linux-kernel - Re: [PATCH RFC] mm: implement write-behind policy for sequential file writes

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Date:   Tue, 3 Oct 2017 00:29:01 +0200
From:   Andreas Dilger <adilger@...ger.ca>
To:     Konstantin Khlebnikov <khlebnikov@...dex-team.ru>
Cc:     Linus Torvalds <torvalds@...ux-foundation.org>,
        linux-fsdevel <linux-fsdevel@...r.kernel.org>,
        linux-mm <linux-mm@...ck.org>,
        Linux Kernel Mailing List <linux-kernel@...r.kernel.org>,
        Jens Axboe <axboe@...nel.dk>, Michal Hocko <mhocko@...e.com>,
        Mel Gorman <mgorman@...e.de>,
        Johannes Weiner <hannes@...xchg.org>,
        Tejun Heo <tj@...nel.org>,
        Andrew Morton <akpm@...ux-foundation.org>
Subject: Re: [PATCH RFC] mm: implement write-behind policy for sequential file
 writes

On Oct 2, 2017, at 10:58 PM, Konstantin Khlebnikov <khlebnikov@...dex-team.ru> wrote:
> 
> On 02.10.2017 22:54, Linus Torvalds wrote:
>> On Mon, Oct 2, 2017 at 2:54 AM, Konstantin Khlebnikov
>> <khlebnikov@...dex-team.ru> wrote:
>>> 
>>> This patch implements write-behind policy which tracks sequential writes
>>> and starts background writeback when have enough dirty pages in a row.
>> This looks lovely to me.
>> I do wonder if you also looked at finishing the background
>> write-behind at close() time, because it strikes me that once you
>> start doing that async writeout, it would probably be good to make
>> sure you try to do the whole file.
> 
> Smaller files or tails is lesser problem and forced writeback here
> might add bigger overhead due to small requests or too random IO.
> Also open+append+close pattern could generate too much IO.
> 
>> I'm thinking of filesystems that do delayed allocation etc - I'd
>> expect that you'd want the whole file to get allocated on disk
>> together, rather than have the "first 256kB aligned chunks" allocated
>> thanks to write-behind, and then the final part allocated much later
>> (after other files may have triggered their own write-behind). Think
>> loads like copying lots of pictures around, for example.
> 
> As far as I know ext4 preallocates space beyond file end for writing
> patterns like append + fsync. Thus allocated extents should be bigger
> than 256k. I haven't looked into this yet.
> 
>> I don't have any particularly strong feelings about this, but I do
>> suspect that once you have started that IO, you do want to finish it
>> all up as the file write is done. No?
> 
> I'm aiming into continuous file operations like downloading huge file
> or writing verbose log. Original motivation came from low-latency server
> workloads which suffers from parallel bulk operations which generates
> tons of dirty pages. Probably for general-purpose usage thresholds
> should be increased significantly to cover only really bulky patterns.
> 
>> It would also be really nice to see some numbers. Perhaps a comparison
>> of "vmstat 1" or similar when writing a big file to some slow medium
>> like a USB stick (which is something we've done very very badly at,
>> and this should help smooth out)?
> 
> I'll try to find out some real cases with numbers.
> 
> For now I see that massive write + fdatasync (dd conf=fdatasync, fio)
> always ends earlier because writeback now starts earlier too.
> Without fdatasync it's obviously slower.
> 
> Cp to usb stick + umount should show same result, plus cp could be
> interrupted at any point without contaminating cache with dirty pages.
> 
> Kernel compilation tooks almost the same time because most files are
> smaller than 256k.

For what it's worth, Lustre clients have been doing "early writes" forever,
when at least a full/contiguous RPC worth (1MB) of dirty data is available,
because network bandwidth is a terrible thing to waste.  The oft-cited case
of "app writes to a file that only lives a few seconds on disk before it is
deleted" is IMHO fairly rare in real life, mostly dbench and back in the
days of disk based /tmp.

Delaying data writes for large files means that 30s * bandwidth of data
could have been written before VM page aging kicks in, unless memory
pressure causes writeout first.  With fast devices/networks, this might
be many GB of data filling up memory that could have been written out.

Cheers, Andreas






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