Java Caching System is one of the mainstream opensource and free Java caches*, along with OSCache, EHCache and JbossCache. Choosing JCS may be the subject of an article by itself, since this API has a vastly undeserved reputation of being a buggy, slow cache. Exactly this reputation has motivated the development of EHCache, which is in fact a fork of JCS. But, JCS has evolved a lot lately and is now a perfectly valid alternative for production; it still has a few occasional bugs, but nothing really bothersome. I’ve recently had this interesting experience of cleaning up and tuning a website powered by JCS. This dynamic Java-based site is exposed to a healthy traffic of 0.6-1.2 Mhits/day, with 12.000-25.000 unique visitors daily, and caching has greatly improved its performance. This article is a collection of tips and best practices not comprised (yet?) in the official JCS documentation.Where to download JCS This is usually the first question when one wants to use JCS. Since JCS is not a ‘real’ Jakarta project, but a module of the Turbine framework, there is no downloading link available on the main site. If you search on Google, this question has popped many times on different mail lists or blogs and it usually has two kinds of answers, both IMHO wrong: - download the source of Turbine and you’ll find JCS in the dependencies. No, you won’t, because Turbine is build with Maven, which is supposed to automagically download all the needed dependencies and bring them to you on a silver plate. Meaning: tons of useless jars hidden somehwere in the murky depths of wherever Maven thinks is a nice install location. Uhh. - build it from scratch. Another sadistic advice, given that JCS is also build with Maven. So you’ll not only need to checkout the sources from CVS, but also install Maven. Then try to build JCS. And eventually give up. Like for instance in my case, I installed the monster\^H\^H\^H\^H\^H\^H wonderful build tool, then ran ‘maven jar’. Instead of the expected result [you know, building the jar !] Maven performed a series of operations like running unit tests, washing teeth, cooking a turkey. Well, I suppose it was doing this, because I couldn’t read the huge gobs of text running quickly on the screen. At the end, it miserably failed, with no logical explanations (too many explanations is the modern equivalent of unexplained). So I gave up. Again. Fortunately, some kind souls at Jakarta (think of these developers as of a sort of secret congregation) provide clandestine latest ‘demavenized’ binary builds in obscure places; for JCS, the
location is here. I used the last 1.1 build without problems for a few weeks and I strongly recommend it.Using the auxiliary disk cache There’s a common misconception that one doesn’t need no stinkin’ disk cache. Even on Hibernate site the example JCS configurations has the auxiliary disk cache commented out. Maybe this comes from the fact that JCS disk cache suffered from a memory leak (not true any more) or from the simplistic reasoning that disk access is inherently slower than memory access. Well it surely is, but at the same time it’s probably much faster than some of the database queries, which could benefit from caching. Also, it is interesting to note that incorrectly dimensioned ‘memory’ caches will make the Java process overflow from main memory to the swap disk. So you’ll use the disk anyway, only in an un-optimized manner ! I wouldn’t advise you to activate the auxiliary cache on disk without limiting its size, otherwise, the cache file would grow indefinitely. Controlling cache size is done by 2 parameters (MaxKeySize and OptimizeAtRemoveCount) example: jcs.auxiliary.DC.attributes.MaxKeySize=2500jcs.auxiliary.DC.attributes.OptimizeAtRemoveCount=2500 Only MaxKeySize is not enough, since it will only limit the number of keys pointing to values which are in disk cache. In fact, removing a value from the disk cache will only remove its key. But, the second (OptimizeAtRemoveCount) parameter will tell the cache to recreate a new file after a certain number of ‘removes’. This new cache file will keep only the cached values corresponding to the remaining keys, thus cleaning all obsolete values, and of course will replace the old cache file. The size of disk cache and the remove count is of course subject of tuning in your own environment. Tuning the memory shrinker Although one of the JCS authors specify that the shrinker “is rarely necessary”, it might come handy especially in memory constrained environments or for really big caches. With one exception: be careful and specify the MaxSpoolPerRun parameter (undocumented yet, but discussed on the mailing list) otherwise the shrinking process might lead to spikes in CPU usage. I am using the shrinker like that: jcs.default.cacheattributes.UseMemoryShrinker=truejcs.default.cacheattributes.ShrinkerIntervalSeconds=3600jcs.default.cacheattributes.MaxSpoolPerRun=300 YMMV. Cache control via servlet Again, undocumented, but people seem to know about it. The servlet class is org.apache.jcs.admin.servlet.JCSAdminServlet but do not expect it to work out of the box ! This servlet uses Velocity thus you’ll need to : - initialize Velocity before trying to access the servlet (or lazy, but you’ll have to modify the servlet source) - copy the templates into the Velocity template location. The templates (JCSAdminServletDefault.vm and JCSAdminServletRegionDetail.vm) are not (bug ? feature ?) in the jar, so you’ll have to retrieve them from the CVS repository. For the moment, they are at this location. These are my findings. I would have really appreciated to have these few pieces of info before starting the cache tuning. If anybody thinks this article is useful and/or needs to be completed, write a comment, send an email, wave hands. I’ll try to come up with more details. *For a complete list, see the corresponding section at Java-source.