Enterprise Applications

Enterprise Applications
Product Family Contracts, Corporate Performance Management, Customer Relationship Management, Financials, Human Resources, Interaction Center, Intelligence, Maintenance Management, manufacturing, Marketing, Order Management, Procurement, Product Lifecycle Management, projects, Sales, Service, Supply Chain Planning, Supply Chain Management Oracle Ebusiness Suite online document available

Infrastructure Software

A Brief look at Oracle’s Database History
Oracle Parallel Server Oracle 8i Transition to Real Application Clusters begins Oracle 9i Integrated Data Warehousing Real Application Clusters Oracle 10g New grid capable features

Federated Database A logical unification of distinct databases
Independent servers No shared resources (including disk) Connected by LAN

Shared Disk Architecture
Equal access to all disks No notion of data ownership on any node Managed by Oracle’s Real Application Clusters (RAC)

Shared Disk Architecture: Scalable
Nodes can be dynamically added and removed from the grid Adding and removing nodes does not require data to be redistributed Multi-version read consistency model Based upon Real Application Clusters

Multi-Version Read Consistency
Writers never block readers and readers never block writers Data is tracked by a System Change Number (SCN) Always provides consistent and accurate results Non-escalating row-level locking Locks are contained at the row level

Example: System Change Number

Shared Disk Architecture: Availability
The loss of a cluster node does not cause a loss of data The loss of a cluster node does not cause another node to “take over” data Processes can be redistributed to other nodes

Traditional Shared-Disk Clustered Databases
Maintaining data coherency is a hard problem Need to synchronize updates to shared data The disk is the only medium for data sharing Disk I/O latencies appear in the critical path when multiple nodes access shared data Disk-based coherency is the main bottleneck to achieving a scalable shared disk cluster Only synthetic fully partitioned workloads scale! Unless data is carefully partitioned to ensure that two nodes never access the same data block, applications on shared-disk systems will bottleneck on inter-node synchronization disk I/O.

Oracle Real Application Clusters (RAC)
An application transparent clustered database single node applications run and scale with no changes Cluster interconnect fabric replaces the disk as the medium for inter-node data sharing Cache Fusion protocol for data sharing results in a scalable cluster for OLTP and DSS workloads Data blocks can be shipped directly between nodes without expensive disk-based synchronization.

Oracle RAC Architecture
Users Centralized Management Console Application Servers/ Network Low Latency Interconnect No Single Point Of Failure High Speed Switch or Interconnect Clustered Database Instances Shared Cache A cluster is a group of independent servers that cooperate as a single system. The primary cluster components are processor nodes, a cluster interconnect, and a shared disk subsystem. The clusters share disk access and resources that manage data, but the distinct hardware cluster nodes do not share memory. A cluster can be made up of multiple single-processors, otherwise known as Symmetric Multi-Processor or SMP nodes. Each node has its own dedicated system memory as well as its own operating system, database instance, and application software. Clusters provide improved fault resilience and modular incremental system growth over single symmetric multi-processors. In the event of system failures, clustering ensures high availability to users. Redundant software components, such as additional nodes, interconnects, and disks, provide high availability. Such redundant hardware architectures avoid single points-of-failure and provide exceptional fault resilience. Hub or Switch Fabric Storage Area Network Drive and Exploit Industry Advances in Clustering Mirrored Disk Subsystem

What is Cache Fusion? The underlying technology that enables RAC
Protocol that allows instances to combine their data caches into a shared global cache Global Cache Service (GCS) coordinates sharing Key features are Direct sharing of volatile buffer caches Efficient inter-node messaging framework Fast recovery from node failures using cache and CPU resources from all surviving nodes

Data Sharing Problem Read Sharing for Queries
query needs to read a data block that is currently in another instance’s buffer cache. Write Sharing for Updates update needs to modify a data block that is currently in another instance’s buffer cache. With Cache Fusion, a disk read is performed only if the block is not already in the global shared cache A query needs a transactionally consistent copy shipped to it. An update needs a current (updateable) copy shipped to it.

Cache Fusion Read Sharing
Uses Oracle’s Consistent Read (CR) scheme undo is applied to make a block transactionally consistent to a System Change Number (SCN). a CR copy is shipped to the requesting instance 1 Query SCN 200 225 Data Block CR is a versioning-based concurrency protocol that allows transactions to perform reads without locks. Uses rollback segments to apply undo. Instance A issues a query at SCN 1000 that requires reading a block currently in Instance B’s buffer cache. Instance B creates a CR clone of the block at SCN 1000, then ships it to Instance A across the interconnect. There is no change in resource ownership, so no impact on B. CR Copy 200 2 3 Instance A Instance B

Cache Fusion Write Sharing
Multiple dirty copies of a data block can exist in the global cache, but only one is current The current copy can move between instances without first being written to disk Changes are logged if not already on disk Non-current dirty copies can directly service queries from any node and instance recovery An instance holding the modify lock on a cache resource (block) has ownership of the resource.

Cache Fusion Write Sharing
Instance A Instance B 4 Update Block 10 Current 225 2 1 Master Copy 225 3 Requester GCS Holder 200 Instance C

Efficient Inter-Node Messaging
Messaging cost independent of cluster size At most 3 nodes involved in a request requester, holder and master (directory) number of messages to service a request is bounded Inter-Node Message Latency exploits high performance interconnect substrates so that on-the-wire message transmission times are minimal Frequency of Inter-Node Synchronization adaptive directory migration based on access patterns fast reconfiguration of resources when a node joins/leaves

Oracle Grid Computing Goals
Storage Grid Database Grid Application Grid Grid Control Half the Cost Highest Quality of Service Easiest to Manage Oracle has created a grid computing infrastructure software that balances all types of workloads across servers, and enables all those servers to be managed as one complete system. Grid computing can achieve the same very high level of reliability as a mainframe because all components are clustered. But unlike mainframes and large UNIX SMP servers, a grid can be built with open systems technologies such as Intel processors and the Linux operating system so it’s very low cost.

Problem with Today’s IT Infrastructure
Islands of Computing Resource Some are melting down Some are almost idle High Costs Hardware Labor Software Hard to Align with Business Priorities CRM ERP DW

Solution: Computing On Demand
Mainframe Model Grid Computing Model Partitioning of one large server Built with high quality, high cost parts Complete, integrated software High quality of service at high cost Coordinated use of many small servers Built with low cost, standard, modular parts Open, Complete, integrated software High quality of service at low cost

What about Grids for the Enterprise?
Early Grid Computing Desktop Grids Scientific Research Grids Globus Toolkit, CERN What about Grids for the Enterprise? 11

Requirements for Enterprise Grids
Run all your applications Stores all your information Highly scalable, available, reliable Secure Easy to manage Make individual systems self-managing Manage thousands of servers at once

10G Introducing Oracle 10G Runs all your applications
Stores all your information Highly scalable, available, reliable Secure Easy to manage Make individual systems self-managing Manage thousands of servers at once 10G

Oracle Database 10G – The First Database Designed for the Grid

Orders of MAGNITUDE… ~354 NEW 10g features * @5 slides / feature *
@2 minutes /slide = 4.5 DAYs [ 9 hour/day ]

Oracle Database 10G – Database for the Grid
Storage for All Your Data Real Application Clusters High Availability Ease of Management Data Provisioning across Grid Business Intelligence on the Grid Application Development on the Grid

Oracle Database 10G – Align Storage with the Business
Problem: Islands of storage “My storage is 50% utilized and growing 30% a year” CRM ERP DW

Oracle Database 10G – Align Storage with the Business
Problem: Islands of storage “My storage is 50% utilized and growing 30% a year” Solution: Groups of standard, modular disks Consolidated, Networked Storage Dynamically Provision

Oracle Grid Storage Management Highly Available and Low Cost
Oracle Automatic Storage Management Manages disk storage groups Mirrors, Stripes, Re-balances Huge reduction in labor cost Built-In Data Protection at Lowest Cost Disk Based Backup and Recovery Flashback in Time Site Recovery Automatic Storage Management Disk Based Backup & Recovery

Automatic Storage Management – Dynamically Provision and Tune Storage
Portable, high performance file system Eliminates need for conventional file system and volume manager Automatic mirroring Automatic I/O tuning Stripes data across disks to balance load

ASM The Operational Stack ASM TODAY
Tables Tables Tablespace Tablespace ASM Files Files File System File System Logical Vols Logical Vols Disks Disk Group “The best way to lower mgmt costs is to remove complexity”

A pool of disks managed as a logical unit
ASM Disk Groups A pool of disks managed as a logical unit Partitions total disk space into uniform sized megabyte units ASM spreads each file evenly across all disks in a disk group Coarse or fine grain striping based on file type Disk groups integrated with Oracle Managed Files Disk Group

Administer disk groups not files
ASM Disk Groups Administer disk groups not files Number of disk groups remains constant while number of files and disks continually increases Fast Disk Group Slow Disk Group

Mirroring with ASM Failure Groups
Controller 1 Controller 2 Storage resources organized into Disk Groups and Failure Groups A Disk Group is a collection of disks managed as a logical unit in which ASM files are stored Disk Groups assigned by DBAs A Failure Group is a set of disks sharing a common resource whose failure needs to be tolerated Redundant copies of an extent are stored in separate Failure Groups Failure Groups assigned by DBAs or automatically by ASM Disk Group 1

Automatic Storage Management – Lowest Labor Cost
8 7 7 6 6 6 5 4 2 2

ASM Delivers Great Performance with no Manual Tuning
22,648 20,590

Automatic Storage Management -Mission Critical, Low Cost Storage for Enterprise Grids
Integrated mirroring Add/drop disk online Best I/O performance Easy Automatic I/O Tuning Up to 50% less DBA/Sys Admin work Low Cost Works well with inexpensive disks Better storage utilization

Oracle DB 10G Stores All Your Data
Complete Integrated Relational Characters, Numbers and Dates Oracle Text Text management and search Oracle interMedia Multimedia management Oracle Locator Location and Proximity Searching XML DB Integrated Native XML Database OCS Files Low-cost and Easy

Oracle DB 10G ULDB - Stores ALL Your Data
Database size limit raised to millions of Terabytes (8 Exabytes) Ultra Large Data Files – Terabytes in single file Unlimited size LOB columns – Terabytes Automatic Storage Management removes file system limits

Align Processing with the Business
Problem: Islands of computation “My servers are 15% utilized“ CRM ERP DW

Align Processing with the Business
Problem: Islands of computation “My servers are 15% utilized“ Solution: Groups of industry standard servers Lowest cost, highest performance Capacity on demand Not Self-healing, Disposable

Oracle Database 10G RAC Capacity on Demand for the Grid
Only Cluster Database that runs Real Applications and Scales Highly Available Runs on standard, low cost servers Proven Hundreds of customers Certified with leading apps ERP CRM DW

Automatic Workload Management
Order Entry Spare Supply Chain Normal Server Allocation

Automatic Workload Management
Order Entry Supply Chain End of Quarter

Oracle Database 10G RAC - Complete, Integrated Clusterware
Complete Oracle cluster software solution Single-vendor support Low Cost No need to purchase additional software Easy to install, manage High quality and functionality across all platforms Common event and management API’s Support for third-party clusterware Connectivity Messaging and Locking Cluster Control/Recovery Services Framework

Benefits of Integrated Clusterware
Lower software cost Easy Deploys in hours not days Single integrated target for cluster management provides improved single system image Less Risk Same high functionality and quality across platforms Single vendor support

Automatic Server Provisioning
Push-button add/drop server to cluster Hands-free allocation and re-allocation of servers to services Automatic routing of service requests to appropriate server with lowest load On server failure, automatic re-allocation of surviving servers to services Works across all platforms

Oracle RAC 10G - Only Solution for Enterprise Grids
Mission Critical Quality of Service on Industry Standard, Low Cost Servers Complete, Integrated Oracle Clusterware Runs all Applications Provides Capacity on Demand RAC Made Easy for Everyone Automatic Server Provisioning

Low Cost Fault Tolerance
Computer Failures Unplanned Downtime Data Failures System Changes Planned Downtime Data Changes

Low Cost Fault Tolerance
Oracle10G RAC Integrated clusterware Integrated, less moving parts, better tested Faster failover between servers Single digit seconds Computer Failures Unplanned Downtime Data Failures System Changes Planned Downtime Data Changes

New Economics for Data Protection & Recovery
Computer Failures Disk-Based Recovery Unplanned Downtime Data Failures Trade cheap disk space for expensive downtime System Changes Planned Downtime Data Changes

Like a “Rewind” button for the Database
Flashback Database New strategy for point-in-time recovery Flashback Log captures old versions of changed blocks Think of it as a continuous backup Replay log to restore DB to time Restores just changed blocks It’s fast - recovers in minutes, not hours It’s easy - single command restore SQL> Flashback Database to ‘2:05 PM’ Old Block Version Disk Write New Block Version Flashback Log Like a “Rewind” button for the Database

Nightly Apply of Incremental Backup
Flash Backup Fully automatic disk-based backup and recovery Set and Forget Nightly incremental backup rolls forward recovery area backup Changed blocks are tracked in production DB Dramatically faster (20x) Use low cost ATA disk array for recovery area Database Area Recovery Area Tape Nightly Apply of Incremental Backup Weekly Archive to Tape

Oracle Database 10G Highest Data Protection for Lowest Cost
Site Failure Protection Redo Shipping Data Guard Corruption Protection On Disk Backups Flash Backup Human Error Protection Flashback Logs Flashback Storage Failure Protection ASM Mirroring

Online Reconfiguration
No Cost System Changes Goal Computer Failures Allow any change to the system with no downtime Unplanned Downtime Data Failures System Changes Online Reconfiguration Planned Downtime Rolling Upgrades Data Changes

Oracle10G High Availability Features
Backup and Recovery Automated Disk-Based Backup and Recovery Drop Database RMAN Database Deregistration Backup of Standby Control File Automated TSPITR Instantiation Simplified Recovery Manager Cataloging of Backup Files Automated Channel Failover for Backup and Restore Automated File Creation During Recovery Simplified Backups to Disk Proxy Copy Backup of Archivelogs Backup and Recovery (Cont) Incrementally Updated Backups Simplified Recovery Through Resetlogs Restore Tolerates Corrupt or Missing Backups Full Database Begin Backup Command Change-Aware Incremental Backups Data Guard Data Guard Broker Support for RAC Automated LogMiner Configuration Log Miner Support for Index-Organized Tables Secured Redo Transmission Data Guard (Cont) Fine-Grained Supplemental Logging Named Data Guard Configurations Simplified Zero Data Loss for Data Guard SQL Apply Zero Downtime Instantiation for SQL Apply Real Time Apply Redo Data and Archivelog Compression Flashback Flashback Database Flashback Reinstantiation Flashback Standby Database Flashback Table Flashback Row History Flashback Drop Flashback Transaction History Online Operations Enhanced Online Redefinition Improved Handling of DDL Locks on Busy Tables Signature-Based Dependency Tracking Using Synonyms Rolling Upgrades with Data Guard SQL Apply

Oracle Database 10G Ease of Management
Self-Managing Database OEM Grid Control Grid-wide operations Scale from one to hundreds of systems with little incremental cost

Business Challenge – How to Scale DBA’s to the Grid ?
Installation 6% Creation & Configuration 12 % Others 15% Software Maintenance 6% Data Loading 6% Ongoing System Management 55% Source: IOUG 2001 DBA Survey

Oracle10G System Management – Built-In Intelligent Infrastructure
Automatic Workload Repository Automatically collects statistics, SQL workload, Feature usage Automatic Maintenance Tasks Pre-packaged, resource controlled Server-Generated Alerts Out-of-the-box, Push vs. Pull, Just-in-time

Oracle10G System Management – Automatic SGA Management
SQL Cache sort Online Users Large Pool Buffer Cache Java Pool SGA Pool PGA Pool Large Batch Jobs sort Java Pool SQL Cache Large Pool Buffer Cache Only 2 memory parameters Advisor helps set parameters Automatically resizes with changes in workload Maximize usage of available memory

Oracle10G System Management – Self Optimizing SQL Management
Oracle Query Optimizer – Proven Technology Comprehensive set of access paths, adaptive search strategy All cost-based transformations Preconfigured task to collect object and system statistics If no statistics available, are collected at parse-time Automatic memory allocations, automatic degree of parallelism Automatic identification and capture of high-load SQL Automatic SQL Tuning Automatic SQL Analysis SQL Access Advisor

Oracle10G System Management – Self Optimizing SQL Management
Automated capture and identification of high-load SQL Automatic SQL Tuning Automatic SQL Analysis SQL Access Advisor High-load SQL Packaged Applications Custom Applications Optimizer Auto SQL Tuning Auto SQL Analysis Access Advisor Packaged Applications SQL Profile Custom Applications SQL Advice Indexes & MVs Custom Applications Well-tuned SQL

Oracle10G System Management – Automatic Database Diagnostic Monitor
Performance expert in a box Automatically provides database-wide performance diagnosis, including RAC Pinpoints root cause and non-problem areas Runs proactively

Enterprise Manager 10G Grid Control Management that Scales to the Grid
Central management for the complete platform Dramatically lower operations costs Application service level management Manage one or many systems with little incremental cost

Scalable Software Maintenance – Discover and Analyze Configurations
Complete inventory of all Oracle software Versions Patch levels Oracle product configuration details Search and compare configurations Change tracking Reference configurations

Scalable Software Maintenance - Automated Software Cloning
Reduce manual labor in software life-cycle From hours to minutes Automate mass provisioning of reference systems Clone to Selected Targets 2 Select Software (and Instances) to Clone 1 3 Update Inventory

Scalable Software Maintenance - Automated Patch Management
Real-time discovery of new patches Security patch rapid deployment dramatically reduces vulnerabilities Automatic staging and application From hours to minutes Rolling RAC upgrade 2 Determine Applicability Apply Patch 3 4 Update Inventory 1 Patch Published

Oracle10G Manageability Features
Infrastructure Easy OracleJVM Monitoring SYSAUX Tablespace Enhanced Wait Model Database Features Usage Tracking Enhanced Database Time Model Top Consumers Performance Monitoring & Diagnostic JDBC: End-to-end Java/J2EE Tracing SQLJ: End-to-end Java/J2EE Tracing Automated Routine Administration Tasks Proactive Server-based Alerts and Notifications Database Statistics and Workload Respository Threshold-Based Alerts Server Configuration Automated Storage Management Configuration Automated RAC Services Configuration Simplified Upgrade for RAC and OPS Databases Automated Enterprise Manager Configuration Automated Portable Clusterware Installation Automated Configuration of Recovery Area Out-of-the-box LDAP Configuration Simplified Initialization Parameters Easy Upgrade Upgrade Information Tool Simplified Database Install User Default Tablespace Instance Tuning User-Initiated Buffer Cache Flushing Database Resource Manager - Adaptive Consumer Group Mapping Database Resource Manager - Fixed CPU Quota New Performance Overview Charts in Oracle Enterprise Manager Improved SQL Reporting Using Oracle Enterprise Manager Integration of Resource Manager and Profiles Automated Checkpoint Tuning Transaction Rollback & Recovery Monitoring Database Performance Analyzer Redo Logfile Sizing Advisor Automated SGA Memory Tuning Application Tuning SQLAccess Advisor Materialized View Tuning API SQL Tuning Advisor Enhanced SQLAccess Advisor Automatic Optimizer Statistics Collection Backup and Recovery Enhanced RMAN Reporting Backup Compression Bounded Backup Window Manage RMAN Scripts Recovery Area Full Alert Storage Management Multiple Default Temporary Tablespace Support for SQL Operations Automated Storage Management Rename Tablespace

Oracle10G Manageability Features (continued)
Network Management Back Up Directory Naming Entries to Local Naming File Dynamic Connection Manager Configuration Easy Connect Naming Method Easy OCI/JDBC Install Improved Network Outage Detection Automated LDAP Discovery for Clients Improved Connection Manager Access Rules Automated Shared Server Configuration Simplified Shared Server Configuration Parameters Space, Object, Transaction Mgmt Automatic Undo Retention Tuning Segment Shrink Advisor Segment Size Estimation Online Segment Shrink Proactive Tablespace Management Undo Advisor Database Utilities SQL*Plus - SPOOL CREATE, REPLACE, and APPEND Options SQL*Plus - Show Recycle Bin SQL*Plus - DBMS_OUTPUT After SELECT SQL*Plus - SET SQLPROMPT Runtime Variable Substitution SQL*Plus -COMPATIBILITY Command Line Option SQL*Plus - Run glogin.sql and login.sql After Each CONNECT iSQL*Plus Input Prompting Scheduler Core Scheduler Features Usability and Manageability Monitoring Recovery Support for Jobs in a Clustered Environment Job Processing ILMS Support Increased Throughput Redo Minimization Dynamic Slave Pool

Transportable Tablespaces – Fastest Way to Provision Data
Oracle can unplug and plug database data files Move and share data without unload and reload Plug/unplug performance independent of tablespace size Mount read-only tablespaces on multiple databases New: Now Works Cross-Platform! 24

Oracle10G Data Pump High performance import and export
60% faster than 9i export (single thread) 15x-20x faster than 9i import (single thread) Scales with parallel threads Network transfer data between databases with no intermediate representation

Same platform or cross platform
Oracle Streams Oracle Oracle Streams moves or copies tablespaces faster than FTP Detach, move, attach with one command Same platform or cross platform

Same platform or cross platform
Oracle Streams Oracle Oracle Streams moves or copies tablespaces faster than FTP Detach, move, attach with one command Same platform or cross platform Optionally stream delta updates Migrate to the Grid with the self-propelled database

Oracle Database 10G– Database for the Grid

Business Intelligence on the Grid
Lower Cost Leverage 10G hardware, software, labor savings Manage millions of terabytes Intelligence when you need it Real-time data feeds and integrated BI capabilities More value from your data Additional integrated BI capabilities

Managing Large Volumes of Data
Partitioning and parallelism are crucial for VLDB Partitioning provides ‘incremental’ operations for: WORK SMARTER Data loading, Indexing, Referential Integrity Backup and Recovery Queries Parallelism for all operations WORK HARDER DBA operations: loading, index-creation, table-creation, data-modification, backup and recovery End-user operations: Queries Unbounded scalability: Real Application Clusters There are two key capabilities necessary for supporting large volumes of data: partitioning and parallelism. Partitioning provides the capability to break operations on very large volumes of data into smaller operations. In many cases, partitioning additionally provides the capability to only operate on the relevant data. This will be illustrated in the next few slides. Parallelism provides the capability to apply multiple CPU resources to a single operation. The key to scalability is the combination of these two capabilities. You need to be able to ‘work smarter’ with partitioning to reduce the scope of the operation, and also ‘work harder’ with parallelism to increase the resource applied to the operation.

Partitioning - Minimal Unit of Work
Intelligent usage of partitioning information is key success factor for availability Partition Pruning Backup and Recovery Read-Write versus Read-Only order table Oracle8 advances Oracle’s innovative ‘best-of-both-worlds’ parallel query architecture. Oracle’s industry-leading technology combines intelligent use of data partitioning in the form of partition elimination and parallelism across partitions, with Oracle’s unique dynamic, intra-partition parallel query execution to deliver superior scalability and uncompromised manageability. In contrast, competing implementations base parallel execution completely on data partitioning, forcing administrators to choose between parallel excution performance and manageability, often resulting in severe manageability trade-offs. Here are the key benefits of Oracle’s real-world parallel query architecture: Eliminates the need to trade-off manageability against performance. Oracle8 administrators have the freedom to choose the data partitioning scheme that best maps to their business requirements in terms of availability and manageability. Oracle’s parallel architecture transparently takes care of delivering scalable query performance--leveraging, but not constrained by data partitioning. Maximum utilization of all available processing resources, even in the presence of real-world data skew. A common technology foundation that delivers performance, scalability and manageability on all parallel hardware architectures: SMP, Clusters and Massively Parallel Processing (MPP) systems. jan99 feb99 mar99 apr99 may99

Partitioning - Rolling Window
Partition level management Range, Composite (range + hash), List On-line addition and removal of partitions Data management operations (loading, index builds) Improved availability Localized disk failures, backup and recovery Add order table jan99 feb99 mar99 apr99 may99 Drop Rolling windows, typical in warehousing, are easy to manage with the Oracle Partitioning Option. Simply take a partition off-line to drop it or add one… remainder of the database remains up and available. Local Index Other data is not affected

Table Compression Table Compression increases: Table Compression:
I/O-subsystem capacity I/O throughput query scan performance buffer cache capacity Table Compression: reduces cost of ownership is easy to use requires little or no table definition changes is transparent to applications Why would any one use table compression? I think there are many reason. Table compression increases I/O subsystem capacity --- because each block can hold more compressed than uncompressed rows. At the same time Table Compression increases I/O throughput. Because the row density is higher, fewer blocks need to be read from the I/O subsystem. That is, with the exact same IO subsystem one will see increased rows read per second. Table Compression also increases buffer cache capacity. Compressed blocks are read into the buffer cache in their compressed format. Only when a column gets accessed it is decompressed. It remains compressed in the buffer cache even after it has been accessed. Table Compression reduces cost of ownership for the IO subsystem because of the reduced number of disks needed. Table compression is very easy to use. One only needs to add the compress attribute to either the table, partition or tablespace. No compression values need to be listed as required in other compression techniques. Table compression is transparent to any application. DML and DLL operations work seamless on compressed tables.

Table Compression: What is it?
Tables can be compressed Compression can also be specified at the partition level Indexes and index-organized tables are not compressed Typical compression ratios are 3:1 - 6:1 Compression is dependent upon the actual data Compression algorithm based on removing data redundancy All DDL/DML commands are supported on compressed tables

Oracle Parallel Query - Scanning
Data is Partitioned into Granules (block range or partition) Each Scanner is Assigned Multiple Granules No two scanners ever contend for the same granule Granules are assigned so that the Load is Balanced Across all Scanners Dynamic Granules Scanner #1 Scanner #2 Scanner #3 . . .

10G Real Time Warehouse Asynchronous CDC
Logical Change Data Based on Streams DW Tables SQL, PL/SQL, Java Transform Archived log files SQL interface to change data Publish/subscribe paradigm Parallel access to log files, leveraging Oracle Streams Parallel transformation of data OLTP DB 4

Oracle10G Business Intelligence Features
Real Time Data Warehousing Asynchronous Change Data Capture Cross-Platform Transportable Tablespaces Enhanced Table Functions External Tables Unload Enhanced MERGE Functionality Data Pump Export and Import Utilities Parallel Data Pump Export and Import SQL*Loader Direct Path Load Support for ROWID Datatype SQL*Loader Direct Path Load Support for VARRAY Datatype SQL*Loader Direct Path Load Support for XMLType Tables VLDB Bigfile Tablespace Enhanced Partition Management in Enterprise Manager Global Partitioned Indexes - Hash Partitioning Partitioned Index-Organized Tables - List Partitioning Partitioned Index-Organized Tables - LOB Support Partitioned Index-Organized Tables - Global Index Maintenance Enhanced Bitmap Index Performance and Space Management Local Partitioned Indexes Manageability Improvements Summary Management Summary Management OLAP Query Performance Improvements Summary Management - Enhanced Partition-aware Materialized View Refresh Summary Management - EXPLAIN PLAN Shows Materialized View Access Summary Management - Enhanced Dimensions Summary Management - Nested Materialized View Refresh Summary Management - Enhanced PCT Refresh Summary Management - Query Rewrite Uses Multiple Materialized OLAP Parallel AGGREGATE Command Parallel SQL IMPORT Command PL/SQL Creation of Analytic Workspaces Intra-Dimensional (Attribute) Aggregation Enhanced Composite Dimensions Indexing PL/SQL OLAP Measure Calculation Definition Complete Analytical Workspace Management Multi-Writer Support XML Interface for Analytic Workspace

Oracle10G Business Intelligence Features (Continued)
Data Mining Frequent Itemsets Attribute Importance Algorithms Enhanced Adaptive Bayes Network JSR-73 RI & TCK - Java Data Mining Multi-User Access Control Complete Oracle Data Mining Management Enhanced Model Seeker PMML Producers / Consumers Enhanced Data Preprocessing Data Mining Rapid Application Development Bio-informatics DOUBLE and FLOAT Datatypes BLAST Queries Statistical Functions Document Clustering Document Clustering Non-negative Matrix Factorization Document Clustering Neural Nets Document Named Entity Extraction Support Vector Machines Taxonomy Builder SQL Analytics Grouped Table Outer Join Increased Number of Aggregates per Query SQL Interrow Calculations Upsert Through SQL Interrow Calculations

Application Development on the Grid
HTML DB Low Cost, Hosted, Web Based Development Environment Improved PL/SQL Performance Database Web Services

HTML DB and the Grid - Business Problem
Departmental and LOB data sharing and information tracking Lots and lots of desktop databases Fragmented Inaccurate Untimely Vulnerable

HTML DB – Perfect for the Grid
Productivity of a Desktop Database Infrastructure of an Enterprise Database Built for the Web Leverages the Grid

Oracle Database 10G Half the Cost Highest Quality of Service
Low cost hardware with high utilization Integrated software stack Self-managing Highest Quality of Service Highest Performance, Scalability, Availability, Reliability, Security Easy to Align with Business Priorities

Oracle Database 10g Performance Metrics
PLSQL up to 2x Table Scans up to 2x SQL Profile Tuning huge Floating point math up to 10x Bulk LOB Update up to 3x Import up to 15x Export up to 35% Incremental backup up 10x Parallel media recovery 2-4x Backup compression 17x Infiniband interconnect ½ latency, 2x block transfer TPC-C Best absolute and best on 4-way Intel +28% on same hardware

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