292 lines
12 KiB
Plaintext
292 lines
12 KiB
Plaintext
|
CFQ (Complete Fairness Queueing)
|
||
|
|
===============================
|
||
|
|
|
||
|
|
The main aim of CFQ scheduler is to provide a fair allocation of the disk
|
||
|
|
I/O bandwidth for all the processes which requests an I/O operation.
|
||
|
|
|
||
|
|
CFQ maintains the per process queue for the processes which request I/O
|
||
|
|
operation(synchronous requests). In case of asynchronous requests, all the
|
||
|
|
requests from all the processes are batched together according to their
|
||
|
|
process's I/O priority.
|
||
|
|
|
||
|
|
CFQ ioscheduler tunables
|
||
|
|
========================
|
||
|
|
|
||
|
|
slice_idle
|
||
|
|
----------
|
||
|
|
This specifies how long CFQ should idle for next request on certain cfq queues
|
||
|
|
(for sequential workloads) and service trees (for random workloads) before
|
||
|
|
queue is expired and CFQ selects next queue to dispatch from.
|
||
|
|
|
||
|
|
By default slice_idle is a non-zero value. That means by default we idle on
|
||
|
|
queues/service trees. This can be very helpful on highly seeky media like
|
||
|
|
single spindle SATA/SAS disks where we can cut down on overall number of
|
||
|
|
seeks and see improved throughput.
|
||
|
|
|
||
|
|
Setting slice_idle to 0 will remove all the idling on queues/service tree
|
||
|
|
level and one should see an overall improved throughput on faster storage
|
||
|
|
devices like multiple SATA/SAS disks in hardware RAID configuration. The down
|
||
|
|
side is that isolation provided from WRITES also goes down and notion of
|
||
|
|
IO priority becomes weaker.
|
||
|
|
|
||
|
|
So depending on storage and workload, it might be useful to set slice_idle=0.
|
||
|
|
In general I think for SATA/SAS disks and software RAID of SATA/SAS disks
|
||
|
|
keeping slice_idle enabled should be useful. For any configurations where
|
||
|
|
there are multiple spindles behind single LUN (Host based hardware RAID
|
||
|
|
controller or for storage arrays), setting slice_idle=0 might end up in better
|
||
|
|
throughput and acceptable latencies.
|
||
|
|
|
||
|
|
back_seek_max
|
||
|
|
-------------
|
||
|
|
This specifies, given in Kbytes, the maximum "distance" for backward seeking.
|
||
|
|
The distance is the amount of space from the current head location to the
|
||
|
|
sectors that are backward in terms of distance.
|
||
|
|
|
||
|
|
This parameter allows the scheduler to anticipate requests in the "backward"
|
||
|
|
direction and consider them as being the "next" if they are within this
|
||
|
|
distance from the current head location.
|
||
|
|
|
||
|
|
back_seek_penalty
|
||
|
|
-----------------
|
||
|
|
This parameter is used to compute the cost of backward seeking. If the
|
||
|
|
backward distance of request is just 1/back_seek_penalty from a "front"
|
||
|
|
request, then the seeking cost of two requests is considered equivalent.
|
||
|
|
|
||
|
|
So scheduler will not bias toward one or the other request (otherwise scheduler
|
||
|
|
will bias toward front request). Default value of back_seek_penalty is 2.
|
||
|
|
|
||
|
|
fifo_expire_async
|
||
|
|
-----------------
|
||
|
|
This parameter is used to set the timeout of asynchronous requests. Default
|
||
|
|
value of this is 248ms.
|
||
|
|
|
||
|
|
fifo_expire_sync
|
||
|
|
----------------
|
||
|
|
This parameter is used to set the timeout of synchronous requests. Default
|
||
|
|
value of this is 124ms. In case to favor synchronous requests over asynchronous
|
||
|
|
one, this value should be decreased relative to fifo_expire_async.
|
||
|
|
|
||
|
|
group_idle
|
||
|
|
-----------
|
||
|
|
This parameter forces idling at the CFQ group level instead of CFQ
|
||
|
|
queue level. This was introduced after a bottleneck was observed
|
||
|
|
in higher end storage due to idle on sequential queue and allow dispatch
|
||
|
|
from a single queue. The idea with this parameter is that it can be run with
|
||
|
|
slice_idle=0 and group_idle=8, so that idling does not happen on individual
|
||
|
|
queues in the group but happens overall on the group and thus still keeps the
|
||
|
|
IO controller working.
|
||
|
|
Not idling on individual queues in the group will dispatch requests from
|
||
|
|
multiple queues in the group at the same time and achieve higher throughput
|
||
|
|
on higher end storage.
|
||
|
|
|
||
|
|
Default value for this parameter is 8ms.
|
||
|
|
|
||
|
|
low_latency
|
||
|
|
-----------
|
||
|
|
This parameter is used to enable/disable the low latency mode of the CFQ
|
||
|
|
scheduler. If enabled, CFQ tries to recompute the slice time for each process
|
||
|
|
based on the target_latency set for the system. This favors fairness over
|
||
|
|
throughput. Disabling low latency (setting it to 0) ignores target latency,
|
||
|
|
allowing each process in the system to get a full time slice.
|
||
|
|
|
||
|
|
By default low latency mode is enabled.
|
||
|
|
|
||
|
|
target_latency
|
||
|
|
--------------
|
||
|
|
This parameter is used to calculate the time slice for a process if cfq's
|
||
|
|
latency mode is enabled. It will ensure that sync requests have an estimated
|
||
|
|
latency. But if sequential workload is higher(e.g. sequential read),
|
||
|
|
then to meet the latency constraints, throughput may decrease because of less
|
||
|
|
time for each process to issue I/O request before the cfq queue is switched.
|
||
|
|
|
||
|
|
Though this can be overcome by disabling the latency_mode, it may increase
|
||
|
|
the read latency for some applications. This parameter allows for changing
|
||
|
|
target_latency through the sysfs interface which can provide the balanced
|
||
|
|
throughput and read latency.
|
||
|
|
|
||
|
|
Default value for target_latency is 300ms.
|
||
|
|
|
||
|
|
slice_async
|
||
|
|
-----------
|
||
|
|
This parameter is same as of slice_sync but for asynchronous queue. The
|
||
|
|
default value is 40ms.
|
||
|
|
|
||
|
|
slice_async_rq
|
||
|
|
--------------
|
||
|
|
This parameter is used to limit the dispatching of asynchronous request to
|
||
|
|
device request queue in queue's slice time. The maximum number of request that
|
||
|
|
are allowed to be dispatched also depends upon the io priority. Default value
|
||
|
|
for this is 2.
|
||
|
|
|
||
|
|
slice_sync
|
||
|
|
----------
|
||
|
|
When a queue is selected for execution, the queues IO requests are only
|
||
|
|
executed for a certain amount of time(time_slice) before switching to another
|
||
|
|
queue. This parameter is used to calculate the time slice of synchronous
|
||
|
|
queue.
|
||
|
|
|
||
|
|
time_slice is computed using the below equation:-
|
||
|
|
time_slice = slice_sync + (slice_sync/5 * (4 - prio)). To increase the
|
||
|
|
time_slice of synchronous queue, increase the value of slice_sync. Default
|
||
|
|
value is 100ms.
|
||
|
|
|
||
|
|
quantum
|
||
|
|
-------
|
||
|
|
This specifies the number of request dispatched to the device queue. In a
|
||
|
|
queue's time slice, a request will not be dispatched if the number of request
|
||
|
|
in the device exceeds this parameter. This parameter is used for synchronous
|
||
|
|
request.
|
||
|
|
|
||
|
|
In case of storage with several disk, this setting can limit the parallel
|
||
|
|
processing of request. Therefore, increasing the value can improve the
|
||
|
|
performance although this can cause the latency of some I/O to increase due
|
||
|
|
to more number of requests.
|
||
|
|
|
||
|
|
CFQ Group scheduling
|
||
|
|
====================
|
||
|
|
|
||
|
|
CFQ supports blkio cgroup and has "blkio." prefixed files in each
|
||
|
|
blkio cgroup directory. It is weight-based and there are four knobs
|
||
|
|
for configuration - weight[_device] and leaf_weight[_device].
|
||
|
|
Internal cgroup nodes (the ones with children) can also have tasks in
|
||
|
|
them, so the former two configure how much proportion the cgroup as a
|
||
|
|
whole is entitled to at its parent's level while the latter two
|
||
|
|
configure how much proportion the tasks in the cgroup have compared to
|
||
|
|
its direct children.
|
||
|
|
|
||
|
|
Another way to think about it is assuming that each internal node has
|
||
|
|
an implicit leaf child node which hosts all the tasks whose weight is
|
||
|
|
configured by leaf_weight[_device]. Let's assume a blkio hierarchy
|
||
|
|
composed of five cgroups - root, A, B, AA and AB - with the following
|
||
|
|
weights where the names represent the hierarchy.
|
||
|
|
|
||
|
|
weight leaf_weight
|
||
|
|
root : 125 125
|
||
|
|
A : 500 750
|
||
|
|
B : 250 500
|
||
|
|
AA : 500 500
|
||
|
|
AB : 1000 500
|
||
|
|
|
||
|
|
root never has a parent making its weight is meaningless. For backward
|
||
|
|
compatibility, weight is always kept in sync with leaf_weight. B, AA
|
||
|
|
and AB have no child and thus its tasks have no children cgroup to
|
||
|
|
compete with. They always get 100% of what the cgroup won at the
|
||
|
|
parent level. Considering only the weights which matter, the hierarchy
|
||
|
|
looks like the following.
|
||
|
|
|
||
|
|
root
|
||
|
|
/ | \
|
||
|
|
A B leaf
|
||
|
|
500 250 125
|
||
|
|
/ | \
|
||
|
|
AA AB leaf
|
||
|
|
500 1000 750
|
||
|
|
|
||
|
|
If all cgroups have active IOs and competing with each other, disk
|
||
|
|
time will be distributed like the following.
|
||
|
|
|
||
|
|
Distribution below root. The total active weight at this level is
|
||
|
|
A:500 + B:250 + C:125 = 875.
|
||
|
|
|
||
|
|
root-leaf : 125 / 875 =~ 14%
|
||
|
|
A : 500 / 875 =~ 57%
|
||
|
|
B(-leaf) : 250 / 875 =~ 28%
|
||
|
|
|
||
|
|
A has children and further distributes its 57% among the children and
|
||
|
|
the implicit leaf node. The total active weight at this level is
|
||
|
|
AA:500 + AB:1000 + A-leaf:750 = 2250.
|
||
|
|
|
||
|
|
A-leaf : ( 750 / 2250) * A =~ 19%
|
||
|
|
AA(-leaf) : ( 500 / 2250) * A =~ 12%
|
||
|
|
AB(-leaf) : (1000 / 2250) * A =~ 25%
|
||
|
|
|
||
|
|
CFQ IOPS Mode for group scheduling
|
||
|
|
===================================
|
||
|
|
Basic CFQ design is to provide priority based time slices. Higher priority
|
||
|
|
process gets bigger time slice and lower priority process gets smaller time
|
||
|
|
slice. Measuring time becomes harder if storage is fast and supports NCQ and
|
||
|
|
it would be better to dispatch multiple requests from multiple cfq queues in
|
||
|
|
request queue at a time. In such scenario, it is not possible to measure time
|
||
|
|
consumed by single queue accurately.
|
||
|
|
|
||
|
|
What is possible though is to measure number of requests dispatched from a
|
||
|
|
single queue and also allow dispatch from multiple cfq queue at the same time.
|
||
|
|
This effectively becomes the fairness in terms of IOPS (IO operations per
|
||
|
|
second).
|
||
|
|
|
||
|
|
If one sets slice_idle=0 and if storage supports NCQ, CFQ internally switches
|
||
|
|
to IOPS mode and starts providing fairness in terms of number of requests
|
||
|
|
dispatched. Note that this mode switching takes effect only for group
|
||
|
|
scheduling. For non-cgroup users nothing should change.
|
||
|
|
|
||
|
|
CFQ IO scheduler Idling Theory
|
||
|
|
===============================
|
||
|
|
Idling on a queue is primarily about waiting for the next request to come
|
||
|
|
on same queue after completion of a request. In this process CFQ will not
|
||
|
|
dispatch requests from other cfq queues even if requests are pending there.
|
||
|
|
|
||
|
|
The rationale behind idling is that it can cut down on number of seeks
|
||
|
|
on rotational media. For example, if a process is doing dependent
|
||
|
|
sequential reads (next read will come on only after completion of previous
|
||
|
|
one), then not dispatching request from other queue should help as we
|
||
|
|
did not move the disk head and kept on dispatching sequential IO from
|
||
|
|
one queue.
|
||
|
|
|
||
|
|
CFQ has following service trees and various queues are put on these trees.
|
||
|
|
|
||
|
|
sync-idle sync-noidle async
|
||
|
|
|
||
|
|
All cfq queues doing synchronous sequential IO go on to sync-idle tree.
|
||
|
|
On this tree we idle on each queue individually.
|
||
|
|
|
||
|
|
All synchronous non-sequential queues go on sync-noidle tree. Also any
|
||
|
|
synchronous write request which is not marked with REQ_IDLE goes on this
|
||
|
|
service tree. On this tree we do not idle on individual queues instead idle
|
||
|
|
on the whole group of queues or the tree. So if there are 4 queues waiting
|
||
|
|
for IO to dispatch we will idle only once last queue has dispatched the IO
|
||
|
|
and there is no more IO on this service tree.
|
||
|
|
|
||
|
|
All async writes go on async service tree. There is no idling on async
|
||
|
|
queues.
|
||
|
|
|
||
|
|
CFQ has some optimizations for SSDs and if it detects a non-rotational
|
||
|
|
media which can support higher queue depth (multiple requests at in
|
||
|
|
flight at a time), then it cuts down on idling of individual queues and
|
||
|
|
all the queues move to sync-noidle tree and only tree idle remains. This
|
||
|
|
tree idling provides isolation with buffered write queues on async tree.
|
||
|
|
|
||
|
|
FAQ
|
||
|
|
===
|
||
|
|
Q1. Why to idle at all on queues not marked with REQ_IDLE.
|
||
|
|
|
||
|
|
A1. We only do tree idle (all queues on sync-noidle tree) on queues not marked
|
||
|
|
with REQ_IDLE. This helps in providing isolation with all the sync-idle
|
||
|
|
queues. Otherwise in presence of many sequential readers, other
|
||
|
|
synchronous IO might not get fair share of disk.
|
||
|
|
|
||
|
|
For example, if there are 10 sequential readers doing IO and they get
|
||
|
|
100ms each. If a !REQ_IDLE request comes in, it will be scheduled
|
||
|
|
roughly after 1 second. If after completion of !REQ_IDLE request we
|
||
|
|
do not idle, and after a couple of milli seconds a another !REQ_IDLE
|
||
|
|
request comes in, again it will be scheduled after 1second. Repeat it
|
||
|
|
and notice how a workload can lose its disk share and suffer due to
|
||
|
|
multiple sequential readers.
|
||
|
|
|
||
|
|
fsync can generate dependent IO where bunch of data is written in the
|
||
|
|
context of fsync, and later some journaling data is written. Journaling
|
||
|
|
data comes in only after fsync has finished its IO (atleast for ext4
|
||
|
|
that seemed to be the case). Now if one decides not to idle on fsync
|
||
|
|
thread due to !REQ_IDLE, then next journaling write will not get
|
||
|
|
scheduled for another second. A process doing small fsync, will suffer
|
||
|
|
badly in presence of multiple sequential readers.
|
||
|
|
|
||
|
|
Hence doing tree idling on threads using !REQ_IDLE flag on requests
|
||
|
|
provides isolation from multiple sequential readers and at the same
|
||
|
|
time we do not idle on individual threads.
|
||
|
|
|
||
|
|
Q2. When to specify REQ_IDLE
|
||
|
|
A2. I would think whenever one is doing synchronous write and expecting
|
||
|
|
more writes to be dispatched from same context soon, should be able
|
||
|
|
to specify REQ_IDLE on writes and that probably should work well for
|
||
|
|
most of the cases.
|