les_10 workshop 2 oracle dba 10g

8/13/2019 les_10 workshop 2 oracle dba 10g

1/27

Copyright 2008, Oracle. All rights reserved.

Managing Schema Objects


2/27

10 - 2 Copyright 2008, Oracle. All rights reserved.

Objectives

After completing this lesson, you should be able to

manage schema objects and: Determine appropriate table types for your

requirements: heap, partition, IOT, or cluster

Perform related DBA tasks: Estimating the size of new tables

Analyzing growth trends

Managing optimizer statistics

Reorganizing schema objects online

Table Types

Partition

IOT

Cluster

DBA Tasks


3/27


Table Types

Related data from one or more tables are

stored together.

Clustered table

Data (including non-key values) is sorted

and stored in a B-tree index structure.

Index-organized table

(IOT)

Data is divided into smaller, more

manageable pieces.Partitioned table

Data is stored as an unordered collection

(heap).

Ordinary (heap-

organized) table

DescriptionType

Heap

IOTPartitioned

Clustered


4/27


What Is a Partition

and Why Use It?

A partition is:

A piece of a very large table or index Stored in its own segment

Used for improved performance and manageability

Table Types

> Partition

IOTCluster

DBA Tasks


5/27


Partitions

Characteristics of partitions are:

Same logical attributes: Same columns,constraints, and indexes

Different physical attributes: Stored in different

tablespaces Transparent to applications

Several partitioning methods


6/27


Creating a Partition


7/2710 - 7 Copyright 2008, Oracle. All rights reserved.

Partitioning Methods

Range partitioning: Maps rows based on logical

ranges of columns valuesfor example, monthsin a year

Hash partitioning: Maps rows based on the hash

value of the partitioning key

List partitioning: Maps rows based on a discrete

list of values, provided by the DBA

Range-hash partitioning: Maps rows using the

range method, and within each range partition,creates hash subpartitions

Range-list partitioning: Maps rows first based on a

range of values, then based on discrete values



Partition Maintenance



Table accessby ROWID

Index-Organized Tables

Regular table access IOT access

Non-key columns

Key column

Row header

Table Types

Partition

> IOTCluster

DBA Tasks



Index-Organized Tables

and Heap Tables

Compared to heap tables, IOTs:

Have faster key-based access to table data

Do not duplicate the storage of primary key values

Require less storage

Use secondary indexes and logical row IDs

Have higher availability because table

reorganization does not invalidate secondary

indexes

IOTs have the following restrictions: Must have a primary key that is not DEFERRABLE

Cannot be clustered

Cannot use composite partitioning

Cannot contain a column of type ROWID or LONG


11/27



Clusters

Clustered orders and

order_itemtables

Cluster Key

(ORD_NO)

101 ORD_DT CUST_CD

05-JAN-97 R01PROD QTY

A4102 20

A5675 19

W0824 10

102 ORD_DT CUST_CD

07-JAN-97 N45

PROD QTYA2091 11

G7830 20

N9587 26

Unclustered orders and

order_itemtables

ORD_NO ORD_DT CUST_CD------ ------ ------

101 05-JAN-97 R01

102 07-JAN-97 N45

ORD_NO PROD QTY ...----- ------ ------

101 A4102 20

102 A2091 11102 G7830 20

102 N9587 26

101 A5675 19

101 W0824 10

Table Types

Partition

IOT

> ClusterDBA Tasks



Cluster Types

Index cluster

Sorted hash

cluster

Hash

cluster

1

2

3

Hash function Hash function



Situations Where Clusters Are Useful

Data is retrieved in the order it

was inserted

Queries using equality predicate

on key

Predictable number of key values

Often joined master-detail tables

Rarely updated key

Evenly distributed key values

Uniform key distribution

Sorted

hashHashIndexCriterion



Sorted Hash Cluster: Overview

New data structure used to store data sorted by

nonprimary key columns: Cluster key values are hashed.

Rows corresponding to a particular cluster key

value are sorted according to the sort key.

Used to guarantee that row order is returned by

queries without sorting data:

Rows are returned in ascending or descending

order for a particular cluster key value. ORDER BY clause is not mandatory to retrieve rows

in ascending order.



Sorted Hash Cluster: Example

CREATE CLUSTER calls_cluster

( origin_number NUMBER

, call_timestamp NUMBER SORT

, call_duration NUMBER SORT)

HASHKEYS 10000

SINGLE TABLE HASH IS origin_number

SIZE 50;

CREATE TABLE calls

( origin_number NUMBER

, call_timestamp NUMBER

, call_duration NUMBER, other_info VARCHAR2(30))

CLUSTER calls_cluster(

origin_number,call_timestamp,call_duration

);

Cluster key

Sort key



Sorted Hash Cluster: Basic Architecture

Cluster key 2

Cluster key 1

Cluster key n

HASHKEYS

SIZE

Block chain

starting points

Rows sorted by

sort key in eachblock chain



Schema Management Tasks

DBA tasks include:

Estimating the size of new tables Analyzing growth trends



Table Types

Partition

IOTCluster

> DBA Tasks



Estimating Resource Usage


20/27



Managing Optimizer Statistics

Not analyzed 1

23



Reorganizing Schema Objects Online

Modifying logical or physical structure of a

schema object, such as a table or index Transparent to users

Space requirements



Reorganizing Objects:

Impact Report



Reorganizing Objects: Review



Basic Steps for Manual

Online Reorganization

1. Verify that the table is a candidate for online

reorganization.2. Create an interim table.

3. Start the redefinition process.

4. Copy dependent objects. (This automaticallycreates any triggers, indexes, grants, and

constraints on the interim table.)

5. Query the DBA_REDEFINITION_ERRORS view to

check for errors.

6. Optionally, synchronize the interim table.

7. Complete the redefinition.

8. Drop the interim table.


26/27


Summary

In this lesson, you should have learned how to manage

schema objects and: Determine appropriate table types for your

requirements

Perform related DBA tasks:

Estimating the size of new tables

Analyzing growth trends




27/27

Practice Overview:

Managing Schema Objects

This practice covers the following topics:

Monitoring table and index space usage Managing optimizer statistics

Reorganizing table and index

les_10 workshop 2 oracle dba 10g

Documents