Not so long ago, in a galaxy not very far away... a middle-aged programmer battled to free memory from the dark side of the hibernate query cache.  He was successful, or so it seemed. For the query cache memory problems had risen from the ashes -- stronger and more bloated than ever...

What's With All This Garbage?

We hit a case at work (http://www.mysql.com/products/enterprise/monitor.html) (again), where the java server process came to a grinding halt.  It wasn't dead, it just wasn't making much forward progress either.  A quick look at the heap stats showed we were nearly at capacity and that garbage collection was eating all CPU time, thus not allowing any real work to happen.  Looks like it is time to whip out the ol' memory profiler.  This time I went with Eclipse's Memory



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You Mean, Memory Is Not Infinite?

We're working hard getting MySQL Enterprise Monitor 2.0, featuring Query Analyzer (http://www.mysql.com/trials/enterprise), ready for release. As part of that, we started really ramping up the number of MySQL servers reporting in query data to see how we could scale. Not surprising (to me, anyway), the first efforts did not go so well. My old friend OutOfMemoryError reared its ugly head once again.

Query Cache -- It's More Than Just Results!

We're big (ab)users of hibernate query caching, and more importantly to us the natural id optimized query cache. Firing up the profiler, I was not shocked to see that the
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I work on the MySQL Enterprise Tools (http://www.mysql.com/products/enterprise/monitor.html) team, formerly of MySQL and now with Sun Microsystems. The 2.0 version of the Enterprise Monitor is well under way. As part of this, the Java server backend has been refactored to utilize Spring and Hibernate. Honestly, I didn't know either one of those technologies before starting this project. Oh, what a fun road it has been...

A big draw for using an off-the-shelf ORM was so that we didn't have to write our own (kind of bad and slightly wrong -- those darn transactions) caching implementations for the custom one-off ORM that existed previously. A lot of our internal meta-model is very static, so clearly caching

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MySQL has a handy feature, that allows you to turn an INSERT into an UPDATE if a unique or primary key duplication is detected:

http://dev.mysql.com/doc/refman/5.1/en/insert-on-duplicate.html

A common usage pattern for this is “lazy initialization“ of a row in a database, which is exactly what my team was using it for yesterday to solve a problem in the backend for version 2.0 of the MySQL Enterprise Monitor. However, we ran into an issue where Hibernate would throw an exception complaining that when the INSERT was turned into an UPDATE, it couldn‘t retrieve the generated primary key value (we are using auto increments on this particular table, as it‘s not a high insertion-rate table).

To understand why this happens, you have to know a little bit about

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