Oracle Database 11gR2 Performance Tuning Cookbook

Oracle Database 11gR2 Performance Tuning Cookbook

By : Ciro Fiorillo

Buy this Book

Oracle Database 11gR2 Performance Tuning Cookbook

By: Ciro Fiorillo

Buy this Book

Overview of this book

Oracle's Database offers great performance, scalability, and many features for DBAs and developers. Due to a wide choice of technologies, successful applications are good candidates to run into performance issues and when a problem arises it's very difficult to identify the cause and the right solution to the problem. The Oracle Database 11g R2 Performance Tuning Cookbook helps DBAs and developers to understand every aspect of Oracle Database that can affect performance. You will be guided through implementing the correct solution in a proactive way before problems arise, and how to diagnose issues on your Oracle database-based solutions. This fast-paced book offers solutions starting from application design and development, through the implementation of well-performing applications, to the details of deployment and delivering best-performance databases. With this book you will quickly learn to apply the right methodology to tune the performance of an Oracle Database, and to optimize application design and SQL and PL/SQL code. By following the real-world examples you will see how to store your data in correct structures and access and manipulate them at a lightning speed. You will learn to speed up sort operations, hack the optimizer and the data loading process, and diagnose and tune memory, I/O, and contention issues. The purpose of this cookbook is to provide concise recipes, which will help you to build and maintain a very high-speed Oracle Database environment.

Oracle Database 11gR2 Performance Tuning Cookbook

Credits

About the Author

Acknowledgement

About the Reviewers

www.PacktPub.com

Preface

Free Chapter

Starting with Performance Tuning

Introduction

Reviewing the performance tuning process

Exploring the example database

Acquiring data using a data dictionary and dynamic performance views

Analyzing data using Statspack reports

Diagnosing performance issues using the alert log

Analyzing data using Automatic Workload Repository (AWR)

Analyzing data using Automatic Database Diagnostic Monitor (ADDM)

A working example

Optimizing Application Design

Introduction

Optimizing connection management

Improving performance sharing reusable code

Reducing the number of requests to the database using stored procedures

Reducing the number of requests to the database using sequences

Reducing the number of requests to the database using materialized views

Optimizing performance with schema denormalization

Avoiding dynamic SQL

Optimizing Storage Structures

Introduction

Avoiding row chaining

Avoiding row migration

Using LOBs

Using index clusters

Using hash clusters

Indexing the correct way

Rebuilding index

Compressing indexes

Using reverse key indexes

Using bitmap indexes

Migrating to index organized tables

Using partitioning

Optimizing SQL Code

Introduction

Using bind variables

Avoiding full table scans

Exploring index lookup

Exploring index skip-scan and index range-scan

Introducing arrays and bulk operations

Optimizing joins

Using subqueries

Tracing SQL activity with SQL Trace and TKPROF

Optimizing Sort Operations

Introduction

Sorting—in-memory and on-disk

Sorting and indexing

Writing top n queries and ranking

Using count, min/max, and group-by

Avoiding sorting in set operations: union, minus, and intersect

Troubleshooting temporary tablespaces

Optimizing PL/SQL Code

Introduction

Using bind variables and parsing

Array processing and bulk-collect

Passing values with NOCOPY (or not)

Using short-circuit IF statements

Avoiding recursion

Using native compilation

Taking advantage of function result cache

Inlining PL/SQL code

Using triggers and virtual columns

Improving the Oracle Optimizer

Introduction

Exploring optimizer hints

Collecting statistics

Using histograms

Managing stored outlines

Introducing Adaptive Cursor Sharing for bind variable peeking

Creating SQL Tuning Sets

Using the SQL Tuning Advisor

Configuring and using SQL Baselines

Other Optimizations

Introduction

Caching results with the client-side result cache

Enabling parallel SQL

Direct path inserting

Using create table as select

Inspecting indexes and triggers overhead

Loading data with SQL*Loader and Data Pump

Tuning Memory

Introduction

Tuning memory to avoid Operating System paging

Tuning the Library Cache

Tuning the Shared Pool

Tuning the Program Global Area and the User Global Area

Tuning the Buffer Cache

Tuning I/O

Introduction

Tuning at the disk level and strategies to distribute Oracle files

Striping objects across multiple disks

Choosing different RAID levels for different Oracle files

Using asynchronous I/O

Tuning checkpoints

Tuning redo logs

Tuning Contention

Introduction

Detecting and preventing lock contention

Investigating transactions and concurrency

Tuning latches

Tuning resources to minimize latch contention

Minimizing latches using bind variables

Dynamic Performance Views

DBA_SQL_PLAN_BASELINES

V$BUFFER_POOL_STATISTICS

V$LOCK

V$LOG

V$SGA

V$SHARED_POOL_RESERVED

V$SQL

X$BH

A Summary of Oracle Packages Used for Performance Tuning

DBMS_WORKLOAD_REPOSITORY

Index

Customer Reviews

5 star

4 star

3 star

2 star

1 star

Using hash clusters

In the previous recipe, we introduced index clusters and tested a particular way to load data in a cluster to optimize the storage of rows with the same cluster key value.

In this recipe, we introduce a different kind of cluster—hash clusters. The biggest difference between index clusters and hash clusters is in the waydata is accessed given a particular cluster key value.

How to do it...

The following steps will demonstrate the use of hash clusters:

Connect to the HR schema of the TESTDB database:
```
CONNECT hr@TESTDB/hr
```

Create the cluster:

CREATE CLUSTER EMP_DEPT_CLUSTER (deptid NUMBER(4))
SIZE 8192 HASHKEYS 100;

Create the first table and populate it with data:

CREATE TABLE CL_DEPARTMENTS CLUSTER EMP_DEPT_CLUSTER
(department_id) AS SELECT * FROM DEPARTMENTS;

Create the second table, populate it with data, and gather statistics:

CREATE TABLE CL_EMPLOYEES CLUSTER EMP_DEPT_CLUSTER
(department_id) AS SELECT * FROM EMPLOYEES;
EXEC DBMS_STATS.GATHER_TABLE_STATS(‹HR›, ‹CL_EMPLOYEES...

Oracle Database 11gR2 Performance Tuning Cookbook

By : Ciro Fiorillo

Oracle Database 11gR2 Performance Tuning Cookbook

By: Ciro Fiorillo

Overview of this book

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Current Title:

Oracle Database 11gR2 Performance Tuning Cookbook

Using hash clusters

How to do it...