> Il giorno 18 mag 2019, alle ore 22:50, Srivatsa S. Bhat <srivatsa@xxxxxxxxxxxxx> ha scritto: > > On 5/18/19 11:39 AM, Paolo Valente wrote: >> I've addressed these issues in my last batch of improvements for BFQ, >> which landed in the upcoming 5.2. If you give it a try, and still see >> the problem, then I'll be glad to reproduce it, and hopefully fix it >> for you. >> > > Hi Paolo, > > Thank you for looking into this! > > I just tried current mainline at commit 72cf0b07, but unfortunately > didn't see any improvement: > > dd if=/dev/zero of=/root/test.img bs=512 count=10000 oflag=dsync > > With mq-deadline, I get: > > 5120000 bytes (5.1 MB, 4.9 MiB) copied, 3.90981 s, 1.3 MB/s > > With bfq, I get: > 5120000 bytes (5.1 MB, 4.9 MiB) copied, 84.8216 s, 60.4 kB/s > Hi Srivatsa, thanks for reproducing this on mainline. I seem to have reproduced a bonsai-tree version of this issue. Before digging into the block trace, I'd like to ask you for some feedback. First, in my test, the total throughput of the disk happens to be about 20 times as high as that enjoyed by dd, regardless of the I/O scheduler. I guess this massive overhead is normal with dsync, but I'd like know whether it is about the same on your side. This will help me understand whether I'll actually be analyzing about the same problem as yours. Second, the commands I used follow. Do they implement your test case correctly? [root@localhost tmp]# mkdir /sys/fs/cgroup/blkio/testgrp [root@localhost tmp]# echo $BASHPID > /sys/fs/cgroup/blkio/testgrp/cgroup.procs [root@localhost tmp]# cat /sys/block/sda/queue/scheduler [mq-deadline] bfq none [root@localhost tmp]# dd if=/dev/zero of=/root/test.img bs=512 count=10000 oflag=dsync 10000+0 record dentro 10000+0 record fuori 5120000 bytes (5,1 MB, 4,9 MiB) copied, 14,6892 s, 349 kB/s [root@localhost tmp]# echo bfq > /sys/block/sda/queue/scheduler [root@localhost tmp]# dd if=/dev/zero of=/root/test.img bs=512 count=10000 oflag=dsync 10000+0 record dentro 10000+0 record fuori 5120000 bytes (5,1 MB, 4,9 MiB) copied, 20,1953 s, 254 kB/s Thanks, Paolo > Please let me know if any more info about my setup might be helpful. > > Thank you! > > Regards, > Srivatsa > VMware Photon OS > >> >>> Il giorno 18 mag 2019, alle ore 00:16, Srivatsa S. Bhat <srivatsa@xxxxxxxxxxxxx> ha scritto: >>> >>> >>> Hi, >>> >>> One of my colleagues noticed upto 10x - 30x drop in I/O throughput >>> running the following command, with the CFQ I/O scheduler: >>> >>> dd if=/dev/zero of=/root/test.img bs=512 count=10000 oflags=dsync >>> >>> Throughput with CFQ: 60 KB/s >>> Throughput with noop or deadline: 1.5 MB/s - 2 MB/s >>> >>> I spent some time looking into it and found that this is caused by the >>> undesirable interaction between 4 different components: >>> >>> - blkio cgroup controller enabled >>> - ext4 with the jbd2 kthread running in the root blkio cgroup >>> - dd running on ext4, in any other blkio cgroup than that of jbd2 >>> - CFQ I/O scheduler with defaults for slice_idle and group_idle >>> >>> >>> When docker is enabled, systemd creates a blkio cgroup called >>> system.slice to run system services (and docker) under it, and a >>> separate blkio cgroup called user.slice for user processes. So, when >>> dd is invoked, it runs under user.slice. >>> >>> The dd command above includes the dsync flag, which performs an >>> fdatasync after every write to the output file. Since dd is writing to >>> a file on ext4, jbd2 will be active, committing transactions >>> corresponding to those fdatasync requests from dd. (In other words, dd >>> depends on jdb2, in order to make forward progress). But jdb2 being a >>> kernel thread, runs in the root blkio cgroup, as opposed to dd, which >>> runs under user.slice. >>> >>> Now, if the I/O scheduler in use for the underlying block device is >>> CFQ, then its inter-queue/inter-group idling takes effect (via the >>> slice_idle and group_idle parameters, both of which default to 8ms). >>> Therefore, everytime CFQ switches between processing requests from dd >>> vs jbd2, this 8ms idle time is injected, which slows down the overall >>> throughput tremendously! >>> >>> To verify this theory, I tried various experiments, and in all cases, >>> the 4 pre-conditions mentioned above were necessary to reproduce this >>> performance drop. For example, if I used an XFS filesystem (which >>> doesn't use a separate kthread like jbd2 for journaling), or if I dd'ed >>> directly to a block device, I couldn't reproduce the performance >>> issue. Similarly, running dd in the root blkio cgroup (where jbd2 >>> runs) also gets full performance; as does using the noop or deadline >>> I/O schedulers; or even CFQ itself, with slice_idle and group_idle set >>> to zero. >>> >>> These results were reproduced on a Linux VM (kernel v4.19) on ESXi, >>> both with virtualized storage as well as with disk pass-through, >>> backed by a rotational hard disk in both cases. The same problem was >>> also seen with the BFQ I/O scheduler in kernel v5.1. >>> >>> Searching for any earlier discussions of this problem, I found an old >>> thread on LKML that encountered this behavior [1], as well as a docker >>> github issue [2] with similar symptoms (mentioned later in the >>> thread). >>> >>> So, I'm curious to know if this is a well-understood problem and if >>> anybody has any thoughts on how to fix it. >>> >>> Thank you very much! >>> >>> >>> [1]. https://lkml.org/lkml/2015/11/19/359 >>> >>> [2]. https://github.com/moby/moby/issues/21485 >>> https://github.com/moby/moby/issues/21485#issuecomment-222941103 >>> >>> Regards, >>> Srivatsa >> >
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