** Changed in: linux (Ubuntu Bionic)
Status: In Progress => Fix Committed
** Changed in: linux (Ubuntu Focal)
Status: In Progress => Fix Committed
** Changed in: linux (Ubuntu Groovy)
Status: In Progress => Fix Committed
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https://bugs.launchpad.net/bugs/1900438
Title:
Bcache bypasse writeback on caching device with fragmentation
Status in linux package in Ubuntu:
Confirmed
Status in linux source package in Bionic:
Fix Committed
Status in linux source package in Focal:
Fix Committed
Status in linux source package in Groovy:
Fix Committed
Status in linux source package in Hirsute:
Confirmed
Bug description:
SRU Justification:
[Impact]
This bug in bcache affects I/O performance on all versions of the kernel
[correct versions affected]. It is particularly negative on ceph if used with
bcache.
Write I/O latency would suddenly go to around 1 second from around 10
ms when hitting this issue and would easily be stuck there for hours
or even days, especially bad for ceph on bcache architecture. This
would make ceph extremely slow and make the entire cloud almost
unusable.
The root cause is that the dirty bucket had reached the 70 percent
threshold, thus causing all writes to go direct to the backing HDD
device. It might be fine if it actually had a lot of dirty data, but
this happens when dirty data has not even reached over 10 percent, due
to having high memory fragmentation. What makes it worse is that the
writeback rate might be still at minimum value (8) due to the
writeback percent not reached, so it takes ages for bcache to really
reclaim enough dirty buckets to get itself out of this situation.
[Fix]
* 71dda2a5625f31bc3410cb69c3d31376a2b66f28 “bcache: consider the
fragmentation when update the writeback rate”
The current way to calculate the writeback rate only considered the dirty
sectors.
This usually works fine when memory fragmentation is not high, but it will
give us an unreasonably low writeback rate when we are in the situation that a
few dirty sectors have consumed a lot of dirty buckets. In some cases, the
dirty buckets reached CUTOFF_WRITEBACK_SYNC (i.e., stopped writeback) while
the dirty data (sectors) had not even reached the writeback_percent threshold
(i.e., started writeback). In that situation, the writeback rate will still be
the minimum value (8*512 = 4KB/s), thus it will cause all the writes to bestuck
in a non-writeback mode because of the slow writeback.
We accelerate the rate in 3 stages with different aggressiveness:
the first stage starts when dirty buckets percent reach above
BCH_WRITEBACK_FRAGMENT_THRESHOLD_LOW (50),
the second is BCH_WRITEBACK_FRAGMENT_THRESHOLD_MID (57),
the third is BCH_WRITEBACK_FRAGMENT_THRESHOLD_HIGH (64).
By default the first stage tries to writeback the amount of dirty data
in one bucket (on average) in (1 / (dirty_buckets_percent - 50)) seconds,
the second stage tries to writeback the amount of dirty data in one bucket
in (1 / (dirty_buckets_percent - 57)) * 100 milliseconds, the third
stage tries to writeback the amount of dirty data in one bucket in
(1 / (dirty_buckets_percent - 64)) milliseconds.
The initial rate at each stage can be controlled by 3 configurable
parameters:
writeback_rate_fp_term_{low|mid|high}
They are by default 1, 10, 1000, chosen based on testing and
production data, detailed below.
A. When it comes to the low stage, it is still far from the 70%
threshold, so we only want to give it a little bit push by setting the
term to 1, it means the initial rate will be 170 if the fragment is 6,
it is calculated by bucket_size/fragment, this rate is very small,
but still much more reasonable than the minimum 8.
For a production bcache with non-heavy workload, if the cache device
is bigger than 1 TB, it may take hours to consume 1% buckets,
so it is very possible to reclaim enough dirty buckets in this stage,
thus to avoid entering the next stage.
B. If the dirty buckets ratio didn’t turn around during the first stage,
it comes to the mid stage, then it is necessary for mid stage
to be more aggressive than low stage, so the initial rate is chosen
to be 10 times more than the low stage, which means 1700 as the initial
rate if the fragment is 6. This is a normal rate
we usually see for a normal workload when writeback happens
because of writeback_percent.
C. If the dirty buckets ratio didn't turn around during the low and mid
stages, it comes to the third stage, and it is the last chance that
we can turn around to avoid the horrible cutoff writeback sync issue,
then we choose 100 times more aggressive than the mid stage, that
means 170000 as the initial rate if the fragment is 6. This is also
inferred from a production bcache, I've got one week's writeback rate
data from a production bcache which has quite heavy workloads,
again, the writeback is triggered by the writeback percent,
the highest rate area is around 100000 to 240000, so I believe this
kind aggressiveness at this stage is reasonable for production.
And it should be mostly enough because the hint is trying to reclaim
1000 bucket per second, and from that heavy production env,
it is consuming 50 buckets per second on average in one week's data.
Option writeback_consider_fragment is to control whether we want
this feature to be on or off, it's on by default.
[Test Case]
I’ve put all my testing results in below google document, the testing clearly
shows the significant performance improvement.
https://docs.google.com/document/d/1AmbIEa_2MhB9bqhC3rfga9tp7n9YX9PLn0jSUxscVW0/edit?usp=sharing
Another testing is that we had built a testing kernel based on bionic
4.15.0-99.100 + the patch, and putting this kernel in a production
environment, it’s an openstack environment with ceph on bcache as the
storage. It runs for more than one month and doesn’t show any issue.
[Regression Potential]
The patch only updates the writeback rate, so it won’t have any impact
on the data safety, the only potential regression I can think of is
that the backing device might be a bit busier after the dirty buckets
reached to BCH_WRITEBACK_FRAGMENT_THRESHOLD_LOW(50% by default) since
the writeback rate is accelerated under this highly fragmented
situation, but that’s because we are trying to avoid all writes hit
the writeback cutoff sync threshold.
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