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Contents
Title and Copyright Information
Preface
Audience
Documentation Accessibility
Related Documents
Conventions
What's New in Oracle Database to Support Very Large Databases?
Oracle Database 11
g
Release 2 (11.2.0.2) New Features to Support Very Large Databases
1
Introduction to Very Large Databases
Introduction to Partitioning
VLDB and Partitioning
Partitioning As the Foundation for Information Lifecycle Management
Partitioning for Every Database
2
Partitioning Concepts
Overview of Partitioning
Basics of Partitioning
Partitioning Key
Partitioned Tables
When to Partition a Table
When to Partition an Index
Partitioned Index-Organized Tables
System Partitioning
Partitioning for Information Lifecycle Management
Partitioning and LOB Data
Collections in XMLType and Object Data
Benefits of Partitioning
Partitioning for Performance
Partition Pruning
Partition-Wise Joins
Partitioning for Manageability
Partitioning for Availability
Partitioning Strategies
Single-Level Partitioning
Range Partitioning
Hash Partitioning
List Partitioning
Composite Partitioning
Composite Range-Range Partitioning
Composite Range-Hash Partitioning
Composite Range-List Partitioning
Composite List-Range Partitioning
Composite List-Hash Partitioning
Composite List-List Partitioning
Partitioning Extensions
Manageability Extensions
Interval Partitioning
Partition Advisor
Partitioning Key Extensions
Reference Partitioning
Virtual Column-Based Partitioning
Overview of Partitioned Indexes
Deciding on the Type of Partitioned Index to Use
Local Partitioned Indexes
Global Partitioned Indexes
Global Range Partitioned Indexes
Global Hash Partitioned Indexes
Maintenance of Global Partitioned Indexes
Global Nonpartitioned Indexes
Miscellaneous Information about Creating Indexes on Partitioned Tables
Partitioned Indexes on Composite Partitions
3
Partitioning for Availability, Manageability, and Performance
Partition Pruning
Benefits of Partition Pruning
Information That Can Be Used for Partition Pruning
How to Identify Whether Partition Pruning Has Been Used
Static Partition Pruning
Dynamic Partition Pruning
Dynamic Pruning with Bind Variables
Dynamic Pruning with Subqueries
Dynamic Pruning with Star Transformation
Dynamic Pruning with Nested Loop Joins
Partition Pruning Tips
Data Type Conversions
Function Calls
Collection Tables
Partition-Wise Joins
Full Partition-Wise Joins
Full Partition-Wise Joins: Single-Level - Single-Level
Full Partition-Wise Joins: Composite - Single-Level
Full Partition-Wise Joins: Composite - Composite
Partial Partition-Wise Joins
Partial Partition-Wise Joins: Single-Level Partitioning
Partial Partition-Wise Joins: Composite
Index Partitioning
Local Partitioned Indexes
Local Prefixed Indexes
Local Nonprefixed Indexes
Global Partitioned Indexes
Prefixed and Nonprefixed Global Partitioned Indexes
Management of Global Partitioned Indexes
Summary of Partitioned Index Types
The Importance of Nonprefixed Indexes
Performance Implications of Prefixed and Nonprefixed Indexes
Guidelines for Partitioning Indexes
Physical Attributes of Index Partitions
Partitioning and Table Compression
Table Compression and Bitmap Indexes
Example of Table Compression and Partitioning
Recommendations for Choosing a Partitioning Strategy
When to Use Range or Interval Partitioning
When to Use Hash Partitioning
When to Use List Partitioning
When to Use Composite Partitioning
When to Use Composite Range-Hash Partitioning
When to Use Composite Range-List Partitioning
When to Use Composite Range-Range Partitioning
When to Use Composite List-Hash Partitioning
When to Use Composite List-List Partitioning
When to Use Composite List-Range Partitioning
When to Use Interval Partitioning
When to Use Reference Partitioning
When to Partition on Virtual Columns
Considerations When Using Read-Only Tablespaces
4
Partition Administration
Creating Partitions
Creating Range-Partitioned Tables and Global Indexes
Creating a Range-Partitioned Table
Creating a Range-Partitioned Global Index
Creating Interval-Partitioned Tables
Creating Hash-Partitioned Tables and Global Indexes
Creating a Hash Partitioned Table
Creating a Hash-Partitioned Global Index
Creating List-Partitioned Tables
Creating Reference-Partitioned Tables
Creating Composite Partitioned Tables
Creating Composite Range-Hash Partitioned Tables
Creating Composite Range-List Partitioned Tables
Creating Composite Range-Range Partitioned Tables
Creating Composite List-* Partitioned Tables
Creating Composite Interval-* Partitioned Tables
Using Subpartition Templates to Describe Composite Partitioned Tables
Specifying a Subpartition Template for a *-Hash Partitioned Table
Specifying a Subpartition Template for a *-List Partitioned Table
Using Multicolumn Partitioning Keys
Using Virtual Column-Based Partitioning
Using Table Compression with Partitioned Tables
Using Key Compression with Partitioned Indexes
Using Partitioning with Segments
Deferred Segment Creation for Partitioning
Truncating Segments That Are Empty
Maintenance Procedures for Segment Creation on Demand
Creating Partitioned Index-Organized Tables
Creating Range-Partitioned Index-Organized Tables
Creating Hash-Partitioned Index-Organized Tables
Creating List-Partitioned Index-Organized Tables
Partitioning Restrictions for Multiple Block Sizes
Partitioning of Collections in XMLType and Objects
Performing PMOs on Partitions that Contain Collection Tables
Maintaining Partitions
Maintenance Operations on Partitions That Can Be Performed
Updating Indexes Automatically
Adding Partitions
Adding a Partition to a Range-Partitioned Table
Adding a Partition to a Hash-Partitioned Table
Adding a Partition to a List-Partitioned Table
Adding a Partition to an Interval-Partitioned Table
Adding Partitions to a Composite *-Hash Partitioned Table
Adding Partitions to a Composite *-List Partitioned Table
Adding Partitions to a Composite *-Range Partitioned Table
Adding a Partition or Subpartition to a Reference-Partitioned Table
Adding Index Partitions
Coalescing Partitions
Coalescing a Partition in a Hash-Partitioned Table
Coalescing a Subpartition in a *-Hash Partitioned Table
Coalescing Hash-Partitioned Global Indexes
Dropping Partitions
Dropping Table Partitions
Dropping Interval Partitions
Dropping Index Partitions
Exchanging Partitions
Exchanging a Range, Hash, or List Partition
Exchanging a Partition of an Interval Partitioned Table
Exchanging a Partition of a Reference-Partitioned Table
Exchanging a Partition of a Table with Virtual Columns
Exchanging a Hash-Partitioned Table with a *-Hash Partition
Exchanging a Subpartition of a *-Hash Partitioned Table
Exchanging a List-Partitioned Table with a *-List Partition
Exchanging a Subpartition of a *-List Partitioned Table
Exchanging a Range-Partitioned Table with a *-Range Partition
Exchanging a Subpartition of a *-Range Partitioned Table
Merging Partitions
Merging Range Partitions
Merging Interval Partitions
Merging List Partitions
Merging *-Hash Partitions
Merging *-List Partitions
Merging *-Range Partitions
Modifying Default Attributes
Modifying Default Attributes of a Table
Modifying Default Attributes of a Partition
Modifying Default Attributes of Index Partitions
Modifying Real Attributes of Partitions
Modifying Real Attributes for a Range or List Partition
Modifying Real Attributes for a Hash Partition
Modifying Real Attributes of a Subpartition
Modifying Real Attributes of Index Partitions
Modifying List Partitions: Adding Values
Adding Values for a List Partition
Adding Values for a List Subpartition
Modifying List Partitions: Dropping Values
Dropping Values from a List Partition
Dropping Values from a List Subpartition
Modifying a Subpartition Template
Moving Partitions
Moving Table Partitions
Moving Subpartitions
Moving Index Partitions
Redefining Partitions Online
Redefining Partitions with Collection Tables
Rebuilding Index Partitions
Rebuilding Global Index Partitions
Rebuilding Local Index Partitions
Renaming Partitions
Renaming a Table Partition
Renaming a Table Subpartition
Renaming Index Partitions
Splitting Partitions
Splitting a Partition of a Range-Partitioned Table
Splitting a Partition of a List-Partitioned Table
Splitting a Partition of an Interval-Partitioned Table
Splitting a *-Hash Partition
Splitting Partitions in a *-List Partitioned Table
Splitting a *-Range Partition
Splitting Index Partitions
Optimizing SPLIT PARTITION and SPLIT SUBPARTITION Operations
Truncating Partitions
Truncating a Table Partition
Truncating a Subpartition
Dropping Partitioned Tables
Partitioned Tables and Indexes Example
Viewing Information About Partitioned Tables and Indexes
5
Using Partitioning for Information Lifecycle Management
What Is ILM?
Oracle Database for ILM
Oracle Database Manages All Types of Data
Regulatory Requirements
Implementing ILM Using Oracle Database
Step 1: Define the Data Classes
Partitioning
The Lifecycle of Data
Step 2: Create Storage Tiers for the Data Classes
Assigning Classes to Storage Tiers
The Costs Savings of Using Tiered Storage
Step 3: Create Data Access and Migration Policies
Controlling Access to Data
Moving Data using Partitioning
Step 4: Define and Enforce Compliance Policies
Data Retention
Immutability
Privacy
Auditing
Expiration
The Benefits of an Online Archive
Oracle ILM Assistant
Lifecycle Setup
Logical Storage Tiers
Lifecycle Definitions
Lifecycle Tables
Preferences
Lifecycle Management
Lifecycle Events Calendar
Lifecycle Events
Event Scan History
Compliance & Security
Current Status
Digital Signatures and Immutability
Privacy & Security
Auditing
Policy Notes
Reports
Implementing an ILM System Manually
6
Using Partitioning in a Data Warehouse Environment
What Is a Data Warehouse?
Scalability
Bigger Databases
Bigger Individual Tables: More Rows in Tables
More Users Querying the System
More Complex Queries
Performance
Partition Pruning
Basic Partition Pruning Techniques
Advanced Partition Pruning Techniques
Partition-Wise Joins
Full Partition-Wise Joins
Partial Partition-Wise Joins
Benefits of Partition-Wise Joins
Performance Considerations for Parallel Partition-Wise Joins
Indexes and Partitioned Indexes
Local Partitioned Indexes
Nonpartitioned Indexes
Global Partitioned Indexes
Materialized Views and Partitioning
Partitioned Materialized Views
Manageability
Partition Exchange Load
Partitioning and Indexes
Partitioning and Materialized View Refresh Strategies
Removing Data from Tables
Partitioning and Data Compression
Gathering Statistics on Large Partitioned Tables
7
Using Partitioning in an Online Transaction Processing Environment
What Is an OLTP System?
Performance
Deciding Whether to Partition Indexes
Using Index-Organized Tables
Manageability
Impact of a Partition Maintenance Operation on a Partitioned Table with Local Indexes
Impact of a Partition Maintenance Operation on Global Indexes
Common Partition Maintenance Operations in OLTP Environments
Removing (Purging) Old Data
Moving or Merging Older Partitions to a Low-Cost Storage Tier Device
8
Using Parallel Execution
Introduction to Parallel Execution
When to Implement Parallel Execution
When Not to Implement Parallel Execution
Fundamental Hardware Requirements
Operations That Can Use Parallel Execution
How Parallel Execution Works
Parallel Execution of SQL Statements
Dividing Work Among Parallel Execution Servers
Parallelism Between Operations
Producer or Consumer Operations
How Parallel Execution Servers Communicate
Degree of Parallelism
Manually Specifying the Degree of Parallelism
Automatic Parallel Degree Policy
Controlling Automatic Degree of Parallelism
In-Memory Parallel Execution
Adaptive Parallelism
Controlling Automatic DOP, Parallel Statement Queuing, and In-Memory Parallel Execution
Parallel Statement Queuing
Managing Parallel Statement Queuing with Resource Manager
Grouping Parallel Statements with BEGIN_SQL_BLOCK .. END_SQL_BLOCK
Managing Parallel Statement Queuing with Hints
Parallel Execution Server Pool
Processing without Enough Parallel Execution Servers
Granules of Parallelism
Block Range Granules
Partition Granules
Balancing the Workload
Parallel Execution Using Oracle RAC
Limiting the Number of Available Instances
Types of Parallelism
About Parallel Queries
Parallel Queries on Index-Organized Tables
Nonpartitioned Index-Organized Tables
Partitioned Index-Organized Tables
Parallel Queries on Object Types
Rules for Parallelizing Queries
About Parallel DDL Statements
DDL Statements That Can Be Parallelized
CREATE TABLE ... AS SELECT in Parallel
Recoverability and Parallel DDL
Space Management for Parallel DDL
Storage Space When Using Dictionary-Managed Tablespaces
Free Space and Parallel DDL
Rules for DDL Statements
Rules for [CREATE | REBUILD] INDEX or [MOVE | SPLIT] PARTITION
Rules for CREATE TABLE AS SELECT
About Parallel DML Operations
When to Use Parallel DML
Enabling Parallel DML
Rules for UPDATE, MERGE, and DELETE
Rules for INSERT ... SELECT
Transaction Restrictions for Parallel DML
Rollback Segments
Recovery for Parallel DML
Space Considerations for Parallel DML
Restrictions on Parallel DML
Data Integrity Restrictions
Trigger Restrictions
Distributed Transaction Restrictions
Examples of Distributed Transaction Parallelization
About Parallel Execution of Functions
Functions in Parallel Queries
Functions in Parallel DML and DDL Statements
About Other Types of Parallelism
Summary of Parallelization Rules
Initializing and Tuning Parameters for Parallel Execution
Using Default Parameter Settings
Forcing Parallel Execution for a Session
Tuning General Parameters for Parallel Execution
Parameters Establishing Resource Limits for Parallel Operations
PARALLEL_FORCE_LOCAL
PARALLEL_MAX_SERVERS
PARALLEL_MIN_PERCENT
PARALLEL_MIN_SERVERS
PARALLEL_MIN_TIME_THRESHOLD
PARALLEL_SERVERS_TARGET
SHARED_POOL_SIZE
Computing Additional Memory Requirements for Message Buffers
Adjusting Memory After Processing Begins
Parameters Affecting Resource Consumption
PGA_AGGREGATE_TARGET
PARALLEL_EXECUTION_MESSAGE_SIZE
Parameters Affecting Resource Consumption for Parallel DML and Parallel DDL
Parameters Related to I/O
DB_CACHE_SIZE
DB_BLOCK_SIZE
DB_FILE_MULTIBLOCK_READ_COUNT
DISK_ASYNCH_IO and TAPE_ASYNCH_IO
Monitoring Parallel Execution Performance
Monitoring Parallel Execution Performance with Dynamic Performance Views
V$PX_BUFFER_ADVICE
V$PX_SESSION
V$PX_SESSTAT
V$PX_PROCESS
V$PX_PROCESS_SYSSTAT
V$PQ_SESSTAT
V$PQ_TQSTAT
V$RSRC_CONS_GROUP_HISTORY
V$RSRC_CONSUMER_GROUP
V$RSRC_PLAN
V$RSRC_PLAN_HISTORY
V$RSRC_SESSION_INFO
Monitoring Session Statistics
Monitoring System Statistics
Monitoring Operating System Statistics
Miscellaneous Parallel Execution Tuning Tips
Creating and Populating Tables in Parallel
Using EXPLAIN PLAN to Show Parallel Operations Plans
Example: Using EXPLAIN PLAN to Show Parallel Operations
Additional Considerations for Parallel DML
Parallel DML and Direct-Path Restrictions
Limitation on the Degree of Parallelism
Increasing INITRANS
Limitation on Available Number of Transaction Free Lists for Segments
Using Multiple Archivers
Database Writer Process (DBWn) Workload
[NO]LOGGING Clause
Creating Indexes in Parallel
Parallel DML Tips
Parallel DML Tip 1: INSERT
Parallel DML Tip 2: Direct-Path INSERT
Parallel DML Tip 3: Parallelizing INSERT, MERGE, UPDATE, and DELETE
Incremental Data Loading in Parallel
Updating the Table in Parallel
Inserting the New Rows into the Table in Parallel
Merging in Parallel
9
Backing Up and Recovering VLDBs
Data Warehouses
Data Warehouse Characteristics
Oracle Backup and Recovery
Physical Database Structures Used in Recovering Data
Data files
Redo Logs
Control Files
Backup Type
Backup Tools
Oracle Recovery Manager (RMAN)
Oracle Enterprise Manager
Oracle Data Pump
User-Managed Backups
Data Warehouse Backup and Recovery
Recovery Time Objective (RTO)
Recovery Point Objective (RPO)
More Data Means a Longer Backup Window
Divide and Conquer
The Data Warehouse Recovery Methodology
Best Practice 1: Use ARCHIVELOG Mode
Is Downtime Acceptable?
Best Practice 2: Use RMAN
Best Practice 3: Use Block Change Tracking
Best Practice 4: Use RMAN Multisection Backups
Best Practice 5: Leverage Read-Only Tablespaces
Best Practice 6: Plan for NOLOGGING Operations in Your Backup/Recovery Strategy
Extract, Transform, and Load
The Extract, Transform, and Load Strategy
Incremental Backup
The Incremental Approach
Flashback Database and Guaranteed Restore Points
Best Practice 7: Not All Tablespaces Are Created Equal
10
Storage Management for VLDBs
High Availability
Hardware-Based Mirroring
RAID 1 Mirroring
RAID 5 Mirroring
Mirroring Using Oracle ASM
Performance
Hardware-Based Striping
RAID 0 Striping
RAID 5 Striping
Striping Using Oracle ASM
Information Lifecycle Management
Partition Placement
Bigfile Tablespaces
Oracle Database File System (DBFS)
Scalability and Manageability
Stripe and Mirror Everything (SAME)
SAME and Manageability
Oracle ASM Settings Specific to VLDBs
Monitoring Database Storage Using Database Control
Index
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