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Dynamic Oracle Performance Analytics

Using Normalized Metrics to Improve Database Speed

  • Roger┬áCornejo

Table of contents

  1. Front Matter
    Pages i-xxi
  2. Performance Tuning Basics

    1. Front Matter
      Pages 1-1
    2. Roger Cornejo
      Pages 3-16
  3. The Dynamic Oracle Performance Analytics (DOPA) Process

    1. Front Matter
      Pages 17-17
    2. Roger Cornejo
      Pages 19-32
    3. Roger Cornejo
      Pages 33-59
    4. Roger Cornejo
      Pages 61-77
    5. Roger Cornejo
      Pages 79-89
    6. Roger Cornejo
      Pages 91-105
    7. Roger Cornejo
      Pages 107-138
  4. Case Studies and Further Applications

    1. Front Matter
      Pages 139-139
    2. Roger Cornejo
      Pages 141-173
    3. Roger Cornejo
      Pages 175-189
    4. Roger Cornejo
      Pages 191-217
  5. Back Matter
    Pages 219-224

About this book

Introduction

Use an innovative approach that relies on big data and advanced analytical techniques to analyze and improve Oracle Database performance. The approach in this book is a step-change away from traditional methods. Instead of relying on a few hand-picked, favorite metrics, or wading through multiple specialized tables of information such as those found in an automatic workload repository (AWR) report, you will draw on all available data, applying big data methods and analytical techniques to draw impactful, focused performance improvement conclusions. 

This book reviews past and present practices, along with available tools, to help you pinpoint areas for improvement. The book then guides you through a step-by-step method that can be used to take advantage of all available metrics to identify problem areas and work toward improving them. The method presented simplifies the tuning process and solves the problem of metric overload.

You will learn how to: collect and normalize data, generate deltas that are useful in performing statistical analysis, create and use a taxonomy to enhance your understanding of problem performance areas in your database and its applications, and create a root cause analysis report that enables understanding of a specific performance problem and its likely solutions. 

What You'll Learn:
  • Collect and prepare metrics for analysis from a wide array of sources
  • Apply statistical techniques to select relevant metrics  
  • Create a taxonomy to provide additional insight into problem areas
  • Provide a metrics-based root cause analysis regarding the performance issue
  • Generate an actionable tuning plan prioritized according to problem areas
  • Monitor performance using database-specific normal ranges


Keywords

Big Data Analytics Oracle Internals Performance Tuning Automatic Workload Repository (AWR) Automatic Database Diagnostic Monitor (ADDM) Active Session History (ASH) Root Cause Analysis Machine Learning Performance Troubleshooting SQL Tuning

Authors and affiliations

  • Roger┬áCornejo
    • 1
  1. 1.DurhamUSA

Bibliographic information