MySQL transactions per second vs. fsyncs per second (2020)
36 comments
·March 21, 2025tandr
LinuxBender
The concepts being described are called "Furious Flushing". I believe Percona did a writeup on this as well some time ago and I had to assist a DBA with getting systems to keep up with Percona MySQL demands regarding furious flushing and adjusting filesystem and memory options. Here [1] is one of them. OS tuning options have changed a bit since 2014 and there are also more recent articles I believe. The biggest win for us was changing the servers to use SSD's and large capacitor backed raid caches.
[1] - https://ftp.fau.de/macports/distfiles/percona/PerconaServer-...
echelon
Are the Percona folks a bunch of core MySQL/MariaDB engineers?
LinuxBender
Not as far as I know but here is a brief history. [1] They will commercially support all the databases including MariaDB. Their goal was to collectively update MySQL to take advantage of modern hardware. They are also useful for companies that have complex replication and backup requirements. They have also created a lot of tools for DBA's to manage data. The DBA's I worked with had a great relationship and great experiences with them.
[1] - https://www.percona.com/sites/default/files/The-Story-of-Per...
tomnipotent
The Percona founders worked at MySQL AB previously.
jiggawatts
It hurts my soul that database engines still don’t batch multiple transactions per disk flush as a default setting.
It’s such an insane bottleneck on modern systems.
Animats
File system APIs should be able to return events "data is transferred, buffer no longer needed" and "data is safely stored on persistent media". That's what databases really need from the file system.
Interestingly, some IBM mainframe hardware makes this distinction, with "channel end" and "device end". But Linux does not.
colanderman
Linux does make this distinction.
Linux has two main disk I/O paths, buffered and direct I/O.
Direct I/O indicates "channel end" by the completion of the write operation. By that point, data has been transferred to disk from the buffer and the buffer can be reused. (Notably, direct I/O may be performed asynchronously via the Linux AIO API.) Contrary to popular belief, this does not indicate that the data is safely committed to disk. [1]
Buffered I/O does not require the concept of "channel end", since write calls complete immediately after the buffer contents have been copied into kernel space. (This mode is what PostgreSQL uses by default. I don't know MySQL.)
In either case, `fsync(2)` (or `fdatasync(2)`) is used to indicate "device end". The disk has indicated that data is safely stored. (This can likewise be monitored asynchronously, either via the AIO API for direct I/O, or `sync_file_range(2)` for buffered I/O. The latter is used by PostgreSQL [2].)
Aside – Linux has also recently grown support for this concept in its networking API, via zerocopy `send(2)` functionality in io_uring.
evanelias
> This mode is what PostgreSQL uses by default. I don't know MySQL.
Assuming the InnoDB storage engine, the default recently changed to Direct I/O as of MySQL 8.4, see https://dev.mysql.com/doc/refman/8.4/en/innodb-parameters.ht...
It was common to set this even before it became the default though, since InnoDB maintains its own buffer pool caching scheme, and there's no sense in duplicating data pages between the InnoDB buffer pool and the OS cache.
The general idea is that you should assign the majority of the system's memory to the InnoDB buffer pool, and then use direct I/O to bypass the system cache, since InnoDB can manage memory more intelligently than the OS. This is because InnoDB has a better understanding of your workload and its own data structures, vs the OS cache being more general-purpose.
Other MySQL storage engines behave differently, for example MyISAM had its own caching only for indexes but relied on the OS cache for row data. (if I'm remembering correctly, that is; been a long while since I've touched MyISAM. It's a non-ACID engine and generally should not be used.)
marsovo
How would that work without risking loss of committed transactions?
> Fully durable transaction commits are synchronous and report a commit as successful and return control to the client only after the log records for the transaction are written to disk. Delayed durable transaction commits are asynchronous and report a commit as successful before the log records for the transaction are written to disk. Writing the transaction log entries to disk is required for a transaction to be durable. Delayed durable transactions become durable when the transaction log entries are flushed to disk.
https://learn.microsoft.com/en-us/sql/relational-databases/l...
TwoPhonesOneKid
Typically the SQL engine will allow flexibility on this. Not all transactions need to prioritize write-to-disk confirmation over throughput. If you're collecting observability metrics, for instance, these don't have the same data coherency constraints your app model (account etc) demand. In this case you can accept the logical commit and the tiny chance it might not actually hit the disk. Postgres at least allows customizing this per transaction, I believe, although I'm not quite sure how it works if you compose transactions with distinct syncrhonization constraints.
marsovo
Sure, but the comment I responded to was lamenting that the commits are not asynchronous by default. The documentation I linked to was all about the considerations and behavior for asynchronous commits.
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toast0
Write data for transaction 1, write data for transaction 2, fsync, signal commit success for transactions 1 and 2.
Up to you how many transactions you want in a batch.
marsovo
Sure, but now when transaction 1 is "committed", it isn't actually guaranteed to be there in the face of interruption. That's a big change to the default behavior...
koolba
You missed a number of steps. The transactions are independent so they signal completion (to trigger the commit fsync) independently.
You can have the first transaction wait a bit to see if any other commits can be batched in the same fsync. However that’s off by default as the assumption is you want the transaction to complete as fast as possible.
At least that’s how PostgreSQL implements it.
Andys
I thought PostgreSQL did, but now that I check the docs, you are correct, the default `commit_delay` is zero. That would be worth increasing a little if you can afford the latency.
anarazel
It works even with that setting at zero! Just requires a bit more concurrency.
bob1029
It is really shocking to me that this isn't more of a thing.
If the I/O block size is 4,096 bytes and you are doing things like updating a user's email address or some boolean preference, you could get a LOT more data packed in per unit space & time. Each block is enough to store an entire page of text or a small image.
The only caveat is that the system needs to be consistently under heavy load, or you would have to force clients to wait unreasonable amounts of time for a sufficient batch to accumulate.
I think the best goldilocks path is to put something like a MPSC ring buffer in front of the command processor and to "take what you can get" in terms of batch size each iteration.
colanderman
They do, if you issue the transactions concurrently (i.e., multiple DB connections). This is "group commit" as referenced in the article.
You can't batch sequential transactions without violating the semantics of `COMMIT`. (Data is after all not durable if it's not flushed to disk!) Hence such behavior is not the default in quality databases.
If you are issuing many sequential writes and you don't care about them being individually committed, you can and should group them.
andrewstuart
Couldn’t be too hard to find max batch time in the mysql source and see what it does…
trhway
>MySQL will group multiple writes with each fsync
in the old days of HDD the Linux IO driver (some of them) would also re-order the writes in the queue to minimize HDD head seeks.
>A modern disk can do ~1000 fsyncs per second
sounds low for SSD. Haven't benchmarked for a while though. Sounds like something a 5-7 HDD disk array would do if i remember numbers correctly.
tibbar
The article seems to imply that fsyncs need to happen in a linear order, that is, 1ms / fsync -> 1000 fsyncs/sec. It seems to imply that any batching happens in a linear order as well, that is, we have to completely finish one batch of fsyncs before the next one begins. Is that true? Obviously some systems (including databases) will happily let the beginning of one transaction overlap with another, only simulating linearizable transactions when that is required by the isolation level. But I don't have a great mental model of what the file systems are doing under the hood.
evanelias
The error semantics of fsync are very important here and this can get messy, for example see https://danluu.com/fsyncgate/
Palomides
on an SSD with PLP (or on optane) I think you can get 20x rate, or more
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throwaway984393
[dead]
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