Product Overview OW

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Oracle Exadata Storage Server Product Overview

Oracle OpenWorldSeptember 2008

2008 Oracle Corporation Proprietary and Confidential


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2008 Oracle Corporation Proprietary and Confidential 2

Exadata Benefits

Extreme Performance 10X to 100X speedup for data warehousing

More pipes to data Massively parallel architecture Wider pipes to data 5X faster than conventional storage

Ship less data through the pipes Process data in storage Unlimited Scalability Linear Scaling of Data Bandwidth Transaction/Job level Quality of Service

Mission Critical Availability and Protection Disaster recovery, backup, point-in-time recovery, data validation,

encryption


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Solutions To Data Bandwidth Bottleneck

Add more pipes Massively parallel architecture Make the pipes wider 5X faster than conventional storage Ship less data through the pipes Process data in storage


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HP Exadata Storage Server Hardware Building block of massively parallel Exadata

Storage Grid Up to 1GB/sec data bandwidth per cell HP DL180 G5

2 Intel quad-core processors 8GB RAM

Dual-port 4X DDR InfiniBand card 12 SAS or SATA disks

Software pre-installed Oracle Exadata Storage Server Software Oracle Enterprise Linux HP Management Software

Hardware Warranty 3 YR Parts/3 YR Labor/3 YR On-site 24X7, 4 Hour response

Exadata Storage Server

RackedExadataStorageServers



HP Exadata Storage Server Hardware Details

8 GB DRAM

Redundant 110/220VPower Supplies

2 Intel Xeon Quad-coreProcessors

Infiniband DDRdual port card

LO100c Management Card

P400 Smart Array DiskController card

- 512M battery backed cache 12 x 3.5 Disk Drives

Included Software:

Oracle Exadata Storage Server Software

Oracle Enterprise Linux

HP Management Software



Scalable

SAS raw capacity per rack: 65TBSATA raw capacity per rack: 216TB Peak throughput per rack : >18GB/s

Scale to 18 cells in one rackAdd racks to scale further

Each cell connectsto 2 Infinibandswitches for Redundancy

This delivers 4x thebandwidth

Infiniband links acrossracks for full connectivity



Massively Parallel Storage Grid Storage cells are organized into a massively

parallel storage grid

Scalable Scales to hundreds of storage cells Data automatically distributed across cells by

ASM

Transparently redistributed when cells areadded or removed

Data bandwidth scales linearly with capacity

Available

Data is mirrored across cells Failure of disk or cell transparently tolerated

Simple Works transparently - no application changes

Exadata bandwidth scaleslinearly with capacity

4 GB/sec

8 GB/sec

16 GB/sec



Exadata Performance Scales

Exadata delivers brawnyhardware for use by Oraclesbrainy software

Performance scales with size

Result More business insight Better decisions

Improved competitiveness

Table Scan Time

Table Size1TB 10 TB 100TB

1 Hour

10 Hour

5 Hour

TypicalWarehouse

Exadata



HP Oracle Database MachinePre-Configured High Performance Data Warehouse

8 DL360 Oracle Database servers 2 quad-core Intel Xeon, 32GB RAM Oracle Enterprise Linux Oracle RAC

14 Exadata Storage Cells (SAS or SATA) Up to 14 TB uncompressed user data on SAS Up to 46 TB uncompressed user data on SATA

4 InfiniBand switches 1 Gigabit Ethernet switch Keyboard, Video, Mouse (KVM) hardware Hardware Warranty

3 YR Parts/3 YR Labor/3 YR On-site 24X7, 4 Hour response time

Add more racks for unlimited scalability


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Exadata Configuration

Each Exadata Cell is a self-contained server which houses diskstorage and runs the Exadata software

Databases are deployed across multiple Exadata Cells Database enhanced to work in cooperation with Exadata intelligent

storage No practical limit to number of Cells that can be in the grid

Exadata Cell

InfiniBand Switch/Network

Single-InstanceDatabase

RACDatabase

Exadata Cell Exadata Cell


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Exadata Architecture

DB Server

DB Instance DBRM

ASM

Single-Instance

Database

RAC

DatabaseDB Server

DB Instance DBRM

ASM

DB Server

DB Instance DBRM

ASM

OEL CELLSRV MS

RS IORM Exadata Cell

i D B P r o t o c o l o v e r

In f i n i B a n d w i t h

Pa t h Fa i l o v e r InfiniBand Switch/Network

CellControl

CLI

EnterpriseManager

OEL CELLSRV MS


OEL CELLSRV MS



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Smart Scan Offload Processing Exadata storage cells implement smart scans to greatly reduce the

data that needs to be processed by database hosts Offload predicate evaluation Only return relevant rows and columns to host Join filtering Incremental backup filtering File creation

Data reduction is usually very large 10x data reduction is common

Completely transparent Even if cell or disk fails during a query

Smart Scan Example: Telco wants to identify customers that spend more than $200 on a single

phone call The information about these premium customers occupies 2MB in a 1

terabyte table


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Traditional Scan Processing

With traditional storage, alldatabase intelligenceresides in the databasehosts

Very large percentage of data returned from storageis discarded by databaseservers

Discarded data consumesvaluable resources, andimpacts the performance of other workloads

I/Os Executed:1 terabyte of datareturned to hosts

DB Host reducesterabyte of data to 1000

customer names thatare returned to client

Rows Returned

SELECT

customer_nameFROM calls

WHERE amount > 200;

Table

ExtentsIdentified

I/Os Issued


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Exadata Smart Scan Processing

Only the relevant columns

customer_nameand required rows where amount>200are are returned to hosts

CPU consumed by predicateevaluation is offloaded

Moving scan processing off the database host frees hostCPU cycles and eliminatesmassive amounts of unproductive messaging

Returns the needle, not theentire hay stack

2MB of data

returned to server

Rows Returned

Smart Scan

Constructed AndSent To Cells

Smart Scan

identifies rows andcolumns within

terabyte table thatmatch request

Consolidated

Result SetBuilt From All

Cells

SELECT

customer_nameFROM calls

WHERE amount > 200;


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Additional Smart Scan Functionality

Join filtering

Star join filtering is performed within Exadata storage cells Dimension table predicates are transformed into filters that are applied to

scan of fact table Example - Select total sales of all Italian wines

Items are scanned to identify Item numbers of Italian wine The Item numbers are used to create a Bloom filter This filter is applied by the cells during the scan of Sales table to

identify sales of Italian wines Backups

I/O for incremental backups is much more efficient since only changedblocks are returned

Create Tablespace (file creation) Formatting of tablespace extents eliminates the I/O associated with the

creation and writing of tablespace blocks


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Exadata Storage GridI/O Resource Management

With traditional storage,creating

a managing shared storage ishampered by the inability tobalance the work between userson the same database or onmultiple databases sharing thestorage subsystem

Hardware isolation is theapproach to ensure separation

Exadata I/O resourcemanagement ensures user defined SLAs are met

Coordination and prioritizationbetween different groups/classesof work within a database andbetween databases

StorageSwitch/Network

.

Database

A.

Database

B

Database

C. . .


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Exadata I/O Resource ManagementDW and Mixed Workload Environments

Ensure different users andtasks within a database areallocated the correctrelative amount of I/Obandwidth

For example: Interactive: 50% of I/O

resources

Reporting: 30% of I/Oresources

ETL: 20% of I/O resources

Exadata Cell Exadata Cell Exadata Cell

DatabaseServer


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Exadata I/O Resource ManagementMulti-Database OLTP Environment

Ensure different databases areallocated the correct relative amount of I/O bandwidth

Database A: 33% I/O of resources Database B: 67% I/O of resources

Ensure different users and tasks withina database are allocated the correctrelative amount of I/O bandwidth

Database A: Reporting: 60% of I/O resources ETL: 40% of I/O resources

Database B: Interactive: 30% of I/O resources Batch: 70% of I/O resources

Exadata Cell Exadata Cell Exadata Cell

Database B(RAC)

Database A(Single-Instance)


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Exadata Scale-Out Storage Grid

Dynamic virtualized storageresources using Automatic StorageManagement (ASM)

Simple and non-intrusive resourceallocation, and reallocation, enablingtrue enterprise grid storage

Database work spread acrossstorage resources for optimalperformance

Powerful storage allocation optionsand management

Flexible configuration for performance and availability

Exadata Cell

InfiniBand Switch/Network

Single-InstanceDatabase

RACDatabase



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Exadata Storage Layout ExampleCell Disks

Cell Disk is the entity that represents a physical diskresiding within a Exadata Storage Cell Automatically discovered and activated

CellDisk


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Exadata Storage Layout ExampleGrid Disks

Cell Disks are logically partitioned into Grid Disks Grid Disk is the entity allocated to ASM as an ASM disk Minimum of one Grid Disk per Cell Disk Can be used to allocate hot, warm and cold regions of a

Cell Disk or to separate databases sharing Exadata Cells

GridDisk


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Exadata Storage Layout ExampleASM Mirroring and Failure Groups

ASM mirroring is used protect against disk failures ASM failure groups are used to protect against cell failures


Hot Hot Hot Hot Hot Hot

Cold Cold Cold Cold Cold Cold

ASMDisk Group

ASMFailure Group

ASMFailure Group


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Exadata Storage Management & Administration

Enterprise Manager Manage & administer Database and ASM Exadata Storage Plug-in

Enterprise Manager Grid Control Plug-in to monitor &

manage Exadata Storage Cells Comprehensive CLI Local Exadata Storage cell management Distributed shell utility to execute CLI across multiple

cells Lights-out 100 Remote management and administration of hardware


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Data Protection Solutions

All single points of failure eliminated by the Exadata Storage architecture

Hardware Assisted Resilient Data (HARD) built in to Exadata Storage Prevent data corruption before it happens

Data Guard provides disaster protection and data corruption protection Automatically maintained second copy of database

Flashback provides human error protection Snapshot-like capabilities to rewind database to before error

Recovery Manager (RMAN) provide backup to disk Archiving and corruption protection Can be used with Oracle Secure Backup (OSB) or third party tape backup

software These work just as they do for traditional non-Exadata storage

Users and database administrator use familiar tools


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Exadata Co-Existence and Migration

Databases can be concurrentlydeployed on Exadata andtraditional storage Tablespaces can exist on Exadata

storage, traditional storage, or acombination of the two, and is

transparent to database applications SQL offload processing requires all

pieces of a tablespace reside onExadata

Online migration if currently using

ASM and ASM redundancy Migration can be done usingRMAN or Data Guard

Exadata Non-Exadata

DatabaseServer

Online Migration


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Telco Exadata Speedup 10X to 72X

- 10.0 20.0 30.0 40.0 50.0 60.0 70.0

Index Creation

CDR Full Table Scan

Warehouse Inventory Report

CRM Service Order Report

CRM Customer Discount Report

Tablespace Creation

Hanset to Customer Mapping Report

28xAverageSpeedup


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Retailer Exadata Speedup 3x to 50x

- 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0

Recall Query

Gift Card Activations

Sales and Customer Counts

Prompt04 Clone for ACL audit

Date to Date MovementComparison - 53 weeks

Materialized Views Rebuild

Merchandising Level 1 Detail byWeek

Supply Chain Vendor - Year - ItemMovement

Merchandising Level 1 Detail:Current - 52 weeks

Merchandising Level 1 Detail:Period Ago

16xAverageSpeedup


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Exadata Benefits

Extreme Performance

10X to 100X speedup for data warehousing More pipes to data Massively parallel architecture Wider pipes to data 5X faster than conventional storage Ship less data through the pipes Process data in storage

Unlimited Scalability Linear Scaling of Data Bandwidth Transaction/Job level Quality of Service

Mission Critical Availability and Protection Disaster recovery, backup, point-in-time recovery, data validation,

encryption


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Exadata Talks At OpenWorld

Four Exadata Talks on Thursday 9/25/2008 09:00 - 10:00 (session S298677)

Moscone South Room 103 Oracles New Database Accelerator: Query Processing Revolutionized

Juan Loaiza, Oracle 12:00 - 13:00 (session S298679)

Moscone South Room 305

Oracles New Database Accelerator: Query Processing Revolutionized Juan Loaiza, Oracle

13:30 - 14:30 (session S298680) Moscone South Room 305 Oracles New Database Accelerator: Query Processing Revolutionized

Juan Loaiza, Oracle 15:00 - 16:00 (session S298681) Moscone South Room 305

Oracles New Database Accelerator: A Technical Overview Kodi Umamageswaran, Oracle; Ron Weiss, Oracle


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Exadata Demos At OpenWorld

Three Demo and Q&A Locations Moscone North Lobby

Live Demonstration, Hardware, Software, and Q&A HP Booth Exhibit Floor

Live Demonstration, Hardware, Software, and Q&A Oracle Campground Demo Moscone West (pod L35)

Q&A


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Documents

Product Overview OW