Oracle Database 12c Release 2 Testing Tools And Techniques For Performance And Scalability
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Oracle Database 12c Release 2 Testing Tools and Techniques for Performance and Scalability
Author: Jim Czuprynski
language: en
Publisher: McGraw Hill Professional
Release Date: 2017-10-05
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Master Oracle Database 12c Release 2 testing and tuning Seamlessly transition to Oracle Database 12c Release 2 and achieve peak performance using the step-by-step instruction and best practices contained in this Oracle Press guide. Written by a team of Oracle ACEs, Oracle Database 12c Release 2 Testing Tools and Techniques for Performance and Scalability clearly explains how to identify, investigate, and resolve performance issues. You will discover how to use troubleshooting tools and test rigs, optimize code and queries, evaluate database performance, perform realistic application testing, capture and replay actual production workloads, and employ Oracle Database In-Memory. •Establish benchmarks and evaluate application workload performance •Configure and deploy SQL Tuning Advisor and SQL Access Advisor •Maximize efficiency using Oracle Database In-Memory and In-Memory Advisor •Identify and repair poorly running code with SQL Monitor •Uncover database problems using Real-Time ADDM and Emergency Monitoring •Work with database workload capture and replay •Analyze third-party code with Workload Intelligence •Identify database objects that will benefit most from In-Memory Column Store (IMCS) •Monitor and manage IMCS objects with In-Memory Central
Database Benchmarking and Stress Testing
Provide evidence-based answers that can be measured and relied upon by your business. Database administrators will be able to make sound architectural decisions in a fast-changing landscape of virtualized servers and container-based solutions based on the empirical method presented in this book for answering “what if” questions about database performance. Today’s database administrators face numerous questions such as: What if we consolidate databases using multitenant features? What if we virtualize database servers as Docker containers? What if we deploy the latest in NVMe flash disks to speed up IO access? Do features such as compression, partitioning, and in-memory OLTP earn back their price? What if we move our databases to the cloud? As an administrator, do you know the answers or even how to test the assumptions? Database Benchmarking and Stress Testing introduces you to database benchmarking using industry-standard test suites such as the TCP series of benchmarks, which are the same benchmarks that vendors rely upon. You’ll learn to run these industry-standard benchmarks and collect results to use in answering questions about the performance impact of architectural changes, technology changes, and even down to the brand of database software. You’ll learn to measure performance and predict the specific impact of changes to your environment. You’ll know the limitations of the benchmarks and the crucial difference between benchmarking and workload capture/reply. This book teaches you how to create empirical evidence in support of business and technology decisions. It’s about not guessing when you should be measuring. Empirical testing is scientific testing that delivers measurable results. Begin with a hypothesis about the impact of a possible architecture or technology change. Then run the appropriate benchmarks to gather data and predict whether the change you’re exploring will be beneficial, and by what order of magnitude. Stop guessing. Start measuring. Let Database Benchmarking and Stress Testing show the way. What You'll Learn Understand the industry-standard database benchmarks, and when each is best used Prepare for a database benchmarking effort so reliable results can be achieved Perform database benchmarking for consolidation, virtualization, and cloud projects Recognize and avoid common mistakes in benchmarking database performance Measure and interpret results in a rational, concise manner for reliable comparisons Choose and provide advice on benchmarking tools based on their pros and cons Who This Book Is For Database administrators and professionals responsible for advising on architectural decisions such as whether to use cloud-based services, whether to consolidate and containerize, and who must make recommendations on storage or any other technology that impacts database performance
Expert Oracle RAC Performance Diagnostics and Tuning
Expert Oracle RAC Performance Diagnostics and Tuning provides comprehensive coverage of the features, technology and principles for testing and tuning RAC databases. The book takes a deep look at optimizing RAC databases by following a methodical approach based on scientific analysis rather than using a speculative approach, twisting and turning knobs and gambling on the system. The book starts with the basic concepts of tuning methodology, capacity planning, and architecture. Author Murali Vallath then dissects the various tiers of the testing implementation, including the operating system, the network, the application, the storage, the instance, the database, and the grid infrastructure. He also introduces tools for performance optimization and thoroughly covers each aspect of the tuning process, using many real-world examples, analyses, and solutions from the field that provide you with a solid, practical, and replicable approach to tuning a RAC environment. The book concludes with troubleshooting guidance and quick reference of all the scripts used in the book. Expert Oracle RAC Performance Diagnostics and Tuning covers scenarios and details never discussed before in any other performance tuning books. If you have a RAC database, this book is a requirement. Get your copy today. Takes you through optimizing the various tiers of the RAC environment. Provides real life case studies, analysis and solutions from the field. Maps a methodical approach to testing, tuning and diagnosing the cluster