Re: [PATCH V3 00/11] block-throttle: add .high limit

Hi,
On Tue, Oct 04, 2016 at 09:28:05AM -0400, Vivek Goyal wrote:

On Mon, Oct 03, 2016 at 02:20:19PM -0700, Shaohua Li wrote:

quoted

Hi,

The background is we don't have an ioscheduler for blk-mq yet, so we can't
prioritize processes/cgroups.

So this is an interim solution till we have ioscheduler for blk-mq?

This is still a generic solution to prioritize workloads.

quoted

This patch set tries to add basic arbitration
between cgroups with blk-throttle. It adds a new limit io.high for
blk-throttle. It's only for cgroup2.

io.max is a hard limit throttling. cgroups with a max limit never dispatch more
IO than their max limit. While io.high is a best effort throttling. cgroups
with high limit can run above their high limit at appropriate time.
Specifically, if all cgroups reach their high limit, all cgroups can run above
their high limit. If any cgroup runs under its high limit, all other cgroups
will run according to their high limit.

Hi Shaohua,

I still don't understand why we should not implement a weight based
proportional IO mechanism and how this mechanism is better than proportional IO .

Agreed that we have issues with proportional IO and we don't have good
solutions for these problems. But I can't see that how this mechanism
will overcome these problems either.

No, I never declare this mechanism is better than proportional IO. The problem
with proportional IO is we don't have a mechanism to measure IO cost, which is
the core for proportional. This mechanism only prioritizes IO. It's not as
useful as proportional, but works for a lot of scenarios.

IIRC, biggest issue with proportional IO was that a low prio group might
fill up the device queue with plenty of IO requests and later when high
prio cgroup comes, it will still experience latencies anyway. And solution
to the problem probably would be to get some awareness in device about 
priority of request and map weights to those priority. That way higher
prio requests get prioritized.

Or run device at lower queue depth. That will improve latencies but migth
reduce overall throughput.

Yep, this is the hardest part. It really depends on the tradeoff between
throughput and latency. Running device at low queue depth sounds working, but
the sacrifice is extremely high for modern SSD. Small size IO throughput has a
range from several MB/s to several GB/s depending on queue depth. If run device
at lower queue depth, the sacrific is big enough to make device sharing no
sense.
 

Or thorottle number of buffered writes (as Jens's writeback throttling)
patches were doing. Buffered writes seem to be biggest culprit for 
increased latencies and being able to control these should help.

big size read can significantly increase latency too. Please note latency isn't
the only factor applications care about. non-interactive workloads don't care
about single IO latency, throughput or amortized latency is more important for
such workloads.

ioprio/weight based proportional IO mechanism is much more generic and
much easier to configure for any kind of storage. io.high is absolute
limit and makes it much harder to configure. One needs to know a lot
about underlying volume/device's bandwidth (which varies a lot anyway
based on workload).
IMHO, we seem to be trying to cater to one specific use case using
this mechanism. Something ioprio/weight based will be much more
generic and we should explore implementing that along with building
notion of ioprio in devices. When these two work together, we might
be able to see good results. Just software mechanism alone might not
be enough.

Agree, proportional IO mechanism is easier to configure. The problem we can't
build it without hardware support.

Thanks,
Shaohua