Tuesday, December 19, 2017

Concurrency Again

It started with long update transactions. Mostly we ignored them - some of our customers have slow servers, and sometimes they try to do transactions that are too large.

jSuneido aborts long update transactions as a defense mechanism. Its optimistic concurrency control has to track overlapping transactions, so if a transaction takes a long time, it can lead to a lot of overlaps.

But some of these long update transactions didn't make much sense. They appeared to be slow in the final commit stage. This stage just writes to the memory mapped files and normally is very fast, nowhere near the 20 second transaction limit.

I started going through the code, trying to see what might explain this. I wondered if it might have something to do with the background (once a minute) task that calls force on the MappedByteBuffers to flush them to external storage. Trying to ensure that files are durably written is tricky these days with so many levels of caching etc. but it seems worth trying.

I would have thought that force itself would be fast since most of the work would be done at the operating system level. But the documentation says that it doesn't return till it finishes writing to storage. I added some logging and found that force is usually fast (a millisecond) but occasionally slow (10's of seconds). There didn't seem to be a particular reason for the slow ones. I assume Windows is doing something that blocks.

The slow force would be enough to cause long update transactions, but force was supposed to be happening in a background thread so it shouldn't have blocked anything.

Crap! The force method was synchronized. And so was a method that transactions needed to use to commit. So the force would block the commit and could cause the problem. The problem was relatively rare because the force was only once a minute and usually fast, and it would have to hit exactly when a transaction was committing.

Did force really need to be synchronized? Did the other methods? Back to the age old problems of concurrency with shared memory and locking.

I removed the synchronized. But then I worried about accessing the array of MappedByteBuffers without any locking. I could make the array reference volatile but not the array elements. So I changed it to use AtomicReferenceArray.

At first I thought it was working ok. I ran tests with a bunch of threads hammering on the database and it seemed to work ok. But then my database got corrupted. Was my change failing? I ran the tests again and everything was fine. Hmmm. I changed the force to run every 10 seconds instead of every minute. Sure enough, now the database would get corrupted every time I ran the test.

It still didn't make sense to me that removing synchronized from force would corrupt the data. I noticed that my force method was also writing a few zeros to the end of the file to force the last modified date of the file to get updated. I could see that having concurrency issues. I changed it to rewrite the first few bytes of the file header instead. That fixed it, no more corruption. Hopefully it's smart enough to see that nothing has actually changed and not physically write to storage.

Everything looked good according to my tests, but that's generally not sufficient when it comes to concurrency. I also feel like I should convince myself that it is "safe", even if only informally.

Writing to the database (the final stage of an update transaction) was protected by a lock. So there could only be a single writer at a time. (Yes, that's a bottleneck, but it's a small part of the overall process so it doesn't reduce concurrency too much.)

But there are multiple reader threads. So the question is visibility, not exclusion. The Java Memory Model makes no guarantees of visibility without either volatile or locking. To ensure visibility I needed writers to release a lock when they were finished, and readers to acquire that same lock when they were starting.

For database transactions, that seemed to be covered. Transactions called synchronized methods (on the same object) at the beginning and end.

But there were other readers besides database transactions. The database checking process was one. It also turned out to be ok because it acquired the commit lock briefly at the start. (And writers released it at the end.)

That left the force process. Part of the problem was that it's low level code. It doesn't (and shouldn't) "know" about transactions or commit locks etc. I needed something at the same level. Luckily, writers called a particular low level method when they ended so I could synchronize that method along with the force method. Oops! Just about repeated the original mistake of force holding a lock while it was working. It didn't need to hold it since the goal wasn't exclusion. I just needed to acquire (and then release) the lock (to ensure visibility). So I made a dummy "sync" method that was synchronized and called that at the start of the force method.

I think I've convinced myself that it is "safe". I wouldn't say I'm one hundred percent sure, but reasonably confident.

Another question is fragility. Would future changes be likely to break this? Minor changes seem pretty safe. The things I'm depending on are reasonably fundamental. If I made bigger changes it could be dangerous, but presumably if I'm making bigger changes I would reconsider concurrency. And I did document it.

So if visibility and exclusion are covered, do I need to use an AtomicReferenceArray? Presumably not, so I reverted those changes and went back to a plain old array.

I did another round of testing on both OS X and Windows and didn't encounter any problems.

The problem with this kind of concurrency issue is that you can't just throw locks at it. The problems are just as likely to come from too many locks as from not enough. I wish you could just lock everything and be done with it. But if you do that, you'll probably have deadlocks, and you'll be back to single threaded performance.

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