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Extreme Performance…. Thomas Kyte http://asktom.oracle.com/. The Beginning. Data Model with Structure Data Independent of Code Set-oriented 1977 the work begins. “A Relational Model for Large Shared Databanks”. E.F. Codd - 1970. GPS 1978. GPS 1978. First RDBMS: Version 2 June 1979.

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Extreme performance

Extreme Performance…

Thomas Kyte

http://asktom.oracle.com/


The beginning

The Beginning...

  • Data Model with Structure

  • Data Independent of Code

  • Set-oriented

  • 1977 the work begins

“A Relational Model forLarge Shared Databanks”

E.F. Codd - 1970


Gps 1978

GPS 1978


Gps 19781

GPS 1978


First rdbms version 2 june 1979

First RDBMS: Version 2 June 1979

  • FIRST Commercial SQL RDBMS

  • Impressive First SQL

    • Joins, Subqueries

    • Outer Joins, Connect By

  • A Simple Server

    • No transactions, ‘Limited’ Reliability

  • Portability from the Start

    • Written in Fortran

    • But multi-platform – PDP11, Dec VAX


Ibm pc 1981

IBM PC – 1981

IBM model number 5150, introduced on August 12, 1981.


Internet as we know it 1983

Internet (as we know it) – 1983

The first TCP/IP-based wide-area network was operational by January 1, 1983 when all hosts on the ARPANET were switched over from the older NCP protocols.


Portability version 3 march 1983

Portability: Version 3 March 1983

  • New Implementation Designed for Portability

    • Written in ‘C’

    • Single Source

  • Architectural Changes

    • Transactions, multi-versioning, no read consistency

    • AI/BI files

  • Oracle Corporation – name established


Cooperative server version 5 april 1985

Cooperative Server: Version 5 April 1985

  • My First Oracle Experience

    • 1st Client/Server

    • Cooperative Server

      • Distributed Processing

      • Parallel Server

    • Portability

      • V5 was first to go beyond 640K memory on PCs

      • Single-user for Macintosh o/s

    • SQL_TRACE

      • select trace('sql',1),1 from dual;


Transaction processing version 6 july 1988

Transaction Processing: Version 6 July 1988

  • New Architecture

    • Performance (first SMP)

    • Availability

    • TPO

    • PL/SQL

  • V6 Lays Architectural Groundwork for the Future

    • This was a rewrite of the entire database fundamentally


  • World wide web 1990 ish

    World Wide Web – 1990’ish

    The World Wide Web was created in 1989 by British scientist Tim Berners-Lee, working at the European Organization for Nuclear Research (CERN) in Geneva, Switzerland, and released in 1992.


    Oracle7 3 february 1996

    Oracle7.3 February 1996

    • Spatial Data Option

    • Tablespaces changes - Coalesce, Temporary Permanent,

    • Trigger compilation, debug

    • Unlimited extents on STORAGE clause.

    • Some init.ora parameters modifiable - TIMED_STATISTICS

    • HASH Joins, Antijoins

    • Histograms

    • Oracle Trace

    • Advanced Replication Object Groups

    • Partitioned Views

    • Bitmapped Indexes

    • Asynchronous read ahead for table scans

    • Standby Database

    • Deferred transaction recovery on instance startup

    • Updatable Join View

    • SQLDBA no longer shipped.

    • Index rebuilds

    • DBV introduced

    • Context Option

    • PL/SQL - UTL_FILE


    Data warehouses growing rapidly tripling in size every two years

    1000

    800

    600

    Terabytes of Data

    Actual

    400

    Projected

    200

    1998

    2000

    2002

    2004

    2006

    2008

    2010

    2012

    Data Warehouses Growing RapidlyTripling In Size Every Two Years

    Size of the Largest Data Warehouses

    Source: Winter TopTen Survey, Winter Corporation, Waltham MA, 2008.


    Extreme performance1

    Extreme Performance


    The performance challenge storage data bandwidth bottleneck

    The Performance ChallengeStorage Data Bandwidth Bottleneck

    • Current warehouse deployments often have bottlenecks limiting the movement of data from disks to servers

      • Storage Array internal bottlenecks on processors and Fibre Channel Loops

      • Limited Fibre Channel host bus adapters in servers

      • Under configured and complex SANs

    • Pipes between disks and servers are 10x to 100x too slow for data size


    Data warehouses start slowdown at 1tb

    10 Hours

    Typical High-End Array

    Table Scan Time

    Typical Mid-Range Array

    5 Hours

    Typical NAS

    1 Hour

    Table Size

    1TB

    10 TB

    100TB

    Data Warehouses Start Slowdown at 1TB


    Solutions to data bandwidth bottleneck

    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


    What we announced at openworld

    What We Announced at OpenWorld

    Extreme Performance | Unlimited Scalability | Enterprise Ready


    Hp oracle database machine the next step in dw hardware solutions

    HP Oracle Database Machine:The next step in DW Hardware Solutions

    Custom

    Reference

    Configurations

    Optimized

    Warehouse

    HP Oracle

    Database

    Machine

    • Complete Flexibility

    • Any OS, any platform

    • Easy fit into a company’s IT standards

    • Documented best-practice configurations for data warehousing

    • Scalable systems pre-installed and pre-configured: ready to run out-of-the-box

    • Highest performance

    • Pre-installed and pre-configured

    • Sold by Oracle


    Products announced

    Products Announced

    HP Exadata Storage Server Hardware

    • Paired with Oracle Exadata Storage Server Software

    • Delivers database intelligence in storage tier

    • Supported for Oracle Enterprise and Red Hat servers running Oracle Database 11g Enterprise Edition*

      HP Oracle Database Machine

    • Simplicity of appliance seamlessly integrated with the database

    • Eliminates all bottlenecks preventing high performance data scans

    • Includes Exadata Storage Server

    • Dramatic performance improvement for data warehouses

    * Linux 5.1 releases with appropriate Infiniband drivers,

    Oracle Database 11g Enterprise Edition vers. 11.1.0.7


    First hp oracle database machine

    FirstHP Oracle Database Machine


    The hp oracle database machine sales support model

    The HP Oracle Database MachineSales / Support Model

    • System Delivery

    • Hardware Service

    • System Sales

    • System Support

    Oracle Technology Sales Manager is the single point for sales

    Oracle is single point for Support


    Second hp exadata storage server hardware

    SecondHP Exadata Storage Server Hardware

    • 2 Intel processors, 8 cores

    • 12 disk drives, up to 12 TB raw storage

    • 2 Infiniband connections

    • Oracle Enterprise Linux OS


    Oracle exadata storage server software reduces data going through the pipes

    Oracle Exadata Storage Server Software Reduces Data Going through the Pipes

    • Intelligent storage server

      • Unique ‘smart scan’ technology

    • Returns query result set

      • Not disk blocks


    Traditional scan processing

    Traditional Scan Processing

    SELECT customer_name

    FROM calls WHERE amount > 200;

    • 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

    Rows Returned

    DB Host reduces terabyte of data to 1000 customer names that are returned to client

    Table Extents Identified

    I/Os Executed:

    1 terabyte of data returned to hosts

    I/Os Issued


    Exadata smart scan processing

    Exadata Smart Scan Processing

    SELECT customer_name

    FROM calls WHERE amount > 200;

    Rows Returned

    • Only the relevant columns

      • customer_name

        and required rows

      • where amount>200

        are 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

    Consolidated Result Set Built From All Cells

    Smart Scan Constructed And Sent To Cells

    Smart Scan identifies rows and columns within terabyte table that match request

    2MB of data returned to server


    Additional smart scan functionality

    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

    • Backups

      • I/O for incremental backups is much more efficient since only changed blocks are returned

    • Create Tablespace (file creation)

      • Formatting of tablespace extents eliminates the I/O associated with the creation and writing of tablespace blocks


    Smart scan transparency

    Smart Scan Transparency

    • Smart scans are transparent to the application

      • No application or SQL changes required

      • Returned data is fully consistent and transactional

      • If a cell dies during a smart scan, the uncompleted portions of the smart scan are transparently routed to another cell

    • Smart Scans correctly handle complex cases including

      • Uncommitted data and locked rows

      • Chained rows

      • Compressed tables

      • National Language Processing

      • Date arithmetic

      • Regular expression searches

      • Partitioned tables

    High Throughput, Reduced Overhead, No Complex Tuning


    Massively parallel storage grid

    16 GB/sec

    8 GB/sec

    4 GB/sec

    Massively Parallel Storage Grid

    • Exadata Storage servers are organized into a massively parallel storage grid

    • Scalable

      • Scales to hundreds of storage servers

      • Data automatically distributed across storage servers by ASM

        • Transparently redistributed when storage servers are added or removed

      • Data bandwidth scales linearly with capacity

    • Available

      • Data is mirrored across storage servers

      • Failure of disk or storage server transparently tolerated

    • Simple

      • Works transparently - no application changes

    Exadata bandwidth scales linearly with capacity


    Exadata performance scales

    Exadata delivers brawny hardware for use by Oracle’s brainy software

    Performance scales with size

    Result

    More business insight

    Better decisions

    Improved competitiveness

    Exadata Performance Scales

    10 Hour

    Table Scan Time

    Typical Warehouse

    5 Hour

    1 Hour

    Exadata

    Table Size

    1TB

    10 TB

    100TB


    Exadata co existence and migration

    Database

    Server

    Online Migration

    Exadata

    Non-Exadata

    Exadata Co-Existence and Migration

    • Databases can be concurrently deployed on Exadata and traditional storage

      • Tablespaces can exist on Exadata storage, traditional storage, or a combination of the two, and is transparent to database applications

      • SQL offload processing requires all pieces of a tablespace reside on Exadata

    • Online migration if currently using ASM and ASM redundancy

    • Migration can be done using RMAN or Data Guard


    M tel exadata speedup 10x to 72x performance improvement

    M-Tel Exadata Speedup 10X to 72X Performance Improvement

    28x

    Average

    Speedup


    Extreme performance

    Plamen Zyumbyulev

    Head of Database Administration

    M-Tel

    “Every query was faster on Exadata compared to our current systems. The smallest performance improvement was 10xand the biggest one was an incredible 72x.”


    Extreme performance

    Grant Salmon

    Chief Executive Officer

    LGR Telecommunications

    “Call Data Record queries that used to run for over 30 minutes now complete in under 1 minute.

    That's extreme performance.”


    Giant eagle exadata speedup 3x to 48x performance improvement

    Giant Eagle Exadata Speedup 3X to 48X Performance Improvement

    16x

    Average

    Speedup


    Extreme performance

    Walt Litzenberger

    Director Enterprise Database Systems

    The CME Group

    “Oracle Exadata outperforms anything we’ve tested to date by 10 to 15 times. This product flat-out screams.”


    Where can you try it

    Where Can You Try It?

    • North America Enterprise Technology Centers (ETC)

      • Atlanta, GA

        • Two HP Oracle Database Machines, each with 8 database server nodes and 14 HP Exadata Storage Server cells holding 12 drives of 1 TB in size each

        • Capacity of about 46 TB of uncompressed data / rack

      • Reston, VA

        • Three HP Oracle Database Machines, each with 8 database server nodes and 14 HP Exadata Storage Server cells holding 12 drives of 300 GB in size each

        • Capacity of about 14 TB of uncompressed data / rack

    A queue has already formed!


    Exadata benefits

    Exadata Benefits

    • Extreme Performance

      • 10X and more speedup for data warehousing

    • Database Aware Storage

      • Smart Scans

    • Massively Parallel Architecture

      • Dynamically Scalable to hundreds of cells

      • 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


    Resources

    Resources

    • Oracle.com:http://www.oracle.com/exadata

    • Oracle Exadata Technology Portal on OTN: http://www.oracle.com/technology/products/bi/db/exadata

    • Oracle Exadata white papers: http://www.oracle.com/technology/products/bi/db/exadata/pdf/exadata-technical-whitepaper.pdf

      http://www.oracle.com/technology/products/bi/db/exadata/pdf/migration-to-exadata-whitepaper.pdf


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