SlideShare a Scribd company logo
Partitioning in Oracle Database 11g
An Oracle White Paper
June 2007
NOTE:
The following is intended to outline our general product direction. It is intended
for information purposes only, and may not be incorporated into any contract. It is
not a commitment to deliver any material, code, or functionality, and should not
be relied upon in making purchasing decisions. The development,release, and
timing of any features or functionality described for Oracle’s products remains at
the sole discretionof Oracle.
Partitioning in Oracle Database 11g Page 2
Partitioning in Oracle Database 11g
Note:......................................................................................................2
Partitioning – Concepts..........................................................................5
Introduction............................................................................................5
Benefits of Partitioning .........................................................................5
Basics of Partitioning.........................................................................5
Partitioning for Manageability ...........................................................7
Partitioning for Performance .............................................................7
Partitioning for Availability ...............................................................8
Partitioning – Modeling for your Business.............................................9
Basic Partitioning Strategies...............................................................9
Partitioning Extensions.....................................................................10
Partition Advisor..............................................................................11
Partitioning Strategies and Extensions at a Glance...........................12
Information Lifecycle Management with Partitioning..........................12
Conclusion...........................................................................................13
Partitioning in Oracle Database 11g Page 3
Partitioning in Oracle Database 11g
PARTITIONING – CONCEPTS
INTRODUCTION
Oracle Partitioning, first introduced in Oracle 8.0 in 1997, is one of the most
important and successful functionalities ofthe Oracle database, improving the
performance,manageability, andavailability for tens of thousands of applications.
Oracle Database 11g introduces the 8th
generation of partitioning which continues
to offer ground-breaking new and enhanced functionality; new partitioning
techniques enable customers to modeleven more businessscenarios while a
complete new framework of partition advice and automationenables the usage of
Oracle Partitioning for everybody. Oracle Database 11g is considered the biggest
new release for partitioning since its first introduction, continuing to protect our
customers' investmentin partitioning for a decade.
BENEFITS OF PARTITIONING
Partitioning can provide tremendous benefits to a wide variety ofapplications by
improving manageability, performance, andavailability. It is not unusual for
partitioning to improve the performance ofcertain queries or maintenance
operations by an order of magnitude.Moreover, partitioning can greatly reduce
the total cost of data ownership, using a “tiered archiving” approach of keeping
older relevant information still online on low cost storage devices. Oracle
Partitioning enables an efficient and simple, yet very powerful approach when
considering Information Lifecycle Management for large environments.
Partitioning also enables databasedesigners and administratorsto tackle some of
the toughest problems posed by cutting-edge applications. Partitioning is a key
tool for building multi-terabyte systems or systems with extremely high
availability requirements.
Basics of Partitioning
Partitioning allows a table, index or index-organized table to be subdivided into
smaller pieces. Each piece of the databaseobject is called a partition. Each
partition has its own name, and may optionally have its own storage
characteristics. From the perspective ofa database administrator, a partitioned
object has multiple pieces that can be managedeither collectively or individually.
This gives the administratorconsiderable flexibility in managing partitioned
Partitioning in Oracle Database 11g Page 4
object. However,from the perspective ofthe application, a partitioned table is
identical to a non-partitioned table; no modifications are necessary when
accessing a partitioned table using SQL DML commands.
Figure 1: Application and DBA perspective of a partitioned table
Database objects - tables, indexes, andindex-organized tables - are partitioned
using a 'partitioning key', a set of columns which determine in whichpartition a
given row will reside. For example the sales table shown in figure 1 is range-
partitioned on sales date, using a monthly partitioning strategy; the table appears
to any application as a single, 'normal' table. However, the DBA can manage and
store each monthly partition individually, potentially usingdifferent storagetiers,
applying table compression to the older data, or store complete ranges of older
data in read only tablespaces.
Irrespective ofthe chosen index partitioning strategy, an index is either coupled or
uncoupled with the underlying partitioning strategy of the underlying table. The
appropriate index partitioning strategy is chosen based on the business
requirements,making partitioning well suited to support any kind of application.
Oracle Database 11g differentiates between three types of partitioned indexes.
 Local Indexes:A local index is an index on a partitioned table that is
coupled with the underlying partitioned table, 'inheriting' the partitioning
strategy from the table. Consequently,each partition of a local index
corresponds to one - and only one - partition of the underlying table. The
coupling enables optimized partitionmaintenance; for example, when a
table partition is dropped, Oracle simply has to drop the corresponding
index partition as well. No costly index maintenance is required. Local
indexes are most common in data warehousing environments.
 Global Partitioned Indexes:A global partitioned index is an index on a
partitioned or non-partitioned table that is partitioned using a different
partitioning-key or partitioning strategy than the table. Global-partitioned
indexes can be partitioned using range or hash partitioning and are
uncoupled from the underlying table. For example, a table could be range-
partitioned by month and have twelve partitions, while an indexon that
table could be range-partitioned using a different partitioning key and have
Partitioning in Oracle Database 11g Page 5
a different numberof partitions. Global partitioned indexes are more
common for OLTP than for data warehousing environments.
 Global Non-Partitioned Indexes:A global non-partitioned index is
essentially identical to an index on a non-partitioned table. The index
structure is not partitioned and uncoupled from the underlying table. In data
warehousing environments,the most common usage of global non-
partitioned indexes is to enforce primarykey constraints.OLTP
environments on the other hand mostly rely onglobal non-partitioned
indexes.
Oracle additionally provides a comprehensiveset of SQL commands for
managing partitioning tables. These include commandsfor adding new partitions,
dropping, splitting, moving, merging, truncating, and optionally compressing
partitions.
Partitioning for Manageability
Oracle Partitioning allows tables and indexes to be partitioned into smaller, more
manageable units, providing database administrators with the ability to pursue a
"divide and conquer" approach to data management.
With partitioning, maintenance operationscan be focusedon particular portions of
tables. For example, a database administratorcould compress a single partition
containing say the data for the year 2006 of a table, rather than compressingthe
entire table. For maintenance operationsacross an entire database object, it is
possible to perform these operations on a per-partition basis, thus dividing the
maintenance processinto more manageable chunks.
A typical usage of partitioning for manageability is to support a 'rolling window'
load process in a data warehouse. Suppose that a DBA loads new data into a table
on weekly basis. That table could be range-partitioned so that each partition
contains one week of data. The load process is simply the addition of a new
partition. Adding a single partition is much more efficient than modifying the
entire table, since the DBA doesnot need to modify any other partitions.
Another advantage of using partitioning is when it is time to remove data,an
entire partition can be dropped which is very efficient and fast, compared to
deleting each row individually.
Partitioning for Performance
By limiting the amount of data to be examined or operated on, partitioning
provides a number of performance benefits. These features include:
 Partitioning Pruning: Partitioning pruning (a.k.a. Partition elimination)
is the simplest and also the most substantialmeans to improve
performance using partitioning. Partition pruning can often improve
query performance byseveral orders of magnitude.For example, suppose
an application contains an ORDERStable containingan historical record
Partitioning in Oracle Database 11g Page 6
of orders, and that this table has been partitioned by week. A query
requesting orders for a single week would only access a single partition
of the ORDERS table. If the table had 2 years of historical data, this
query would access one partition instead of 104 partitions. This query
could potentially execute 100x faster simply because of partition pruning.
Partition pruning works with all of Oracle's other performancefeatures.
Oracle will utilize partition pruning in conjunction with any indexing
technique, join technique, or parallel access method.
 Partition-wise Joins: Partitioning can also improve the performanceof
multi-table joins, by using a technique known as partition-wise joins.
Partition-wise joins can be applied whentwo tables are being joined
together, and at least one of these tables is partitioned on the join key.
Partition-wise joins break a large join into smaller joins of 'identical' data
sets for the joined tables. 'Identical' here is definedas covering exactly
the same set of partitioning key values on both sides of the join, thus
ensuring that only a join of these 'identical' data sets will produce a result
and that other data sets do not have to be considered.Oracle is using
either the fact of already (physical) equi-partitioned tables for the join or
is transparentlyredistributing (= “repartitioning”) one table at runtime to
create equi-partitioned data sets matching the partitioning of the other
table, completing the overall join inless time. This offerssignificant
performance benefits both for serial and parallel execution.
Partitioning for Availability
Partitioned database objects provide partition independence. This characteristic of
partition independence can be an important part of a high-availability strategy. For
example, if one partition of a partitioned table is unavailable, all of the other
partitions of the table remain online and available. The application can continue to
execute queries and transactions against this partitioned table, and these database
operations will run successfully if they do not need to access the unavailable
partition.
The database administrator can specify that each partition be stored in a separate
tablespace; this would allow the administrator to do backup and recovery
operations on each individual partition, independent of the other partitions in the
table. Therefore in the event of a disaster, the databasecould be recovered with
just the partitions comprising of the active data, and then the inactive data in the
other partitions could be recovered at a convenient time. Thus decreasing the
system down-time.
Moreover, partitioning can reduce scheduled downtime. The performance gains
provided by partitioning may enable database administratorsto complete
maintenance operationson large database objects in relatively small batch
windows.
Partitioning in Oracle Database 11g Page 7
PARTITIONING – MODELING FOR YOUR BUSINESS
Oracle Database 11g provides the most comprehensiveset of partitioning
strategies, allowing a customer to optimally align the data subdivision with the
actual business requirements. All available partitioning strategies rely on
fundamentaldata distribution methodsthat can be used for either single (one-
level) or compositepartitioned tables. Furthermore,Oracle provides a variety of
partitioning extensions, increasing the flexibility forthe partitioning key
selection, providing automated partition creation as-needed, and advising on
partitioning strategies for non-partitioned objects.
Basic Partitioning Strategies
Oracle Partitioning offers three fundamental data distributionmethods that control
how the data is actually going to placed into the variousindividual partitions,
namely:
 Range: The data is distributed based on a range of values of the
partitioning key (for a date column as the partitioning key, the 'January-
2007' partition contains rowswith the partitioning-key values between
'01-JAN-2007' and '31-JAN-2007'). The data distribution is a continuum
without any holes and the lower boundary of a range is automatically
defined by the upper boundary of the preceding range.
 List: The data distribution is defined by a list of values of the partitioning
key (for a region column as the partitioning key, the 'North America'
partition may contain values 'Canada', 'USA', and 'Mexico'). A special
'DEFAULT' partition can be definedto catch all values for a partition key
that are not explicitly defined by any of the lists.
 Hash: A hash algorithm is applied to the partitioning key to determine
the partition for a given row. Unlike the othertwo data distribution
methods, hash does not provide any logical mapping between the data
and any partition.
Using the above-mentioned data distribution methods, a table can be partitioned
either as single or composite partitioned table:
 Single (one-level) Partitioning:A table is defined by specifying one of
the data distribution methodologies, using one or more columnsas the
partitioning key. For example consider a table with a numbercolumn as
the partitioning key and two partitions 'less_than_five_hundred' and
'less_than_thousand', the 'less_than_thousand' partition contains rows
where the following condition is true: 500 <= Partitioning key <1000.
You can specify Range, List, and Hash partitioned tables.
 Composite Partitioning:A combination of two data distribution
methods are used to define a composite partitioned table. First, the table
is partitioned by data distribution method one and then each partition is
Partitioning in Oracle Database 11g Page 8
further subdivided into subpartitions using a second data distribution
method. All sub-partitions for a given partition together represent a
logical subset of the data. For example, a range-hash composite
partitioned table is first range-partitioned, and then each individual range-
partition is further sub-partitioned using the hash partitioning technique.
Available composite partitioningtechniques are range-hash, range-list,
range-range, list-range, list-list, and list-hash.
 Index-organized tables (IOTs) can be partitionedusing range, hash, and
list partitioning. Composite partitioningis not supported for IOTs.
Partitioning Extensions
In addition to the basic partitioning strategies, Oracle provides partitioning
extensions. The extensions in Oracle Database 11g mainly focus on two
objectives:
(a) Enhance the manageability ofa partitioned table significantly.
(b) Extend the flexibility indefining a partitioning key.
The extensions are namely:
Interval Partitioning:A new partitioning strategy in Oracle Database 11g,
Interval partitioning extends the capabilities of the range method to define equi-
partitioned ranges using an interval definition.Rather than specifying individual
ranges explicitly, Oracle will create any partition automatically as-needed
whenever data for a partition is inserted for the very first time. Interval
partitioning greatly improves the manageability of a partitioned table. For
example, an interval partitionedtable could be defined so that Oracle creates a
new partition for every month in a calendar year; a partition is then automatically
created for 'September 2007' as soon as the first record for this month is inserted
into the database.
The available techniques for an interval partitioned table are Interval, Interval-
List, Interval-Hash,and Interval-Range.
REF Partitioning: Oracle Database 11g allows to partition a table by leveraging
an existing parent-child relationship. The partitioning strategy of the parent table
is inherited to its child table without the necessity to store the parent's partitioning
key columns in the child table. Without REF Partitioning you have to duplicate all
partitioning key columns from the parent table to the child table if you want to
take advantage fromthe same partitioning strategy; REF Partitioning on the other
hand allows you to naturally partition tables according to the logical data model
without requiring to store the partitioning key columns, thus reducing the manual
overhead for denormalizationand saving space. REF Partitioning also
transparently inherits all partition maintenance operationsthat change the logical
shape of a table from the parent table to the child table. Furthermore,REF
Partitioning automatically enables partition-wise joins for the equi-partitions of
Partitioning in Oracle Database 11g Page 9
the parent and child table, improving the performancefor this operation. For
example, a parent table ORDERS isRange partitionedon the ORDER_DATE
column; its child table ORDER ITEMS does not contain the ORDER_DATE
column but can be partitioned by reference to the ORDERS table. If the ORDERS
table is partitioned by month, all order items for orders in 'Jan-2007' will then be
stored in a single partitionin the ORDER ITEMS table, equi-partitioned to the
parent table ORDERS. If apartition 'Feb-2007' is added to the ORDERS table
Oracle will transparently add the equivalent partition to the ORDER ITEMS table.
All basic partitioning strategies are available for REF Partitioning.
Virtual column-basedPartitioning: In previous versions of Oracle, a table could
only be partitioned if the partitioningkey physically existed inthe table. Virtual
columns, a new functionality in Oracle Database 11g, removes that restriction
and allows the partitioning key to be defined by an expression, using one or more
existing columns of a table, and storing the expression as metadata only.
Partitioning has been enhanced to allow a partitioning strategy being defined on
virtual columns, thus enabling a more comprehensivematch of the business
requirements.It is not uncommon to see columns being overloaded with
information; for example a 10 digit account ID can include an account branch
information as the leading three digits. With the extension of virtual column-
based Partitioning, the ACCOUNTStable containinga column ACCOUNT_ID
can be extended with a virtual (derived) column ACCOUNT_BRANCHthat is
derived from the first three digits of the ACCOUNT_ID column which becomes
the partitioning key for this table.
Virtual column-based Partitioning is supported with all basic partitioning
strategies.
Partition Advisor
The SQL Access Advisor in Oracle Database 11g has been enhanced to generate
partitioning recommendations,in addition to the ones it already provides for
indexes, materialized views and materialized view logs. Recommendations
generated by the SQL Access Advisor – either for Partitioning only or holistically
- will show the anticipated performance gains that will result if they are
implemented. The generated script can either be implemented manually or
submitted onto a queue within Oracle Enterprise Manager.
With the extension of partitioning advice, customers not only can get
recommendation specifically for partitioning but also a more comprehensive
holistic recommendation of SQL Access Advisor, improving the collective
performance of SQL statements overall.
The Partition Advisor, integrated into the SQL Access Advisor, is part of Oracle's
Tuning Pack, an extra licensable option. It can be used from within Enterprise
Manager or via a command line interface.
Partitioning in Oracle Database 11g Page 10
Partitioning Strategies and Extensions at a Glance
The following table gives a conceptual overviewof all available basic partitioning
strategies in Oracle Database 11g:
Partitioning Strategy Data Distribution Sample Business Case
Range Partitioning Based on consecutive ranges of
values.
 Orders table range
partitioned by order_date
List Partitioning Based on unordered lists of
values.
 Orders table list partitioned
by country
Hash Partitioning Based on a hash algorithm.  Orders table hash partitioned
by customer_id
Composite Partitioning
 Range-Range
 Range-List
 Range-Hash
 List-List
 List-Range
 List-Hash
Based on a combination of two
of the above-mentioned basic
techniques of Range, List,
Hash, and Interval Partitioning
 Orders table is range
partitioned by order_date
and sub-partitioned by hash
on customer_id
 Orders table is range
partitioned by order_date
and sub-partitioned by range
on shipment_date
In addition to the available partitioning strategies, Oracle Database 11g provides
the following partitioning extensions:
Partitioning Extension Partitioning Key Sample Business Case
Interval Partitioning
 Interval
 Interval-Range
 Interval-List
 Interval-Hash
An extension to Range
Partition. Defined by an
interval, providing equi-width
ranges. With the exception of
the first partition all partitions
are automatically created on-
demand when matching data
arrives.
 Orders table partitioned by
order_date with a predefined
daily interval, starting with
'01-Jan-2007'
REF Partitioning Partitioning for a child table is
inherited from the parent table
through a primary key –
foreign key relationship. The
partitioning keys are not stored
in actual columns in the child
table.
 (Parent) Orders table range
partitioned by order_date
and inherits the partitioning
technique to (child) order
lines table. Column
order_date is only present in
the parent orders table
Virtual column based
Partitioning
Defined by one of the above-
mentioned partition techniques
and the partitioning key is
based on a virtual column.
Virtual columns are not stored
on disk and only exist as
metadata.
 Orders table has a virtual
column that derives the sales
region based on the first
three digits of the customer
account number. The orders
table is then list partitioned
by sales region.
Partitioning in Oracle Database 11g Page 11
INFORMATION LIFECYCLE MANAGEMENT WITH PARTITIONING
Today's challenge of storing vast quantities ofdata for the lowest possible cost
can be optimally addressedusing Oracle Partitioning. The independence of
individual partitions is the key enabler for addressing the online portion of a
“tiered archiving”strategy. Specifically in tables containing historical data, the
importance - andaccess pattern – of the data heavily relies on the age of the data;
Partitioning enables individual partitions (or groups of partitions) to be stored on
different storage tiers, providing different physical attributes and price points. For
example an Orderstable containing2 years worth of data could have only the
most recent quarter beingstored on an expensive high-end storage tier and keep
the rest of the table (almost 90% of the data) on an inexpensivelow cost storage
tier. Through Oracle Partitioning, the storage costsare reduced by factors (cost
savings of 50% or more are not uncommon), without impacting the end user
access, thus optimizing the cost of ownership for the stored information.
The Oracle ILM Assistant which is a freely available tool downloadable from
OTN, can illustrate those cost savings, show you how to partition the table and
advise when it is time to move partitionsto other storage tiers.
CONCLUSION
Considering the new and improved functionality for Oracle Partitioning, Oracle
Database 11g is the most significant release since the introduction of Oracle
Partitioning in 1997. In every major release, Oracle has enhanced the functionality
of Partitioning, by either adding new partitioningtechniques, enhancing the
scalability, or extending the manageability and maintenance capabilities. Oracle
plans to continue to add new partitioningtechniques to ensure that an optimal
partitioning technique is available for every business requirement.
Partitioning is for everybody. Oracle Partitioning can greatly enhance the
manageability, performance, andavailability of almost any database application.
Partitioning can be applied tocutting-edge applications and indeed partitioning
can be a crucial technology ingredient to ensure these applications’ success.
Partitioning can also be applied to more commonplace database applications in
order to simplify the administration and costs of managing such applications.
Since partitioning is transparent to the application, it can be easily implemented
because no costly and time-consuming application changes are required.
Partitioning in Oracle Database 11g Page 12
Partitioning in Oracle Database 11g
June 2007
Author: Hermann Baer
Contributing Authors:
Oracle Corporation
World Headquarters
500 Oracle Parkway
Redwood Shores, CA 94065
U.S.A.
Worldwide Inquiries:
Phone: +1.650.506.7000
Fax: +1.650.506.7200
oracle.com
Copyright © 2007, Oracle. All rights reserved.
This document is provided for information purposes only and the
contents hereof are subject to change without notice.
This document is not warranted to be error-free, nor subject to any
other warranties or conditions, whether expressed orally or implied
in law, including implied warranties and conditions of merchantability
or fitness for a particular purpose. We specifically disclaim any
liability with respect to this document and no contractual obligations
are formed either directly or indirectly by this document. This document
may not be reproduced or transmitted in any form or by any means,
electronic or mechanical, for any purpose, without our prior written permission.
Oracle is a registered trademark of Oracle Corporation and/or its affiliates.
Other names may be trademarks of their respective owners.

More Related Content

What's hot

Teradata 13.10
Teradata 13.10Teradata 13.10
Teradata 13.10
Teradata
 
New Features Sql 2008
New Features Sql 2008New Features Sql 2008
New Features Sql 2008
tomerl
 
Oracle 11g data warehouse introdution
Oracle 11g data warehouse introdutionOracle 11g data warehouse introdution
Oracle 11g data warehouse introdution
Aditya Trivedi
 
NENUG Apr14 Talk - data modeling for netezza
NENUG Apr14 Talk - data modeling for netezzaNENUG Apr14 Talk - data modeling for netezza
NENUG Apr14 Talk - data modeling for netezza
Biju Nair
 
Managing user Online Training in IBM Netezza DBA Development by www.etraining...
Managing user Online Training in IBM Netezza DBA Development by www.etraining...Managing user Online Training in IBM Netezza DBA Development by www.etraining...
Managing user Online Training in IBM Netezza DBA Development by www.etraining...
Ravikumar Nandigam
 
Using R on Netezza
Using R on NetezzaUsing R on Netezza
Using R on Netezza
Ajay Ohri
 
DB Optimizer Datasheet - Automated SQL Profiling & Tuning for Optimized Perfo...
DB Optimizer Datasheet - Automated SQL Profiling & Tuning for Optimized Perfo...DB Optimizer Datasheet - Automated SQL Profiling & Tuning for Optimized Perfo...
DB Optimizer Datasheet - Automated SQL Profiling & Tuning for Optimized Perfo...
Embarcadero Technologies
 
Course content (netezza dba)
Course content (netezza dba)Course content (netezza dba)
Course content (netezza dba)
Ravikumar Nandigam
 
Teradata sql-tuning-top-10
Teradata sql-tuning-top-10Teradata sql-tuning-top-10
Teradata sql-tuning-top-10
Roland Wenzlofsky
 
Whats New Sql Server 2008 R2 Cw
Whats New Sql Server 2008 R2 CwWhats New Sql Server 2008 R2 Cw
Whats New Sql Server 2008 R2 Cw
Eduardo Castro
 
Getting to know oracle database objects iot, mviews, clusters and more…
Getting to know oracle database objects iot, mviews, clusters and more…Getting to know oracle database objects iot, mviews, clusters and more…
Getting to know oracle database objects iot, mviews, clusters and more…
Aaron Shilo
 
Data ware house
Data ware houseData ware house
Oracle architecture
Oracle architectureOracle architecture
Oracle architecture
Sandeep Kamath
 
An Introduction to Netezza
An Introduction to NetezzaAn Introduction to Netezza
An Introduction to Netezza
Vijaya Chandrika
 
Introduction to oracle(2)
Introduction to oracle(2)Introduction to oracle(2)
Introduction to oracle(2)
Sumit Tambe
 
Srinivas BI Consultant Profile
Srinivas BI Consultant ProfileSrinivas BI Consultant Profile
Srinivas BI Consultant Profile
Srinivas V
 
Oracle Complete Interview Questions
Oracle Complete Interview QuestionsOracle Complete Interview Questions
Oracle Complete Interview Questions
Sandeep Sharma IIMK Smart City,IoT,Bigdata,Cloud,BI,DW
 
Sql server 2016 new features
Sql server 2016 new featuresSql server 2016 new features
Sql server 2016 new features
Ajeet Singh
 
8 i locally_mgr_tbsp
8 i locally_mgr_tbsp8 i locally_mgr_tbsp
8 i locally_mgr_tbsp
Anil Pandey
 

What's hot (19)

Teradata 13.10
Teradata 13.10Teradata 13.10
Teradata 13.10
 
New Features Sql 2008
New Features Sql 2008New Features Sql 2008
New Features Sql 2008
 
Oracle 11g data warehouse introdution
Oracle 11g data warehouse introdutionOracle 11g data warehouse introdution
Oracle 11g data warehouse introdution
 
NENUG Apr14 Talk - data modeling for netezza
NENUG Apr14 Talk - data modeling for netezzaNENUG Apr14 Talk - data modeling for netezza
NENUG Apr14 Talk - data modeling for netezza
 
Managing user Online Training in IBM Netezza DBA Development by www.etraining...
Managing user Online Training in IBM Netezza DBA Development by www.etraining...Managing user Online Training in IBM Netezza DBA Development by www.etraining...
Managing user Online Training in IBM Netezza DBA Development by www.etraining...
 
Using R on Netezza
Using R on NetezzaUsing R on Netezza
Using R on Netezza
 
DB Optimizer Datasheet - Automated SQL Profiling & Tuning for Optimized Perfo...
DB Optimizer Datasheet - Automated SQL Profiling & Tuning for Optimized Perfo...DB Optimizer Datasheet - Automated SQL Profiling & Tuning for Optimized Perfo...
DB Optimizer Datasheet - Automated SQL Profiling & Tuning for Optimized Perfo...
 
Course content (netezza dba)
Course content (netezza dba)Course content (netezza dba)
Course content (netezza dba)
 
Teradata sql-tuning-top-10
Teradata sql-tuning-top-10Teradata sql-tuning-top-10
Teradata sql-tuning-top-10
 
Whats New Sql Server 2008 R2 Cw
Whats New Sql Server 2008 R2 CwWhats New Sql Server 2008 R2 Cw
Whats New Sql Server 2008 R2 Cw
 
Getting to know oracle database objects iot, mviews, clusters and more…
Getting to know oracle database objects iot, mviews, clusters and more…Getting to know oracle database objects iot, mviews, clusters and more…
Getting to know oracle database objects iot, mviews, clusters and more…
 
Data ware house
Data ware houseData ware house
Data ware house
 
Oracle architecture
Oracle architectureOracle architecture
Oracle architecture
 
An Introduction to Netezza
An Introduction to NetezzaAn Introduction to Netezza
An Introduction to Netezza
 
Introduction to oracle(2)
Introduction to oracle(2)Introduction to oracle(2)
Introduction to oracle(2)
 
Srinivas BI Consultant Profile
Srinivas BI Consultant ProfileSrinivas BI Consultant Profile
Srinivas BI Consultant Profile
 
Oracle Complete Interview Questions
Oracle Complete Interview QuestionsOracle Complete Interview Questions
Oracle Complete Interview Questions
 
Sql server 2016 new features
Sql server 2016 new featuresSql server 2016 new features
Sql server 2016 new features
 
8 i locally_mgr_tbsp
8 i locally_mgr_tbsp8 i locally_mgr_tbsp
8 i locally_mgr_tbsp
 

Viewers also liked

2b manipulasi-string
2b manipulasi-string2b manipulasi-string
2b manipulasi-string
Si Comell
 
Victoria robins m.las fuentes de energía
Victoria robins m.las fuentes de energíaVictoria robins m.las fuentes de energía
Victoria robins m.las fuentes de energía
killer606
 
Decreto micorosa (1)
Decreto micorosa (1)Decreto micorosa (1)
Decreto micorosa (1)
ilfattoquotidiano.it
 
Personalized Learning: What it is. What it isn't.
Personalized Learning: What it is. What it isn't.Personalized Learning: What it is. What it isn't.
Personalized Learning: What it is. What it isn't.
The Institute @ CESA #1
 
dana new resume 2014 data entry
dana new resume 2014 data entrydana new resume 2014 data entry
dana new resume 2014 data entry
D joneZ
 
certification of examination
certification of examinationcertification of examination
certification of examinationJesie Ocampo
 
Semana santa
Semana santaSemana santa
Semana santa
Ing_Luis_Arroyo
 
Increase customers without increasing headcount
Increase customers without increasing headcountIncrease customers without increasing headcount
Increase customers without increasing headcount
Solarwinds N-able
 
Preservação da informação na biblioteca digital
Preservação da informação na biblioteca digitalPreservação da informação na biblioteca digital
Preservação da informação na biblioteca digital
Cariniana Rede
 
Wis awards ad with media partners
Wis awards ad with media partnersWis awards ad with media partners
Wis awards ad with media partners
Alibaba.com
 
02 b capitulo-cuarto
02 b capitulo-cuarto02 b capitulo-cuarto
02 b capitulo-cuarto
Santy Quinata
 
Preservação Digital da Informação Técnico Científica
Preservação Digital da Informação Técnico CientíficaPreservação Digital da Informação Técnico Científica
Preservação Digital da Informação Técnico Científica
Cariniana Rede
 
8 day program, 4 days hike wadi rum
8 day program, 4 days hike wadi rum 8 day program, 4 days hike wadi rum
8 day program, 4 days hike wadi rum
Jezra Travel
 
Semana santa
Semana santaSemana santa
Semana santa
Jogeal
 
Preservação 2
Preservação 2Preservação 2
Preservação 2
Cariniana Rede
 
SUSTRACCIÓN DE NÚMEROS ENTEROS
SUSTRACCIÓN DE NÚMEROS ENTEROSSUSTRACCIÓN DE NÚMEROS ENTEROS
SUSTRACCIÓN DE NÚMEROS ENTEROS
Gabriel112127
 

Viewers also liked (16)

2b manipulasi-string
2b manipulasi-string2b manipulasi-string
2b manipulasi-string
 
Victoria robins m.las fuentes de energía
Victoria robins m.las fuentes de energíaVictoria robins m.las fuentes de energía
Victoria robins m.las fuentes de energía
 
Decreto micorosa (1)
Decreto micorosa (1)Decreto micorosa (1)
Decreto micorosa (1)
 
Personalized Learning: What it is. What it isn't.
Personalized Learning: What it is. What it isn't.Personalized Learning: What it is. What it isn't.
Personalized Learning: What it is. What it isn't.
 
dana new resume 2014 data entry
dana new resume 2014 data entrydana new resume 2014 data entry
dana new resume 2014 data entry
 
certification of examination
certification of examinationcertification of examination
certification of examination
 
Semana santa
Semana santaSemana santa
Semana santa
 
Increase customers without increasing headcount
Increase customers without increasing headcountIncrease customers without increasing headcount
Increase customers without increasing headcount
 
Preservação da informação na biblioteca digital
Preservação da informação na biblioteca digitalPreservação da informação na biblioteca digital
Preservação da informação na biblioteca digital
 
Wis awards ad with media partners
Wis awards ad with media partnersWis awards ad with media partners
Wis awards ad with media partners
 
02 b capitulo-cuarto
02 b capitulo-cuarto02 b capitulo-cuarto
02 b capitulo-cuarto
 
Preservação Digital da Informação Técnico Científica
Preservação Digital da Informação Técnico CientíficaPreservação Digital da Informação Técnico Científica
Preservação Digital da Informação Técnico Científica
 
8 day program, 4 days hike wadi rum
8 day program, 4 days hike wadi rum 8 day program, 4 days hike wadi rum
8 day program, 4 days hike wadi rum
 
Semana santa
Semana santaSemana santa
Semana santa
 
Preservação 2
Preservação 2Preservação 2
Preservação 2
 
SUSTRACCIÓN DE NÚMEROS ENTEROS
SUSTRACCIÓN DE NÚMEROS ENTEROSSUSTRACCIÓN DE NÚMEROS ENTEROS
SUSTRACCIÓN DE NÚMEROS ENTEROS
 

Similar to Partitioning 11g-whitepaper-159443

Microsoft SQL Azure - Scaling Out with SQL Azure Whitepaper
Microsoft SQL Azure - Scaling Out with SQL Azure WhitepaperMicrosoft SQL Azure - Scaling Out with SQL Azure Whitepaper
Microsoft SQL Azure - Scaling Out with SQL Azure Whitepaper
Microsoft Private Cloud
 
EstlGd.DataPartitioning
EstlGd.DataPartitioningEstlGd.DataPartitioning
EstlGd.DataPartitioning
Daren Bieniek
 
8 i index_tables
8 i index_tables8 i index_tables
8 i index_tables
Anil Pandey
 
Data warehouse physical design
Data warehouse physical designData warehouse physical design
Data warehouse physical design
Er. Nawaraj Bhandari
 
Database Performance Management in Cloud
Database Performance Management in CloudDatabase Performance Management in Cloud
Database Performance Management in Cloud
Dr. Amarjeet Singh
 
Why To Use Data Partitioning?
Why To Use Data Partitioning?Why To Use Data Partitioning?
Why To Use Data Partitioning?
raima sen
 
The High Performance DBA Optimizing Databases For High Performance
The High Performance DBA Optimizing Databases For High PerformanceThe High Performance DBA Optimizing Databases For High Performance
The High Performance DBA Optimizing Databases For High Performance
Embarcadero Technologies
 
Oracle
OracleOracle
A Survey And Comparison Of Relational And Non-Relational Database
A Survey And Comparison Of Relational And Non-Relational DatabaseA Survey And Comparison Of Relational And Non-Relational Database
A Survey And Comparison Of Relational And Non-Relational Database
Karla Adamson
 
SURVEY ON IMPLEMANTATION OF COLUMN ORIENTED NOSQL DATA STORES ( BIGTABLE & CA...
SURVEY ON IMPLEMANTATION OF COLUMN ORIENTED NOSQL DATA STORES ( BIGTABLE & CA...SURVEY ON IMPLEMANTATION OF COLUMN ORIENTED NOSQL DATA STORES ( BIGTABLE & CA...
SURVEY ON IMPLEMANTATION OF COLUMN ORIENTED NOSQL DATA STORES ( BIGTABLE & CA...
IJCERT JOURNAL
 
Remote DBA Experts 11g Features
Remote DBA Experts 11g FeaturesRemote DBA Experts 11g Features
Remote DBA Experts 11g Features
Remote DBA Experts
 
Whitepaper - Information management with oracle
Whitepaper - Information management with oracleWhitepaper - Information management with oracle
Whitepaper - Information management with oracle
infoMENTUM
 
No sql database
No sql databaseNo sql database
No sql database
vishal gupta
 
Partitioning kendralittle
Partitioning kendralittlePartitioning kendralittle
Partitioning kendralittle
ngupt28
 
Obiee11g working with partitions
Obiee11g working with partitionsObiee11g working with partitions
Obiee11g working with partitions
Amit Sharma
 
1. Briefly describe the major components of a data warehouse archi.docx
1. Briefly describe the major components of a data warehouse archi.docx1. Briefly describe the major components of a data warehouse archi.docx
1. Briefly describe the major components of a data warehouse archi.docx
monicafrancis71118
 
Data management in cloud study of existing systems and future opportunities
Data management in cloud study of existing systems and future opportunitiesData management in cloud study of existing systems and future opportunities
Data management in cloud study of existing systems and future opportunities
Editor Jacotech
 
Collaborate 2009 - Migrating a Data Warehouse from Microsoft SQL Server to Or...
Collaborate 2009 - Migrating a Data Warehouse from Microsoft SQL Server to Or...Collaborate 2009 - Migrating a Data Warehouse from Microsoft SQL Server to Or...
Collaborate 2009 - Migrating a Data Warehouse from Microsoft SQL Server to Or...
djkucera
 
EOUG95 - Client Server Very Large Databases - Paper
EOUG95 - Client Server Very Large Databases - PaperEOUG95 - Client Server Very Large Databases - Paper
EOUG95 - Client Server Very Large Databases - Paper
David Walker
 
A introduction to oracle data integrator
A introduction to oracle data integratorA introduction to oracle data integrator
A introduction to oracle data integrator
chkamal
 

Similar to Partitioning 11g-whitepaper-159443 (20)

Microsoft SQL Azure - Scaling Out with SQL Azure Whitepaper
Microsoft SQL Azure - Scaling Out with SQL Azure WhitepaperMicrosoft SQL Azure - Scaling Out with SQL Azure Whitepaper
Microsoft SQL Azure - Scaling Out with SQL Azure Whitepaper
 
EstlGd.DataPartitioning
EstlGd.DataPartitioningEstlGd.DataPartitioning
EstlGd.DataPartitioning
 
8 i index_tables
8 i index_tables8 i index_tables
8 i index_tables
 
Data warehouse physical design
Data warehouse physical designData warehouse physical design
Data warehouse physical design
 
Database Performance Management in Cloud
Database Performance Management in CloudDatabase Performance Management in Cloud
Database Performance Management in Cloud
 
Why To Use Data Partitioning?
Why To Use Data Partitioning?Why To Use Data Partitioning?
Why To Use Data Partitioning?
 
The High Performance DBA Optimizing Databases For High Performance
The High Performance DBA Optimizing Databases For High PerformanceThe High Performance DBA Optimizing Databases For High Performance
The High Performance DBA Optimizing Databases For High Performance
 
Oracle
OracleOracle
Oracle
 
A Survey And Comparison Of Relational And Non-Relational Database
A Survey And Comparison Of Relational And Non-Relational DatabaseA Survey And Comparison Of Relational And Non-Relational Database
A Survey And Comparison Of Relational And Non-Relational Database
 
SURVEY ON IMPLEMANTATION OF COLUMN ORIENTED NOSQL DATA STORES ( BIGTABLE & CA...
SURVEY ON IMPLEMANTATION OF COLUMN ORIENTED NOSQL DATA STORES ( BIGTABLE & CA...SURVEY ON IMPLEMANTATION OF COLUMN ORIENTED NOSQL DATA STORES ( BIGTABLE & CA...
SURVEY ON IMPLEMANTATION OF COLUMN ORIENTED NOSQL DATA STORES ( BIGTABLE & CA...
 
Remote DBA Experts 11g Features
Remote DBA Experts 11g FeaturesRemote DBA Experts 11g Features
Remote DBA Experts 11g Features
 
Whitepaper - Information management with oracle
Whitepaper - Information management with oracleWhitepaper - Information management with oracle
Whitepaper - Information management with oracle
 
No sql database
No sql databaseNo sql database
No sql database
 
Partitioning kendralittle
Partitioning kendralittlePartitioning kendralittle
Partitioning kendralittle
 
Obiee11g working with partitions
Obiee11g working with partitionsObiee11g working with partitions
Obiee11g working with partitions
 
1. Briefly describe the major components of a data warehouse archi.docx
1. Briefly describe the major components of a data warehouse archi.docx1. Briefly describe the major components of a data warehouse archi.docx
1. Briefly describe the major components of a data warehouse archi.docx
 
Data management in cloud study of existing systems and future opportunities
Data management in cloud study of existing systems and future opportunitiesData management in cloud study of existing systems and future opportunities
Data management in cloud study of existing systems and future opportunities
 
Collaborate 2009 - Migrating a Data Warehouse from Microsoft SQL Server to Or...
Collaborate 2009 - Migrating a Data Warehouse from Microsoft SQL Server to Or...Collaborate 2009 - Migrating a Data Warehouse from Microsoft SQL Server to Or...
Collaborate 2009 - Migrating a Data Warehouse from Microsoft SQL Server to Or...
 
EOUG95 - Client Server Very Large Databases - Paper
EOUG95 - Client Server Very Large Databases - PaperEOUG95 - Client Server Very Large Databases - Paper
EOUG95 - Client Server Very Large Databases - Paper
 
A introduction to oracle data integrator
A introduction to oracle data integratorA introduction to oracle data integrator
A introduction to oracle data integrator
 

Recently uploaded

Should Repositories Participate in the Fediverse?
Should Repositories Participate in the Fediverse?Should Repositories Participate in the Fediverse?
Should Repositories Participate in the Fediverse?
Paul Walk
 
快速办理(Vic毕业证书)惠灵顿维多利亚大学毕业证完成信一模一样
快速办理(Vic毕业证书)惠灵顿维多利亚大学毕业证完成信一模一样快速办理(Vic毕业证书)惠灵顿维多利亚大学毕业证完成信一模一样
快速办理(Vic毕业证书)惠灵顿维多利亚大学毕业证完成信一模一样
3a0sd7z3
 
一比一原版(USYD毕业证)悉尼大学毕业证如何办理
一比一原版(USYD毕业证)悉尼大学毕业证如何办理一比一原版(USYD毕业证)悉尼大学毕业证如何办理
一比一原版(USYD毕业证)悉尼大学毕业证如何办理
k4ncd0z
 
办理新西兰奥克兰大学毕业证学位证书范本原版一模一样
办理新西兰奥克兰大学毕业证学位证书范本原版一模一样办理新西兰奥克兰大学毕业证学位证书范本原版一模一样
办理新西兰奥克兰大学毕业证学位证书范本原版一模一样
xjq03c34
 
快速办理(新加坡SMU毕业证书)新加坡管理大学毕业证文凭证书一模一样
快速办理(新加坡SMU毕业证书)新加坡管理大学毕业证文凭证书一模一样快速办理(新加坡SMU毕业证书)新加坡管理大学毕业证文凭证书一模一样
快速办理(新加坡SMU毕业证书)新加坡管理大学毕业证文凭证书一模一样
3a0sd7z3
 
Securing BGP: Operational Strategies and Best Practices for Network Defenders...
Securing BGP: Operational Strategies and Best Practices for Network Defenders...Securing BGP: Operational Strategies and Best Practices for Network Defenders...
Securing BGP: Operational Strategies and Best Practices for Network Defenders...
APNIC
 
How to make a complaint to the police for Social Media Fraud.pdf
How to make a complaint to the police for Social Media Fraud.pdfHow to make a complaint to the police for Social Media Fraud.pdf
How to make a complaint to the police for Social Media Fraud.pdf
Infosec train
 
Integrating Physical and Cybersecurity to Lower Risks in Healthcare!
Integrating Physical and Cybersecurity to Lower Risks in Healthcare!Integrating Physical and Cybersecurity to Lower Risks in Healthcare!
Integrating Physical and Cybersecurity to Lower Risks in Healthcare!
Alec Kassir cozmozone
 
Discover the benefits of outsourcing SEO to India
Discover the benefits of outsourcing SEO to IndiaDiscover the benefits of outsourcing SEO to India
Discover the benefits of outsourcing SEO to India
davidjhones387
 
怎么办理(umiami毕业证书)美国迈阿密大学毕业证文凭证书实拍图原版一模一样
怎么办理(umiami毕业证书)美国迈阿密大学毕业证文凭证书实拍图原版一模一样怎么办理(umiami毕业证书)美国迈阿密大学毕业证文凭证书实拍图原版一模一样
怎么办理(umiami毕业证书)美国迈阿密大学毕业证文凭证书实拍图原版一模一样
rtunex8r
 
Honeypots Unveiled: Proactive Defense Tactics for Cyber Security, Phoenix Sum...
Honeypots Unveiled: Proactive Defense Tactics for Cyber Security, Phoenix Sum...Honeypots Unveiled: Proactive Defense Tactics for Cyber Security, Phoenix Sum...
Honeypots Unveiled: Proactive Defense Tactics for Cyber Security, Phoenix Sum...
APNIC
 
一比一原版新西兰林肯大学毕业证(Lincoln毕业证书)学历如何办理
一比一原版新西兰林肯大学毕业证(Lincoln毕业证书)学历如何办理一比一原版新西兰林肯大学毕业证(Lincoln毕业证书)学历如何办理
一比一原版新西兰林肯大学毕业证(Lincoln毕业证书)学历如何办理
thezot
 
HijackLoader Evolution: Interactive Process Hollowing
HijackLoader Evolution: Interactive Process HollowingHijackLoader Evolution: Interactive Process Hollowing
HijackLoader Evolution: Interactive Process Hollowing
Donato Onofri
 
Bengaluru Dreamin' 24 - Personal Branding
Bengaluru Dreamin' 24 - Personal BrandingBengaluru Dreamin' 24 - Personal Branding
Bengaluru Dreamin' 24 - Personal Branding
Tarandeep Singh
 

Recently uploaded (14)

Should Repositories Participate in the Fediverse?
Should Repositories Participate in the Fediverse?Should Repositories Participate in the Fediverse?
Should Repositories Participate in the Fediverse?
 
快速办理(Vic毕业证书)惠灵顿维多利亚大学毕业证完成信一模一样
快速办理(Vic毕业证书)惠灵顿维多利亚大学毕业证完成信一模一样快速办理(Vic毕业证书)惠灵顿维多利亚大学毕业证完成信一模一样
快速办理(Vic毕业证书)惠灵顿维多利亚大学毕业证完成信一模一样
 
一比一原版(USYD毕业证)悉尼大学毕业证如何办理
一比一原版(USYD毕业证)悉尼大学毕业证如何办理一比一原版(USYD毕业证)悉尼大学毕业证如何办理
一比一原版(USYD毕业证)悉尼大学毕业证如何办理
 
办理新西兰奥克兰大学毕业证学位证书范本原版一模一样
办理新西兰奥克兰大学毕业证学位证书范本原版一模一样办理新西兰奥克兰大学毕业证学位证书范本原版一模一样
办理新西兰奥克兰大学毕业证学位证书范本原版一模一样
 
快速办理(新加坡SMU毕业证书)新加坡管理大学毕业证文凭证书一模一样
快速办理(新加坡SMU毕业证书)新加坡管理大学毕业证文凭证书一模一样快速办理(新加坡SMU毕业证书)新加坡管理大学毕业证文凭证书一模一样
快速办理(新加坡SMU毕业证书)新加坡管理大学毕业证文凭证书一模一样
 
Securing BGP: Operational Strategies and Best Practices for Network Defenders...
Securing BGP: Operational Strategies and Best Practices for Network Defenders...Securing BGP: Operational Strategies and Best Practices for Network Defenders...
Securing BGP: Operational Strategies and Best Practices for Network Defenders...
 
How to make a complaint to the police for Social Media Fraud.pdf
How to make a complaint to the police for Social Media Fraud.pdfHow to make a complaint to the police for Social Media Fraud.pdf
How to make a complaint to the police for Social Media Fraud.pdf
 
Integrating Physical and Cybersecurity to Lower Risks in Healthcare!
Integrating Physical and Cybersecurity to Lower Risks in Healthcare!Integrating Physical and Cybersecurity to Lower Risks in Healthcare!
Integrating Physical and Cybersecurity to Lower Risks in Healthcare!
 
Discover the benefits of outsourcing SEO to India
Discover the benefits of outsourcing SEO to IndiaDiscover the benefits of outsourcing SEO to India
Discover the benefits of outsourcing SEO to India
 
怎么办理(umiami毕业证书)美国迈阿密大学毕业证文凭证书实拍图原版一模一样
怎么办理(umiami毕业证书)美国迈阿密大学毕业证文凭证书实拍图原版一模一样怎么办理(umiami毕业证书)美国迈阿密大学毕业证文凭证书实拍图原版一模一样
怎么办理(umiami毕业证书)美国迈阿密大学毕业证文凭证书实拍图原版一模一样
 
Honeypots Unveiled: Proactive Defense Tactics for Cyber Security, Phoenix Sum...
Honeypots Unveiled: Proactive Defense Tactics for Cyber Security, Phoenix Sum...Honeypots Unveiled: Proactive Defense Tactics for Cyber Security, Phoenix Sum...
Honeypots Unveiled: Proactive Defense Tactics for Cyber Security, Phoenix Sum...
 
一比一原版新西兰林肯大学毕业证(Lincoln毕业证书)学历如何办理
一比一原版新西兰林肯大学毕业证(Lincoln毕业证书)学历如何办理一比一原版新西兰林肯大学毕业证(Lincoln毕业证书)学历如何办理
一比一原版新西兰林肯大学毕业证(Lincoln毕业证书)学历如何办理
 
HijackLoader Evolution: Interactive Process Hollowing
HijackLoader Evolution: Interactive Process HollowingHijackLoader Evolution: Interactive Process Hollowing
HijackLoader Evolution: Interactive Process Hollowing
 
Bengaluru Dreamin' 24 - Personal Branding
Bengaluru Dreamin' 24 - Personal BrandingBengaluru Dreamin' 24 - Personal Branding
Bengaluru Dreamin' 24 - Personal Branding
 

Partitioning 11g-whitepaper-159443

  • 1. Partitioning in Oracle Database 11g An Oracle White Paper June 2007
  • 2. NOTE: The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development,release, and timing of any features or functionality described for Oracle’s products remains at the sole discretionof Oracle. Partitioning in Oracle Database 11g Page 2
  • 3. Partitioning in Oracle Database 11g Note:......................................................................................................2 Partitioning – Concepts..........................................................................5 Introduction............................................................................................5 Benefits of Partitioning .........................................................................5 Basics of Partitioning.........................................................................5 Partitioning for Manageability ...........................................................7 Partitioning for Performance .............................................................7 Partitioning for Availability ...............................................................8 Partitioning – Modeling for your Business.............................................9 Basic Partitioning Strategies...............................................................9 Partitioning Extensions.....................................................................10 Partition Advisor..............................................................................11 Partitioning Strategies and Extensions at a Glance...........................12 Information Lifecycle Management with Partitioning..........................12 Conclusion...........................................................................................13 Partitioning in Oracle Database 11g Page 3
  • 4. Partitioning in Oracle Database 11g PARTITIONING – CONCEPTS INTRODUCTION Oracle Partitioning, first introduced in Oracle 8.0 in 1997, is one of the most important and successful functionalities ofthe Oracle database, improving the performance,manageability, andavailability for tens of thousands of applications. Oracle Database 11g introduces the 8th generation of partitioning which continues to offer ground-breaking new and enhanced functionality; new partitioning techniques enable customers to modeleven more businessscenarios while a complete new framework of partition advice and automationenables the usage of Oracle Partitioning for everybody. Oracle Database 11g is considered the biggest new release for partitioning since its first introduction, continuing to protect our customers' investmentin partitioning for a decade. BENEFITS OF PARTITIONING Partitioning can provide tremendous benefits to a wide variety ofapplications by improving manageability, performance, andavailability. It is not unusual for partitioning to improve the performance ofcertain queries or maintenance operations by an order of magnitude.Moreover, partitioning can greatly reduce the total cost of data ownership, using a “tiered archiving” approach of keeping older relevant information still online on low cost storage devices. Oracle Partitioning enables an efficient and simple, yet very powerful approach when considering Information Lifecycle Management for large environments. Partitioning also enables databasedesigners and administratorsto tackle some of the toughest problems posed by cutting-edge applications. Partitioning is a key tool for building multi-terabyte systems or systems with extremely high availability requirements. Basics of Partitioning Partitioning allows a table, index or index-organized table to be subdivided into smaller pieces. Each piece of the databaseobject is called a partition. Each partition has its own name, and may optionally have its own storage characteristics. From the perspective ofa database administrator, a partitioned object has multiple pieces that can be managedeither collectively or individually. This gives the administratorconsiderable flexibility in managing partitioned Partitioning in Oracle Database 11g Page 4
  • 5. object. However,from the perspective ofthe application, a partitioned table is identical to a non-partitioned table; no modifications are necessary when accessing a partitioned table using SQL DML commands. Figure 1: Application and DBA perspective of a partitioned table Database objects - tables, indexes, andindex-organized tables - are partitioned using a 'partitioning key', a set of columns which determine in whichpartition a given row will reside. For example the sales table shown in figure 1 is range- partitioned on sales date, using a monthly partitioning strategy; the table appears to any application as a single, 'normal' table. However, the DBA can manage and store each monthly partition individually, potentially usingdifferent storagetiers, applying table compression to the older data, or store complete ranges of older data in read only tablespaces. Irrespective ofthe chosen index partitioning strategy, an index is either coupled or uncoupled with the underlying partitioning strategy of the underlying table. The appropriate index partitioning strategy is chosen based on the business requirements,making partitioning well suited to support any kind of application. Oracle Database 11g differentiates between three types of partitioned indexes.  Local Indexes:A local index is an index on a partitioned table that is coupled with the underlying partitioned table, 'inheriting' the partitioning strategy from the table. Consequently,each partition of a local index corresponds to one - and only one - partition of the underlying table. The coupling enables optimized partitionmaintenance; for example, when a table partition is dropped, Oracle simply has to drop the corresponding index partition as well. No costly index maintenance is required. Local indexes are most common in data warehousing environments.  Global Partitioned Indexes:A global partitioned index is an index on a partitioned or non-partitioned table that is partitioned using a different partitioning-key or partitioning strategy than the table. Global-partitioned indexes can be partitioned using range or hash partitioning and are uncoupled from the underlying table. For example, a table could be range- partitioned by month and have twelve partitions, while an indexon that table could be range-partitioned using a different partitioning key and have Partitioning in Oracle Database 11g Page 5
  • 6. a different numberof partitions. Global partitioned indexes are more common for OLTP than for data warehousing environments.  Global Non-Partitioned Indexes:A global non-partitioned index is essentially identical to an index on a non-partitioned table. The index structure is not partitioned and uncoupled from the underlying table. In data warehousing environments,the most common usage of global non- partitioned indexes is to enforce primarykey constraints.OLTP environments on the other hand mostly rely onglobal non-partitioned indexes. Oracle additionally provides a comprehensiveset of SQL commands for managing partitioning tables. These include commandsfor adding new partitions, dropping, splitting, moving, merging, truncating, and optionally compressing partitions. Partitioning for Manageability Oracle Partitioning allows tables and indexes to be partitioned into smaller, more manageable units, providing database administrators with the ability to pursue a "divide and conquer" approach to data management. With partitioning, maintenance operationscan be focusedon particular portions of tables. For example, a database administratorcould compress a single partition containing say the data for the year 2006 of a table, rather than compressingthe entire table. For maintenance operationsacross an entire database object, it is possible to perform these operations on a per-partition basis, thus dividing the maintenance processinto more manageable chunks. A typical usage of partitioning for manageability is to support a 'rolling window' load process in a data warehouse. Suppose that a DBA loads new data into a table on weekly basis. That table could be range-partitioned so that each partition contains one week of data. The load process is simply the addition of a new partition. Adding a single partition is much more efficient than modifying the entire table, since the DBA doesnot need to modify any other partitions. Another advantage of using partitioning is when it is time to remove data,an entire partition can be dropped which is very efficient and fast, compared to deleting each row individually. Partitioning for Performance By limiting the amount of data to be examined or operated on, partitioning provides a number of performance benefits. These features include:  Partitioning Pruning: Partitioning pruning (a.k.a. Partition elimination) is the simplest and also the most substantialmeans to improve performance using partitioning. Partition pruning can often improve query performance byseveral orders of magnitude.For example, suppose an application contains an ORDERStable containingan historical record Partitioning in Oracle Database 11g Page 6
  • 7. of orders, and that this table has been partitioned by week. A query requesting orders for a single week would only access a single partition of the ORDERS table. If the table had 2 years of historical data, this query would access one partition instead of 104 partitions. This query could potentially execute 100x faster simply because of partition pruning. Partition pruning works with all of Oracle's other performancefeatures. Oracle will utilize partition pruning in conjunction with any indexing technique, join technique, or parallel access method.  Partition-wise Joins: Partitioning can also improve the performanceof multi-table joins, by using a technique known as partition-wise joins. Partition-wise joins can be applied whentwo tables are being joined together, and at least one of these tables is partitioned on the join key. Partition-wise joins break a large join into smaller joins of 'identical' data sets for the joined tables. 'Identical' here is definedas covering exactly the same set of partitioning key values on both sides of the join, thus ensuring that only a join of these 'identical' data sets will produce a result and that other data sets do not have to be considered.Oracle is using either the fact of already (physical) equi-partitioned tables for the join or is transparentlyredistributing (= “repartitioning”) one table at runtime to create equi-partitioned data sets matching the partitioning of the other table, completing the overall join inless time. This offerssignificant performance benefits both for serial and parallel execution. Partitioning for Availability Partitioned database objects provide partition independence. This characteristic of partition independence can be an important part of a high-availability strategy. For example, if one partition of a partitioned table is unavailable, all of the other partitions of the table remain online and available. The application can continue to execute queries and transactions against this partitioned table, and these database operations will run successfully if they do not need to access the unavailable partition. The database administrator can specify that each partition be stored in a separate tablespace; this would allow the administrator to do backup and recovery operations on each individual partition, independent of the other partitions in the table. Therefore in the event of a disaster, the databasecould be recovered with just the partitions comprising of the active data, and then the inactive data in the other partitions could be recovered at a convenient time. Thus decreasing the system down-time. Moreover, partitioning can reduce scheduled downtime. The performance gains provided by partitioning may enable database administratorsto complete maintenance operationson large database objects in relatively small batch windows. Partitioning in Oracle Database 11g Page 7
  • 8. PARTITIONING – MODELING FOR YOUR BUSINESS Oracle Database 11g provides the most comprehensiveset of partitioning strategies, allowing a customer to optimally align the data subdivision with the actual business requirements. All available partitioning strategies rely on fundamentaldata distribution methodsthat can be used for either single (one- level) or compositepartitioned tables. Furthermore,Oracle provides a variety of partitioning extensions, increasing the flexibility forthe partitioning key selection, providing automated partition creation as-needed, and advising on partitioning strategies for non-partitioned objects. Basic Partitioning Strategies Oracle Partitioning offers three fundamental data distributionmethods that control how the data is actually going to placed into the variousindividual partitions, namely:  Range: The data is distributed based on a range of values of the partitioning key (for a date column as the partitioning key, the 'January- 2007' partition contains rowswith the partitioning-key values between '01-JAN-2007' and '31-JAN-2007'). The data distribution is a continuum without any holes and the lower boundary of a range is automatically defined by the upper boundary of the preceding range.  List: The data distribution is defined by a list of values of the partitioning key (for a region column as the partitioning key, the 'North America' partition may contain values 'Canada', 'USA', and 'Mexico'). A special 'DEFAULT' partition can be definedto catch all values for a partition key that are not explicitly defined by any of the lists.  Hash: A hash algorithm is applied to the partitioning key to determine the partition for a given row. Unlike the othertwo data distribution methods, hash does not provide any logical mapping between the data and any partition. Using the above-mentioned data distribution methods, a table can be partitioned either as single or composite partitioned table:  Single (one-level) Partitioning:A table is defined by specifying one of the data distribution methodologies, using one or more columnsas the partitioning key. For example consider a table with a numbercolumn as the partitioning key and two partitions 'less_than_five_hundred' and 'less_than_thousand', the 'less_than_thousand' partition contains rows where the following condition is true: 500 <= Partitioning key <1000. You can specify Range, List, and Hash partitioned tables.  Composite Partitioning:A combination of two data distribution methods are used to define a composite partitioned table. First, the table is partitioned by data distribution method one and then each partition is Partitioning in Oracle Database 11g Page 8
  • 9. further subdivided into subpartitions using a second data distribution method. All sub-partitions for a given partition together represent a logical subset of the data. For example, a range-hash composite partitioned table is first range-partitioned, and then each individual range- partition is further sub-partitioned using the hash partitioning technique. Available composite partitioningtechniques are range-hash, range-list, range-range, list-range, list-list, and list-hash.  Index-organized tables (IOTs) can be partitionedusing range, hash, and list partitioning. Composite partitioningis not supported for IOTs. Partitioning Extensions In addition to the basic partitioning strategies, Oracle provides partitioning extensions. The extensions in Oracle Database 11g mainly focus on two objectives: (a) Enhance the manageability ofa partitioned table significantly. (b) Extend the flexibility indefining a partitioning key. The extensions are namely: Interval Partitioning:A new partitioning strategy in Oracle Database 11g, Interval partitioning extends the capabilities of the range method to define equi- partitioned ranges using an interval definition.Rather than specifying individual ranges explicitly, Oracle will create any partition automatically as-needed whenever data for a partition is inserted for the very first time. Interval partitioning greatly improves the manageability of a partitioned table. For example, an interval partitionedtable could be defined so that Oracle creates a new partition for every month in a calendar year; a partition is then automatically created for 'September 2007' as soon as the first record for this month is inserted into the database. The available techniques for an interval partitioned table are Interval, Interval- List, Interval-Hash,and Interval-Range. REF Partitioning: Oracle Database 11g allows to partition a table by leveraging an existing parent-child relationship. The partitioning strategy of the parent table is inherited to its child table without the necessity to store the parent's partitioning key columns in the child table. Without REF Partitioning you have to duplicate all partitioning key columns from the parent table to the child table if you want to take advantage fromthe same partitioning strategy; REF Partitioning on the other hand allows you to naturally partition tables according to the logical data model without requiring to store the partitioning key columns, thus reducing the manual overhead for denormalizationand saving space. REF Partitioning also transparently inherits all partition maintenance operationsthat change the logical shape of a table from the parent table to the child table. Furthermore,REF Partitioning automatically enables partition-wise joins for the equi-partitions of Partitioning in Oracle Database 11g Page 9
  • 10. the parent and child table, improving the performancefor this operation. For example, a parent table ORDERS isRange partitionedon the ORDER_DATE column; its child table ORDER ITEMS does not contain the ORDER_DATE column but can be partitioned by reference to the ORDERS table. If the ORDERS table is partitioned by month, all order items for orders in 'Jan-2007' will then be stored in a single partitionin the ORDER ITEMS table, equi-partitioned to the parent table ORDERS. If apartition 'Feb-2007' is added to the ORDERS table Oracle will transparently add the equivalent partition to the ORDER ITEMS table. All basic partitioning strategies are available for REF Partitioning. Virtual column-basedPartitioning: In previous versions of Oracle, a table could only be partitioned if the partitioningkey physically existed inthe table. Virtual columns, a new functionality in Oracle Database 11g, removes that restriction and allows the partitioning key to be defined by an expression, using one or more existing columns of a table, and storing the expression as metadata only. Partitioning has been enhanced to allow a partitioning strategy being defined on virtual columns, thus enabling a more comprehensivematch of the business requirements.It is not uncommon to see columns being overloaded with information; for example a 10 digit account ID can include an account branch information as the leading three digits. With the extension of virtual column- based Partitioning, the ACCOUNTStable containinga column ACCOUNT_ID can be extended with a virtual (derived) column ACCOUNT_BRANCHthat is derived from the first three digits of the ACCOUNT_ID column which becomes the partitioning key for this table. Virtual column-based Partitioning is supported with all basic partitioning strategies. Partition Advisor The SQL Access Advisor in Oracle Database 11g has been enhanced to generate partitioning recommendations,in addition to the ones it already provides for indexes, materialized views and materialized view logs. Recommendations generated by the SQL Access Advisor – either for Partitioning only or holistically - will show the anticipated performance gains that will result if they are implemented. The generated script can either be implemented manually or submitted onto a queue within Oracle Enterprise Manager. With the extension of partitioning advice, customers not only can get recommendation specifically for partitioning but also a more comprehensive holistic recommendation of SQL Access Advisor, improving the collective performance of SQL statements overall. The Partition Advisor, integrated into the SQL Access Advisor, is part of Oracle's Tuning Pack, an extra licensable option. It can be used from within Enterprise Manager or via a command line interface. Partitioning in Oracle Database 11g Page 10
  • 11. Partitioning Strategies and Extensions at a Glance The following table gives a conceptual overviewof all available basic partitioning strategies in Oracle Database 11g: Partitioning Strategy Data Distribution Sample Business Case Range Partitioning Based on consecutive ranges of values.  Orders table range partitioned by order_date List Partitioning Based on unordered lists of values.  Orders table list partitioned by country Hash Partitioning Based on a hash algorithm.  Orders table hash partitioned by customer_id Composite Partitioning  Range-Range  Range-List  Range-Hash  List-List  List-Range  List-Hash Based on a combination of two of the above-mentioned basic techniques of Range, List, Hash, and Interval Partitioning  Orders table is range partitioned by order_date and sub-partitioned by hash on customer_id  Orders table is range partitioned by order_date and sub-partitioned by range on shipment_date In addition to the available partitioning strategies, Oracle Database 11g provides the following partitioning extensions: Partitioning Extension Partitioning Key Sample Business Case Interval Partitioning  Interval  Interval-Range  Interval-List  Interval-Hash An extension to Range Partition. Defined by an interval, providing equi-width ranges. With the exception of the first partition all partitions are automatically created on- demand when matching data arrives.  Orders table partitioned by order_date with a predefined daily interval, starting with '01-Jan-2007' REF Partitioning Partitioning for a child table is inherited from the parent table through a primary key – foreign key relationship. The partitioning keys are not stored in actual columns in the child table.  (Parent) Orders table range partitioned by order_date and inherits the partitioning technique to (child) order lines table. Column order_date is only present in the parent orders table Virtual column based Partitioning Defined by one of the above- mentioned partition techniques and the partitioning key is based on a virtual column. Virtual columns are not stored on disk and only exist as metadata.  Orders table has a virtual column that derives the sales region based on the first three digits of the customer account number. The orders table is then list partitioned by sales region. Partitioning in Oracle Database 11g Page 11
  • 12. INFORMATION LIFECYCLE MANAGEMENT WITH PARTITIONING Today's challenge of storing vast quantities ofdata for the lowest possible cost can be optimally addressedusing Oracle Partitioning. The independence of individual partitions is the key enabler for addressing the online portion of a “tiered archiving”strategy. Specifically in tables containing historical data, the importance - andaccess pattern – of the data heavily relies on the age of the data; Partitioning enables individual partitions (or groups of partitions) to be stored on different storage tiers, providing different physical attributes and price points. For example an Orderstable containing2 years worth of data could have only the most recent quarter beingstored on an expensive high-end storage tier and keep the rest of the table (almost 90% of the data) on an inexpensivelow cost storage tier. Through Oracle Partitioning, the storage costsare reduced by factors (cost savings of 50% or more are not uncommon), without impacting the end user access, thus optimizing the cost of ownership for the stored information. The Oracle ILM Assistant which is a freely available tool downloadable from OTN, can illustrate those cost savings, show you how to partition the table and advise when it is time to move partitionsto other storage tiers. CONCLUSION Considering the new and improved functionality for Oracle Partitioning, Oracle Database 11g is the most significant release since the introduction of Oracle Partitioning in 1997. In every major release, Oracle has enhanced the functionality of Partitioning, by either adding new partitioningtechniques, enhancing the scalability, or extending the manageability and maintenance capabilities. Oracle plans to continue to add new partitioningtechniques to ensure that an optimal partitioning technique is available for every business requirement. Partitioning is for everybody. Oracle Partitioning can greatly enhance the manageability, performance, andavailability of almost any database application. Partitioning can be applied tocutting-edge applications and indeed partitioning can be a crucial technology ingredient to ensure these applications’ success. Partitioning can also be applied to more commonplace database applications in order to simplify the administration and costs of managing such applications. Since partitioning is transparent to the application, it can be easily implemented because no costly and time-consuming application changes are required. Partitioning in Oracle Database 11g Page 12
  • 13. Partitioning in Oracle Database 11g June 2007 Author: Hermann Baer Contributing Authors: Oracle Corporation World Headquarters 500 Oracle Parkway Redwood Shores, CA 94065 U.S.A. Worldwide Inquiries: Phone: +1.650.506.7000 Fax: +1.650.506.7200 oracle.com Copyright © 2007, Oracle. All rights reserved. This document is provided for information purposes only and the contents hereof are subject to change without notice. This document is not warranted to be error-free, nor subject to any other warranties or conditions, whether expressed orally or implied in law, including implied warranties and conditions of merchantability or fitness for a particular purpose. We specifically disclaim any liability with respect to this document and no contractual obligations are formed either directly or indirectly by this document. This document may not be reproduced or transmitted in any form or by any means, electronic or mechanical, for any purpose, without our prior written permission. Oracle is a registered trademark of Oracle Corporation and/or its affiliates. Other names may be trademarks of their respective owners.