Presentation - Optimize Your IT Investment With Exadata

<Insert Picture Here>

Optimize Your IT Investment with Exadata

Alvin Tai

Lead Database Architect (Infrastructure & Data Warehouse)

Copyright © 2010, Oracle Corporation and/or its

affiliates – 2 –

Building Database Systems

Database Server

[CPUs, Memory]

Storage

[disks]

Storage Network

[cards(HBAs), switches, arrays, ports, channels]

Database Software

Business Applications

© 2009 Oracle Corporation - Confidential

Bandwidth Problem

• Can’t ship data to Database servers fast enough

© 2009 Oracle Corporation - Confidential

Solving the Data Bandwidth Problem

2 possible approaches to solving the problem

• Wider pipes and More pipes

• Less data going through the pipes



What if…

Industry Experts in database, operating system, hardware, and storage

could architect your system

to be extremely fast, scalable, and highly-available

using low-cost components

with some “special Oracle sauce”

and then build and install it for you.

Database Server

[CPUs, Memory]

Storage

[disks]

Storage Network

[cards(HBAs), switches, arrays, ports, channels]

Database Software

Business Applications

Exadata V2 Goals

• Ideal Database Platform

• Best Machine for Data Warehousing

• Best Machine for OLTP

• Best Machine for Database Consolidation

• Unique Architecture Makes it

• Fastest, Lowest Cost

© 2010 Oracle Corporation 6

Exadata Value Proposition

• Extremely Fast and Predictable Performance

• Intelligent Storage

• Smart Flash Cache

• Lower TCO

• Hybrid Columnar Compression

• Consolidated workloads

• Low Risk

• Existing Oracle skills

• Faster time to value

Exadata Hardware Architecture

Database Grid Intelligent Storage Grid

InfiniBand Network

• Redundant 40Gb/s switches

• Unified server & storage network

• 14 High-performance low-cost

storage servers• 8 Dual-processor x64 database servers

OR

• 2 Eight-processor x64 database servers

Scaleable Grid of industry standard servers for Compute and Storage

• Eliminates long-standing tradeoff between Scalability, Availability, Cost

•100 TB High Speed disk, or336 TB High Capacity disk

•5.3 TB PCI Flash

•Data mirrored across storage servers

Copyright © 2010, Oracle Corporation and/or its affiliates – 8 –

Start Small and Grow

Balanced Incremental Scaling

for OLTP and DW


Full Rack

Half Rack

Quarter Rack

Complete Family Of Database MachinesFor OLTP, Data Warehousing & Consolidated Workloads

• Quarter, Half, Full and Multi-Racks • Full and Multi-Racks

Oracle Exadata X2-8Oracle Exadata X2-2

Copyright © 2010, Oracle Corporation and/or its affiliates – 10 –



Exadata Product Capacity

X2-8

Full Rack

X2-2

Full Rack

X2-2

Half Rack

X2-2

Quarter Rack

Raw Disk1High Perf Disk 100 TB 100 TB 50 TB 21 TB

High Cap Disk 336 TB 336 TB 168 TB 72 TB

Raw Flash1 5.3 TB 5.3 TB 2.6 TB 1.1 TB

User

Data2

(assuming no

compression)

High Perf Disk 28 TB 28 TB 14 TB 6 TB

High Cap Disk100 TB 100 TB 50 TB 21 TB

1 – Raw capacity calculated using 1 GB = 1000 x 1000 x 1000 bytes and 1 TB = 1000 x 1000 x 1000 x 1000 bytes.

2 - User Data: Actual space for end-user data, computed after single mirroring (ASM normal redundancy) and after allowing space for database structures such as temp, logs, undo, and indexes. Actual user data capacity varies by application. User Data capacity calculated using 1 TB = 1024 * 1024 * 1024 * 1024 bytes.

Intelligent Storage

© 2008 Oracle Corporation – Proprietary and Confidential – 13 –

Traditional Scan Processing

• With traditional storage,

all database intelligence

resides in the database

hosts

• Very large percentage of

data returned from

storage is discarded by

database servers

• Discarded data

consumes valuable

resources, and impacts

the performance of other

workloads

I/Os Executed:

1 terabyte of data

returned to hosts

DB Host reduces

terabyte of data to 2MB

of sales rows that met

the criteria and returns it

to the client

Rows Returned

SELECT

count(revenue)

FROM sales

WHERE discount

= 6%;

Table

Extents

Identified

I/Os Issued

© 2008 Oracle Corporation – Proprietary and Confidential – 14 –

Exadata Smart Scan Processing

• Only the relevant columns

• revenue

and required rows

• where discount = 6%

are returned to hosts

• CPU consumed by predicate evaluation is offloaded

• Moving scan processing off the database host frees host CPU cycles and eliminates massive amounts of unproductive messaging

• Returns the needle, not the entire hay stack

2MB of data returned

to server

Rows Returned

Smart Scan

Constructed And

Sent To Cells

Smart Scan

identifies rows and

columns within

terabyte table that

match request

Consolidated

Result Set

Built From All

Cells

SELECT

count(revenue)

FROM sales

WHERE discount

= 6%;


Exadata Smart Flash CacheExtreme Performance OLTP

5X More I/Os than

1000 Disk Enterprise

Storage Array

• Exadata has 5 TB of flash

• 56 Flash PCI cards avoid disk

controller bottlenecks

• Intelligently manages flash

• Smart Flash Cache holds hot data

• Avoids large scan wipe-outs of cache

• Gives speed of flash, cost of disk

• Exadata flash cache achieves:

• Over 1 million IO/sec from SQL (8K)

• Sub-millisecond response times

Order_date Ship_date Cust_

ID

Prod_I

D

Amount

03-SEP-2009 19-SEP-2009 10075 32932 10,000.00

03-SEP-2009 05-SEP-2009 20098 20098 20,000.00

03-SEP-2009 07-OCT-2009 10089 20010 15,000.00

03-SEP-2009 01-OCT-2009 20100 10000 35,000.00

03-SEP-2009 19-OCT-2009 80300 30000 10,000.00

03-SEP-2009 03-NOV-2009 10000 2030 40,000.00

Exadata Storage IndexTransparent I/O Elimination with No Overhead

• Exadata Storage Indexes maintains summary information about table data in

memory

• Stores MIN and MAX values of filter columns

• Typically one index entry for every MB of disk

• Eliminates disk I/Os if MIN and MAX can never match “where” clause of a query

• “Negative index”

• Completely automatic and transparent

MIN ship_date = ’01-OCT-2009’

MAX ship_date = ’03-NOV-2009’

Select * from orders where ship_date < ’31-SEP-2009’

Only first set of rows can match

New

MIN ship_date = ’19-SEP-2009’

MAX ship_date = ’07-OCT-2009’

Cost Savings

Exadata Hybrid Columnar CompressionWarehousing and Archiving

Warehouse Compression

• 10x average storage savings

• 10x Scan I/O reduction

Archive Compression

• 15x average storage savings

• Up to 50x on some data

• Some access overhead

• For cold or historical data

Optimized for Speed Optimized for Space

Smaller Warehouse

Faster Performance

Reclaim 93% of Disks

Keep Data Online

Can mix compression types by partition for ILM

Compression Integrated End-to-End

• Oracle provides Integrated End-to-End Compression• Data stays compressed through

full workflows

• Faster, in elapsed time

• Much less overhead, CPU consumption comparable to uncompressed

• Others have point solutions• Compression of just disk, or

just tape, or just network

• Data must be uncompressed and recompressed for workflow

• Poor compression or slow performance

End-to-End Compression

• Stored compressed – less disk

• Read compressed – faster I/O

• Compressed in Flash – less I/O

• Processed compressed – less CPU

• Send compressed – faster Infiniband

• Cached compressed – less I/O

• Processed compressed – less CPU

• Cloned compressed

• Faster, cheaper test, dev, DR

• Backed Up compressed

• Faster, lower cost


Standardized and Simple to Deploy

• All Database Machines are the same

• Delivered ready-to-run

• Tested

• Highly supportable

• No unique configuration issues

• Identical to config used by Oracle Engineering

• Runs existing OLTP and DW applications

• Full 30 years of Oracle DB capabilities

• No Exadata certification required

• Leverages Oracle ecosystem

• Skills, knowledge base, people, partners

Deploy in Days,

Not Months


Benefits Multiply

1 TB

with compression

10 TB of user data

Requires 10 TB of IO

100 GB

with partition pruning

20 GB

with Storage Indexes

5 GB Smart Scan on

Memory or Flash

Subsecond

On Database

Machine

Data is 10x Smaller, Scans are 2000x faster

© 2009 Oracle Corporation - Confidential© 2008 Oracle Corporation – 22 –

Scale-Out MPP Architecture

• The database, ASM, and Exadata Cells each

play a role in Oracle’s scale-out storage

architecture

• Responsibilities are placed in the optimal

location

• DB – Real Application Clusters

• ASM – Reliable Storage Pool

• Exadata Cell – Database Intelligent Storage

• Seamless integration simplifies management

ASMReliable Storage

Pool

Real Application Clusters

ExadataDatabase

Intelligent Storage

Oracle Database Machine: High Availability

Problem Database Machine Solution

Power failureRedundant PDUs in the rack and

redundant power supplies for all servers

Switch failureRedundant Infiniband switches; dual-ported

bonded HCA’s in all servers for redundancy

Ethernet port/link failure4 Ethernet ports in database servers; Can

be bonded for protection

Disk failureOracle Automatic Storage Management: all

disks are mirrored

Database Server failureOracle Real Application Clusters protects

from n-1 server failures

Storage Server failureOracle Automatic Storage Management: all

disks are mirrored across storage servers

Failure Protection

• Redundant Hardware

• Servers, Storage, Network

• Database Level HA

• Tolerate failures and changes

• Fully Active Remote Replica


Active

Data Guard

GoldenGate

Replication

RAC

ASM

Flashback

Secure

Backup

Online

Redefinition

ERP

CRM

Warehouse

Data Mart

HR


Balanced and Optimized

• Custom systems do not achieve full performance

• Component imbalance, misconfiguration, bottleneck

• Exadata is engineered and optimized end-to-end

• Double-digit GB/sec transfers from disk to database

• Disk, flash, controller, bus, HBA, network, CPUs, etc

• DB libraries optimized with firmware, drivers, OS, network

• Years of tuning

• No bottleneck

• Move I/T talent to higher value business needs

• Not designing, tuning, maintaining hardware configs

Optimized

End-to-End


Best Machine for Data Warehousing

Optimized for strategic warehousing

Ad hoc queries over detail data

Only Oracle provides 21 GB/sec per rack of IO bandwidth,

with up to 50 GB/sec with Flash

Optimized for operational warehousing

Tactical, short-running queries integrated with operational

processes

Only Oracle provides advanced warehouse indexing

capabilities running at 1M IOPS

Optimized for real-world data loading

Only Oracle provides multi-version read consistency

with the ability to load at 5TB/hr

Optimized for advanced analytics

Only Oracle provides integrated OLAP, data mining,

spatial and statistics

27

World’s Fastest OLTP MachineUnique OLTP capabilities

• Runs business applications “on the Grid”• Oracle eBusiness Suite

• Oracle Peoplesoft

• Oracle Siebel• Fault-tolerant, scale-out Database Servers

• Real Application Clusters

• Data Guard

• Online Operations

• Fault-tolerant, scale-out Storage Servers • Automatic Storage Management

• Exadata Storage Servers

Siebel 8.0.0.8 Testing on Quarter Rack

Database Machine

• Full MAA Configuration

• Combination of Call Center, Partner Relationship Management, and

EAI workload

• 30,588 Concurrent Users

• 420,295 business transactions per hour

• 9,451 IOPs

• 22% CPU utilization per database server node

• 75% Exadata Smart Flash Cache Hits

© 2010 Oracle Corporation

29

Consolidate Database Servers

• Many databases can run on Database Machine servers

• Shared Configuration

• Applications connect to a database service that runs on one or more database servers

• Services can grow, shrink, & movedynamically

• Large databases can span nodes using RAC

• Multiple small databases can run on a single node

• Predictable performance

• Instance caging provides predictable CPU resources when multiple databases run on the same node

• Restricts a database to subset of processors

ERP CRM

Warehouse

Data

Mart

HR

© 2010 Oracle Corporation


Conclusion - Exadata V2Ideal Database Platform

• Best for Data Warehousing

• Best for OLTP

• Best for Database Consolidation

30

Hybrid Columnar Compression

Intelligent Storage Grid

Fastest, Lowest Cost

Smart Flash Cache

Business answers in seconds, not hours

Copyright © 2010 Oracle Corporation and/or its affiliates–32 –

New - Exadata Database Machine X2-8 Full Rack Extreme Performance for Consolidation, Large OLTP and DW

• 2 x64 Eight-processor Database servers (Sun Fire 4800)

• High Core, High Memory Database Servers

• 128 CPU cores (64 per server)

• 2 TB (1 TB per server)

• 10 GigE connectivity to Data Center

• 16 x 10GbE ports (8 per server)

• 14 Exadata Storage Servers X2-2

• All with High Performance 600GB SAS disks

OR

• All with High Capacity 2 TB SAS disks

• 3 Sun Datacenter InfiniBand Switch 36

• 36-port Managed QDR (40Gb/s) switch

• 1 “Admin” Cisco Ethernet switch

• Redundant Power Distributions Units (PDUs)

Add more racks for additional scalability


Exadata Database Machine X2-2 Full Rack Pre-Configured for Extreme Performance

• 8 x64 Dual-procesor Database Servers (Sun Fire X4170 M2)

• 96 cores (12 per server)

• 768 GB memory (96GB per server)





OR





• Keyboard, Video, Mouse (KVM) hardware


Add more racks for additional scalability


• 4 x64 Dual-procesor Database Servers (Sun Fire X4170

M2)







OR







Can Upgrade to a Full Rack

Exadata Database Machine X2-2 Half Rack Pre-Configured for Extreme Performance


Can Upgrade to an Half Rack

Exadata Database Machine X2-2 Quarter Rack Pre-Configured for Extreme Performance

• 2 x64 Dual-procesor Database Servers (Sun Fire X4170 M2)







OR







Presentation - Optimize Your IT Investment With Exadata

Documents

Transcript of Presentation - Optimize Your IT Investment With Exadata