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									Performance Designs

Designing for Specific Performance and Testing




                              Brendon Higgins CEng MBCS CITP
                                           NetApp User Group
                                                   June 2009
Presenter


Brendon Higgins CEng MBCS CITP
NetApp Certified Data Management Administrator




  Author Images used
    on web forums
                                   Data Centre Services Engineer
                                                 DLA Piper UK LLP
                                          Brendon.Higgins@dla.com



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Why Bother Attending


        Learn about storage performance at the design stage
                  based on a case study example.


                   How is performance measured
                   What performance should be expected
                   What performance is being delivered




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Introduction to DLA Piper


Global Legal Firm

       More than 8,000 people across more than 65 offices in 28 countries


       $2,262,000,000 annual revenue


       DLA Piper represents more than 140 of the top 250 Fortune 500 clients
        and nearly half of the FTSE 350 or their subsidiaries




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Overview of units of performance




          Storage Systems   Cars

          Throughput        Maximum Speed
          Capacity (GB)     Capacity (cc)
          IOPS              BHP
          Latency           0-60 time
          Cost
                            Cost
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Warning – Maths!




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Storage - Mebibyte


The megabyte (MB) unit is used in NetApp storage as a
 measure of capacity and it is based on the binary
 system
                             220 or 1,048,576 bytes



                       Kilobyte 210
                       Megabyte 220
                                           Multiples of 1024
                       Gigabyte 230
                       Terabyte 240
                       Petabyte 250


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Throughput


Throughput is a measure of the total data moved through a channel in
 a given time

             Megabytes per second (MB/s) are the units used in this
              presentation

             Standard S.I. prefixes indicating multiplication by 1,000
                   1,000 kilo
                   1,000,000 mega
                   1,000,000,000 giga

             Duplex communication is assumed between the devices {two way
              street}




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Quoted Throughput


It is important to understand the difference throughput quoted
             maximum {theoretical | achievable | sustained}
             peak measured
             ‘good’



Guideline Figures – But what type of measure?

           Device                           Speed (bit/s)   Speed (byte/s)
           Fast Ethernet (100base-X)          100 Mbit/s       12.5 MB/s
           Gigabit Ethernet (1000base-X)     1,000 Mbit/s      125 MB/s
           iSCSI over Gigabit Ethernet       1,000 Mbit/s      125 MB/s
           Fibre Channel 4GFC (4.25 GHz)     3,400 Mbit/s      425 MB/s




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Moving Data




        10Gb
                       5 Minutes


                                   10 Gb




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Moving Data


                                   10 Gb = 10,240 MB
                                   10,240 ÷ 300 =
                                   34 MB per sec moved

        10Gb
                       5 Minutes

                                                        34 MB/s
                                        10 Gb




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Moving Data


                                           10 Gb = 10,240 MB
                                           10,240 ÷ 300 =
                                           34 MB per sec moved

        10Gb
                       5 Minutes

                                                                34 or 36
                                                10 Gb            MB/s?

But throughput is measured as MB/s ‘106’
10,737,418,240 bytes ÷ 300 = 35,791,394
36 MB/s
288Mbps (8x for bits)

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Maths Error


The classic mistake is to interchange throughput MB/s with binary MB
            1,000,000 bytes vs 1,048,576 bytes
            4.9% error margin




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Maths Error


The classic mistake is to interchange throughput MB/s with binary MB
            1,000,000 bytes vs 1,048,576 bytes
            4.9% error margin


Or worse, network megabits (Mb/s) when describing megabytes
            131,072 vs 1,048,576
            1/8 required value
            87.5% error margin!


Remember NASA’s Mars Polar Lander? - $125m craft destroyed after a mix-
 up between imperial and metric measurements




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Input/Output Operations Per Second




                  Data


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‘IOPS’


The measurement is taken as
             Total number of IOPS
             Average number of random read IOPS
             Average number of random write IOPS
             Average number of sequential read IOPS
             Average number of sequential write IOPS



Each IOP in a NetApp system is
             between 4 KB (4,096 bytes) and 128KB
             but can peak to 256KB




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Rotational latency



  Time in milliseconds (ms)
  required to move the head to the
  data


  Sequential vs Random




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Cost



          “What would you do if it was your money?”




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What performance should be expected




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 Real World Performance


Predicting the future and assumptions…


    Guestimation for specification


    Multiplying averages in design


    Performance metrics of little value
        Beware FUD - Fear, Uncertainty, and Doubt




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iSCSI vs FCP


A classic ‘conversation’ point for
  block level performance and a
  good illustration of FUD. Ask
  the person next to you, which
  they think is the best…

                       Calm down, calm
                            down!


There is no correct answer as it
 depends on the other
 components which make up
 the system and external
 factors such as cost.


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Design Requirement


As fast as possible… What else




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Case Study: Design Requirement


The application supplier’s required specifications for the SQL
 server based on observed history using similar sized
 deployments.


       100 Gb of storage in the first year
             Then growth to 500Gb over the next 5 years
       At least 400 IOPS
       At least 425 MB/s throughput
       Latency not greater than 12 ms




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Theoretical performance
characteristics of devices




             Competitive Advantage


             http://www.spec.org/


             http://en.wikipedia.org/wiki/List_of_device_bandwidths




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Graph of Disk Performance


                Random 4KB Workload - Can Vary




                          120 and below for 10k
                          220 and below for 15k
                        50-60 and below for SATA.
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Case Study: Options



                       Single Filer                                                                                                                                                                                                                                                                                Dual Filers (Act./Act.)
                       3 Shelves                                                                                                                                                                                                                                                                                   3 Shelves - S/W Ownership
                       42 Disks                                                                                                                                                                                                                                                                                    21 Disks per Filer
                                                                                                                                                                                                                                                                                                                                                                                                                                                                             NetApp

                                                                                                                                                                                                                                                                                                                                                                                                                                                                         FAS 3050



                                                                                                                                                                                                                                                                                                                                                                                                                                                                  activity      status        power




                                                                                                                                                                                NetApp

                                                                                                                                                                            FAS 3050                                                                                                                                                                                                                                                                                         NetApp

                                                                                                                                                                                                                                                                                                                                                                                                                                                                         FAS 3050

                                                                                                                                                                     activity      status        power




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NetApp Storage Recapitulation


 All NetApp operations are made with 4Kb blocks


 Data write latency is host to filer memory
       Back to back CPs (CP generated CP)


 Aggregate is physical unit
       Only data disks affect performance




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Following Example Disk Configuration




                               1 Spare disk per filer
                               20 Disks in each aggregate
                               RAID Group Size of 16 with 2 groups
                               RAID – DP so a parity and double parity disk per
                               raid group




                       16 Data disks available in each aggregate


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Calculating Data Rates in Aggregates


16x 300Gb 15K FC data disks in the aggregate
Each NetApp disk IOP is equal to either 4, 64 or 128 KB of storage
The throughput for each IOP/s (1024 x 4) ÷ 1000 = 4.096KB/s




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Calculating Data Rates in Aggregates


16x 300Gb 15K FC data disks in the aggregate
Each NetApp disk IOP is equal to either 4, 64 or 128 KB of storage
The throughput for each IOP/s (1024 x 4) ÷ 1000 = 4.096KB/s


16x data disks @ 220 IOPS = 3,520 IOPS
Each IOPS @ 4.096, 65.536 or 131.072 KB/s




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Calculating Data Rates in Aggregates


16x 300Gb 15K FC data disks in the aggregate
Each NetApp disk IOP is equal to either 4, 64 or 128 KB of storage
The throughput for each IOP/s (1024 x 4) ÷ 1000 = 4.096KB/s


16x data disks @ 220 IOPS = 3,520 IOPS
Each IOPS @ 4.096, 65.536 or 131.072 KB/s


      3,520 x 4.096 = 14,418 KBps or 14 MB/s
      3,520 x 65.536 = 230,686.72 KBps or 231 MB/s
      3,520 x 131.072 = 461,373.44 KBps or 461 MB/s




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What performance is being delivered




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Stress test the design and get host
based IO reports

A realistic simulation of the IO pattern of the application can be
  created using 3rd party tools.


Two of the free tools available are:
      Microsoft’s SQLIO.exe from www.microsoft.com/downloads


      Intel’s IOMeter from www.iometer.org/
      IOMeter also has a GUI




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SQLIO.exe: 8KB Sequential - Report


8 threads reading for 300 secs from file E:\SQLIOtest\sqlio_1v1f.dat
  using 8KB sequential IOs
using specified size: 50000 MB for file: E:\SQLIOtest\sqlio_1v1f.dat
CUMULATIVE DATA:
throughput metrics:
IOs/sec: 6837.39
MBs/sec: 53.41
latency metrics:
Min_Latency(ms): 0
Avg_Latency(ms): 9
Max_Latency(ms): 1449
histogram:
ms: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 2324+
%: 59 3 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 14

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SQLIO.exe: 8KB Random - Report


8 threads reading for 300 secs from file E:\SQLIOtest\sqlio_1v1f.dat
   using 8KB random IOs
using specified size: 50000 MB for file: E:\SQLIOtest\sqlio_1v1f.dat
CUMULATIVE DATA:
throughput metrics:
IOs/sec: 3386.12
MBs/sec:               26.45
latency metrics:
Min_Latency(ms): 0
Avg_Latency(ms): 18
Max_Latency(ms): 774
histogram:
ms: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24+
%: 5 0 1 2 3 5 6 6 5 5 4 4 4 3 3 3 3 3 2 2 2 2 2 2 26
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Filer Statistic


Filer
      Sysstat
      Lun Status
      Statit
      FilerView


Host
      Perfstat
      System Manager
      Operations Manager
      Others…



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NetApp System Manager




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  Statit Disks – During 8k Stress Test

disk              ut%      xfers   ureads--chain-usecs writes--chain-usecs cpreads-chain-usecs
/aggr4/plex0/rg0:
2c.16               1       3.59     0.69   1.00 6692     1.71   3.37    932   1.19     2.98        373
2c.17               2       4.14     0.69   1.00 15962    2.40   2.98    760   1.06     2.75        282
2c.18              95     205.80   203.85   1.98 9107     1.37   2.40   4256   0.58     2.09       7261
2c.19              93     202.93   201.56   1.98 9121     0.69   3.81   4051   0.69     2.42       3984
2c.20              95     206.12   204.91   1.98 8987     0.66   4.00   4890   0.55     2.00       7095
1b.21              94     207.78   206.54   1.98 9216     0.69   3.85   4980   0.55     2.67       5750
2c.22              93     203.09   201.77   1.98 8973     0.74   3.57   4180   0.58     2.23       6531
1b.32              95     208.44   206.81   1.99 9397     0.79   3.33   6350   0.84     1.78       5140
2c.33              95     209.55   207.78   1.98 9446     0.79   3.30   5768   0.98     2.08       6974
1b.34              94     203.64   202.08   1.98 9038     0.76   3.41   5677   0.79     1.90       6263
2c.35              95     207.94   206.44   1.98 9513     0.76   3.41   6566   0.74     2.11       7593
2c.36              95     208.60   207.10   1.98 9463     0.82   3.19   6636   0.69     2.54       5712
1b.37              96     212.27   210.97   1.98 9585     0.74   3.50   5500   0.55     1.81       9895
2c.38              95     208.68   207.17   1.98 9348     0.76   3.38   6143   0.74     2.00       6357
1b.48              95     207.17   206.01   1.98 9572     0.69   3.81   7949   0.47     2.06       7243
1b.49              94     206.09   204.83   1.98 9206     0.76   3.45   6440   0.50     2.00       5289
/aggr4/plex0/rg1:
1b.50               0       0.63     0.00   ....      .   0.50   5.63   1150   0.13     4.80        833
1b.51               0       0.63     0.00   ....      .   0.50   5.63   1243   0.13     6.60        576
1b.52              94     207.20   206.38   1.98   9032   0.50   5.21   4485   0.32     2.42       8759
1b.53              94     206.04   205.33   1.98   9297   0.42   6.13   3347   0.29     3.00       3152


   Insert filename here                                                          Date of presentation   38
Statit Throughput


The sum of


            (Read Xfers x (Chain length x IOP Size))
            + (Write Xfers x (Chain length x IOP Size))
            + (CP Read Xfers x (Chain length x IOP Size))

For each data disk gives the throughput in KBps




Insert filename here                                  Date of presentation   39
Measuring Data Rates


Read Xfers = 203; Chains = 1.98                      CP Read Xfer / Chains
Write Xfers = 1.37; Chains = 2.4
CP Read Xfers = 0.58; Chains = 2.09      Write Xfer / Chains
                                         Read Xfer /
                                         Chains
                                      disk             ut%   xfers    ureads--chain-usecs writes--chain-usecs cpreads-chain-usecs
                                      /aggr4/plex0/rg0:
                                      2c.16              1     3.59     0.69   1.00 6692     1.71   3.37    932   1.19   2.98    373
                                      2c.17              2     4.14     0.69   1.00 15962    2.40   2.98    760   1.06   2.75    282
                                      2c.18             95   205.80   203.85   1.98 9107     1.37   2.40   4256   0.58   2.09   7261
                                      2c.19             93   202.93   201.56   1.98 9121     0.69   3.81   4051   0.69   2.42   3984
                                      2c.20             95   206.12   204.91   1.98 8987     0.66   4.00   4890   0.55   2.00   7095
                                      1b.21             94   207.78   206.54   1.98 9216     0.69   3.85   4980   0.55   2.67   5750
                                      2c.22             93   203.09   201.77   1.98 8973     0.74   3.57   4180   0.58   2.23   6531
                                      1b.32             95   208.44   206.81   1.99 9397     0.79   3.33   6350   0.84   1.78   5140
                                      2c.33             95   209.55   207.78   1.98 9446     0.79   3.30   5768   0.98   2.08   6974
                                      1b.34             94   203.64   202.08   1.98 9038     0.76   3.41   5677   0.79   1.90   6263
                                      2c.35             95   207.94   206.44   1.98 9513     0.76   3.41   6566   0.74   2.11   7593
                                      2c.36             95   208.60   207.10   1.98 9463     0.82   3.19   6636   0.69   2.54   5712
                                      1b.37             96   212.27   210.97   1.98 9585     0.74   3.50   5500   0.55   1.81   9895
                                      2c.38             95   208.68   207.17   1.98 9348     0.76   3.38   6143   0.74   2.00   6357
                                      1b.48             95   207.17   206.01   1.98 9572     0.69   3.81   7949   0.47   2.06   7243
                                      1b.49             94   206.09   204.83   1.98 9206     0.76   3.45   6440   0.50   2.00   5289
                                      /aggr4/plex0/rg1:
                                      1b.50              0     0.63     0.00   ....      .   0.50   5.63   1150   0.13   4.80    833
                                      1b.51              0     0.63     0.00   ....      .   0.50   5.63   1243   0.13   6.60    576
                                      1b.52             94   207.20   206.38   1.98   9032   0.50   5.21   4485   0.32   2.42   8759
                                      1b.53             94   206.04   205.33   1.98   9297   0.42   6.13   3347   0.29   3.00   3152




 Insert filename here                                                                         Date of presentation               40
Measuring Data Rates


Read Xfers = 203; Chains = 1.98
Write Xfers = 1.37; Chains = 2.4
CP Read Xfers = 0.58; Chains = 2.09

(203 x (1.98 x 4.096)) + (1.37 x (2.4 x 4.096)) + (0.58 x (2.09 x 4.096))
Gives the output per disk then multiply by 16 data disks




 Insert filename here                                        Date of presentation   41
Measuring Random Data Rates


Read Xfers = 203; Chains = 1.98
Write Xfers = 1.37; Chains = 2.4
CP Read Xfers = 0.58; Chains = 2.09

(203 x (1.98 x 4.096)) + (1.37 x (2.4 x 4.096)) + (0.58 x (2.09 x 4.096))
Gives the output per disk then multiply by 16 data disks

Throughput = 26,636 KBps or 26 MB/s



 sqlio v1.5.SG
 throughput metrics:
 IOs/sec: 3386.12
 MBs/sec: 26.45


 Insert filename here                                        Date of presentation   42
Measuring Serial Data Rates


Read Xfers = 256; Chains = 3.7
Write Xfers = 0.74; Chains = 3.82
CP Read Xfers = 0.86; Chains = 2.48


(256 x (3.7 x 4.096)) + (0.74 x (3.82 x 4.096)) + (0.86 x (2.48 x 4.096))
Gives the output per disk then multiply by 16 data disks
= 62,400 KBps or 62 MB/s*


sqlio v1.5.SG
throughput metrics:
IOs/sec: 6837.39                               NB: System
MBs/sec: 53.41*                                was not idle
                                               during the test


Insert filename here                                        Date of presentation   43
Calculating Worse Case Data Rate


16x data disks @ 220 IOPS = 3,520 IOPS
Each IOPS @ 4.096KB/s
3,520 x 4.096 = 14,418 KBps or 14 MB/s


A conservative numbers have been used for the IOPS and no estimate
  of ‘cache/chaining advantage’ has been made. Performance can
  only be higher if nothing has failed on the system.




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Case Study: Observed Results


System                                     Random Read             Random Write
Single FAS3070                             IOs/sec 6,068           IOs/sec 10,221
1 Aggregate with 41 disks                  MBs/sec 47.40           MBs/sec 79.85

1 Test data file                           Avg_Lat.(ms) 10         Avg_Lat.(ms) 5

                       The IOPs and MB/s figures have been combined for the two files
Single FAS3070                             IOs/sec 9,128           IOs/sec 9,293
1 Aggregate with 41 disks                  MBs/sec 71.3            MBs/sec 72.6

2 Test data files                          Avg_Lat.(ms) 13         Avg_Lat.(ms)12.5

Active / Active FAS3070                    IOs/sec 9,192           IOs/sec 19,629
Software Ownership                         MBs/sec 71.81           MBs/sec 153.35

One Aggregate of 19 & 21 disk              Avg_Lat.(ms) 12.5       Avg_Lat.(ms) 5.5



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SQL IOPs Types


 Sequential writes to Transaction Logs
 Random reads from the Data Files




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A Week of Live Data




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Production System


Once the new SQL server entered production the applications
 team began reporting performance issues which they believed
 to be caused by the storage.


The previous slide showed the typical performance and
 throughput, which did not look like a storage bottleneck. This
 issue was resolved with another tool.




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SQL Server 2005 Waits and Queues




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Getting Help


NetApp Forums and Communities sites

         https://forums.netapp.com       http://communities.netapp.com




Support forum:                        General User Community:
Months live: 8                        Months live: 13
Membership: 13,715                    Membership: 16,800
average # replies per post: 4.46      Avge 2-4 replies per thread
% threads marked as answered: 35.10   Avge of 50K visits per month
                                      162+ countries represented




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Q&A


Sorry time limit with 2nd presentation due


                               Again the forums are a great asset




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