frits hoogland - oracle usergroup norway 2013 exadata … · exadata and oltp frits hoogland -...

EXADATA AND OLTPFrits Hoogland - Oracle Usergroup Norway 2013

Thursday, April 18, 13

Who am I?• Frits Hoogland

– Working with Oracle products since 1996

• Blog: http://fritshoogland.wordpress.com• Twitter: @fritshoogland• Email: [email protected]• Oracle ACE Director• OakTable Member

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Note!!

• This presentation has been made benchmarking an older version of the Oracle appliances.

• The versions are explicitly stated.

• The message of the presentation doesn’t change!

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What is Exadata?• Engineered system specifically for oracle database.• Ability to reach high number of read IOPS and huge

bandwidth.• Has it’s own patchbundles.• Validated versions and patch versions across database,

clusterware, o/s and storage, firmware.• Dedicated, private storage for databases.• ASM.• Recent hardware & recent CPU.• No virtualisation.

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Exadata versions• Oracle database 64 bit version >= 11 (.2)

• ASM 64 bit version >= 11 (.2)– Exadata communication is using in skgxp code

• Linux OL5 x64– No UEK kernel used (except X2-8)‣Update! Exadata 11.2.3.2.0 uses

› 2.6.32-400.1.1.el5uek

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Exadata hardware• Intel Xeon server hardware

• Infiniband 40Gb/s

• Oracle cell (storage) server– Flash to mimic SAN cache– High performance disks or high capacity disks‣ 600GB 15k RPM / ~ 5ms latency‣ 2/3TB 7.2k RPM / ~ 8ms latency

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Flash• Flashcards are in every storage server

– Total of 384GB per storage server*

• Do not confuse exadata STORAGE server flashcache with oracle database flashcache!

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Flash• Flash can be configured either as cache or as

diskgroup or both.– cache: flashlog, flashcache*

• When flash is used as diskgroup latency is ~ 1 ms– Faster than disk– My guess was < 400µs‣ 1µs infiniband‣ 200µs flash IO time‣ some time for storage server

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Flash• Flash is restricted* to 4x96GB = 384GB per storage server.

– Totals: – Q:1152GB, H:2688GB, F:5376GB

• Net (ASM Normal redundancy): – Q: 576GB, H:1344GB, F:2688GB

• That is a very limited amount of storage.

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Exadata specific features• The secret sauce of exadata: the storage server

– smartscan

– storage indexes

– EHCC *

– IO Resource manager

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OLTP• How does OLTP look like (in general | simplistic)

– Fetch small amount of data‣ Invoice numbers, client id, product id‣ select single values or small ranges via index

– Create or update rows‣ Sold items on invoice, payments, order status‣ insert or update values

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• A great way to mimic or measure OLTP performance is

SLOB

– Silly Little Oracle Benchmark

– Author: Kevin Closson

http://oaktable.net/articles/slob-silly-little-oracle-benchmark

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SLOBIt can do reading:FOR i IN 1..5000 LOOP v_r := dbms_random.value(257, 10000) ; SELECT COUNT(c2) into x FROM cf1 where custid > v_r - 256 AND custid < v_r;END LOOP;

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SLOBAnd writing:FOR i IN 1..500 LOOP v_r := dbms_random.value(257, 10000) ; UPDATE cf1 set c2 = 'AAAAAAAABBBBBBBBAAAAAAAABBBBBBBBAAAAAAAABBBBBBBBAAAAAAAABBBBBBBBAAAAAAAABBBBBBBBAAAAAAAABBBBBBBBAAAAAAAABBBBBBBBAAAAAAAABBBBBBBB', ....up to column 20 (c20).... where custid > v_r - 256 AND custid < v_r; COMMIT;END LOOP;

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SLOB• Lets run SLOB with 0 writers and 1 reader at:• Single instance database, 10G SGA, 9G cache.

>> Cold cache <<

• Exadata V2 / Oracle 11.2.0.2 / HP – Half rack / 7 storage servers / 84 disks (15k rpm)

• Exadata X2 / Oracle 11.2.0.2 / HC – Quarter rack / 3 storage servers / 36 disks (7.2k rpm)

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SLOB - 1 reader

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0

2.5

5.0

7.5

10.0

V2 / Half rack X2 / Quarter rack -00

5.0

Response time


SLOB - 1 reader

17

0

2.5

5.0

7.5

10.0

V2 / Half rack X2 / Quarter rack -0

4.0

5.0

Response time


SLOB - 1 reader

18

0

2.5

5.0

7.5

10.0

V2 / Half rack X2 / Quarter rack ODA0

4.0

5.0

Response time


SLOB - 1 reader

19

0

2.5

5.0

7.5

10.0

V2 / Half rack X2 / Quarter rack ODA

4.04.0

5.0

Response time


SLOB - 1 reader

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• V2 time: 5 sec - CPU: 84.3%– PIO: 10’768 (0.8%) -- IO time 0.8 sec– LIO: 1’299’493

• X2 time: 4 sec - CPU: 75.7%– PIO: 10’922 (0.8%) -- IO time 0.9 sec– LIO: 1’300’726

• ODA tm: 4 sec - CPU: 55.2% (20 disks 15k rpm)– PIO: 10’542 (0.8%) -- IO time 2.2 sec– LIO: 1’297’502


SLOB - 1 reader - conclusion• The time spend on PIO is 15% - 45%

• Majority of time spend on LIO/CPU time

• Because main portion is CPU, fastest CPU “wins”– Actually: fastest CPU, memory bus and memory.

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SLOB - 1 reader - LIO• Let’s do a pre-warmed cache run

– Pre-warmed means: no PIO, data already in BC

– This means ONLY LIO speed is measured

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SLOB - 1 reader - LIO• ODA: 1 sec

• X2: 2 sec

• V2: 3 sec

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SLOB - 1 reader - LIO• Reason: LIO essentially means

– Reading memory– CPU processing

Use ‘dmidecode’ to look to the system’s components!

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• V2– Intel Xeon E5540 @ 2.53GHz (2s8c16t)– L1:128kB, L2:1MB, L3:8MB– Memory: Type DDR3, speed 800 Mhz

• X2:– Intel Xeon X5670 @ 2.93GHz (2s12c24t)– L1:384kB, L2:1.5MB, L3:12MB– Memory: Type DDR3, speed 1333 Mhz

• ODA– Intel Xeon X5675 @ 3.07GHz (2s12c24t)– L1:384kB, L2:1.5MB, L3:12MB– Memory: Type DDR3, speed 1333 Mhz

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SLOB - LIO - multiple readers• Let’s take the 1 reader figures, and scale up.

• What would ODA, Exadata V2 and Exadata X2 do?

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SLOB - LIO - multiple readers

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0

7.5

15.0

22.5

30.0

1 10 20 30 40 50 60 70 80

LIO read response time

oda x2 v2



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0

7.5

15.0

22.5

30.0

1 10 20 30 40 50 60 70 80


oda x2 v2



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0

7.5

15.0

22.5

30.0

1 10 20 30 40 50 60 70 80


oda x2 v2



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0

7.5

15.0

22.5

30.0

1 10 20 30 40 50 60 70 80


oda x2 v2



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0

7.5

15.0

22.5

30.0

1 10 20 30 40 50 60 70 80


oda x2 v2

Core difference and slower memory shows when # readers exceeds core count.



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7.5

15.0

22.5

30.0

1 10 20 30 40 50 60 70 80


oda x2 v2

Core difference and slower memory shows when # readers exceeds core count.

Same memory speed: CPU speed matters less with more concurrency.



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0

7.5

15.0

22.5

30.0

1 10 20 30 40 50 60 70 80


oda x2 v2



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0

7.5

15.0

22.5

30.0

1 10 20 30 40 50 60 70 80


oda x2 v2

Lesser core’s and slower memory make LIO processing increasingly slower with more concurrency



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0

7.5

15.0

22.5

30.0

1 10 20 30 40 50 60 70 80


oda x2 v2

Lesser core’s and slower memory make LIO processing increasingly slower with more concurrency

For LIO processing ODA (non-Exadata) and Exadata does not matter.



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• Conclusion:

– LIO performance is impacted by:

‣CPU speed‣Number of sockets and core’s‣ L1/2/3 cache sizes‣Memory speed

– Exadata does not matter here!


SLOB - LIO - multiple readers• When comparing entirely different systems also

consider:

– Oracle version – O/S and version (scheduling)– Hyper threading / CPU architecture– NUMA (Exadata/ODA: no NUMA!)

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SLOB - PIO - 1 reader• But how about physical IO?

– Lower the buffercache to 4M – sga_max_size to 1g– cpu_count to 1– db_cache_size to 1M (results in 4M)

• Slob run with 1 reader

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SLOB - PIO - 1 reader

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0

28

55

83

110

1 10 20 30 40 50 60 70 80

PIO reader response time

oda x2 v2



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0

28

55

83

110

1 10 20 30 40 50 60 70 80


oda x2 v2

Surprise! ODA is the fastest here with 73 seconds.



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0

28

55

83

110

1 10 20 30 40 50 60 70 80


oda x2 v2


The X2 is only a little slower with 76 seconds.



35

0

28

55

83

110

1 10 20 30 40 50 60 70 80


oda x2 v2


The X2 is only a little slower with 76 seconds.

The V2 is the slowest with 106 seconds.



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Total time (s) CPU time (s) IO time (s)

ODA 73 17 60

X2 76 33 55

V2 106 52 52

• IO ODA:– 60/1264355= 0.047 ms

• IO X2:– 55/1265602= 0.043 ms

• IO V2:– 52/1240941= 0.042 ms


SLOB - PIO - 1 reader• This is not random disk IO!

– Average latency of random IO 15k rpm disk ~ 5ms– Average latency of random IO 7.2k rpm disk ~ 8ms

• So this must come from a cache or is not random disk IO– Exadata has flashcache.– On ODA, data probably very nearby on disk.

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• Exadata IO takes (way) more CPU. • Roughly the same time is spend on doing IO’s.

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ODA 73 17 60

X2 76 33 55

V2 106 52 52


10 readers

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SLOB - PIO - 10 readers

40

0

1000

2000

3000

4000

1 10 20 30 40 50 60 70 80


oda x2 v2



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1000

2000

3000

4000

1 10 20 30 40 50 60 70 80


oda x2 v2

Now IO responsetime on ODA is way higher than Exadata (3008s)



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1000

2000

3000

4000

1 10 20 30 40 50 60 70 80


oda x2 v2

Now IO responsetime on ODA is way higher than Exadata (3008s)

Both Exadata’s perform alike: X2 581s, V2 588s.



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ODA 3008 600 29428

X2 581 848 5213

V2 588 1388 4866

• IO ODA:– 29428/13879603 = 2.120 ms

• IO X2:– 5213/14045812 = 0.371 ms

• IO V2:– 4866/14170303 = 0.343 ms


20 readers

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0

1250

2500

3750

5000

1 10 20 30 40 50 60 70 80


oda x2 v2



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• IO ODA:– 88756/28246604 =0.003142183039 = 3.142 ms

• IO X2:– 13010/28789330=0.0004519035351 = 0.452 ms

• IO V2:– 12405/28766804=0.0004312262148 = 0.431 ms


ODA 4503 1377 88756

X2 721 2069 13010

V2 747 3373 12405



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0

1500

3000

4500

6000

1 10 20 30 40 50 60 70 80


oda x2 v2



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4500

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1 10 20 30 40 50 60 70 80


oda x2 v2

ODA (20 x 15krpm HDD) disk capacity is saturated so response time increases with more readers.



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0

1500

3000

4500

6000

1 10 20 30 40 50 60 70 80


oda x2 v2

ODA (20 x 15krpm HDD) disk capacity is saturated so response time increases with more readers.

Flashcache is not saturated, so response time of IO of 10-20-30 readers increases very little.


...up to 80 readers

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2500

5000

7500

10000

1 10 20 30 40 50 60 70 80


oda x2 v2



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2500

5000

7500

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oda x2 v2

ODA response time more or less increases linear.



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0

2500

5000

7500

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1 10 20 30 40 50 60 70 80


oda x2 v2


X2 flashcache (3x96GB) is not saturated, so little increase in response time.



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0

2500

5000

7500

10000

1 10 20 30 40 50 60 70 80


oda x2 v2


X2 flashcache (3x96GB) is not saturated, so little increase in response time.

The V2 response time (with more flashcache!) starts increasing at 70 readers. A bottleneck is showing up! (7x96GB!!)



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0

37500

75000

112500

150000

1 10 20 30 40 50 60 70 80

PIO readers IOPS

oda x2 v2

IOPS view instead of responsetime



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0

37500

75000

112500

150000

1 10 20 30 40 50 60 70 80

PIO readers IOPS

oda x2 v2


3x96GB Flashcache and IB can serve > 115’851 read IOPS!



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0

37500

75000

112500

150000

1 10 20 30 40 50 60 70 80

PIO readers IOPS

oda x2 v2



This V2 has more flashcache, so decline in read IOPS probably due to something else!



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0

37500

75000

112500

150000

1 10 20 30 40 50 60 70 80

PIO readers IOPS

oda x2 v2



This V2 has more flashcache, so decline in read IOPS probably due to something else!

ODA maxed out at ~ 11’200 read IOPS



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V2 top 5 timed events with 80 readers:Event Waits Time(s) (ms) time Wait Class------------------------------ ------------ ----------- ------ ------ ----------cell single block physical rea 102,345,354 56,614 1 47.1 User I/Olatch: cache buffers lru chain 27,187,317 33,471 1 27.8 Otherlatch: cache buffers chains 14,736,819 19,594 1 16.3 ConcurrencDB CPU 13,427 11.2wait list latch free 932,930 553 1 .5 Other

X2 top 5 timed events with 80 readers:Event Waits Time(s) (ms) time Wait Class------------------------------ ------------ ----------- ------ ------ ----------cell single block physical rea 102,899,953 68,209 1 87.9 User I/ODB CPU 9,297 12.0latch: cache buffers lru chain 10,917,303 1,585 0 2.0 Otherlatch: cache buffers chains 2,048,395 698 0 .9 Concurrenccell list of blocks physical r 368,795 522 1 .7 User I/O



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44.1%



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44.1%

2.9%


SLOB - PIO - 80 readers• On the V2, cache concurrency control throttles throughput• On the X2, this happens only very minimal- V2: CPU: Intel Xeon E5540 @ 2.53GHz (2s8c16t)- X2: CPU: Intel Xeon X5670 @ 2.93GHz (2s12c24t)

V2Event Waits <1ms <2ms <4ms <8ms <16ms <32ms <=1s >1s-------------------------- ----- ----- ----- ----- ----- ----- ----- ----- -----latch: cache buffers chain 14.7M 44.1 37.0 16.3 2.6 .0 .0latch: cache buffers lru c 27.2M 37.2 42.6 20.0 .2 .0 .0

X2latch: cache buffers chain 2048. 91.8 7.5 .6 .0 .0latch: cache buffers lru c 10.9M 97.4 2.3 .2 .0

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SLOB - Read IO

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1 LIO 80 LIO 1 PIO 80 PIO

ODA 1 11 73 9795

X2 (HC disks) 2 11 76 976

V2 (HP disks) 3 22 106 1518


SLOB - Read IO

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1 LIO 80 LIO 1 PIO 80 PIO

ODA 1 11 73 9795

X2 (HC disks) 2 11 76 976

V2 (HP disks) 3 22 106 1518

1 PIO w/o flashcache 80 PIO w/o flashcache

ODA 73 9795

X2 167 ? (> 18000)

V2 118 5098


SLOB - Read IO• For scalability, OLTP needs buffered IO (LIO)

• Flashcache is EXTREMELY important physial IO scalability

• Probably should not let flash be used for something else– Unless you can always keep all your small reads in

cache

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SLOB - Read IO• Flashcache mimics a SAN/NAS cache

– So nothing groundbreaking here, it does what current, normal infra should do too...

– The bandwidth needed to deliver the data to the database is provided by Infiniband

– 1 Gb ethernet = 120MB/s, 4 Gb fiber = 400MB/s

• Infiniband is generally available outside of Oracle

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SLOB - Read IO• How much IOPS can a single cell do?

– According to https://blogs.oracle.com/mrbenchmark/entry/inside_the_sun_oracle_database

– A single cell can do 75’000 IOPS from flash (8kB)‣ Personal calculation: 60’000 IOPS with 8kB

• Flashcache cache– Caches small reads* (8kB and less) mostly– Large multiblock reads are not cached, unless

segment property ‘cell_flash_cache’ is set to ‘keep’.

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https://blogs.oracle.com/mrbenchmark/entry/inside_the_sun_oracle_database




SLOB - Read IO• Is Exadata a good idea for OLTP?

– From a strictly technical point of view, there is no benefit.

• But...– Exadata gives you IORM– Exadata gives you reasonably up to date hardware– Exadata gives a system engineered for performance– Exadata gives you dedicated disks – Exadata gives a validated combination of database,

clusterware, operating system, hardware, firmware.

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Writing and Exadata• Exadata storage servers provide NO redundancy for data

– That’s a function of ASM

• Exadata is configured with either– Normal redundancy (mirroring) or– High redundancy (triple mirroring)

• to provide data redundancy.

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Writing and Exadata• Reading has no problem with normal/high redundancy.

• During writes, all two or three AU’s need to be written.

• This means when you calculate write throughput, you need to double all physical writes if using normal redundancy.

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Writing on Exadata• But we got flash! Right?

• Yes, you got flash. – But it probably doesn’t do what you think it does:

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Writing on ExadataThis is on the half rack V2 HP:

[oracle@dm01db01 [] stuff]$ dcli -l celladmin -g cell_group cellcli -e "list metriccurrent where name like \'FL_.*_FIRST\'"dm01cel01: FL_DISK_FIRST FLASHLOG 316,563 IO requestsdm01cel01: FL_FLASH_FIRST FLASHLOG 9,143 IO requestsdm01cel02: FL_DISK_FIRST FLASHLOG 305,891 IO requestsdm01cel02: FL_FLASH_FIRST FLASHLOG 7,435 IO requestsdm01cel03: FL_DISK_FIRST FLASHLOG 307,634 IO requestsdm01cel03: FL_FLASH_FIRST FLASHLOG 10,577 IO requestsdm01cel04: FL_DISK_FIRST FLASHLOG 299,547 IO requestsdm01cel04: FL_FLASH_FIRST FLASHLOG 10,381 IO requestsdm01cel05: FL_DISK_FIRST FLASHLOG 311,978 IO requestsdm01cel05: FL_FLASH_FIRST FLASHLOG 10,888 IO requestsdm01cel06: FL_DISK_FIRST FLASHLOG 315,084 IO requestsdm01cel06: FL_FLASH_FIRST FLASHLOG 10,022 IO requestsdm01cel07: FL_DISK_FIRST FLASHLOG 323,454 IO requestsdm01cel07: FL_FLASH_FIRST FLASHLOG 8,807 IO requests

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Writing on ExadataThis is on the quarter rack X2 HC:[root@xxxxdb01 ~]# dcli -l root -g cell_group cellcli -e "list metriccurrent where name like \'FL_.*_FIRST\'"xxxxcel01: FL_DISK_FIRST FLASHLOG 68,475,141 IO requestsxxxxcel01: FL_FLASH_FIRST FLASHLOG 9,109,142 IO requestsxxxxcel02: FL_DISK_FIRST FLASHLOG 68,640,951 IO requestsxxxxcel02: FL_FLASH_FIRST FLASHLOG 9,229,226 IO requestsxxxxcel03: FL_DISK_FIRST FLASHLOG 68,388,238 IO requestsxxxxcel03: FL_FLASH_FIRST FLASHLOG 9,072,660 IO requests

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Writing on Exadata• Please mind these are cumulative numbers!

• The half-rack is a POC machine, no heavy usage between POC’s.

• The quarter-rack has had some load, but definately not heavy OLTP.

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Writing on Exadata• I can imagine flashlog can prevent long write times if

disk IO’s queue.– A normal configured database on Exadata has online

redo in DATA and in RECO diskgroup– Normal redundancy means every log write must be

done 4 times

• Log writer wait times:– V2 min: 16ms (1 writer), max: 41ms (20 writers)– X2 min: 39ms (10 writers), max: 110ms (40 writers)

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Writing on Exadata: conclusion• Log file write response time on Exadata is not in the

same range as reads.

• There’s the flashlog feature, but it might work different than the whitepaper explains

• Be careful with heavy writing on Exadata. – There’s no Exadata specific improvement for writes*.

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Thank you for attending!

Questions?

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Thanks, Links, etc.• VX Company• Klaas-Jan Jongsma• Martin Bach• Kevin Closson

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frits hoogland - oracle usergroup norway 2013 exadata … · exadata and oltp frits hoogland -...

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