServiceImpl$$EnhancerByCGLIB$$a1d7290c took 0.0 seconds
[ 2013-01-18 11:38:12,697 [main] driver.EhcacheFibonacciServiceImpl.flushFibonacciCache():30  INFO ]: Royal Ehcache flush
[ 2013-01-18 11:38:20,286 [main] driver.SpringCacheTesterDriver.doHeavyLifting():52  INFO ]: com.kilo.driver.EhcacheFibonacciServiceImpl$$EnhancerByCGLIB$$a1d7290c took 7.588 seconds
[ 2013-01-18 11:38:20,287 [main] driver.EhcacheFibonacciServiceImpl.flushFibonacciCache():30  INFO ]: Royal Ehcache flush

The runs reflect roughly the same behavior as with the concurrent map usage.

This will serve as a primer and we will have some more fun in the next post where we explore slightly more involved use cases.

References:

• http://static.springsource.org/spring/docs/3.1.0.M1/spring-framework-reference/html/cache.html
• http://ehcache.org/ehcache.xml
• Testbed available at https://github.com/kilokahn/spring-testers/tree/master/spring-cache-tester