Oracle 9i database software User manual

Oracle9i
Database Performance Planning
Release 2 (9.2)
March 2002
Part No. A96532-01
Oracle9i Database Performance Planning, Release 2 (9.2)
Part No. A96532-01
Copyright © 2001, 2002 Oracle Corporation. All rights reserved.
Primary Author: Andrew Holdsworth
Contributing Author: Lenore Luscher
Contributors: Jorn Bartels, Maria Colgan, Michele Cyran, Bjorn Engsig, Cecilia Gervasio, Connie Dialeris
Green, Mattias Jankowitz, Peter Kilpatrick, Anjo Kolk, JP Polk, Virag Saksena, Sabrina Whitehouse,
Graham Wood
Graphic Designer: Valarie Moore
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Contents
Send Us Your Comments .................................................................................................................... v
Preface........................................................................................................................................................... vii
1
Designing and Developing for Performance
Oracle’s New Methodology ..............................................................................................................
Understanding Investment Options ...............................................................................................
Understanding Scalability ................................................................................................................
What is Scalability?.......................................................................................................................
Internet Scalability........................................................................................................................
Factors Preventing Scalability.....................................................................................................
System Architecture ...........................................................................................................................
Hardware and Software Components.......................................................................................
Configuring the Right System Architecture for Your Requirements..................................
Application Design Principles ......................................................................................................
Simplicity In Application Design .............................................................................................
Data Modeling ............................................................................................................................
Table and Index Design .............................................................................................................
Using Views.................................................................................................................................
SQL Execution Efficiency ..........................................................................................................
Implementing the Application .................................................................................................
Trends in Application Development .......................................................................................
Workload Testing, Modeling, and Implementation...................................................................
Sizing Data...................................................................................................................................
Estimating Workloads ...............................................................................................................
1-2
1-2
1-3
1-3
1-4
1-6
1-7
1-7
1-10
1-14
1-14
1-14
1-15
1-18
1-18
1-20
1-22
1-23
1-23
1-23
iii
Application Modeling ................................................................................................................
Testing, Debugging, and Validating a Design........................................................................
Deploying New Applications.........................................................................................................
Rollout Strategies ........................................................................................................................
Performance Checklist ...............................................................................................................
2
Monitoring and Improving Application Performance
Importance of Statistics .....................................................................................................................
Statistics Gathering Tools ............................................................................................................
Importance of Historical Data and Baselines............................................................................
Performance Intuition ..................................................................................................................
The Oracle Performance Improvement Method ...........................................................................
Introduction to Performance Improvement..............................................................................
Steps in The Oracle Performance Improvement Method .....................................................
How to Check the Operating System.......................................................................................
A Sample Decision Process for Performance Conceptual Modeling ..................................
Top Ten Mistakes Found in Oracle Systems...........................................................................
Performance Characteristics of Hardware Configurations ..................................................
3
1-25
1-25
1-27
1-27
1-27
2-2
2-6
2-8
2-8
2-9
2-9
2-11
2-12
2-12
2-14
2-16
Emergency Performance Techniques
Introduction to Emergency Performance Techniques.................................................................. 3-2
Steps in the Emergency Performance Method .............................................................................. 3-2
Index
iv
Send Us Your Comments
Oracle9i Database Performance Planning, Release 2 (9.2)
Part No. A96532-01
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v
vi
Preface
This book describes ways to improve Oracle performance by starting with good
application design and using statistics to monitor application performance. It
explains the Oracle Performance Improvement Method, as welll as emergency
performance techniques for dealing with performance problems.
This preface contains these topics:
■
Audience
■
Organization
■
Related Documentation
■
Conventions
■
Documentation Accessibility
vii
Audience
Oracle9i Database Performance Planning is a high-level aid for people responsible for
the operation, maintenance, and performance of Oracle. To use this book, you could
be a database administrator, application designer, programmer, or manager. You
should be familiar with Oracle9i, the operating system, and application design
before reading this manual.
Organization
This document contains:
Chapter 1, "Designing and Developing for Performance"
This chapter describes performance issues to consider when designing Oracle
applications.
Chapter 2, "Monitoring and Improving Application Performance"
This chapter describes the Oracle Performance Improvement Method and the
importance of statistics for application performance improvements.
Chapter 3, "Emergency Performance Techniques"
This chapter describes techniques for dealing with performance emergencies.
Related Documentation
Before reading this manual, you should have already read Oracle9i Database
Concepts, the Oracle9i Application Developer’s Guide - Fundamentals, and the Oracle9i
Database Administrator’s Guide.
For more information about Oracle Enterprise Manager and its optional
applications, see Oracle Enterprise Manager Concepts Guide and Oracle Enterprise
Manager Administrator’s Guide.
For more information about tuning the Oracle Application Server, see the Oracle
Application Server Performance and Tuning Guide.
Many of the examples in this book use the sample schemas of the seed database,
which is installed by default when you install Oracle. Refer to Oracle9i Sample
Schemas for information on how these schemas were created and how you can use
them yourself.
In North America, printed documentation is available for sale in the Oracle Store at
viii
http://oraclestore.oracle.com/
Customers in Europe, the Middle East, and Africa (EMEA) can purchase
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Conventions
This section describes the conventions used in the text and code examples of the this
documentation set. It describes:
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Conventions in Text
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Conventions in Code Examples
Conventions in Text
We use various conventions in text to help you more quickly identify special terms.
The following table describes those conventions and provides examples of their use.
ix
Convention
Meaning
Example
Bold
Bold typeface indicates terms that are
When you specify this clause, you create an
defined in the text or terms that appear in index-organized table.
a glossary, or both.
Italics
Italic typeface indicates book titles,
Oracle9i Database Concepts
emphasis, syntax clauses, or placeholders.
You can specify the parallel_clause.
Run Uold_release.SQL where old_release
refers to the release you installed prior to
upgrading.
UPPERCASE
Uppercase monospace typeface indicates
monospace
elements supplied by the system. Such
(fixed-width font) elements include parameters, privileges,
datatypes, RMAN keywords, SQL
keywords, SQL*Plus or utility commands,
packages and methods, as well as
system-supplied column names, database
objects and structures, user names, and
roles.
You can specify this clause only for a NUMBER
column.
You can back up the database using the BACKUP
command.
Query the TABLE_NAME column in the USER_
TABLES data dictionary view.
Specify the ROLLBACK_SEGMENTS parameter.
Use the DBMS_STATS.GENERATE_STATS
procedure.
lowercase
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executables and sample user-supplied
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computer and database names, net
service names, and connect identifiers, as
well as user-supplied database objects
and structures, column names, packages
and classes, user names and roles,
program units, and parameter values.
Enter sqlplus to open SQL*Plus.
The department_id, department_name,
and location_id columns are in the
hr.departments table.
Set the QUERY_REWRITE_ENABLED
initialization parameter to true.
Connect as oe user.
Conventions in Code Examples
Code examples illustrate SQL, PL/SQL, SQL*Plus, or other command-line
statements. They are displayed in a monospace (fixed-width) font and separated
from normal text as shown in this example:
SELECT username FROM dba_users WHERE username = ’MIGRATE’;
The following table describes typographic conventions used in code examples and
provides examples of their use.
x
Convention
Meaning
Example
[]
Brackets enclose one or more optional
items. Do not enter the brackets.
DECIMAL (digits [ , precision ])
{}
Braces enclose two or more items, one of
which is required. Do not enter the
braces.
{ENABLE | DISABLE}
|
A vertical bar represents a choice of two
{ENABLE | DISABLE}
or more options within brackets or braces.
[COMPRESS | NOCOMPRESS]
Enter one of the options. Do not enter the
vertical bar.
...
Horizontal ellipsis points indicate either:
■
■
.
.
.
Other notation
That we have omitted parts of the
code that are not directly related to
the example
CREATE TABLE ... AS subquery;
That you can repeat a portion of the
code
SELECT col1, col2, ... , coln FROM
employees;
Vertical ellipsis points indicate that we
have omitted several lines of code not
directly related to the example.
You must enter symbols other than
brackets, braces, vertical bars, and ellipsis
points as it is shown.
SQL> SELECT NAME FROM V$DATAFILE;
NAME
-----------------------------------/fsl/dbs/tbs_01.dbf
/fs1/dbs/tbs_02.dbf
.
.
.
/fsl/dbs/tbs_09.dbf
9 rows selected.
acctbal NUMBER(11,2);
acct
CONSTANT NUMBER(4) := 3;
Italics
Italicized text indicates variables for
CONNECT SYSTEM/system_password
which you must supply particular values.
UPPERCASE
Uppercase typeface indicates elements
supplied by the system. We show these
terms in uppercase in order to distinguish
them from terms you define. Unless terms
appear in brackets, enter them in the
order and with the spelling shown.
However, because these terms are not
case sensitive, you can enter them in
lowercase.
SELECT last_name, employee_id FROM
employees;
SELECT * FROM USER_TABLES;
DROP TABLE hr.employees;
xi
Convention
Meaning
Example
lowercase
Lowercase typeface indicates
programmatic elements that you supply.
For example, lowercase indicates names
of tables, columns, or files.
SELECT last_name, employee_id FROM
employees;
sqlplus hr/hr
Documentation Accessibility
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JAWS, a Windows screen
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Accessibility of Code Examples in Documentation
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documentation may contain links to Web sites of other companies or organizations
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sites.
xii
1
Designing and Developing for Performance
Good system performance begins with design and continues throughout the life of
your system. Carefully consider performance issues during the initial design phase,
and it will be easier to tune your system during production.
This chapter contains the following sections:
■
Oracle’s New Methodology
■
Understanding Investment Options
■
Understanding Scalability
■
System Architecture
■
Application Design Principles
■
Workload Testing, Modeling, and Implementation
■
Deploying New Applications
Designing and Developing for Performance 1-1
Oracle’s New Methodology
Oracle’s New Methodology
System performance has become increasingly important as computer systems get
larger and more complex and as the Internet plays a bigger role in business
applications. In order to accommodate this, Oracle Corporation has designed a new
performance methodology. It is based on years of Oracle designing and
performance experience, and it explains clear and simple activities that can
dramatically improve system performance.
Performance strategies vary in their effectiveness, and systems with different
purposes, such as operational systems and decision support systems, require
different performance skills. This book examines the considerations that any
database designer, administrator, or performance expert should focus their efforts
on.
System performance is designed and built into a system. It does not just happen.
Performance problems are usually the result of contention for, or exhaustion of,
some system resource. When a system resource is exhausted, the system is unable to
scale to higher levels of performance. This new performance methodology is based
on careful planning and design of the database, to prevent system resources from
becoming exhausted and causing down-time. By eliminating resource conflicts,
systems can be made scalable to the levels required by the business.
See Also: Oracle9i Database Performance Tuning Guide and Reference
Understanding Investment Options
With the availability of relatively inexpensive, high-powered processors, memory,
and disk drives, there is a temptation to buy more system resources to improve
performance. In many situations, new CPUs, memory, or more disk drives can
indeed provide an immediate performance improvement. However, any
performance increases achieved by adding hardware should be considered a
short-term relief to an immediate problem. If the demand and load rates on the
application continue to grow, then the chance that you will face the same problem
in the near future is very likely.
In other situations, additional hardware does not improve the system's performance
at all. Poorly designed systems perform poorly no matter how much extra hardware
is allocated. Before purchasing additional hardware, make sure that there is no
serialization or single threading going on within the application. Long-term, it is
generally more valuable to increase the efficiency of your application in terms of the
number of physical resources used for each business transaction.
1-2
Oracle9i Database Performance Planning
Understanding Scalability
Understanding Scalability
The word scalability is used in many contexts in development environments. The
following section provides an explanation of scalability that is aimed at application
designers and performance specialists.
What is Scalability?
Scalability is a system’s ability to process more workload, with a proportional
increase in system resource usage. In other words, in a scalable system, if you
double the workload, then the system would use twice as many system resources.
This sounds obvious, but due to conflicts within the system, the resource usage
might exceed twice the original workload.
Examples of bad scalability due to resource conflicts include the following:
■
Applications requiring significant concurrency management as user
populations increase
■
Increased locking activities
■
Increased data consistency workload
■
Increased operating system workload
■
Transactions requiring increases in data access as data volumes increase
■
■
Poor SQL and index design resulting in a higher number of logical I/Os for the
same number of rows returned
Reduced availability, because database objects take longer to maintain
An application is said to be unscalable if it exhausts a system resource to the point
where no more throughput is possible when it’s workload is increased. Such
applications result in fixed throughputs and poor response times.
Examples of resource exhaustion include the following:
■
Hardware exhaustion
■
Table scans in high-volume transactions causing inevitable disk I/O shortages
■
Excessive network requests, resulting in network and scheduling bottlenecks
■
Memory allocation causing paging and swapping
■
Excessive process and thread allocation causing operating system thrashing
Designing and Developing for Performance 1-3
Understanding Scalability
This means that application designers must create a design that uses the same
resources, regardless of user populations and data volumes, and does not put loads
on the system resources beyond their limits.
Internet Scalability
Applications that are accessible through the Internet have more complex
performance and availability requirements. Some applications are designed and
written only for Internet use, but even typical back-office applications, such as a
general ledger application, might require some or all data to be available online.
Characteristics of Internet age applications include the following:
1-4
■
Availability 24 hours a day, 365 days a year
■
Unpredictable and imprecise number of concurrent users
■
Difficulty in capacity planning
■
Availability for any type of query
■
Multitier architectures
■
Stateless middleware
■
Rapid development timescale
■
Minimal time for testing
Oracle9i Database Performance Planning
Understanding Scalability
Required Workload
Figure 1–1 Internet Workload Growth Curve
Time
Figure 1–1 illustrates the classic Internet/e-business and demand growth curve,
with demand growing at an increasing rate. Applications must scale with the
increase of workload and also when additional hardware is added to support
increasing demand. Design errors can cause the implementation to reach its
maximum, regardless of additional hardware resources or re-design efforts.
Internet applications are challenged by very short development timeframes with
limited time for testing and evaluation. However, bad design generally means that
at some point in the future, the system will need to be re-architected or
re-implemented. If an application with known architectural and implementation
limitations is deployed on the Internet, and if the workload exceeds the anticipated
demand, then there is real chance of failure in the future. From a business
perspective, poor performance can mean a loss of customers. If Web users do not
get a response in seven seconds, then the user’s attention could be lost forever.
In many cases, the cost of re-designing a system with the associated downtime costs
in migrating to new implementations exceeds the costs of properly building the
original system. The moral of the story is simple: design and implement with
scalability in mind from the start.
Designing and Developing for Performance 1-5
Understanding Scalability
Factors Preventing Scalability
When building applications, designers and architects should aim for as close to
perfect scalability as possible. This is sometimes called linear scalability, where
system throughput is directly proportional to the number of CPUs.
In real life, linear scalability is impossible for reasons beyond a designer’s control.
However, making the application design and implementation as scalable as possible
should ensure that current and future performance objectives can be achieved
through expansion of hardware components and the evolution of CPU technology.
Factors Preventing Linear Scalability
1.
Poor Application Design, Implementation, and Configuration
The application has the biggest impact on scalability. For example:
■
Poor schema design can cause expensive SQL that does not scale.
■
Poor transaction design can cause locking and serialization problems.
■
Poor connection management can cause poor response times and unreliable
systems.
However, the design is not the only problem. The physical implementation of
the application can be the weak link. For example:
■
■
■
■
2.
Systems can move to production environments with bad I/O strategies.
The production environment could use different execution plans than those
generated in testing.
Memory-intensive applications that allocate a large amount of memory
without much thought for freeing the memory at runtime can cause
excessive memory usage.
Inefficient memory usage and memory leaks put a high stress on the
operating virtual memory subsystem. This impacts performance and
availability.
Incorrect Sizing of Hardware Components
Bad capacity planning of all hardware components is becoming less of a
problem as relative hardware prices decrease. However, too much capacity can
mask scalability problems as the workload is increased on a system.
1-6
Oracle9i Database Performance Planning
System Architecture
3.
Limitations of Software Components
All software components have scalability and resource usage limitations. This
applies to application servers, database servers, and operating systems.
Application design should not place demands on the software beyond what it
can handle.
4.
Limitations of Hardware Components
Hardware is not perfectly scalable. Most multiprocessor machines can get close
to linear scaling with a finite number of CPUs, but after a certain point each
additional CPU can increase performance overall, but not proportionately.
There might come a time when an additional CPU offers no increase in
performance, or even degrades performance. This behavior is very closely
linked to the workload and the operating system setup.
Note: These factors are based on Oracle Corporation’s Server
Performance group’s experience of tuning unscalable systems.
System Architecture
There are two main parts to a system’s architecture:
■
Hardware and Software Components
■
Configuring the Right System Architecture for Your Requirements
Hardware and Software Components
Hardware Components
Today’s designers and architects are responsible for sizing and capacity planning of
hardware at each tier in a multitier environment. It is the architect's responsibility to
achieve a balanced design. This is analogous to a bridge designer who must
consider all the various payload and structural requirements for the bridge. A
bridge is only as strong as its weakest component. As a result, a bridge is designed
in balance, such that all components reach their design limits simultaneously.
Designing and Developing for Performance 1-7
System Architecture
The main hardware components are the following:
■
CPU
■
Memory
■
I/O Subsystem
■
Network
CPU There can be one or more CPUs, and they can vary in processing power from
simple CPUs found in hand-held devices to high-powered server CPUs. Sizing of
other hardware components is usually a multiple of the CPUs on the system.
Memory Database and application servers require considerable amounts of memory
to cache data and avoid time-consuming disk access.
I/O Subsystem The I/O subsystem can vary between the hard disk on a client PC and
high performance disk arrays. Disk arrays can perform thousands of I/Os each
second and provide availability through redundancy in terms of multiple I/O paths
and hot pluggable mirrored disks.
Network All computers in a system are connected to a network, from a modem line
to a high speed internal LAN. The primary concerns with network specifications are
bandwidth (volume) and latency (speed).
See Also: Oracle9i Database Performance Tuning Guide and Reference
for more information on tuning these resources
Software Components
The same way computers have common hardware components, applications have
common functional components. By dividing software development into functional
components, it is possible to comprehend the application design and architecture
better. Some components of the system are performed by existing software bought
to accelerate application implementation or to avoid re-development of common
components.
The difference between software components and hardware components is that
while hardware components only perform one task, a piece of software can perform
the roles of various software components. For example, a disk drive only stores and
retrieves data, but a client program can manage the user interface and perform
business logic.
1-8
Oracle9i Database Performance Planning
System Architecture
Most applications involve the following components:
■
Managing the User Interface
■
Implementing Business Logic
■
Managing User Requests and Resource Allocation
■
Managing Data and Transactions
Managing the User Interface This component is the most visible to application users.
This includes the following functions:
■
Painting the screen in front of the user
■
Collecting user data and transferring it to business logic
■
Validating data entry
■
Navigating through levels or states of the application
Implementing Business Logic This component implements core business rules that are
central to the application function. Errors made in this component could be very
costly to repair. This component is implemented by a mixture of declarative and
procedural approaches. An example of a declarative activity is defining unique and
foreign keys. An example of procedure-based logic is implementing a discounting
strategy.
Common functions of this component include the following:
■
Moving a data model to a relational table structure
■
Defining constraints in the relational table structure
■
Coding procedural logic to implement business rules
Managing User Requests and Resource Allocation This component is implemented in all
pieces of software. However, there are some requests and resources that can be
influenced by the application design and some that cannot.
In a multiuser application, most resource allocation by user requests are handled by
the database server or the operating system. However, in a large application where
the number of users and their usage pattern is unknown or growing rapidly, the
system architect must be proactive to ensure that no single software component
becomes overloaded and unstable.
Designing and Developing for Performance 1-9
System Architecture
Common functions of this component include the following:
■
Connection management with the database
■
Executing SQL efficiently (cursors and SQL sharing)
■
Managing client state information
■
Balancing the load of user requests across hardware resources
■
Setting operational targets for hardware/software components
■
Persistent queuing for asynchronous execution of tasks
Managing Data and Transactions This component is largely the responsibility of the
database server and the operating system.
Common functions of this component include the following:
■
Providing concurrent access to data using locks and transactional semantics
■
Providing optimized access to the data using indexes and memory cache
■
Ensuring that data changes are logged in the event of a hardware failure
■
Enforcing any rules defined for the data
Configuring the Right System Architecture for Your Requirements
Configuring the initial system architecture is a largely iterative process. Architects
must satisfy the system requirements within budget and schedule constraints. If the
system requires interactive users transacting business or making decisions based on
the contents of a database, then user requirements drive the architecture. If there are
few interactive users on the system, then the architecture is process-driven.
Examples of interactive user applications:
1-10
■
Accounting and bookkeeping applications
■
Order entry systems
■
Email servers
■
Web-based retail applications
■
Trading systems
Oracle9i Database Performance Planning
System Architecture
Examples of process-driven applications:
■
Utility billing systems
■
Fraud detection systems
■
Direct mail
In many ways, process-driven applications are easier to design than multiuser
applications because the user interface element is eliminated. However, because the
objectives are process-oriented, architects not accustomed to dealing with large data
volumes and different success factors can become confused. Process-driven
applications draw from the skills sets used in both user-based applications and data
warehousing. Therefore, this book focuses on evolving system architectures for
interactive users.
Note: Generating a system architecture is not a deterministic
process. It requires careful consideration of business requirements,
technology choices, existing infrastructure and systems, and actual
physical resources, such as budget and manpower.
The following questions should stimulate thought on architecture, though they are
not a definitive guide to system architecture. These questions demonstrate how
business requirements can influence the architecture, ease of implementation, and
overall performance and availability of a system. For example:
■
How many users will the system support?
Most applications fall into one of the following categories:
–
Very few users on a lightly-used or exclusive machine
For this type of application, there is usually one user. The focus of the
application design is to make the single user as productive as possible by
providing good response time, yet make the application require minimal
administration. Users of these applications rarely interfere with each other
and have minimal resource conflicts.
–
A medium to large number of users in a corporation using shared
applications
For this type of application, the users are limited by the number of
employees in the corporation actually transacting business through the
system. Therefore, the number of users is predictable. However, delivering
a reliable service is crucial to the business. The users will be using a shared
Designing and Developing for Performance 1-11
System Architecture
resource, so design efforts must address response time under heavy system
load, escalation of resource for each session usage, and room for future
growth.
–
An infinite user population distributed on the Internet
For this type of application, extra engineering effort is required to ensure
that no system component exceeds its design limits. This would create a
bottleneck that brings the system to a halt and becomes unstable. These
applications require complex load balancing, stateless application servers,
and efficient database connection management. In addition, statistics and
governors should be used to ensure that the user gets some feedback if their
requests cannot be satisfied due to system overload.
■
What will be the user interaction method?
The choices of user interface range from a simple Web browser to a custom
client program.
■
Where are the users located?
The distance between users influences how the application is engineered to
cope with network latencies. The location also affects which times of the day are
busy, when it is impossible to perform batch or system maintenance functions.
■
What is the network speed?
Network speed affects the amount of data and the conversational nature of the
user interface with the application and database servers. A highly
conversational user interface can communicate with back-end servers on every
key stroke or field level validation. A less conversational interface works on a
screen-sent and a screen-received model. On a slow network, it is impossible to
get good data entry speeds with a highly conversational user interface.
■
How much data will the user access, and how much of that data is largely read
only?
The amount of data queried online influences all aspects of the design, from
table and index design to the presentation layers. Design efforts must ensure
that user response time is not a function of the size of the database. If the
application is largely read only, then replication and data distribution to local
caches in the application servers become a viable option. This also reduces
workload on the core transactional server.
■
1-12
What is the user response time requirement?
Oracle9i Database Performance Planning
System Architecture
Consideration of the user type is important. If the user is an executive who
requires accurate information to make split second decisions, then user
response time cannot be compromised. Other types of users, such as users
performing data entry activities, might not need such a high level of
performance.
■
Do users expect 24 hour service?
This is mandatory for today's Internet applications where trade is conducted 24
hours a day. However, corporate systems that run in a single time zone might
be able to tolerate after-hours downtime. This after-hours downtime can be
used to run batch processes or to perform system administration. In this case, it
might be more economic not to run a fully-available system.
■
Must all changes be made in real time?
It is important to determine if transactions need to be executed within the user
response time, or if they can they be queued for asynchronous execution.
The following are secondary questions, which can also influence the design, but
really have more impact on budget and ease of implementation. For example:
■
How big will the database be?
This influences the sizing of the database server machine. On systems with a
very large database, it might be necessary to have a bigger machine than
dictated by the workload. This is because the administration overhead with
large databases is largely a function of the database size. As tables and indexes
grow, it takes proportionately more CPUs to allow table reorganizations and
index builds to complete in an acceptable time limit.
■
What is the required throughput of business transactions?
■
What are the availability requirements?
■
Do skills exist to build and administer this application?
■
What compromises will be forced by budget constraints?
Designing and Developing for Performance 1-13
Application Design Principles
Application Design Principles
This section describes design decisions that are involved in building applications.
Simplicity In Application Design
Applications are no different than any other designed and engineered product.
Well-designed structures, machines, and tools are usually reliable, easy to use and
maintain, and simple in concept. In the most general terms, if the design looks right,
then it probably is right. This principle should always be kept in mind when
building applications.
Consider some of the following design issues:
■
■
■
■
■
If the table design is so complicated that nobody can fully understand it, then
the table is probably designed badly.
If SQL statements are so long and involved that it would be impossible for any
optimizer to effectively optimize it in real time, then there is probably a bad
statement, underlying transaction, or table design.
If there are indexes on a table and the same columns are repeatedly indexed,
then there is probably a bad index design.
If queries are submitted without suitable qualification for rapid response for
online users, then there is probably a bad user interface or transaction design.
If the calls to the database are abstracted away from the application logic by
many layers of software, then there is probably a bad software development
method.
Data Modeling
Data modeling is important to successful relational application design. This should
be done in a way that quickly represents the business practices. Chances are, there
will be heated debates about the correct data model. The important thing is to apply
greatest modeling efforts to those entities affected by the most frequent business
transactions. In the modeling phase, there is a great temptation to spend too much
time modeling the non-core data elements, which results in increased development
lead times. Use of modeling tools can then rapidly generate schema definitions and
can be useful when a fast prototype is required.
1-14
Oracle9i Database Performance Planning
Application Design Principles
Table and Index Design
Table design is largely a compromise between flexibility and performance of core
transactions. To keep the database flexible and able to accommodate unforeseen
workloads, the table design should be very similar to the data model, and it should
be normalized to at least 3rd normal form. However, certain core transactions
required by users can require selective denormalization for performance purposes.
Examples of this technique include storing tables pre-joined, the addition of derived
columns, and aggregate values. Oracle provides numerous options for storage of
aggregates and pre-joined data by clustering and materialized view functions.
These features allow a simpler table design to be adopted initially.
Again, focus and resources should be spent on the business critical tables, so that
good performance can be achieved. For non-critical tables, shortcuts in design can
be adopted to enable a more rapid application development. If, however, in
prototyping and testing a non-core table becomes a performance problem, then
remedial design effort should be applied immediately.
Index design is also a largely iterative process, based on the SQL generated by
application designers. However, it is possible to make a sensible start by building
indexes that enforce primary key constraints and indexes on known access patterns,
such as a person's name. As the application evolves and testing is performed on
realistic sizes of data, certain queries will need performance improvements for
which building a better index is a good solution. The following list of indexing
design ideas should be considered when building a new index:
■
Appending Columns to an Index or Using Index-Organized Tables
■
Using a Different Index Type
■
Finding the Cost of an Index
■
Serializing within Indexes
■
Ordering Columns in an Index
Appending Columns to an Index or Using Index-Organized Tables
One of the easiest ways to speed up a query is to reduce the number of logical I/Os
by eliminating a table access from the execution plan. This can be done by
appending to the index all columns referenced by the query. These columns are the
select list columns and any required join or sort columns. This technique is
particularly useful in speeding up online applications response times when
time-consuming I/Os are reduced. This is best applied when testing the application
with properly sized data for the first time.
Designing and Developing for Performance 1-15
Application Design Principles
The most aggressive form of this technique is to build an index-organized table
(IOT). However, you must be careful that the increased leaf size of an IOT does not
undermine the efforts to reduce I/O.
Using a Different Index Type
There are several index types available, and each index has benefits for certain
situations. The following list gives performance ideas associated with each index
type.
B-Tree Indexes These are the standard index type, and they are excellent for primary
key and highly-selective indexes. Used as concatenated indexes, B-tree indexes can
be used to retrieve data sorted by the index columns.
Bitmap Indexes These are suitable for low cardinality data. Through compression
techniques, they can generate a large number of rowids with minimal I/O.
Combining bitmap indexes on non-selective columns allows efficient AND and OR
operations with a great number of rowids with minimal I/O. Bitmap indexes are
particularly efficient in queries with COUNT(), because the query can be satisfied
within the index.
Function-based Indexes These indexes allow access through a B-tree on a value
derived from a function on the base data. Function-based indexes have some
limitations with regards to the use of nulls, and they require that you have the
cost-based optimizer enabled.
Function-based indexes are particularly useful when querying on composite
columns to produce a derived result or to overcome limitations in the way data is
stored in the database. An example of this is querying for line items in an order
exceeding a certain value derived from (sales price - discount) x quantity, where
these were columns in the table. Another example is to apply the UPPER function to
the data to allow case-insensitive searches.
See Also: Oracle9i Database Performance Tuning Guide and Reference
Partitioned Indexes Partitioning a global index allows partition pruning to take place
within an index access, which results in reduced I/Os. By definition of good range
or list partitioning, fast index scans of the correct index partitions can result in very
fast query times.
1-16
Oracle9i Database Performance Planning
Application Design Principles
Reverse Key Indexes These are designed to eliminate index hot spots on insert
applications. These indexes are excellent for insert performance, but they are limited
in that they cannot be used for index range scans.
Finding the Cost of an Index
Building and maintaining an index structure can be expensive, and it can consume
resources such as disk space, CPU, and I/O capacity. Designers must ensure that
the benefits of any index outweigh the negatives of index maintenance.
Use this simple estimation guide for the cost of index maintenance: Each index
maintained by an INSERT, DELETE, or UPDATE of the indexed keys requires about
three times as much resource as the actual DML operation on the table. What this
means is that if you INSERT into a table with three indexes, then it will be
approximately 10 times slower than an INSERT into a table with no indexes. For
DML, and particularly for INSERT-heavy applications, the index design should be
seriously reviewed, which might require a compromise between the query and
INSERT performance.
Serializing within Indexes
Use of sequences, or timestamps, to generate key values that are indexed
themselves can lead to database hotspot problems, which affect response time and
throughput. This is usually the result of a monotonically growing key that results in
a right-growing index. To avoid this problem, try to generate keys that insert over
the full range of the index. This results in a well-balanced index that is more
scalable and space efficient. You can achieve this by using a reverse key index or
using a cycling sequence to prefix and sequence values.
Ordering Columns in an Index
Designers should be flexible in defining any rules for index building. Depending on
your circumstances, use one of the following two ways to order the keys in an
index:
1.
Order columns most selectivity first. This method is the most commonly used,
because it provides the fastest access with minimal I/O to the actual rowids
required. This technique is used mainly for primary keys and for very selective
range scans.
2.
Order columns to reduce I/O by clustering or sorting data. In large range scans,
I/Os can usually be reduced by ordering the columns in the least selective
order, or in a manner that sorts the data in the way it should be retrieved.
Designing and Developing for Performance 1-17
Application Design Principles
Using Views
Views can speed up and simplify application design. A simple view definition can
mask data model complexity from the programmers whose priorities are to retrieve,
display, collect, and store data.
However, while views provide clean programming interfaces, they can cause
sub-optimal, resource-intensive queries. The worst type of view use is when a view
references other views, and when they are joined in queries. In many cases,
developers can satisfy the query directly from the table without using a view.
Usually, because of their inherent properties, views make it difficult for the
optimizer to generate the optimal execution plan.
SQL Execution Efficiency
In the design and architecture phase of any system development, care should be
taken to ensure that the application developers understand SQL execution
efficiency. To do this, the development environment must support the following
characteristics:
■
Good Database Connection Management
Connecting to the database is an expensive operation that is highly unscalable.
Therefore, the number of concurrent connections to the database should be
minimized as much as possible. A simple system, where a user connects at
application initialization, is ideal. However, in a Web-based or multitiered
application, where application servers are used to multiplex database
connections to users, this can be difficult. With these types of applications,
design efforts should ensure that database connections are pooled and are not
reestablished for each user request.
■
Good Cursor Usage and Management
Maintaining user connections is equally important to minimizing the parsing
activity on the system. Parsing is the process of interpreting a SQL statement
and creating an execution plan for it. This process has many phases, including
syntax checking, security checking, execution plan generation, and loading
shared structures into the shared pool. There are two types of parse operations:
■
1-18
Hard Parsing. A SQL statement is submitted for the first time, and no
match is found in the shared pool. Hard parses are the most
resource-intensive and unscalable, because they perform all the operations
involved in a parse.
Oracle9i Database Performance Planning
Application Design Principles
■
Soft Parsing. A SQL statement is submitted for the first time, and a match is
found in the shared pool. The match can be the result of previous execution
by another user. The SQL statement is shared, which is good for
performance. However, soft parses are not ideal, because they still require
syntax and security checking, which consume system resources.
Because parsing should be minimized as much as possible, application
developers should design their applications to parse SQL statements once and
execute them many times. This is done through cursors. Experienced SQL
programmers should be familiar with the concept of opening and re-executing
cursors.
Application developers must also ensure that SQL statements are shared within
the shared pool. To do this, bind variables to represent the parts of the query
that change from execution to execution. If this is not done, then the SQL
statement is likely to be parsed once and never re-used by other users. To
ensure that SQL is shared, use bind variables and do not use string literals with
SQL statements. For example:
Statement with string literals:
SELECT * FROM emp
WHERE ename
LIKE ’KING’;
Statement with bind variables:
SELECT * FROM emp
WHERE ename
LIKE :1;
The following example shows the results of some tests on a simple OLTP
application:
Test
#Users Supported
No Parsing all statements
270
Soft Parsing all statements
150
Hard Parsing all statements
60
Re-Connecting for each Transaction
30
These tests were performed on a four-CPU machine. The differences increase as
the number of CPUs on the system increase.
Designing and Developing for Performance 1-19
Application Design Principles
Implementing the Application
The choice of development environment and programming language is largely a
function of the skills available in the development team and architectural decisions
made when specifying the application. There are, however, some simple
performance management rules that can lead to scalable, high-performance
applications.
1.
Choose a development environment suitable for software components, and do
not let it limit your design for performance decisions. If it does, then you
probably chose the wrong language or environment.
■
User Interface
The programming model can vary between HTML generation and calling
the windowing system directly. The development method should focus on
response time of the user interface code. If HTML or Java is being sent over
a network, then try to minimize network volume and interactions.
■
Business Logic
Interpreted languages, such as Java and PL/SQL, are ideal to encode
business logic. They are fully portable, which makes upgrading logic
relatively easy. Both languages are syntactically rich to allow code that is
easy to read and interpret. If business logic requires complex mathematical
functions, then a compiled binary language might be needed. The business
logic code can be on the client machine, the application server, and the
database server. However, the application server is the most common
location for business logic.
■
User Requests and Resource Allocation
Most of this is not affected by the programming language, but tools and 4th
generation languages that mask database connection and cursor
management might use inefficient mechanisms. When evaluating these
tools and environments, check their database connection model and their
use of cursors and bind variables.
■
Data Management and Transactions
Most of this is not affected by the programming language.
2.
1-20
When implementing a software component, implement its function and not the
functionality associated with other components. Implementing another
component’s functionality results in sub-optimal designs and implementations.
This applies to all components.
Oracle9i Database Performance Planning
Application Design Principles
3.
Do not leave gaps in functionality or have software components
under-researched in design, implementation, or testing. In many cases, gaps are
not discovered until the application is rolled out or tested at realistic volumes.
This is usually a sign of poor architecture or initial system specification. Data
archival/purge modules are most frequently neglected during initial system
design, build, and implementation.
4.
When implementing procedural logic, implement in a procedural language,
such as C, Java, PL/SQL. When implementing data access (queries) or data
changes (DML), use SQL. This rule is specific to the business logic modules of
code where procedural code is mixed with data access (non-procedural SQL)
code. There is great temptation to put procedural logic into the SQL access. This
tends to result in poor SQL that is resource-intensive. SQL statements with
DECODE case statements are very often candidates for optimization, as are
statements with a large amount of OR predicates or set operators, such as UNION
and MINUS.
5.
Cache frequently accessed, rarely changing data that is expensive to retrieve on
a repeated basis. However, make this cache mechanism easy to use, and ensure
that it is really cheaper than accessing the data in the original method. This is
applicable to all modules where frequently used data values should be cached
or stored locally, rather than be repeatedly retrieved from a remote or expensive
data store.
The most common examples of candidates for local caching include the
following:
■
■
■
■
■
Today's date. SELECT SYSDATE FROM DUAL can account for over 60% of the
workload on a database.
The current user name.
Repeated application variables and constants, such as tax rates, discounting
rates, or location information.
Caching data locally can be further extended into building a local data
cache into the application server middle tiers. This helps take load off the
central database servers. However, care should be taken when constructing
local caches so that they do not become so complex that they cease to give a
performance gain.
Local sequence generation.
The design implications of using a cache should be considered. For example, if
a user is connected at midnight and the date is cached, then the date value he
has becomes invalid.
Designing and Developing for Performance 1-21
Application Design Principles
6.
Optimize the interfaces between components, and ensure that all components
are used in the most scalable configuration. This rule requires minimal
explanation and applies to all modules and their interfaces.
7.
Use foreign key references. Enforcing referential integrity through an
application is expensive. You can maintain a foreign key reference by selecting
the column value of the child from the parent and ensuring that it exists. The
foreign key constraint enforcement supplied by Oracle (which does not use
SQL) is fast, easy to declare, and does not create network traffic.
Trends in Application Development
The two biggest challenges in application development today are the increased use
of Java to replace compiled C or C++ applications, and increased use of
object-oriented techniques, influencing the schema design.
Java provides better portability of code and availability to programmers. However,
there are a number of performance implications associated with Java. Because Java
is an interpreted language, it is slower at executing similar logic than compiled
languages such as C. As a result, resource usage of client machines increases. This
requires more powerful CPUs to be applied in the client or middle-tier machines
and greater care from programmers to produce efficient code.
Because Java is an object-oriented language, it encourages insulation of data access
into classes not performing the business logic. As a result, programmers might
invoke methods without knowledge of the efficiency of the data access method
being used. This tends to result in database access that is very minimal and uses the
simplest and crudest interfaces to the database.
With this type of software design, queries do not always include all the WHERE
predicates to be efficient, and row filtering is performed in the Java program. This is
very inefficient. In addition, for DML operations, and especially for INSERTs, single
INSERTs are performed, making use of the array interface impossible. In some
cases, this is made more inefficient by procedure calls. More resources are used
moving the data to and from the database than in the actual database calls.
In general, it is best to place data access calls next to the business logic to achieve
the best overall transaction design.
The acceptance of object-orientation at a programming level has led to the creation
of object-oriented databases within the Oracle Server. This has manifested itself in
many ways, from storing object structures within BLOBs and only using the
database effectively as an indexed card file to the use of the Oracle object relational
features.
1-22
Oracle9i Database Performance Planning
Workload Testing, Modeling, and Implementation
If you adopt an object-oriented approach to schema design, then make sure that you
do not lose the flexibility of the relational storage model. In many cases, the
object-oriented approach to schema design ends up in a heavily denormalized data
structure that requires considerable maintenance and REF pointers associated with
objects. Often, these designs represent a step backward to the hierarchical and
network database designs that were replaced with the relational storage method.
In summary, if you are storing your data in your database for the long-term and you
anticipate a degree of ad hoc queries or application development on the same
schema, then you will probably find that the relational storage method gives the
best performance and flexibility.
Workload Testing, Modeling, and Implementation
Sizing Data
You could experience errors in your sizing estimates when dealing with variable
length data if you work with a poor sample set. Also, as data volumes grow, your
key lengths could grow considerably, altering your assumptions for column sizes.
When the system becomes operational it becomes harder to predict database
growth, especially that of indexes. Tables grow over time, and indexes are subject to
the individual behavior of the application in terms of key generation, insertion
pattern, and deletion of rows. The worst case is where you insert using an
ascending key and then delete most rows from the left-hand side but not all the
rows. This leaves gaps and wasted space. If you have index use like this make sure
that you know how to use the online index rebuild facility.
Most good DBAs monitor space allocation for each object and look for objects that
could grow out of control. A good understanding of the application can highlight
objects that could grow rapidly or unpredictably. This is a crucial part of both
performance and availability planning for any system. When implementing the
production database, the design should attempt to ensure that minimal space
management takes place when interactive users are using the application. This
applies for all data, temp, and rollback segments.
Estimating Workloads
Estimation of workloads for capacity planning and testing purposes is often
described as a black art. When considering the number of variables involved it is
easy to see why this process is largely impossible to get precisely correct. However,
designers need to specify machines with CPUs, memory, and disk drives, and
Designing and Developing for Performance 1-23
Workload Testing, Modeling, and Implementation
eventually roll out an application. There are a number of techniques used for sizing,
and each technique has merit. When sizing, it is best to use at least two methods to
validate your decision-making process and provide supporting documentation.
Extrapolating From a Similar System
This is an entirely empirical approach where an existing system of similar
characteristics and known performance is used as a basis system. The specification
of this system is then modified by the sizing specialist according to the known
differences. This approach has merit in that it correlates with an existing system, but
it provides little assistance when dealing with the differences.
This approach is used in nearly all large engineering disciplines when preparing the
cost of an engineering project be it a large building, a ship, a bridge, or an oil rig. If
the reference system is an order of magnitude different in size from the anticipated
system, then some of the components could have exceeded their design limits.
Benchmarking
The benchmarking process is both resource and time consuming, and it might not
get the correct results. By simulating in a benchmark an application in early
development or prototype form, there is a danger of measuring something that has
no resemblance to the actual production system. This sounds strange, but over the
many years of benchmarking customer applications with the database development
organization, we have yet to see good correlation between the benchmark
application and the actual production system. This is mainly due to the number of
application inefficiencies introduced in the development process.
However, benchmarks have been used successfully to size systems to an acceptable
level of accuracy. In particular, benchmarks are very good at determining the actual
I/O requirements and testing recovery processes when a system is fully loaded.
Benchmarks by their nature stress all system components to their limits. As all
components are being stressed be prepared to see all errors in application design
and implementation manifest themselves while benchmarking. Benchmarks also
test database, operating system, and hardware components. Because most
benchmarks are performed in a rush, expect setbacks and problems when a system
component fails. Benchmarking is a stressful activity, and it takes considerable
experience to get the most out of a benchmarking exercise.
1-24
Oracle9i Database Performance Planning
Workload Testing, Modeling, and Implementation
Application Modeling
Modeling the application can range from complex mathematical modeling exercises
to the classic simple calculations performed on the back of an envelope. Both
methods have merit, with one attempting to be very precise and the other making
gross estimates. The down side of both methods is that they do not allow for
implementation errors and inefficiencies.
The estimation and sizing process is an imprecise science. However, by
investigating the process, some intelligent estimates can be made. The whole
estimation process makes no allowances for application inefficiencies introduced by
writing bad SQL, poor index design, or poor cursor management. A good sizing
engineer builds in margin for application inefficiencies. A good performance
engineer discovers the inefficiencies and makes the estimates look realistic. The
process of discovering the application inefficiencies is described in the Oracle
performance method.
Testing, Debugging, and Validating a Design
The testing process mainly consists of functional and stability testing. At some point
in the process, performance testing is performed.
The following list describes some simple rules for performance testing an
application. If correctly documented, this provides important information for the
production application and the capacity planning process after the application has
gone live.
■
Test with realistic data volumes and distributions.
All testing must be done with fully populated tables. The test database should
contain data representative of the production system in terms of data volume
and cardinality between tables. All the production indexes should be built and
the schema statistics should be populated correctly.
■
Use the correct optimizer mode.
All testing should be performed with the optimizer mode that will be used in
production. All Oracle research and development effort is focused upon the
cost-based optimizer, and therefore Oracle Corporation recommends the use of
the cost-based optimizer.
■
Test a single user performance.
A single user on an idle or lightly used system should be tested for acceptable
performance. If a single user cannot get acceptable performance under ideal
Designing and Developing for Performance 1-25
Workload Testing, Modeling, and Implementation
conditions, it is impossible there will be good performance under multiple users
where resources are shared.
■
Obtain and document plans for all SQL statements.
Obtain an execution plan for each SQL statement, and some metrics should be
obtained for at least one execution of the statement. This process should be used
to validate that a good execution plan is being obtained by the optimizer and
the relative cost of the SQL statement is understood in terms of CPU time and
physical I/Os. This process assists in identifying the heavy use transactions that
will require the most tuning and performance work in the future.
■
Attempt multiuser testing.
This process is difficult to perform accurately, because user workload and
profiles might not be fully quantified. However, transactions performing DML
statements should be tested to ensure that there are no locking conflicts or
serialization problems.
■
Test with the correct hardware configuration.
It is important to test with a configuration as close to the production system as
possible. This is particularly important with respect to network latencies, I/O
sub-system bandwidth and processor type and speed. A failure to do this could
result in an incorrect analysis of potential performance problems.
■
Measure steady state performance.
When benchmarking, it is important to measure the performance under steady
state conditions. Each benchmark run should have a ramp-up phase, where
users are connected to the application and gradually start performing work on
the application. This process allows for frequently cached data to be initialized
into the cache and single execution operations, such as parsing, to be completed
prior to the steady state condition. Likewise, at the end of a benchmark run,
there should be a ramp-down period, where resources are freed from the
system and users cease work and disconnect.
1-26
Oracle9i Database Performance Planning
Deploying New Applications
Deploying New Applications
This section describes design decisions involved deploying applications.
Rollout Strategies
When new applications are rolled out, two strategies are commonly adopted:
■
Big Bang Approach - All users migrate to the new system at once.
■
Trickle Approach - Users slowly migrate from existing systems to the new one.
Both approaches have merits and disadvantages. The Big Bang approach relies on
good testing of the application at the required scale, but has the advantage of
minimal data conversion and synchronization with the old system, because it is
simply switched off. The Trickle approach allows debugging of scalability issues as
the workload increases, but might mean that data needs to be migrated to and from
legacy systems as the transition takes place.
It is hard to recommend one approach over the other, because each method has
associated risks that could lead to system outages as the transition takes place.
Certainly, the Trickle approach allows profiling of real users as they are introduced
to the new application and allows the system to be reconfigured only affecting the
migrated users. This approach affects the work of the early adopters, but limits the
load on support services. This means that unscheduled outages only affect a small
percentage of the user population.
The decision on how to roll out a new application is specific to each business. The
approach adopted will have its own unique pressures and stresses. The more testing
and knowledge derived from the testing process, the more you will realize what is
best for the rollout.
Performance Checklist
To assist in the rollout process, build a list of tasks that, if performed correctly,
increase the chance of good performance in production and, if there is a problem,
enable rapid debugging of the application. For example:
1.
When you create the control file for the production database, allow for growth
by setting MAXINSTANCES, MAXDATAFILES, MAXLOGFILES, MAXLOGMEMBERS,
and MAXLOGHISTORY to values higher than what you anticipate for the rollout.
This results in more disk space usage and bigger control files, but saves time
later should these need extension in an emergency.
Designing and Developing for Performance 1-27
Deploying New Applications
2.
Set block size and optimizer mode to that used to develop the application.
Export the schema statistics from the development/test environment to the
production database if the testing was done on representative data volumes and
the current SQL execution plans are correct.
3.
Set the minimal number of initialization parameters. The important parameters
to set size the various caches within the SGA. The additional parameters that
specify the behavior of the archive dump destinations should be set for backup
and debugging purposes. Ideally, most other parameters should be left at
default. If there is more tuning to perform, this shows up when the system is
under load.
See Also: Oracle9i Database Performance Tuning Guide and Reference
for guidance on setting minimal parameters in initial instance
configuration
4.
Be prepared to manage block contention by setting storage options of database
objects. Tables and indexes that experience high INSERT/UPDATE/DELETE
rates should be created with either automatic segment space management or
multiple freelists and an increased setting of INITRANS. To avoid contention of
rollback segments, either automatic undo management should be used or
multiple rollback segments should be created to support the required user
population.
See Also: Oracle9i Database Administrator’s Guide for more
information on using automatic undo management and on
managing free space with automatic segment space management
1-28
5.
All SQL statements should be verified to be optimal and their resource usage
understood.
6.
Validate that middleware and programs that connect to the database are
efficient in their connection management and do not logon/logoff repeatedly.
7.
Validate that the SQL statements use cursors efficiently. Each SQL statement
should be parsed once and then executed multiple times. The most common
reason this does not happen is because bind variables are not used properly and
WHERE clause predicates are sent as string literals. If the precompilers are used
to develop the application, then make sure that the parameters
MAXOPENCURSORS, HOLD_CURSOR, and RELEASE_CURSOR have been reset
from the default values prior to precompiling the application.
Oracle9i Database Performance Planning
Deploying New Applications
8.
Validate that all schema objects have been correctly migrated from the
development environment to the production database. This includes tables,
indexes, sequences, triggers, packages, procedures, functions, java objects,
synonyms, grants, and views. Ensure that any modifications made in testing are
made to the production system.
9.
As soon as the system is rolled out, establish a baseline set of statistics from the
database and operating system. To do this, use Enterprise Manager or
Statspack. This first set of statistics validates or corrects any assumptions made
in the design and rollout process.
10. Start anticipating the first bottleneck (there will always be one) and follow the
Oracle performance method to make performance improvement.
Designing and Developing for Performance 1-29
Deploying New Applications
1-30
Oracle9i Database Performance Planning
2
Monitoring and Improving Application
Performance
This chapter contains the following sections:
■
Importance of Statistics
■
The Oracle Performance Improvement Method
Monitoring and Improving Application Performance 2-1
Importance of Statistics
Importance of Statistics
Before reacting to a problem, collect all possible statistics and get an overall picture
of the application. Getting a complete landscape of the system may take
considerable effort. But, if data has already been collected and embedded into the
application,thenthisprocessismuch easier.
After collecting as much initial data as possible, outline issues found from the
statistics, the same way doctors collect symptoms from patients. Reacting to
symptoms too early in the performance analysis process generally results in an
incorrect analysis, which wastes time later. For example, it is extremely risky for a
doctor to prescribe open heart surgery for a patient who complains of chest pains
on the initial consultation.
Operating System Statistics
Operating system statistics provide information on the usage and performance of
the main hardware components of the system, as well as the performance of the
operating system itself. This information is crucial for detecting potential resource
exhaustion, such as CPU cycles and physical memory, and for detecting bad
performance of peripherals, such as disk drives.
Operating system statistics are only an indication of how the hardware and
operating system are working. Many system performance analysts react to a
hardware resource shortage by installing more hardware. This is a reactionary
response to a series of symptoms shown in the operating system statistics. It is
always best to consider operating system statistics as a diagnostic tool, similar to the
way many doctors use body temperature, pulse rate, and patient pain when making
a diagnosis. To help identify bottlenecks, gather operating system statistics for all
servers in the system under performance analysis.
Operating system statistics include the following:
■
CPU Statistics
■
Virtual Memory Statistics
■
Disk Statistics
■
Network Statistics
CPU Statistics CPU utilization is the most important operating system statistic in the
tuning process. Get CPU utilization for the entire system and for each individual
CPU on multi-processor environments. Utilization for each CPU can detect
single-threading and scalability issues.
2-2
Oracle9i Database Performance Planning
Importance of Statistics
Most operating systems report CPU usage as time spent in user space or mode and
time spent in kernel space or mode. These additional statistics allow better analysis
of what is actually being executed on the CPU.
On an Oracle data server system, where there is generally only one application
running, the server runs database activity in user space. Activities required to
service database requests (such as scheduling, synchronization, I/O, memory
management, and process/thread creation and tear down) run in kernel mode. In a
system where all CPU is fully utilized, a healthy Oracle system runs between 65%
and 95% in user space.
Note: On UNIX systems, where wait for I/O is derived for part of
the CPU statistics, this value should be treated as idle time.
Virtual Memory Statistics Virtual memory statistics should mainly be used as a check
to validate that there is very little paging or swapping activity on the system.
System performance degrades rapidly and unpredictably when paging or swapping
occurs.
Individual process memory statistics can detect memory leaks due to a
programming failure to deallocate memory taken from the process heap. These
statistics should be used to validate that memory usage does not increase after the
system has reached a steady state after startup. This problem is particularly acute
on shared server applications on middle tier machines where session state may
persist across user interactions, and on completion state information that is not fully
deallocated.
Disk Statistics Because the database resides on a set of disks, the performance of the
I/O subsystem is very important to the performance of the database. Most
operating systems provide extensive statistics on disk performance. The most
important disk statistics are the current response time and the length of the disk
queues. These statistics show if the disk is performing optimally or if the disk is
being overworked. If a disk shows response times over 20 milliseconds, then it is
performing badly or is overworked. This is your bottleneck. If disk queues start to
exceed two, then the disk is a potential bottleneck of the system.
Network Statistics Network statistics can be used in much the same way as disk
statistics to determine if a network or network interface is overloaded or not
performing optimally. In today's networked applications, network latency can be a
large portion of the actual user response time. For this reason, these statistics are a
crucial debugging tool.
Monitoring and Improving Application Performance 2-3
Importance of Statistics
Database Statistics
Database statistics provide information on the type of load on the database, as well
as the internal and external resources used by the database. When database
resources become exhausted, it is possible to identify bottlenecks in the application.
Database statistics can be queried directly from the database in a relational manner
using SQL. These statistics can be inserted back into the database with the INSERT
INTO x AS SELECT ... or CREATE TABLE x AS SELECT ... statements. This is the
basis of most snapshot mechanisms that allow statistical gathering over time. Most
statistics are contained in a series of virtual tables or views known as the V$ tables,
because they are prefixed with V$. These are read only, and they are owned by SYS.
Many of the tables contain identifiers and keys that can be joined to other V$ tables.
In order to get meaningful database statistics, the TIMED_STATISTICS parameter
must be enabled for the database instance. The performance impact of having
TIMED_STATISTICS enabled is minimal compared to instance performance. The
performance improvements and debugging value of a complete set of statistics
make this parameter crucial to effective performance analysis.
The core database statistics are:
■
Buffer Cache
■
Shared Pool
■
Wait Events
Buffer Cache The buffer cache manages blocks read from disk into buffers in
memory. It also holds information on the most recently used buffers and those
modified in normal database operation. To get best query performance, a user query
accesses all required data blocks within the buffer cache, thus satisfying the query
from memory. However, this might not always happen, because the database is
many multiples the size of the buffer cache. With this in mind, it is easy to see that
the buffer cache requires management and tuning.
The objective in tuning the buffer cache is to get acceptable user query time by
having as many of the required blocks in the cache as possible. Also, eliminate time
consuming I/Os without inducing any serialization points or performance spikes as
old blocks are aged out of the cache. This process requires a working knowledge of
the buffer cache mechanism, the database writer, and the checkpointing mechanism.
Most information can be extracted from the V$SYSSTAT table.
Shared Pool The shared pool contains information about user sessions, shared data
structures used by all database sessions, and the dictionary cache.
2-4
Oracle9i Database Performance Planning
Importance of Statistics
Querying the shared pool allows analysis of the SQL statements run in the database.
This is particularly important if you have limited or no knowledge of the
application source code. In addition to the actual SQL, you can determine how
many times it is run and how much CPU and disk I/Os are performed by the SQL.
This information can be extracted from the V$SQL table. Analyzing this information
is crucial in objective bottleneck identification when debugging an unknown
application.
Wait Events In the process of usual database server operations, there are times when
processes need to share resources or synchronize with other processes; for example,
allocating memory in the shared pool or waiting for a lock. Similarly, there are times
when the database process gives control to external code or other processes out of
its control; for example, performing I/O and waiting for the log writer to
synchronize the redo log.
In these cases, the user process stops working and starts waiting. This wait time
becomes part of the eventual user response time. If there are multiple processes
queuing on a shared resource or demanding the same external resource, then the
database starts to single-thread, and scalability is impacted. Performance analysis
should determine why queuing on resources in the database is happening.
The V$SYSTEM_EVENT, V$SESSION_EVENT, and V$SESSION_WAIT tables allow
querying of historical wait events or wait events in real time. The V$SESSION_
WAIT table has additional columns that can be joined to other V$ tables based on the
wait event recorded. These additional join columns specified in V$SESSION_WAIT
allow focused drill down and analysis of the wait event.
See Also: Oracle9i Database Reference for reference information on
the V$ tables
Application Statistics
Application statistics are probably the most difficult statistics to get, but they are the
most important statistics in measuring any performance improvements made to the
system. At a minimum, application statistics should provide a daily summary of
user transactions processed for each working period. More complete statistics
provide precise details of what transactions were processed and the response times
for each transaction type. Detailed statistics also provide statistics on the
decomposition of each transaction time spent in the application server, the network,
the database, and so on.
Monitoring and Improving Application Performance 2-5
Importance of Statistics
The best statistics require considerable instrumentation of the application. This is
best built into the application from the start, because it is difficult to retrofit into
existing applications.
Statistics Gathering Tools
Operating System Data Gathering Tools
Table 2–1 shows the various tools for gathering operating statistics on UNIX.
Table 2–1 UNIX Tools for Operating Statistics
UNIX
CPU
sar, vmstat, mpstat, iostat
Memory
sar, vmstat
Disk
sar, iostat
Network
netstat
For Windows NT/2000, use the Performance Monitor tool.
Database Data Gathering Tools
Oracle provides three primary data gathering tools. These tools are increasingly
more complex to install and run. However, as they increase in complexity, they
provide better reporting output. The tools are:
1.
Statspack
Statspack builds on the BSTAT/ESTAT scripts, but it extends the data capture to
store all statistics in a database repository, which allows better baseline setting
and offline analysis. The statspack report provides considerably more
information than BSTAT/ESTAT in a format useful for bottleneck detection.
This mechanism is the best way to record and collect database statistics.
2.
Oracle Enterprise Manager (EM)
Oracle Enterprise Manager provides a graphical user interface for collecting,
storing, and reporting performance data. The EM Intelligent Agent data
gathering service can collect this performance data on a scheduled basis. A
single agent can manage the data collections for all Oracle databases and the
operating system of the target node. The data is automatically stored in an
historical data repository for performance reporting. Data stored in the
2-6
Oracle9i Database Performance Planning
Importance of Statistics
repository can be used to analyze many facets of database performance, such as
database load, cache allocations and efficiency, resource contention, and
high-impact SQL.
Performance data collections can be initiated directly from the EM Console or
through the EM Diagnostics Pack - Capacity Planner application. HTML reports
of historical performance data can be generated from the EM Console. These
reports provide a comprehensive analysis of database system usage and
performance, which can be easily accessed and navigated from a browser. EM
also provides a graphical real-time Performance Overview for monitoring a
subset of these performance metrics using line charts, bar graphs, and so forth.
The Performance Overview charts let you troubleshoot existing performance
problems by drilling into performance data to track down the source of a
performance bottleneck. For example, a decline in the memory sort percentage
can be immediately investigated by drilling down to the sessions and
corresponding SQL responsible for high-volume sort activity. High-impact SQL
statements discovered through this process can be further investigated by
launching SQL diagnostic tools in the context of the problem.
3.
BSTAT/ESTAT scripts
These scripts are located in the $ORACLE_HOME/rdbms/admin directory in
files UTLBSTAT.SQL and UTLESTAT.SQL. They produce a simple report of
database activity between two points in time. The reports can then be archived
over time. These statistics represent the bare minimum of statistics that should
be kept.
Note: BSTAT/ESTAT is not up to date with many of the new
features introduced since 8.0, and eventually will be desupported.
Users who require help for performance tuning, and are running
any release earlier than Oracle 8.0, are asked to provide Statspack
output rather than BSTAT/ESTAT. Statspack is much easier to
interpret, provides more detailed information, and makes tuning
faster and more effective.
See Also: Oracle Enterprise Manager Concepts Guide
Monitoring and Improving Application Performance 2-7
Importance of Statistics
Importance of Historical Data and Baselines
One of the biggest challenges for performance engineers is determining what
changed in the system to cause a satisfactory application to start having
performance problems. The list of possibilities on a modern complex system is
extensive.
Historical performance data is crucial in eliminating as many variables as possible.
This means that you should collect operating system, database, and application
statistics from the first day an application is rolled out into production. This applies
even if the performance is unsatisfactory. As the applications stabilize and the
performance characteristics are better understood, a set of statistics becomes the
baseline for future reference. These statistics can be used to correlate against a day
when performance is not satisfactory. They are also essential for future capacity and
growth planning.
Performance Intuition
Database and operating system statistics provide an indication of how well a
system is performing. By correlating statistics with actual throughput, you can see
how the system is performing and determine where future bottlenecks and resource
shortages could exist. This is a skill acquired through the experience of monitoring
systems and working with the Oracle server.
CPU utilization is the easiest system usage statistic to understand and monitor.
Monitoring this statistic over time, you can see how the system is used during the
work day and over a number of weeks. However, this statistic provides no
indication of how many business transactions were executed or what resources
were used for each transaction.
Two other statistics that give a better indication of actual business transactions
executed are the number of commits and the volume of redo generated. These are
found in the V$SYSSTAT view under USER COMMITS and REDO SIZE. These
statistics show the number of actual transactions and the volume of data changed in
the database. If these statistics increase in number over time, and if application and
transaction logic are not altered, then you know that more business transactions
were executed. The number of logical blocks read (V$SYSSTAT statistic ’session
logical reads’) also indicates the query workload on a system. Be careful
interpreting this number. A change in the number of logical blocks read can be a
result of an execution plan change rather than an increase in workload.
With experience, it becomes easy to correlate database statistics with the application
workload. A performance DBA learns to use intuition with database statistics and
the application profile to determine a system's workload characteristics. A DBA
2-8
Oracle9i Database Performance Planning
The Oracle Performance Improvement Method
must also anticipate the expected performance of frequently executed transactions.
Understanding the core SQL statements in an application is key to performance
diagnosis. Much of this activity can be done informally.
For example, a core business transaction is required to run in a subsecond response
time. Initial investigation of the transaction shows that this transaction performs 200
logical reads, of which 40 are always obtained from disk. Taking a disk response
time of 20 milliseconds, the likely I/O time is 40 x .02 = 0.8 seconds, which probably
fails the response time target. The DBA requests that the transaction be rewritten,
and the number of logical I/Os is reduced to 80, with an average of five coming
from disk.
To avoid poor performance, it is wise to perform this type of calculation before
production roll out. The process should be repeated after the system is in
production, because the data volumes grow and the transaction statistics can
change.
The Oracle Performance Improvement Method
Introduction to Performance Improvement
Oracle's performance methodology helps you to pinpoint performance problems in
your Oracle system. This involves identifying bottlenecks and fixing them. It is
recommended that changes be made to a system only after you have confirmed that
there is a bottleneck.
Performance improvement, by its nature, is iterative. For this reason, removing the
first bottleneck might not lead to performance improvement immediately, because
another bottleneck might be revealed. Also, in some cases, if serialization points
move to a more inefficient sharing mechanism, then performance could degrade.
With experience, and by following a rigorous method of bottleneck elimination,
applications can be debugged and made scalable.
Performance problems generally result from either a lack of throughput,
unacceptable user/job response time, or both. The problem might be localized
between application modules, or it might be for the entire system.
Before looking at any database or operating system statistics, it is crucial to get
feedback from the most important components of the system: the users of the
system and the people ultimately paying for the application. Typical user feedback
includes statements like the following:
Monitoring and Improving Application Performance 2-9
The Oracle Performance Improvement Method
■
■
■
■
"The online performance is so bad that it prevents my staff from doing
their jobs."
"The billing run takes too long."
"When I experience high amounts of Web traffic, the response time becomes
unacceptable, and I am losing customers."
"I am currently performing 5000 trades a day, and the system is maxed out.
Next month, we roll out to all our users, and the number of trades is expected to
quadruple."
From candid feedback, it is easy to set critical success factors for any performance
work. Determining the performance targets and the performance engineer's exit
criteria make managing the performance process much simpler and more successful
at all levels. These critical success factors are better defined in terms of real business
goals rather than system statistics.
Some real business goals for these typical user statements might be:
■
■
■
"The billing run must process 1,000,000 accounts in a three-hour window."
"At a peak period on a Web site, the response time will not exceed five seconds
for a page refresh."
"The system must be able to process 25,000 trades in an eight-hour window."
The ultimate measure of success is the user's perception of system performance. The
performance engineer’s role is to eliminate any bottlenecks that degrade
performance. These bottlenecks could be caused by inefficient use of limited shared
resources or by abuse of shared resources, causing serialization. Because all shared
resources are limited, the goal of a performance engineer is to maximize the number
of business operations with efficient use of shared resources. At a very high level,
the entire database server can be seen as a shared resource. Conversely, at a low
level, a single CPU or disk can be seen as shared resources.
The Oracle performance improvement method can be applied until performance
goals are met or deemed impossible. This process is highly iterative, and it is
inevitable that some investigations will be made that have little impact on the
performance of the system. It takes time and experience to develop the necessary
skills to accurately pinpoint critical bottlenecks in a timely manner. However, prior
experience can sometimes work against the experienced engineer who neglects to
use the data and statistics available to him. It is this type of behavior that
encourages database tuning by myth and folklore. This is a very risky, expensive,
and unlikely to succeed method of database tuning.
2-10
Oracle9i Database Performance Planning
The Oracle Performance Improvement Method
Today's systems are so different and complex that hard and fast rules for
performance analysis cannot be made. In essence, the Oracle performance
improvement method defines a way of working, but not a definitive set of rules.
With bottleneck detection, the only rule is that there are no rules! The best
performance engineers use the data provided and think laterally to determine
performance problems.
Steps in The Oracle Performance Improvement Method
1.
Get candid feedback from users. Determine the performance project’s scope and
subsequent performance goals, as well as performance goals for the future. This
process is key in future capacity planning.
2.
Get a full set of operating system, database, and application statistics from the
system when the performance is both good and bad. If these are not available,
then get whatever is available. Missing statistics are analogous to missing
evidence at a crime scene: They make detectives work harder and it is more
time-consuming.
3.
Sanity-check the operating systems of all machines involved with user
performance. By sanity-checking the operating system, you look for hardware
or operating system resources that are fully utilized. List any over-used
resources as symptoms for analysis later. In addition, check that all hardware
shows no errors or diagnostics.
4.
Check for the top ten most common mistakes with Oracle, and determine if any
of these are likely to be the problem. List these as symptoms for analysis later.
These are included because they represent the most likely problems.
See Also: "Top Ten Mistakes Found in Oracle Systems" on
page 2-14
5.
Build a conceptual model of what is happening on the system using the
symptoms as clues to understand what caused the performance problems.
See Also: "A Sample Decision Process for Performance
Conceptual Modeling" on page 2-12
6.
Propose a series of remedy actions and the anticipated behavior to the system,
and apply them in the order that can benefit the application the most. A golden
rule in performance work is that you only change one thing at a time and then
Monitoring and Improving Application Performance 2-11
The Oracle Performance Improvement Method
measure the differences. Unfortunately, system downtime requirements might
prohibit such a rigorous investigation method. If multiple changes are applied
at the same time, then try to ensure that they are isolated.
7.
Validate that the changes made have had the desired effect, and see if the user's
perception of performance has improved. Otherwise, look for more bottlenecks,
and continue refining the conceptual model until your understanding of the
application becomes more accurate.
8.
Repeat the last three steps until performance goals are met or become
impossible due to other constraints.
This method identifies the biggest bottleneck and uses an objective approach to
performance improvement. The focus is on making large performance
improvements by increasing application efficiency and eliminating resource
shortages and bottlenecks. In this process, it is anticipated that minimal (less than
10%) performance gains are made from instance tuning, and large gains (100% +)
are made from isolating application inefficiencies.
How to Check the Operating System
The following list should be considered when checking operating system
symptoms.
■
Check CPU utilization in user and kernel space for the total system and on each
CPU.
■
Confirm that there is no paging or swapping.
■
Check that network latencies between machines are acceptable.
■
Find disks with poor response times or long queues.
■
Confirm that there are no hardware errors.
A Sample Decision Process for Performance Conceptual Modeling
Conceptual modeling is almost deterministic. However, as your performance
tuning experience increases, you will appreciate that there are no real rules to
follow. A flexible "heads up" approach is required to interpret the various statistics
and make good decisions.
This section illustrates how a performance engineer might look for bottlenecks. Use
this only as a guideline for the process. With experience, performance engineers add
to the steps involved. This analysis assumes that statistics for both the operating
system and the database have been gathered.
2-12
Oracle9i Database Performance Planning
The Oracle Performance Improvement Method
1.
Is the response time/batch run time acceptable for a single user on an empty or
lightly loaded machine?
If it is not acceptable, then the application is probably not coded or designed
optimally, and it will never be acceptable in a multiple user situation when
system resources are shared. In this case, get application internal statistics, and
get SQL Trace and SQL plan information. Work with developers to investigate
problems in data, index, transaction SQL design, and potential deferral of work
to batch/background processing.
2.
Is all the CPU being utilized?
If the kernel utilization is over 40%, then investigate the operating system for
network transfers, paging, swapping, or process thrashing. Otherwise, move
onto CPU utilization in user space. Check to see if there are any non-database
jobs consuming CPU on the machine limiting the amount of shared CPU
resources, such as backups, file transforms, print queues, and so on. After
determining that the database is using most of the CPU, investigate the top SQL
by CPU utilization. These statements form the basis of all future analysis. Check
the SQL and the transactions submitting the SQL for optimal execution. In
Oracle Server releases prior to 9i, use buffer gets as the measure for CPU usage.
With release 9i, Oracle provides the actual CPU statistics in V$SQL.
See Also: Oracle9i Database Reference for more information on
V$SQL
If the application is optimal and there are no inefficiencies in the SQL execution,
consider rescheduling some work to off-peak hours or using a bigger machine.
3.
At this point, the system performance is unsatisfactory, yet the CPU resources
are not fully utilized.
In this case, you have serialization and unscalable behavior within the server.
Get the WAIT_EVENTS statistics from the server, and determine the biggest
serialization point. If there are no serialization points, then the problem is most
likely outside the database, and this should be the focus of investigation.
Elimination of WAIT_EVENTS involves modifying application SQL and tuning
database parameters. This process is very iterative and requires the ability to
drill down on the WAIT_EVENTS systematically to eliminate serialization
points.
Monitoring and Improving Application Performance 2-13
The Oracle Performance Improvement Method
Top Ten Mistakes Found in Oracle Systems
This section lists the most common mistakes found in Oracle systems. By following
Oracle’s performance improvement methodology, you should be able to avoid these
mistakes altogether. If you find these mistakes in your system, then re-engineer the
application where the performance effort is worthwhile.
See Also: Oracle9i Database Performance Tuning Guide and Reference
for more information on wait events
1.
Bad Connection Management
The application connects and disconnects for each database interaction. This
problem is common with stateless middleware in application servers. It has
over two orders of magnitude impact on performance, and it is totally
unscalable.
2.
Bad Use of Cursors and the Shared Pool
Not using cursors results in repeated parses. If bind variables are not used, then
there is hard parsing of all SQL statements. This has an order of magnitude
impact in performance, and it is totally unscalable. Use cursors with bind
variables that open the cursor and execute it many times. Be suspicious of
applications generating dynamic SQL.
3.
Getting Database I/O Wrong
Many sites lay out their databases poorly over the available disks. Other sites
specify the number of disks incorrectly, because they configure disks by disk
space and not I/O bandwidth.
4.
Redo Log Setup Problems
Many sites run with too few redo logs that are too small. Small redo logs cause
system checkpoints to continuously put a high load on the buffer cache and I/O
system. If there are too few redo logs, then the archive cannot keep up, and the
database will wait for the archive process to catch up.
5.
Serialization of data blocks in the buffer cache due to lack of free lists, free list
groups, transaction slots (INITRANS), or shortage of rollback segments.
This is particularly common on INSERT-heavy applications, in applications that
have raised the block size to 8K or 16K, or in applications with large numbers of
active users and few rollback segments.
2-14
Oracle9i Database Performance Planning
The Oracle Performance Improvement Method
6.
Long Full Table Scans
Long full table scans for high-volume or interactive online operations could
indicate poor transaction design, missing indexes, or poor SQL optimization.
Long table scans, by nature, are I/O intensive and unscalable.
7.
In Disk Sorting
In disk sorts for online operations could indicate poor transaction design,
missing indexes, or poor SQL optimization. Disk sorts, by nature, are
I/O-intensive and unscalable.
8.
High Amounts of Recursive (SYS) SQL
Large amounts of recursive SQL executed by SYS could indicate space
management activities, such as extent allocations, taking place. This is
unscalable and impacts user response time. Recursive SQL executed under
another user ID is probably SQL and PL/SQL, and this is not a problem.
9.
Schema Errors and Optimizer Problems
In many cases, an application uses too many resources because the schema
owning the tables has not been successfully migrated from the development
environment or from an older implementation. Examples of this are missing
indexes or incorrect statistics. These errors can lead to sub-optimal execution
plans and poor interactive user performance. When migrating applications of
known performance, export the schema statistics to maintain plan stability
using the DBMS_STATS package.
Likewise, optimizer parameters set in the initialization parameter file can
override proven optimal execution plans. For these reasons, schemas, schema
statistics, and optimizer settings should be managed together as a group to
ensure consistency of performance.
10. Use of Nonstandard Initialization Parameters
These might have been implemented based on poor advice or incorrect
assumptions. In particular, parameters associated with SPIN_COUNT on latches
and undocumented optimizer features can cause a great deal of problems that
can require considerable investigation.
Monitoring and Improving Application Performance 2-15
The Oracle Performance Improvement Method
Performance Characteristics of Hardware Configurations
Again, today's systems are so different and complex that hard and fast rules for
performance analysis cannot be made. However, this section provides some of the
numbers that you should consider.
1.
2-16
Disk characteristics:
■
Size 512MB - 36GB
■
Seek 5 - 10msec
■
Transfer 5 - 10msec
■
Thoughput 20 - 40 I/O seconds for each disk
■
Controller throughput at 1750 I/Os a second
2.
Speed reading from memory should be 1 - 10 microseconds.
3.
Point-to-point network latencies should be 1 - 25msec.
4.
Busy systems: (worst case)
■
Operational systems - 60% usr, 40% sys
■
Decision support systems - 90% usr, 10% sys
Oracle9i Database Performance Planning
3
Emergency Performance Techniques
This chapter contains the following sections:
■
Introduction to Emergency Performance Techniques
■
Steps in the Emergency Performance Method
Emergency Performance Techniques 3-1
Introduction to Emergency Performance Techniques
Introduction to Emergency Performance Techniques
This chapter provides techniques for dealing with performance emergencies.
Hopefully, you have had the opportunity to read the first two chapters of this book,
where a detailed methodology is defined for establishing and improving
application performance. However, in an emergency situation, a component of the
system has changed to transform it from a reliable, predictable system to one that is
unpredictable and not satisfying user requests.
In this case, the role of the performance engineer is to rapidly determine what has
changed and take appropriate actions to resume normal service as quickly as
possible. In many cases, it is necessary to take immediate action, and a rigorous
performance improvement project is unrealistic.
After addressing the immediate performance problem, the performance engineer
must collect sufficient debugging information either to get better clarity on the
performance problem or to at least ensure that it does not happen again.
The method for debugging emergency performance problems is the same as the
method described in the performance improvement method earlier in this book.
However, shortcuts are taken in various stages because of the timely nature of the
problem. Keeping detailed notes and records of facts found as the debugging
process progresses is essential for later analysis and justification of any remedial
actions. This is analogous to a doctor keeping good patient notes for future
reference.
Steps in the Emergency Performance Method
The Emergency Performance Method is as follows:
1.
Survey the performance problem and collect the symptoms of the performance
problem. This process should include the following:
■
■
2.
3-2
User feedback on how the system is underperforming. Is the problem
throughput or response time?
Ask the question, "What has changed since we last had good performance?"
This answer can give clues to the problem; however, getting unbiased
answers in an escalated situation can be difficult.
Sanity-check the hardware utilization of all components of the application
system. Check where the highest CPU utilization is, and check the disk,
memory usage, and network performance on all the system components. This
quick process identifies which tier is causing the problem. If the problem is in
Oracle9i Database Performance Planning
Steps in the Emergency Performance Method
the application, then shift analysis to application debugging. Otherwise, move
on to database server analysis.
3.
Determine if the database server is constrained on CPU or if it is spending time
waiting on wait events. If the database server is CPU-constrained, then
investigate the following:
■
■
■
■
■
Sessions that are consuming large amounts of CPU at the operating system
level
Sessions or statements that perform many buffer gets at the database level
(check V$SESSTAT, V$SQL)
Execution plan changes causing sub-optimal SQL execution (these can be
difficult to locate)
Incorrect setting of initialization parameters
Algorithmic issues as a result of code changes or upgrades of all
components
If the database sessions are waiting on events, then follow the wait events listed
in V$SESSION_WAIT to determine what is causing serialization. In cases of
massive contention for the library cache, it might not be possible to logon or
submit SQL to the database. In this case, use historical data to determine why
there is suddenly contention on this latch. If most waits are for I/O, then
sample the SQL being run by the sessions that are performing all of the I/Os.
4.
Apply emergency action to stabilize the system. This could involve actions that
take parts of the application off-line or restrict the workload that can be applied
to the system. It could also involve a system restart or the termination of job in
process. These naturally have service level implications.
5.
Validate that the system is stable. Having made changes and restrictions to the
system, validate that the system is now stable, and collect a reference set of
statistics for the database. Now follow the rigorous performance method
described earlier in this book to bring back all functionality and users to the
system. This process may require significant application re-engineering before it
is complete.
See Also: Chapter 2, "Monitoring and Improving Application
Performance" for detailed information on the performance
improvement method and a list of the most common mistakes
made with Oracle
Emergency Performance Techniques 3-3
Steps in the Emergency Performance Method
3-4
Oracle9i Database Performance Planning
Index
A
applications
deploying, 1-27
design principles, 1-14
development trends, 1-22
implementing, 1-20
performance, 2-8
B
baselines, 2-8
benchmarking workloads, 1-24
big bang rollout strategy, 1-27
bit-mapped indexes, 1-16
bottlenecks
fixing, 2-9
identifying, 2-9
BSTAT/ESTAT scripts, 2-7
B-tree indexes, 1-16
buffer caches, 2-4
business logic, 1-9, 1-20
C
column order, 1-17
conceptual modeling,
CPUs, 1-8
statistics, 2-2
2-12
D
data
and transactions,
baselines, 2-8
gathering, 2-6
historical, 2-8
modeling, 1-14
queries, 1-12
searches, 1-12
database statistics, 2-4
databases
size, 1-13
debugging designs, 1-25
deploying applications, 1-27
design principles, 1-14
designs
debugging, 1-25
testing, 1-25
validating, 1-25
development environments, 1-20
disk statistics, 2-3
E
EM (Enterprise Manager), 2-6
emergencies
performance, 3-2
Emergency Performance Method,
Enterprise Manager, 2-6
estimating workloads, 1-23
benchmarking, 1-24
extrapolating, 1-24
extrapolating workloads, 1-24
3-2
F
1-10
function-based indexes,
1-16
Index-1
G
gathering data,
network statistics,
networks, 1-8
2-6
O
H
hardware components,
historical data, 2-8
hours of service, 1-13
1-7
I
implementing business logic, 1-9
indexes
adding columns, 1-15
appending columns, 1-15
bit-mapped, 1-16
B-tree, 1-16
column order, 1-17
costs, 1-17
design, 1-15
function-based, 1-16
partitioned, 1-16
reverse key, 1-17
sequences in, 1-17
serializing in, 1-17
index-organized tables, 1-16
Internet scalability, 1-4
IOT (index-organized table), 1-16
L
linear scalability,
2-3
1-6
object-orientation, 1-22
operating system statistics, 2-2
operating systems
checking, 2-12
collecting symptoms, 2-12
Oracle performance improvement method,
steps, 2-11
2-9
P
partitioned indexes, 1-16
performance emergencies, 3-2
performance improvement method,
steps, 2-11
programming languages, 1-20
2-9
Q
queries
data,
1-12
R
resource allocation, 1-9, 1-20
response time, 1-12
reverse key indexes, 1-17
rollout strategies
big bang approach, 1-27
trickle approach, 1-27
M
managing the user interface,
memory, 1-8
modeling
conceptual, 2-12
data, 1-14
workloads, 1-25
N
network speed,
Index-2
1-12
1-9
S
scalability, 1-3
factors preventing, 1-6
Internet, 1-4
linear, 1-6
service hours, 1-13
shared pool, 2-4
software components, 1-8
statistics
correlation with application workload,
2-8
databases, 2-4
buffer caches, 2-4
shared pool, 2-4
gathering tools, 2-6
BSTAT/ESTAT scripts, 2-7
database data, 2-6
Oracle Enterprise Manager, 2-6
Statspack, 2-6
operating systems, 2-2
CPU statistics, 2-2
disk statistics, 2-3
network statistics, 2-3
virtual memory statistics, 2-3
Statspack, 2-6
system architecture, 1-7
configuration, 1-10
hardware components, 1-7
CPUs, 1-8
I/O subsystems, 1-8
memory, 1-8
networks, 1-8
software components, 1-8
data and transactions, 1-10
implementing business logic, 1-9
managing the user interface, 1-9
user requests and resource allocation,
response time,
1-12
V
validating designs, 1-25
views, 1-18
virtual memory statistics,
2-3
W
workloads
estimating, 1-23
benchmarking, 1-24
extrapolating, 1-24
modeling, 1-25
testing, 1-25
1-9
T
tables
design, 1-15
testing designs, 1-25
transactions and data, 1-10
trickle rollout strategy, 1-27
U
user requests, 1-9
users
interaction method, 1-12
interfaces, 1-20
location, 1-12
network speed, 1-12
number of, 1-11
requests, 1-20
Index-3
Index-4
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