Expert Oracle Exadata - Parent Directory

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CHAPTER 15 COMPUTE NODE LAYOUTmore than the aggregate ingest bandwidth of the database grid. The scan rate is therefore throttled. The queryshould indeed run faster than noncompressed, but as we can see there is more to it than simple math. Thehypothetical query cannot complete in 1/10th the time. In such a case the physical scan rate for the full rackwould be throttled back to roughly 45 GBps, and so the query would complete in approximately 11 seconds—1/6th the time as in the noncompressed case. This example does not take into consideration any other factor thatmay cause consumers to throttle producers, such as join processing and sorting. It considers only the aggregateiDB ingest bandwidth in the database grid. Other factors, such as database grid CPU-saturation (due to heavy joinand sort processing) can further throttle the flow of data over iDB. There is a direct correlation between theselectivity of a query, the host processor utilization level, and the performance improvement delivered by EHCC. Ioften have to remind people that the concept of compression as a performance feature is quite new, and oftenmisrepresented.Non-RAC ConfigurationCompute nodes may be configured in a number of ways. If your application does not need the highavailability or scale-out features of Oracle RAC, then Exadata provides an excellent platform fordelivering high performance for standalone database servers. You can manage I/O service levelsbetween independent databases by configuring the IORM. See Chapter 7 for more information aboutIORM. In a non-RAC configuration each compute node will have its own, non-clustered, ASM instancethat provides storage for all databases on that server. Even though your database servers may beindependent of one another they can still share Exadata storage (cell disks). This allows each database tomake use of the full I/O bandwidth of the Exadata storage subsystem. Note that in this configurationClusterware is not installed at all. Just like any other standalone database server, multiple databasescoexist quite nicely within the same disk groups. For example, let’s say you have three databases on yourserver, called SALES, HR, and PAYROLL. All three databases can share the same disk groups for storage. Todo this, all three databases would set their instance parameters as follows:db_create_file_dest='DATA1_DG'db_recovery_file_dest='RECO1_DG'In Figure 15-1 we see all eight compute nodes in an Exadata full rack configuration runningstandalone databases. For example, DB1, Node 1, uses the DATA1_DG and RECO1_DG disk groups, which areserviced by the local (nonclustered) ASM instance. Each ASM instance has its own set of ASM diskgroups, which consist of grid disks from all storage cells. At the storage cell, these independent ASMinstances cannot share grid disks. Each ASM instance will have its own, private set of grid disks.500
CHAPTER 15 COMPUTE NODE LAYOUTDB1DB2DB3DB4Database: DB1ASM Diskgroups for DB1DB5DB6DB7DB8Infiniband SwitchDATA_01_DG Disk GroupRECO_01_DG Disk GroupDATA_01_DGDisk GroupEach ASM disk groupconsists of 12 grid gisksfrom each storage cell.DATA_02_DG Disk GroupDATA_03_DG Disk GroupDATA_04_DG Disk GroupDATA_05_DG Disk GroupDATA_06_DG Disk GroupDATA_07_DG Disk GroupDATA_02_DG Disk GroupDATA_03_DG Disk GroupDATA_04_DG Disk GroupDATA_05_DG Disk GroupDATA_06_DG Disk GroupDATA_07_DG Disk GroupDATA_08_DG Disk GroupDATA_08_DG Disk GroupFigure 15-1. Example of a non-RAC Exadata configuration14 Storage Cells, 168 Celldisks, 16 ASM Disk Groups501
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IntroductionThank you for purchasin
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INTRODUCTIONwere implementing Exada
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CHAPTER 1 WHAT IS EXADATA?end of t
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C H A P T E R 2Offloading / Smart S
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CHAPTER 2 OFFLOADING / SMART SCANR
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CHAPTER 2 OFFLOADING / SMART SCAN3
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CHAPTER 2 OFFLOADING / SMART SCANo
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CHAPTER 2 OFFLOADING / SMART SCANS
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C H A P T E R 3Hybrid Columnar Comp
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CHAPTER 3 HYBRID COLUMNAR COMPRESS
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C H A P T E R 4Storage IndexesStora
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CHAPTER 4 STORAGE INDEXESMonitorin
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CHAPTER 4 STORAGE INDEXESVersion:
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CHAPTER 4 STORAGE INDEXES• For e
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CHAPTER 4 STORAGE INDEXES• _cell
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CHAPTER 4 STORAGE INDEXESSYS@EXDB1
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CHAPTER 4 STORAGE INDEXESpositives
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CHAPTER 4 STORAGE INDEXESIncorrect
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CHAPTER 4 STORAGE INDEXES---------
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C H A P T E R 5Exadata Smart Flash
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CHAPTER 5 EXADATA SMART FLASH CACH
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C H A P T E R 6Exadata Parallel Ope
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CHAPTER 6 MAKING PCBSParameter Def
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CHAPTER 6 MAKING PCBSTable 6-2. Hi
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CHAPTER 6 MAKING PCBSSo as you can
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CHAPTER 6 MAKING PCBS-- switch to
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CHAPTER 7 RESOURCE MANAGEMENTimpor
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CHAPTER 7 RESOURCE MANAGEMENTSQL>
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C H A P T E R 8Configuring ExadataO
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CHAPTER 9 RECOVERING EXADATAprovid
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CHAPTER 10 EXADATA WAIT EVENTSSYS@
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CHAPTER 10 EXADATA WAIT EVENTScell
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C H A P T E R 11Understanding Exada
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CHAPTER 11 UNDERSTANDING EXADATA P
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CHAPTER 12 MONITORING EXADATA PERF
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CHAPTER 13 MIGRATING TO EXADATA Ke
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Page 470 and 471: C H A P T E R 14Storage LayoutIn Or
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Page 512 and 513: C H A P T E R 16Unlearning Some Thi
Page 514 and 515: CHAPTER 16 UNLEARNING SOME THINGS
Page 536 and 537: A P P E N D I X ACellCLI and dcliCe
Page 538 and 539: APPENDIX A CELLCLI AND DCLILIST FL
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Page 546 and 547: A P P E N D I X BOnline Exadata Res
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Index• AAccess control list (ACL)
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• INDEXnetwork componentsclient a
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• INDEX• Epredicate offload, 36
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• INDEXOTHER_GROUPS consumer grou
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• INDEXCPU utilization, 152mixed
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• INDEXstructure, 105sub-query, 1
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Expert Oracle Exadatan n nKerry Osb
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Contents• About the Authors......
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• CONTENTSHow to Verify That Smar
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• CONTENTSControlling ESFC Usage
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• CONTENTSSummary ...............
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• CONTENTS• Chapter 12: Monitor
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• CONTENTS• Chapter 16: Unlearn
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About the Technical Reviewer Kevin
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