Transcript Exadata Overview

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Exadata Database Machine
Morana Kobal Butković
Senior Sales Consultant
Oracle Hrvatska
Exadata Goals
• Ideal Oracle Database Platform
• Best Machine for Data Warehousing
• Best Machine for OLTP
• Best Machine for Database Consolidation
• Unique Architecture Makes it
• Fast and cost efficient
Exadata in the Marketplace
• Launched in Fall 2008
• Seeing rapid adoption in all geographies and industries
Agenda
• Hardware Architecture
• Key Technologies
• Consolidation & Protection
The Products
Exadata Storage Server & Database Machine
• Exadata Storage Server
• Storage Product Optimized for Oracle
Database
• Extreme I/O and SQL Processing
performance
• Combination of hardware and
software
• Exadata Storage Server Software
• Exadata Database Machine
• Pre-Configured High Performance
• Balanced performance
configuration
• Takes the guess work out of
building an Oracle deployment
• Exadata Storage Server Software
• Oracle Database 11.2
Exadata Storage Server Building Block
• Hardware by Sun
• Software by Oracle
• Uses high performance components
• 12 disks - 600 GB 15K RPM SAS 2.0,
or 2TB 7200 RPM SATA
• 2 Xeon quad-core processors with PCI 2.0
• Dual ported 40 Gb/sec InfiniBand
• 4 96 GB PCI Flash Cards
• Runs at full disk and flash bandwidth
Exadata Hardware Architecture
Scalable Grid of industry standard servers for Compute and Storage
• Eliminates long-standing tradeoff between Scalability, Availability, Cost
Database Grid
• 8 compute servers (1U)
Storage Grid
• 14 storage servers (2U)
• 64 Intel cores
• 112 Intel cores in storage
InfiniBand Network
• 100 TB SAS disk, or
336 TB SATA disk
• Redundant 40Gb/s switches
• 5 TB PCI Flash
• Unified server & storage net
• Data mirrored across
storage servers
Database Server Hardware
Dual-redundant, hotswappable power supplies
72 GB DRAM (18 x 4GB)
4 x 2.5” 146GB Disk Drives
ILOM
4 x 1GbE Interfaces
InfiniBand QDR
(40Gb/s) dual
port card
2 Quad-Core Intel®
Xeon® E5540 Processors
Disk Controller
HBA with 512M
battery backed
cache
Installed Software:
• Oracle Enterprise Linux
• Oracle Database 11.2 Software
• Drivers
Start Small and Grow
Field Upgradeable
Quarter
Rack
Half
Rack
Full
Rack
Balanced Incremental Scaling for OLTP and DW
Scales to 8 Racks by Just Adding Cables
Full Bandwidth and Redundancy
Exadata Database Machine
Product Family
Quarter
Rack
Half Rack
Full Rack
2-8 Full Racks
Database Servers
2
4
8
16-64
Exadata Storage Servers
3
7
14
28-112
Total Disk Capacity SAS
21 TB
50 TB
100 TB
200 – 800TB
Total Disk Capacity SATA
70 TB
168 TB
336 TB
336 – 2688TB
User Data (uncompressed
SAS)
6 TB
14 TB
28 TB
56 – 224 TB
I/O Throughput (disks SAS)
4.5 GB/sec
10.5 GB/sec
21 GB/sec
42 - 168 GB/sec
I/O Throughput (flash)
11 GB/sec
25 GB/sec
50 GB/sec
100 - 400 GB/sec
Flash IOPS
225,000
500,000
1,000,000
1M – 8M
Racks
1
1
1
2-8
Standardized and Simple to Deploy
• All Database Machines are the same
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Delivered Tested and Ready-to-Run
Highly Optimized
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
Deploy in Days,
Not Months
• Leverages Oracle ecosystem
• Skills, knowledge base, people, partners
Agenda
• Hardware Architecture
• Key Technologies
• Consolidation & Protection
Keys to Speed and Cost Advantage
Exadata Hybrid
Exadata Intelligent
Columnar Compression
Storage Grid
Exadata Smart
Flash Cache
Exadata Intelligent Storage Grid
Most Scalable Data Processing
• Data Intensive processing runs in Exadata
Storage Grid
• Filter rows and columns as data streams from
disks
• Example: How much product X sold last quarter
• Exadata Storage Reads 10TB from disk
• Exadata Storage Filters rows by Product & Date
• Sends 100GB of matching data to DB Servers
• Scale-out storage parallelizes execution and
removes bottlenecks
Simple Query Example
Optimizer
Chooses
Partitions to
Access
What were my
sales yesterday?
Oracle
Database Grid
Select
sum(sales)
where
Date=’24-Sept’
SUM
Exadata
Storage Grid
Scan compressed
blocks in
partitions
Retrieve sales
amounts for
Sept 24
10 TB scanned
100 GB returned to servers
Exadata Intelligent Storage
• Exadata storage servers also run more complex
operations in storage
Exadata Intelligent
Storage Grid
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Join filtering
Incremental backup filtering
I/O prioritization
Storage Indexing
Database level security
Offloaded scans on encrypted data
Data Mining Model Scoring
Smart File Creation
• 10x reduction in data sent to DB servers
is common
Exadata is Smart Storage
• Storage Server is smart storage, not a DB node
• Storage remains an independent tier
Compute and Memory
Intensive Processing
• Database Servers
• Perform complex database processing such as
joins, aggregation, etc.
• Exadata Storage Servers
Data Intensive
Processing
• Search tables and indexes filtering out data that is
not relevant to a query
• Cells serve data to multiple databases enabling
OLTP and consolidation
• Simplicity, and robustness of storage appliance
Exadata Hybrid Columnar Compression
• Data is organized and compressed by column
Query
• Dramatically better compression
• Speed Optimized Query Mode for Data
Warehousing
• 10X compression typical
• Runs faster because of Exadata offload!
• Space Optimized Archival Mode for
infrequently accessed data
• 15X to 50X compression typical
Faster and Simpler
Backup, DR, Caching,
Reorg, Clone
Benefits Multiply
Exadata Hybrid Columnar Compression
How it works
Compression
Unit
• Tables are organized into sets of a few thousand rows
• Compression Units (CUs)
• Within CU, data is organized by column, then
compressed
• Column organization brings similar values close together,
enhancing compression
Reduces
Table
Size
4x
to 50x
Reduction
4x to 40x
• Useful for data that is bulk loaded and queried
• Update activity is light
• Exadata servers offload filtering, projection, etc. for
scans on compressed data
• Return compressed blocks to database so buffer cache
benefits from compression
Compression Ratio of Real-World Data
• Compression Ratio varies by
customer and table
• Trials were run on largest table
at 10 large companies
• Average Query Compression
ratio was 13x
• On top of Oracle’s already
highly efficient format
Hybrid Columnar Comparisons
Uncompressed
Uncompressed
OLTP Compress
OLTP
Hybrid
Pure
Column
Table Size
Pure
Columnar
Cliff
Hybrid
Pure Column
Scan Time
Row Lookup Time
• Exadata Hybrid Columnar Compression is a second generation
columnar technology combining the best of row and column formats
• Best compression – matching full columnar
• Excellent scan time – Compression provides 10x speedup
• After 10x I/O reduction, most queries become CPU bound
• Good single row lookup – no full columnar “cliff”
Exadata Smart Flash Cache
Breaks the Disk Random I/O Bottleneck
300 I/O per Sec
• Trade-off between traditional disks drives and
Flash
• Disk drives are cheap, high capacity but low I/Os per
second
• Flash is expensive, lower capacity but can support
tens of thousands of I/Os per second
• Ideal Solution - Exadata Smart Flash Cache
Tens of Thousands of
I/O’s per Second
• Keep most data on disk for low cost
• Transparently move hot data to flash
• Use flash cards instead of flash disks to avoid disk
controller limitations
• Flash cards in Exadata storage
• High bandwidth, low latency interconnect
Sun FlashFire in Exadata
Sun Flash Accelerator F20 PCIe Card
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Cell cache on the storage cells
Write-though cache, transparently used to accelerate reads
4 x Cards (384GB/cell) used to create a cache on the cell
Database Machine has 5 TB of flash storage
Able to pull 3.6GB/sec total bandwidth from each storage cell, for
Full Rack:
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50GB/sec total from flash
21GB/sec from SAS disk, 12Gb/sec SATA disk
Up to 50,000 Disk IOPS SAS or Up to 20,000 Disk IOPS SATA
Up to 1,000,000 Flash IOPS
Exadata Smart Flash Cache
• Performance
• Use PCIe cards instead of SSDs to avoid slow disk interface
• Capacity
• Efficient Compression increases effective performance and capacity by up
to 10X
• Smart Caching
• Caches data intelligently to maximize Flash usage for frequently read data
• Automatically skips caching of infrequently read objects or avoid caching
data that will not fit in the cache
• Database awareness enables caching only data likely to be
accessed again
• User can further optimize caching policies by specifying whether or not to
cache specific database objects
Exadata is Architected for Flash
• Traditional storage arrays now offer optional flash disks
Exadata Flash
Architecture
Scale-Out Storage
No bottlenecks to scaling flash I/O
InfiniBand
Highest throughput, lowest latency
Intelligent Storage
Key to using full flash bandwidth
Even InfiniBand can’t send 50GB/sec
PCI Flash
Avoids disk controller bottlenecks.
Cards in storage enable HA, RAC
Compression
Multiply flash capacity 10x
Also multiplies data scan rates
Flash Cache
Speed of flash, cost of disk
Optionally specify table placement
Exadata Storage Index
Transparent I/O Elimination with No Overhead
Table
A
Index
B C D
1
3
5
5
8
Min B = 1
Max B =5
• Exadata Storage Indexes maintain summary
information about table data in memory
• Store MIN and MAX values of 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
Min B = 3 • Completely automatic and transparent
Max B =8
3
Select * from Table where B<2 - Only first set of rows can match
Benefits Multiply
Example
10 TB of user data
Normally 10 TB of IO
1 TB
with 10x compression
100 GB
with partition pruning
Seconds
On Exadata
50 GB
with Storage Indexes
Scan 50GB in Flash
10 GB returned after
Exadata Filtering
Data is 10x Smaller, Scan is 2000x faster
Agenda
• Hardware Architecture
• Key Technologies
• Consolidation & Protection
Unified Hardware, Specialized Software
• Exadata enables a single hardware architecture for
all database needs
OLAP
• Massively parallel hardware, InfiniBand, & Flash for
all DB applications and workloads
• Enables Strategic building block approach to IT
• Domain specialization is in software, not hardware
ETL
Data Mining
• Analytics
• OLAP, Statistics, Spatial, Data Mining, etc.
• Warehousing
• Flexible Partitioning, Bitmap Indexing, Join
indexing, Materialized Views, Result Cache
• Data
• Relational, XML, Objects, Secure Files
• OLTP, Security, HA
Platform for Database Consolidation
• Consolidation is key to reducing costs
ERP
• Administration, hardware, software, data center
CRM
• Many databases can be consolidated on Exadata
Warehouse
Data Mart
HR
• Multiple small databases within a node
• Large databases can span nodes using RAC
• Exadata serves as farm/cloud for databases
• Exadata delivers performance for complex
workloads that mix OLTP and DW
• Complex OLTP with batch and reporting
• Complex Warehousing with thousands of users
• Multiple databases running different applications
Consolidate Database Storage
ERP
CRM
Warehouse
Data Mart
HR
• Exadata and ASM allow all storage servers to be
shared across databases
• Shared Configuration
• Advanced ASM data striping spreads every
database across all storage servers
• Eliminates hot-spots and captive unused space
• Full storage grid performance available to all
databases
• Predictable Performance
• Exadata I/O resource manager prioritizes I/Os to
ensure predictable performance
• At user, job, application, or database level
• No need for isolated storage islands
Consolidate Database Servers
• Many databases can run on Database Machine
servers
ERP
CRM
Warehouse
HR
Data
Mart
• Shared Configuration
• Applications connect to a database service that
runs on one or more database servers
• Services can grow, shrink, & move
dynamically
• 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
Resources
• Oracle.com:
http://www.oracle.com/exadata
• Oracle Exadata Technology Portal on OTN:
http://www.oracle.com/technology/products/bi/db/exadata