9/26/2013 How to Minimize and Optimize I/Os in your RPG Application Data3/IBM COMMON Sweden Stockholm, Sweden September 30th to October 1th 2013 Gottfried Schimunek Senior Architect Application Design IBM STG Software Development Lab Services 3605 Highway 52 North Rochester, MN 55901 Tel 507-253-2367 Fax 845-491-2347 [email protected] IBM ISV Enablement Follow us @IBMpowersystems Learn more at www.ibm.com/power Agenda Disk I/O definitions and concepts Disk I/O configuration/settings related to performance High-level description of common disk IO performance symptoms Common disk I/O related performance problems Review common disk I/O problems with performance tools Case Studies Quiz ( 3 or 4 questions) 2 © 2013 IBM Corporation 1 9/26/2013 IO Subsystem Definitions and Concepts Page Faults - Faulting occurs when a referenced page, or piece of data, is not in memory. This causes programs to stop because they must wait for the data to be paged in. Faulting is normal behavior on IBM i. However, the size of the storage pools can affect the faulting rates, and storage pools that are too small can result in excessive faulting. You can examine and set the storage pool sizes by using the Work with System Status (WRKSYSSTS) command. If you have too many active threads or threads that use too many system resources, you will see numerous page faults for the storage pools in which applications are running. Increasing the storage pool size or decreasing the activity level might reduce the number of page faults. IO Pending Faults – Waiting for a fault that is currently in progress from another job. Synchronous IO versus asynchronous IO Synchronous IO requests require the jobs to wait for the IO operation to complete before the job can continue to process. Asynchronous IO’s are background IO operations that occur while the jobs is processing records, but can be converted to synchronous if IO bottlenecks occur. Paging - Paging is the movement of data in and out of memory, both synchronously and asynchronously. Pages can be written out to storage or removed from memory without being written if they have not been changed. Faulting causes paging to occur on the server. Write cache - When a disk write operation is requested, the data is written to a memory buffer and is queued to be written out to a disk device at a later time (this later operation is called destaging). After a buffer is queued, disk operation completion is signaled. As far as the waiting application is concerned, the write operation is over. Of course, data is not on a disk surface yet, so what happens if a system loses power before destaging is complete? In this situation, a write cache is protected by an independent source of power, a battery, which keeps write cache contents intact until power is restored and data can be evacuated to its proper place on a disk surface. This is called non-volatile storage (NVS). Write cache overruns - A write cache absorbs the disk write activity until physical disk device is overwhelmed to the point where the destaging operation queue backs up and there is no more memory left in a buffer pool to accept new write operations from system. Now new disk operations have to wait until some earlier operations are complete and free some memory. This is called a write cache overrun. Write cache efficiency - As data is sitting in the write cache waiting to be destaged to the disk, cache management logic tries to apply all kinds of optimizations to reduce the actual number of disk accesses. For example, a series of writes to the adjacent sectors can be coalesced into a single multi-sector operation. Multiple writes to the same sector may result in multiple updates to the data in cache, before data is ever written out. The purpose of the write cache efficiency ratio metric is to show how successful the cache software was at this task. For example, if write cache efficiency is 15%, it means that the number of write operations was reduced by 15% by the cache management software. This metric is only defined for internal disk units and is calculated as: 100 - ((DSDWOP/DIVISOR) * 100) / DSWRTS DIVISOR depends on the disk configuration. It is 1 in non-RAID configurations, 2 for RAID 5, and 3 for RAID 6. It reflects the additional disk writes that result from the RAID. In general, this metric is more important to the storage adapter cache management software designers. But it can also give an insight into workload behavior. One has to be very careful with this metric. If RAID © longer 2013 IBM Corporation 3 configuration is in the exposed mode due to a single disk failure, the number of physical disk writes will no correspond to the assumptions and this metric will no longer be valid. IO Subsystem Technical Definition and Concepts Extended adaptive cache - Extended Adaptive Cache is an advanced read cache technology that improves both the I/O subsystem and system response times by reducing the number of physical I/O requests that are read from disk. Extended Adaptive Cache operates at the disk subsystem controller level, and does not affect the AS/400 system processor. Management of the cache is performed automatically within the I/O adapter. It is designed to cache data by using a predictive algorithm. The algorithm considers how recently and how frequently the host has accessed a predetermined range of data. Physical Disk IO - the traffic toward the storage subsystem Logical DB IO - the IO request which retrieve records from memory through the open data path (ODP) to the program object. If the requested data is not to be found in memory, it generates a physical I/O and the system fetches it from the disks. Disk service times – the time required for the disk IO subsystem to performance the IO request with no waits. Expert cache - Expert cache is a set of algorithms the operating system uses to maximize the efficiency of the cache and main storage usage, as workloads change over the course of a typical day. By caching in main storage, the system not only eliminates accesses to the storage devices, but all associated I/O traffic on the internal system buses as well. In addition, an algorithm running in the main processor has a better view of actual application trends and should do a better job, overall, of assessing what data should be cached. Expert Cache works by minimizing the effect of synchronous DASD I/Os on a job. The best candidates for performance improvement are those jobs that are most affected by synchronous DASD I/Os. Internal Arms SAS Arms Solid State Drives (SSD) External Arms LUN’s Fiber Channels Independent Auxiliary Storage Pools (IASP) -Independent disk pools provide the ability to group together storage that can be taken off-line or brought online independent of system data or other unrelated data. An independent disk pool can be either: Privately connected to a single system. Also known as stand-alone or primary IASPs Switched among multiple systems or partitions in a clustered environment Virtual IO 4 © 2013 IBM Corporation 2 9/26/2013 Disk I/O requests Faults: Demand paging: Implicit memory request - Referenced instruction/data (virtual address) NOT in memory - Either DB or NDB Fault: Generally re-read of data that was subject of earlier BRING Fault I/O size - Page= 4 KB - Block= 32 KB (Java up to 64KB) Bring: Anticipatory paging (not counted as a fault) - Transfer objects to main storage For example: program "CALL" or blocks of DB records Initial physical DB input via "BRING" SETOBJACC of entire object - Bring I/O size: Bring: Explicitly reads virtual pages in to memory and improves perfomance by anticipation! Clear: Memory cleared - set to binary=0 – particularly when current content not valid. Exchange: Implictly identifies pages whose contents are blocking/"Sequential Only" replaced without "aging algorithm"! Purge: Memory pages written to disk – for example. journal pages. - 4 KB default, 128 KB optimum More with DB - SQL statement establish size 5 © 2013 IBM Corporation Disk Subsystems Collection Services records disk I/O Information QAPMDISK Performance Database file Write Request Read Request A. CPU A. Synchronous or asynchronous requests for pages in main storage to be written A. Can it be held in IOA cache? A. Else physical write May reference virtual addresses not in main storage DISK Controller A. Is it in the IOA cache? Cache DISK DRIVES A. 6 Else physical read © 2013 IBM Corporation 3 9/26/2013 Disk operations Categorized by Main Storage Management - Database I/O Physical or logical file I/O - Non-database I/O Disk I/O not related to physical or logical file I/O Categorized by concurrency with processing - Synchronous I/O Processing waits: Does not continue until I/O completes Some database I/O Servicing memory faults Contributes response/run - Asynchronous I/O Processing concurrent with I/O WRITE typically asynchronous FORCE operations, SEQONLY(*YES) DB input Disk I/O DB I/O Non-DBwithout) I/O Journal deposits with commitment control (synchronous Synchronous Read Write Asynchronous Synchronous Read Read Write 7 Asynchronous Write Read Write © 2013 IBM Corporation Asynchronous I/O wait DISK I/O REQUEST ISSUED Data becomes available to job JOB NEEDS THE DATA FROM THE I/O REQUEST OVERLAPPED: Job Processing & Disk I/O JOB PROCESSING Time REQUEST SCHEDULED DISK REQUEST PROCESSING Start DISK I/O REQUEST ISSUED Finish JOB NEEDS THE DATA FROM THE I/O REQUEST OVERLAPPED JOB Processing & Disk I/O Data becomes Available to job Asynchronous Disk I/O Wait Time JOB PROCESSING Time REQUEST SCHEDULED DISK REQUEST PROCESSING Star t Finish WHY DOES THIS HAPPEN? 1 FASTER CPU/LESS CPU CONTENTION 2 SLOWER DISK RESPONSE 3 Improved Code (Job uses less CPU) TOTAL RUN TIME IMPROVEMENT FROM A CHANGE CAN BE LESS THAN EXPECTED A Faster CPU may not help as much as expected! 8 © 2013 IBM Corporation 4 9/26/2013 Logical DB I/O versus physical disk I/O (1) Application program performs a READ operation (2) Data in the job work area (ODP)? - Data is moved into the program variables No logical DB I/O No physical I/O (3) Data in the partition buffer? - Moved to job work area/program variables Logical DB I/O No physical I/O (4) Data not in partition buffer? - Data read from disk subsystem - Data moved to job work area - Data is moved to program variables Logical DB I/O Physical I/O PROGRAM-A 1 JOB WORK AREAS Pgm Variables 2 ODP 3 LDIO PARTITION BUFFER 4 PDIO IOP/IOA Disk 9 © 2013 IBM Corporation Impact of queuing on response time Service time * Queuing Multiplier = Response time S*QM = T QM=1/(1-U) U= Utilization 10 Service Time (secs) S Queuing Multiplier QM Resp Time (secs) T 0.005 3 0.015 0.010 3 0.030 0.050 3 0.150 0.100 3 0.300 © 2013 IBM Corporation 5 9/26/2013 Disk storage allocation Space assignment to object usually follows space availability Example: Drive #1 is 15% full Drive #2 is 50% full System will favor allocating space on drive #1 Disk accesses usually follow space usage Example: Following from disk allocation method: Drive #1 ( 70 GB) - 50% full Drive #2 (140 GB) - 50% full Busy = operations per second 140 GB drive may be ~2 times busier 140 GB Following more data 50% of 140 GB (70 GB) versus 50% of 70 GB (35 GB) 70 GB 50% 11 50% © 2013 IBM Corporation “Mixed” drives Consider three drives Mixing drives of different capacities in the same ASP with insufficient Similar physical attributes write cache may cause performance problems. Rotational Delay, Seek time, etc. Service time = 5 milliseconds Assume even distribution of data/no cache benefits Disk service time = 5 milliseconds 35 GB drive half as busy (20%) as 70 GB drive (40%) 70 GB drive half as busy (40%) as 140 GB drive (80%) 35 GB drive: QM= 1 / (1-0.20) = 1 /0.80 = 1.25 35 GB drive averages (1.25 x 5 msecs) = 6.25 milliseconds/operation 70 GB drive: QM= 1 / (1-0.40) = 1 / 0.60 = 1.66 70 GB drive averages (1.66 x 5 msecs) = 8.33 milliseconds/operation 140 GB drive: QM= 1 / (1-0.80) = 1 / 0.20 = 5.00 140 GB drive averages (5.00 x 5 msecs) = 25.00 milliseconds/operation 12 © 2013 IBM Corporation 6 9/26/2013 Balancing disk Restore objects Spreads large objects over all arms in an ASP 1 MB extents Rebalance disk - Trace ASP Balance (TRCASPBAL) command Monitors data access on disk units within the specified ASP High-use data/ Low-use data on the units is identified Statistics collected for ASP may be used to balance disk drives - Start ASP Balance (STRASPBAL) command Performs ASP balancing on one or more ASPs Capacity balancing Data balance based on percentage disk space used Usage balancing (*USAGE) Requires high-use/low-use data from TRCASPBAL Attempts to balance arm utilization within ASP Balancing soon after collection of statistics Usefulness diminished with aging statistics 13 © 2013 IBM Corporation Example: Disk response imbalance Unit Size IOP Unit Name Type (M) Util ------------- ---- ------- ---ASP ID/ASP Rsc Name: 1/ 0001 DD013 4328 132,309 .0 0002 DD016 4328 132,309 .0 0003 DD004 4328 132,309 .0 0004 DD015 4328 132,309 .0 0005 DD012 4328 132,309 .0 0006 DD007 4328 132,309 .0 0007 DD002 4328 132,309 .0 0008 DD006 4328 132,309 .0 0009 DD020 4328 123,488 .0 0010 DD003 4328 123,488 .0 0011 DD018 4328 132,309 .0 0012 DD019 4328 123,488 .0 0013 DD010 4328 123,488 .0 0014 DD022 4328 132,309 .0 0015 DD024 4328 132,309 .0 0016 DD005 4328 132,309 .0 0017 DD008 4328 132,309 .0 0018 DD001 4328 132,309 .0 0019 DD021 4328 132,309 .0 0020 DD014 4328 132,309 .0 0021 DD023 4328 123,488 .0 0022 DD017 4328 123,488 .0 0023 DD011 4328 123,488 .0 0024 DD009 4328 123,488 .0 0025 DD049 4328 123,488 .0 0026 DD050 4328 123,488 .0 0027 DD051 4328 123,488 .0 0028 DD052 4328 123,488 .0 0029 DD053 4328 123,488 .0 0030 DD054 4328 123,488 .0 0031 DD055 4328 123,488 .0 0032 DD056 4328 105,847 .0 0033 DD057 4328 105,847 .0 0034 DD058 4328 105,847 .0 0035 DD059 4328 123,488 .0 0036 DD060 4328 105,847 .0 Total for ASP ID: 1 4,516,140 Average Total 4,516,140 Average 14 IOP Dsk CPU --Percent-- Op Per K Per Name Util Full Util Second I/O ---------- ------- ------- -------- --------CMB01 CMB01 CMB01 CMB01 CMB01 CMB01 CMB01 CMB01 CMB01 CMB01 CMB01 CMB01 CMB01 CMB01 CMB01 CMB01 CMB01 CMB01 CMB01 CMB01 CMB01 CMB01 CMB01 CMB01 CMB10 CMB10 CMB10 CMB10 CMB10 CMB10 CMB10 CMB10 CMB10 CMB10 CMB10 CMB10 5.2 5.2 5.2 5.2 5.2 5.2 5.2 5.2 5.1 5.1 5.2 5.2 5.2 5.2 5.2 5.1 5.2 5.2 5.2 5.1 5.2 5.1 5.2 5.2 15.8 15.8 15.8 15.7 15.7 15.8 15.8 15.7 15.8 15.7 15.8 15.8 - Average Time Per I/O -Service Wait Response ------- ------ -------- 41.8 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 2.0 3.0 3.4 2.7 2.6 2.6 3.1 2.5 2.6 2.4 3.0 2.4 2.5 2.5 2.7 2.9 2.8 2.3 3.1 2.8 2.6 2.6 3.2 2.7 31.3 32.3 34.8 32.3 33.6 30.3 37.8 36.9 34.9 44.3 29.3 41.2 15.69 24.72 32.19 29.40 27.05 22.36 42.75 20.75 21.21 21.23 29.58 19.30 19.98 22.44 24.16 26.06 27.46 17.43 23.66 21.20 24.20 21.06 39.51 24.00 99.97 101.86 105.69 99.71 118.01 110.91 99.21 109.57 101.89 113.90 118.92 110.55 5.9 23.2 22.2 14.7 17.9 21.0 10.7 20.8 23.6 20.5 18.3 22.9 24.4 20.3 19.2 20.2 17.5 22.2 25.9 24.4 20.6 25.1 13.9 20.8 35.6 35.9 35.7 37.2 32.5 33.5 37.0 36.2 37.4 36.1 31.6 37.5 .0012 .0012 .0010 .0009 .0009 .0011 .0007 .0012 .0012 .0011 .0010 .0012 .0012 .0011 .0011 .0011 .0010 .0013 .0013 .0013 .0010 .0012 .0008 .0011 .0031 .0031 .0032 .0032 .0028 .0027 .0038 .0033 .0034 .0038 .0024 .0037 .0001 .0004 .0004 .0003 .0004 .0004 .0004 .0005 .0004 .0003 .0003 .0004 .0004 .0003 .0003 .0005 .0003 .0003 .0004 .0004 .0006 .0003 .0002 .0004 .0096 .0114 .0165 .0098 .0115 .0078 .0208 .0188 .0114 .0449 .0062 .0313 .0013 .0016 .0014 .0012 .0013 .0015 .0011 .0017 .0016 .0014 .0013 .0016 .0016 .0014 .0014 .0016 .0013 .0016 .0017 .0017 .0016 .0015 .0010 .0015 .0127 .0145 .0197 .0130 .0143 .0105 .0246 .0221 .0148 .0487 .0086 .0350 40.3 13.4 52.44 30.4 .0025 .0116 .0141 40.3 13.4 52.44 30.4 .0025 .0116 .0141 © 2013 IBM Corporation 7 9/26/2013 Reorganize physical file member First ... - Reorganize the DB file member to remove deleted records Compresses deleted records/optionally reorganizes by key - Alternatively, consider re-using deleted records Then ... SAVE the file DELETE the file RESTORE the file Space Allocation up to 1 MB File Object File Object DLTREC DLTREC DLTREC DLTREC Object DLTREC DLTREC DLTREC DLTREC Many jobs processing files sequentially have reported up to 50% improvement with deleted records removed from a physical file. Check with the application provider! 15 © 2013 IBM Corporation Solid State Drives (SSD) Today’s applications can often benefit with a faster storage option SSD high speed can really help get rid of I/O bottlenecks, bridging the gap between memory and disk speeds Improve performance And save space, energy at the same time Processors Memory Disk SSD Very, very, very, very, very fast < 10’s ns Very, very, very fast Fast ~100 ns ~200,000 ns Very, very slow comparatively 1,000,000 8,000,000 ns Access Speed 16 © 2013 IBM Corporation 8 9/26/2013 Mixed SSD + HDD Can be Great Solution It is typical for data bases to have a large percentage of data which is infrequently used (“cold”) and a small percentage of data which is frequently used (“hot”) Hot data may be only 10-20% capacity, but represent 80-90% activity SSD offers best price performance when focused on “hot” data HDD offers best storage cost, so focus it on “cold” data …. sort of a hierarchal approach Cold Hot May be able to use larger HDD and/or a larger % capacity used Can run SSD closer to 100% capacity 17 © 2013 IBM Corporation SSD Performance 8000 30000 7000 25000 6000 20000 5000 15000 4000 3000 10000 2000 5000 1000 0 0 SSD HDD Random I/O’s per second (Sustained ) 18 SSD HDD Power Consumption in Watts Required for 135K IOPS performance © 2013 IBM Corporation 9 9/26/2013 IBM i Load Balancer Monitors partition/ASP using “trace” - User turns trace on during a peak time - User turns trace off after reasonable sample time - Negligible performance impact expected - Tool monitors “reads” to identify hot data - TRCASPBAL followed by STRASPBAL TYPE(*HSM) Upon command, moves hot data to SSD, cold data to HDD Minimal performance impact, done in background Re-monitor and rebalance any time - Probably a weekly or monthly activity - Perhaps less often if data not volatile Place DB2 objects on SSD through new parameters on DB2 commands - CRTPF / CHGPF - CREATE / ALTER TABLE - CREATE INDEX 19 © 2013 IBM Corporation Where should SSD be considered? Where server performance is really important and I/O dependent Where server has a lot of HDD with low capacity utilization (or ought to have them configured this way) Where high value (from a performance perspective) can be focused in SSD Fairly small portion of total data (“hot data”) Specific indexes/tables/files/libraries of the operating system or application Best workload characteristics for SSD Lots of random reads … low percentage of sequential/predictable reads Higher percentage reads than writes Assuming a disk adapter/controller with enough write cache, SSD writes may or may not be that much faster than HDD writes Whitepaper at http://www.ibm.com/systems/resources/ssd_ibmi.pdf 20 © 2013 IBM Corporation 10 9/26/2013 SSD Analyzer Tool for IBM i • Quick, easy, no-charge analysis introduced 4Q 2009 • Looks at standard performance report output – • Provides “probably yes”, “probably no”, or “maybe” SSD ANALYSIS TOOL (ANZSSDDTA) Type choices, press Enter. PERFORMANCE MEMBER . . . . . . . LIBRARY . . . . . . . . . . . *DEFAULT__ __________ Name, *DEFAULT Name Additional Parameters REPORT TYPE . . . . . . . . TIME PERIOD:: START TIME AND DATE:: BEGINNING TIME . . . . . . BEGINNING DATE . . . . . . END TIME AND DATE:: ENDING TIME . . . . . . . ENDING DATE . . . . . . . NUMBER OF RECORDS IN REPORT F3=Exit F4=Prompt F24=More keys . . *SUMMARY *DETAIL, *SUMMARY, *BOTH . . . . *AVAIL__ *BEGIN__ Time, *AVAIL Date, *BEGIN . . . . . . *AVAIL__ *END____ 50__ Time, *AVAIL Date, *END 0 - 9999 F5=Refresh F12=Cancel Bottom F13=How to use this display Available via http://www.ibm.com/support/techdocs in “Presentations & Tools”. Search using keyword SSD. 21 © 2013 IBM Corporation Common Disk IO Performance Symptoms - Longer nightly batch runs - Intermittent response problems with IO intensive transactions - High disk utilization - High disk response time for some arms - Noticeable seize/lock conflicts due to high disk response times - High percentage full on arms - Longer save/restore and system back up times 22 © 2013 IBM Corporation 11 9/26/2013 Potential Causes Customers often assume high disk response times are caused by the lack of arms, but the following causes of disk response issues are more common The typical disk response problems are the following: Excessive page faulting - Memory pools not properly configured - Excessive amount of records being paged in the memory pools - Lack of memory Expert Cache hasn’t been turned on Small read/write cache IO adapters (IOA) Too many arms/LUN’s attached to one IOA Excessive amount of synchronous writes causing write cache overruns - Forced write ratio - Journal cache or commitment control not enabled - Lack of blocked writes Excessive amount of synchronous reads due to poor programming techniques Programs are not blocking the read requests 23 © 2013 IBM Corporation Potential Causes Arm balance issues (hot objects) - ASP balance not performed after new arms were added - Raid parity was started with a subset of arms initially configured - Different size arms configured to a specific IOA Save/Restore activity occurring during production hours External storage configuration problems • • • Insufficient number of logical units (LUN’s) configured Insufficient fiber channel configuration Insufficient amount of write cache Workload needs to be tuned to reduce unnecessary IO Workload simply too IO intensive for arm configuration Hardware errors IO Subsystem undersized 24 © 2013 IBM Corporation 12 9/26/2013 Actions/Preventions The first action is to verify all the necessary IO performance features have been enabled/installed: – Expert cache – QQRYDEGREE system value = *IO – HA Journal performance LPP The 2nd action should always be to prevent unnecessary page faulting – Page faulting for some objects may be unavoidable. These object could be faulted in quicker with solid state drives (SSD) The 3rd action is to determine when the worst disk response times occur, and which jobs and programs/SQL statements are responsible The 4th step is to determine if there are specific arms with higher response times, higher percent busy, higher operations per second, and/or higher k per I/O The 5th step is to determine if those arms with poor response times are attached to a specific IOA, and the size of the read/write cache available 25 © 2013 IBM Corporation Reviewing general IO performance via Performance tools System Report The disk utilization section of the system report with show the average service times, wait times, and response times for each arm Remember this is an average for each arm using 5-15 minute intervals for the number of intervals selected and this includes both reads and write response times The guideline for reads is 5 ms per IO or less The guideline for writes is .5 ms per IO or less Look for arms with higher response times, utilization, percentage full, ops/sec, k/IO Look to see if arms with response problems are all attached to the same IOP/IOA 26 © 2013 IBM Corporation 13 9/26/2013 Reviewing general IO performance via Performance tools Component Report Page down to disk activity section of the component report Review write cache efficiency column The write cache efficiency should be over 60% Review write cache overrun column • The write cache overruns higher then 0 are worth investigating • Review the write cache size of the IOA’s connected to the arms with poor response • Review the number of arms and the percentage full of these arms • Determine which jobs and programs are driving the high read/write volume 27 © 2013 IBM Corporation Case Study 1 – Hot Objects The following PDI graph shows the poor response times for intervals with less workload 28 © 2013 IBM Corporation 14 9/26/2013 Case Study 1 – Hot Objects PDI - Disk response times by arm 29 © 2013 IBM Corporation Case Study 1 – Hot Objects PDI Job Watcher – intervals with highest synchronous disk response times 30 © 2013 IBM Corporation 15 9/26/2013 Case Study 1 – Hot Objects PDI Job Watcher - Jobs driving the most synchronous IO 31 © 2013 IBM Corporation Case Study 1 – Hot Objects iDoctor Job Watcher – intervals with highest synchronous disk response times 32 © 2013 IBM Corporation 16 9/26/2013 Case Study 1 – Hot Objects iDoctor Job Watcher - Jobs driving the most synchronous IO 33 © 2013 IBM Corporation Case Study 1 – Hot Objects iDoctor – QSPLMAINT call stack (DLTSPLF job) 34 © 2013 IBM Corporation 17 9/26/2013 Case Study 1 – Hot Objects iDoctor – RCV_RQS call stack (DSPJRNA Command) 35 © 2013 IBM Corporation Case Study 2 – Job Watcher 36 © 2013 IBM Corporation 18 9/26/2013 Case Study 2 – Job Watcher 37 © 2013 IBM Corporation Case Study 2 – Job Watcher 38 © 2013 IBM Corporation 19 9/26/2013 Case Study 2 – Job Watcher 39 © 2013 IBM Corporation Case Study 2 – Job Watcher 40 © 2013 IBM Corporation 20 9/26/2013 Case Study 2 – Job Watcher 41 © 2013 IBM Corporation Case Study 2 At this point you know: - Which jobs are waiting - The type of contention and the length of time per interval – Disk writes - Which program is driving the writes - The type of write operations (blocked inserts - QDBPUTM) - The file being written to What you don’t know is: - Why are the writes being performed synchronously The possible causes are: - Write cache overruns - The object being written to is only on a subset of arms (hot object) - The writes are forced to be synchronous 42 © 2013 IBM Corporation 21 9/26/2013 Case Study 2 – Disk Watcher 43 © 2013 IBM Corporation Case Study 2 – Disk Watcher 44 © 2013 IBM Corporation 22 9/26/2013 Case Study 2 – Disk Watcher 45 © 2013 IBM Corporation DSPFD Command A display file description command (DSPFD) against the file with long write times shows the force write ratio of 1 46 © 2013 IBM Corporation 23 9/26/2013 Quiz (1 of 2) For integrated disks controlled by IBM i, you may use RAID-5 and mirroring only. True False Higher disk drive utilization always results in increased disk response times. True False Increased queuing beyond a critical level may result in disk response time being significantly impacted. True False 47 © 2013 IBM Corporation Quiz solutions (1 of 2) For integrated disks controlled by IBM i, you may use RAID-5 and mirroring only. True False Higher disk drive utilization always results in increased disk response times. True False Increased queuing beyond a critical level may result in disk response time being significantly impacted. True False 48 © 2013 IBM Corporation 24 9/26/2013 Quiz (2 of 2) Increased disk adapter cache can improve disk subsystem performance. True False Read-intensive workloads with high levels of random reads are more likely to benefit from Solid State Drives (SSD) than other workloads. True False 49 © 2013 IBM Corporation Quiz solutions (2 of 2) Increased disk adapter cache can improve disk subsystem performance. True False Read-intensive workloads with high levels of random reads are more likely to benefit from Solid State Drives (SSD) than other workloads. True False 50 © 2013 IBM Corporation 25 9/26/2013 Summary I/Os can be optimized without touching application programs Simple best practices can lead to significant I/O performance improvements Optimization can significantly improve performance and runtimes by – Reducing I/Os and wait times – Avoiding I/Os rather than optimizing 51 © 2013 IBM Corporation Thank You! 52 © 2013 IBM Corporation 26 9/26/2013 IBM Systems Lab Services and Training Leverage the skills and expertise of IBM's technical consultants to implement projects that achieve faster business value Ensure a smooth upgrade Improve your availability Design for efficient virtualization Reduce management complexity Assess your system security Optimize database performance Modernize applications for iPad How to contact us at COMMON: For Lab Services: Contact Mark Even at [email protected] For Technical Training: Contact Lisa Ryan at [email protected] Meet Mark and Lisa in the IBM Expo booth Follow us at @IBMSLST Learn more ibm.com/systems/services/labservices Deliver training classes & conferences 53 © 2013 IBM Corporation Special notices This document was developed for IBM offerings in the United States as of the date of publication. 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IBM is not responsible for printing errors in this document that result in pricing or information inaccuracies. All prices shown are IBM's United States suggested list prices and are subject to change without notice; reseller prices may vary. IBM hardware products are manufactured from new parts, or new and serviceable used parts. Regardless, our warranty terms apply. Any performance data contained in this document was determined in a controlled environment. Actual results may vary significantly and are dependent on many factors including system hardware configuration and software design and configuration. Some measurements quoted in this document may have been made on development-level systems. There is no guarantee these measurements will be the same on generallyavailable systems. Some measurements quoted in this document may have been estimated through extrapolation. Users of this document should verify the applicable data for their specific environment. Revised September 26, 2006 54 54 © 2013 IBM Corporation 27 9/26/2013 Special notices (cont.) 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Revised November 28, 2012 55 Other company, product and service names may be trademarks or service marks of others. 55 © 2013 IBM Corporation Notes on benchmarks and values The IBM benchmarks results shown herein were derived using particular, well configured, development-level and generally-available computer systems. Buyers should consult other sources of information to evaluate the performance of systems they are considering buying and should consider conducting application oriented testing. For additional information about the benchmarks, values and systems tested, contact your local IBM office or IBM authorized reseller or access the Web site of the benchmark consortium or benchmark vendor. IBM benchmark results can be found in the IBM Power Systems Performance Report at http://www.ibm.com/systems/p/hardware/system_perf.html . All performance measurements were made with AIX or AIX 5L operating systems unless otherwise indicated to have used Linux. For new and upgraded systems, the latest versions of AIX were used. All other systems used previous versions of AIX. The SPEC CPU2006, LINPACK, and Technical Computing benchmarks were compiled using IBM's high performance C, C++, and FORTRAN compilers for AIX 5L and Linux. For new and upgraded systems, the latest versions of these compilers were used: XL C for AIX v11.1, XL C/C++ for AIX v11.1, XL FORTRAN for AIX v13.1, XL C/C++ for Linux v11.1, and XL FORTRAN for Linux v13.1. For a definition/explanation of each benchmark and the full list of detailed results, visit the Web site of the benchmark consortium or benchmark vendor. TPC http://www.tpc.org SPEC http://www.spec.org LINPACK http://www.netlib.org/benchmark/performance.pdf Pro/E http://www.proe.com GPC http://www.spec.org/gpc VolanoMark http://www.volano.com STREAM http://www.cs.virginia.edu/stream/ SAP http://www.sap.com/benchmark/ Oracle, Siebel, PeopleSoft http://www.oracle.com/apps_benchmark/ Baan http://www.ssaglobal.com Fluent http://www.fluent.com/software/fluent/index.htm TOP500 Supercomputers http://www.top500.org/ Ideas International http://www.ideasinternational.com/benchmark/bench.html Storage Performance Council http://www.storageperformance.org/results Revised December 2, 2010 56 56 © 2013 IBM Corporation 28 9/26/2013 Notes on HPC benchmarks and values The IBM benchmarks results shown herein were derived using particular, well configured, development-level and generally-available computer systems. Buyers should consult other sources of information to evaluate the performance of systems they are considering buying and should consider conducting application oriented testing. For additional information about the benchmarks, values and systems tested, contact your local IBM office or IBM authorized reseller or access the Web site of the benchmark consortium or benchmark vendor. IBM benchmark results can be found in the IBM Power Systems Performance Report at http://www.ibm.com/systems/p/hardware/system_perf.html . All performance measurements were made with AIX or AIX 5L operating systems unless otherwise indicated to have used Linux. For new and upgraded systems, the latest versions of AIX were used. All other systems used previous versions of AIX. The SPEC CPU2006, LINPACK, and Technical Computing benchmarks were compiled using IBM's high performance C, C++, and FORTRAN compilers for AIX 5L and Linux. For new and upgraded systems, the latest versions of these compilers were used: XL C for AIX v11.1, XL C/C++ for AIX v11.1, XL FORTRAN for AIX v13.1, XL C/C++ for Linux v11.1, and XL FORTRAN for Linux v13.1. Linpack HPC (Highly Parallel Computing) used the current versions of the IBM Engineering and Scientific Subroutine Library (ESSL). For Power7 systems, IBM Engineering and Scientific Subroutine Library (ESSL) for AIX Version 5.1 and IBM Engineering and Scientific Subroutine Library (ESSL) for Linux Version 5.1 were used. For a definition/explanation of each benchmark and the full list of detailed results, visit the Web site of the benchmark consortium or benchmark vendor. http://www.spec.org SPEC LINPACK http://www.netlib.org/benchmark/performance.pdf Pro/E http://www.proe.com GPC http://www.spec.org/gpc STREAM http://www.cs.virginia.edu/stream/ Fluent http://www.fluent.com/software/fluent/index.htm TOP500 Supercomputers http://www.top500.org/ AMBER http://amber.scripps.edu/ FLUENT http://www.fluent.com/software/fluent/fl5bench/index.htm GAMESS http://www.msg.chem.iastate.edu/gamess GAUSSIAN http://www.gaussian.com ANSYS http://www.ansys.com/services/hardware-support-db.htm Click on the "Benchmarks" icon on the left hand side frame to expand. Click on "Benchmark Results in a Table" icon for benchmark results. ABAQUS http://www.simulia.com/support/v68/v68_performance.php ECLIPSE http://www.sis.slb.com/content/software/simulation/index.asp?seg=geoquest& MM5 http://www.mmm.ucar.edu/mm5/ MSC.NASTRAN http://www.mscsoftware.com/support/prod%5Fsupport/nastran/performance/v04_sngl.cfm STAR-CD www.cd-adapco.com/products/STAR-CD/performance/320/index/html Revised December 2, 2010 NAMD http://www.ks.uiuc.edu/Research/namd HMMER http://hmmer.janelia.org/ 57 http://powerdev.osuosl.org/project/hmmerAltivecGen2mod 57 © 2013 IBM Corporation Notes on performance estimates rPerf for AIX rPerf (Relative Performance) is an estimate of commercial processing performance relative to other IBM UNIX systems. It is derived from an IBM analytical model which uses characteristics from IBM internal workloads, TPC and SPEC benchmarks. The rPerf model is not intended to represent any specific public benchmark results and should not be reasonably used in that way. The model simulates some of the system operations such as CPU, cache and memory. However, the model does not simulate disk or network I/O operations. rPerf estimates are calculated based on systems with the latest levels of AIX and other pertinent software at the time of system announcement. Actual performance will vary based on application and configuration specifics. The IBM eServer pSeries 640 is the baseline reference system and has a value of 1.0. Although rPerf may be used to approximate relative IBM UNIX commercial processing performance, actual system performance may vary and is dependent upon many factors including system hardware configuration and software design and configuration. Note that the rPerf methodology used for the POWER6 systems is identical to that used for the POWER5 systems. Variations in incremental system performance may be observed in commercial workloads due to changes in the underlying system architecture. All performance estimates are provided "AS IS" and no warranties or guarantees are expressed or implied by IBM. Buyers should consult other sources of information, including system benchmarks, and application sizing guides to evaluate the performance of a system they are considering buying. For additional information about rPerf, contact your local IBM office or IBM authorized reseller. ======================================================================== CPW for IBM i Commercial Processing Workload (CPW) is a relative measure of performance of processors running the IBM i operating system. Performance in customer environments may vary. The value is based on maximum configurations. More performance information is available in the Performance Capabilities Reference at: www.ibm.com/systems/i/solutions/perfmgmt/resource.html Revised April 2, 2007 58 58 © 2013 IBM Corporation 29
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