Performance Tuning Siebel Software on the Sun Platform

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and also provides for easier monitoring. Keeping tables with equal extent sizes in their own tablespace reduces fragmentation as old and new extent allocations are always of the same size within a given tablespace, leaving no room for empty oddsized pockets in between. This leads to compact data placement which reduces the number of I/Os done. 3. Build a script to create all of the tables and indexes. This script should have the tables being created in their appropriate tablespaces with the appropriate parameters like freelists, freelist_groups, pctfree, pctused, and so on. Use this script to place all of the tables in their tablespaces and then import the data. This will result in a clean, defragmented, optimized, and right-sized database. The tablespaces should also be built to be locally managed. This allows the space management to be done locally within the tablespace, unlike default (dictionary managed) tablespaces that write to the system tablespace for every extent change. The list of hot tables for <strong>Siebel</strong> is available in Appendix B. 7.6.2 Properly Locating Data on the Disk for Best <strong>Performance</strong> To achieve the incredible capacity on current disk drives, disk manufacturers have implemented zone bit recording. This means that the outer edge of the disk drive has more available storage area than the inside edge of the disk drive; that is, the number of sectors per track decreases as you move toward the center of the disk. Disk drive manufactures take advantage of this situation by recording more data on the outer edges. Since the disk drive rotates at a constant speed, the outer tracks have faster transfer rates than the inner tracks. For example, a Seagate 36 Gbyte Cheetah 1 drive has a data transfer speed range of 57 MBytes/sec on the inner tracks to 86 Mbytes/sec on the outer tracks -- a 50% improvement in transfer speed. For benchmarking purposes, it is desirable to: 1. Place active large block transfers on the outer edges of the disk to minimize data transfer time. 2. Place active random small block transfers on the outer edges of the disk drive only if active large block transfers are not in the benchmark. 3. Place inactive random small block transfers on the inner sections of disk drive to minimize the impact of the data transfer speed discrepancies. Further, if the benchmark only deals with small block I/Os, like SPC Benchmark-1 2 benchmarking, the priority is to put the most active LUNs on the outer edge and the less active LUNs on the inner edge of the disk drive. 1 The Cheetah 15 KB RPM disk drive datasheet can be found at www.seagate.com. 2 Further information about SPC Benchmark-1 TM can be found at www.Storage<strong>Performance</strong>.org. <strong>Performance</strong> <strong>Tuning</strong> <strong>Siebel</strong> <strong>Software</strong> on the Sun Platform Page 40
86 MB/second 57 MB/second Figure 7.6.2 Figure 7.6.2 shows a zone bit recording example with five zones. The outer edge holds the most data and has the fastest transfer rate. 7.6.3 Disk Layout and Oracle Data Partitioning An I/O subsystem with less contention and high throughput is key for obtaining high performance with Oracle. After analyzing the <strong>Siebel</strong> workload an appropriate design was made. The I/O subsystem consisted of Sun StorEdge SE6320 connected to the E2900 database server via fiber channel. The SE6320 has 2 base + 2 expansion arrays driven through two controllers. Each tray consists of 14x36Gbyte disks at 15,000 RPM. That means there are 56 total disks providing over 2 Tbytes of total storage. Each tray has a cache of 1Gbyte. All of the trays were formatted in the RAID 0 mode and two LUNs per tray were created. Eight striped volumes of 300 Gbytes each were carved. Each volume was striped across seven physical disks with stripe sizes of 64KB. Eight filesystems (ufs) were built on top of these striped volumes: T4disk1, T4disk2, T4disk3, T4disk4, T4disk5, T4disk6, T4disk7, T4disk8. The following example shows the tuning done at the disk array level. Please note that cache writebehind was turned off and disk scrubber was turned off. <strong>Performance</strong> <strong>Tuning</strong> <strong>Siebel</strong> <strong>Software</strong> on the Sun Platform Page 41
Page 1 and 2: Performance <stron
Page 3 and 4: Abstract This paper discusses the p
Page 5 and 6: 7.6.6 Oracle Parameters Tun
Page 7 and 8: 1 Tuning for Price
Page 9 and 10: 2 Siebel Applicati
Page 11 and 12: 3 Optimal Sun/Siebel</stron
Page 13 and 14: 3.1 Hardware and Software</
Page 15 and 16: 5 10,000 Concurrent Users: Test Res
Page 17 and 18: 6 Siebel Scalabili
Page 19 and 20: Cost per Siebel Us
Page 21 and 22: 7.1 Tuning Solaris
Page 23 and 24: 7.1.3 The Solaris Kernel and TCP/IP
Page 25 and 26: In the file $SIEBEL_ROOT/bin/enu/ua
Page 27 and 28: 7.2.3 Assignment Manager Tu
Page 29 and 30: MQ series parameter tuning: PERFQMG
Page 31 and 32: Investigating the Reason for the Fa
Page 33 and 34: let a Siebel proce
Page 35 and 36: Description The reason for this sym
Page 37 and 38: Parameter Scope Default Tuned Value
Page 39: 7.6 Tuning <strong
Page 43 and 44: DATA_51200K INDX_512K DATA_5120K TE
Page 45 and 46: 7.6.4 Solaris MPSS Tuning</
Page 47 and 48: Siebel Object Name
Page 49 and 50: instance_name=oramst job_queue_proc
Page 51 and 52: ORAPERF.S_PRI_LST T4 WHERE T4.PAYME
Page 53 and 54: the database during peak load. In t
Page 55 and 56: use connection pooling, so you woul
Page 57 and 58: Oracle Database Server 1. Larger th
Page 59 and 60: 160 siebelapp2_1 eSalesObjMgr_enu 1
Page 61 and 62: 9.10 To Produce a Stack Trace for t
Page 63 and 64: Count indv cuml rcnt nsec Lock Call
Page 65 and 66: 5. Once the user has stopped at the
Page 67 and 68: 10 Appendix A: Transaction Response
Page 69 and 70: eSls1_115DDSubCategory1.3 0.125 0.1
Page 71 and 72: CC3_2newSolution 0.047 0.136 3.281
Page 73 and 74: 11 Appendix B: Database Objects Gro
Page 75 and 76: S_OPTY_BU_M8 INDEX 2,334,720 S_ORDE
Page 77 and 78: log file parallel write 550,101 515
Page 79: Acknowledgements Thanks to

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