Author: Roger Cornejo Full Title: Dynamic Oracle Performance Analytics: Using Normalized Metrics To Improve Database Speed Publisher: Apress; 1st ed. edition (December 7, 2018) Year: 2018 ISBN-13: 9781484241370 (978-1-4842-4137-0), 9781484241363 (978-1-4842-4136-3) ISBN-10: 1484241371, 1484241363 Pages: 224 Language: English Genre: Educational: Database Management File type: EPUB (True), PDF (True) Quality: 10/10 Price: 29.95 € Use an innovative approach that relies on big data and advanced analytical techniques to analyze and improve Oracle Database performance. The approach used in this book represents a step-change paradigm shift 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 help the performance tuner draw impactful, focused performance improvement conclusions. This book briefly reviews past and present practices, along with available tools, to help you recognize areas where improvements can be made. 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. 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 Features: ✓ Presents a dynamic process that overcomes limitations of older tuning approaches ✓ The process in this book does not rely on AWR, and can be applied in any database ✓ The method draws from big data techniques to massively scale across thousands of available metrics Who This Book Is For: Professional tuners: responsible for maintaining the efficient operation of large-scale databases who wish to focus on analysis, who want to expand their repertoire to include a big data methodology and use metrics without being overwhelmed, who desire to provide accurate root cause analysis and avoid the cyclical fix-test cycles that are inevitable when speculation is used. ------------- Our members see more. Join us!
