In our work to improve MySQL scalability we tested many opportunities to scale the MySQL Server and the InnoDB storage engine. The InnoDB buffer pool was often one of the hottest contention points in the server. This is very natural since every access to a data page, UNDO page, index page uses the buffer pool and even more so when those pages are read from disk and written to disk.
As usual there were two ways to split the buffer pool mutex, one way is to split it functionally into different mutexes protecting different parts. There have been experiments in particular on splitting out the buffer pool page hash table, the flush list. Other parts that have been broken out in experiments are the LRU list, the free list and other data structures internally in the buffer pool. Additionally it is as usual possible to split the buffer pool into multiple buffer pools. Interestingly one can also combine using multiple buffer pools with splitting the buffer pool mutex into smaller parts. The advantage of using multiple buffer pools is that it is very rare that it is necessary to grab multiple mutexes for the buffer pool operation which quickly becomes the case when splitting the buffer pool into multiple mutex protection areas.
After working on scalability improvements in MySQL and InnoDB I noted that all the discussion was around how to split the buffer pool mutex and no dicsussion centered around how to make multiple buffer pools out of the buffer pool. I decided to investigate how difficult it would be to make this change. I quickly realised that it needed a thorugh walk through of the code. It required a code check that required checking about 150 methods and their interaction. This sounds like a very big task, but fortunately the InnoDB code is well structured and have fairly simple dependencies between its methods. After this walk through of the buffer pool code one quickly found that there were 3 different ways of getting hold of the buffer pool, one method was to calculate it using the space id and page id. This is the normal method in most methods used in the external buffer pool interface. However there were numerous occasions where we only had access to the block or page data structure and it would be a bit useless to recalculate the hash value in every method that needed access to the buffer pool data structure. So it was decided to leave a reference to the buffer pool in every page data structure. There were also a few occasions where one needed to access all buffer pools.
The analysis proved that most of the accesses to the buffer pool was completely independent of other accesses to the buffer pool for other pages. InnoDB uses read-ahead and neighbour writes in the IO operations that are started from the buffer pool. These always operate on an extent of 64 pages. Thus it made sense to map the pages of 64 pages into one buffer pool to avoid having to operate on multiple buffer pools on every IO operation.
With these design ideas there were only a few occasions where it was necessary to operate on all buffer pools. One such operation was when the log required knowledge of the page with the oldest LSN of the buffer pool. Now this operation requires looping over all buffer pools and checking the minimum LSN of each buffer pool instance. This is a fairly rare operation so isn't a scalability issue.
The other operation with requirement to loop over all pages needed a bit more care, this operation is the background operation flushing buffer pool pages to disk. A couple of problems needs consideration here. First it is necessary to flush pages regularly from all buffer pool instances, secondly it's still important to flush neighbours. Given that many disks are fairly slow, it can be problematic to spread the load in this manner to many buffer pools. This is an important consideration when deciding how many buffer pool instances to configure.
The default number of buffer pool is one and for most small configurations with less than 8 cores it's mostly a good idea not to increase this value. If you have an installation that uses 8 cores or more one should also pay attention to the disk subsystem that is used. Given that InnoDB often writes up to 64 neighbours in each operation and that the flushing should happen each second, it makes sense to have a disk subsystem capable of having 500 IO operations per second to use 8 buffer pool instances. This can be set in the innodb_io_capacity configuration variable. One SSD drive should be capable of handling this, two fast hard drives or 3 slow ones.
In our experiments we have mostly used 8 buffer pools, more buffer pools can be useful at times. The main problem with many buffer pools is related to the IO operations. It is important to have a balanced IO load in the MySQL server.
Our analysis of using multiple buffer pool instances have shown some interesting facts. First the accesses to the buffer pools is in no way evenly spread out. This is not surprising given that e.g. the root page of an index is a very frequently accessed page. So using sysbench with only one table, there will obviously be much more accesses to certain buffer pool instances. Our experiments shows that in sysbench using 8 buffer pools, the hottest buffer pool receives about one third of all accesses. Given that sysbench is a worst case scenario for the multiple buffer pool case, this means that most applications that tend to use more tables and more indexes should have a much more even load on the buffer pools.
So how much does multiple buffer pools improve the scalability of the MySQL Server. The answer is as usual dependent on application, OS, HW and so forth. But some general ideas can be found from our experiments. In sysbench using a load which is entirely held in main memory, so the disk is only used for flushing data pages and logging, in this system the multiple buffer pools can provide up to 10% improvement of the throughput in the system. In dbStress, the benchmark Dimitri uses, we have seen all the way up to 30% improvement. The reason here is most likely that dbStress uses more tables and have avoided many other bottlenecks in the MySQL Server and thus the buffer pool was a worse bottleneck in dbStress compared to sysbench. From the code it is also easy to see that the more IO operations the buffer pool performs, the more the buffer pool mutex will be acquired and also often held for a longer time. One such example is the search for a free page on the LRU list every time a read is performed into the buffer pool from the disk.
Furthermore the use of multiple buffer pool opens up for many more improvements and also it doesn't remove the possibility to split the buffer pool mutex even more.
Another manner of displaying the importance of using multiple buffer pools is the mutex statistics on the buffer pool mutex. With one buffer pool the buffer pool had about 750k accesses per second in a sysbench test where the MySQL Server had access to 16 cores. 50% of those accesses met a mutex already held, so it's obvious that the InnoDB mutex subsystem is very well aligned with the buffer pool mutex which have very short duration which makes spinning waiting for it very fruitful. Anyways a mutex which is held 50% of the time makes the buffer pool mutex a limiting factor of the MySQL Server. Quite a few threads will often spend time in the queue waiting for the buffer pool mutex. So splitting the buffer pool into 8 instances even in sysbench means that the hottest buffer pool receives about one third of the 750k accesses so should be held about 17% of the time. Our later experiments shows that the hottest buffer pool mutexes are now held up to about 14-15% of the time. So the theory matches the real world fairly well. This means that the buffer pool is still a major factor in the MySQL Scalability equation but is now more on par with the other bottlenecks in the MySQL Server.
The development project of multiple buffer pools happened at a time when the MySQL and InnoDB teams could start working together. I was impressed by the willingness to cooperate and the competence in the InnoDB team that made it possible to introduce multiple buffer pools into MySQL 5.5. Our cooperation has continued since then and this has led to improvements in productivity on both parts. So for you as a MySQL user this spells good times going forward.