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.
  
  latency
  -------
  This parameter is used to enable/disable the latency mode of the CFQ
  scheduler. If latency mode (called low_latency) is 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
  request which are marked with REQ_NOIDLE go 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 marked with REQ_NOIDLE.
  
  A1. We only do tree idle (all queues on sync-noidle tree) on queues marked
      with REQ_NOIDLE. 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_NOIDLE request comes in, it will be scheduled
      roughly after 1 second. If after completion of REQ_NOIDLE request we
      do not idle, and after a couple of milli seconds a another REQ_NOIDLE
      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_NOIDLE, 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_NOIDLE 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_NOIDLE
  A2. I would think whenever one is doing synchronous write and not expecting
      more writes to be dispatched from same context soon, should be able
      to specify REQ_NOIDLE on writes and that probably should work well for
      most of the cases.