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