Database Benchmarking and Stress Testing: An Evidence-Based Approach to Decisions on Architecture and Technology

Bert Scalzo

Database Benchmarking and Stress Testing: An Evidence-Based Approach to Decisions on Architecture and Technology
  • 出版商: Apress
  • 出版日期: 2018-10-09
  • 售價: $1,250
  • 貴賓價: 9.5 折 $1,188
  • 語言: 英文
  • 頁數: 260
  • 裝訂: Paperback
  • ISBN: 1484240073
  • ISBN-13: 9781484240076
  • 相關分類: 資料庫

    • 海外代購書籍(需單獨結帳)

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商品描述

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
 

商品描述(中文翻譯)

提供基於證據的答案，這些答案可以被您的企業測量和依賴。根據本書中提出的實證方法，數據庫管理員將能夠在虛擬化服務器和基於容器的解決方案快速變化的環境中做出明智的架構決策，以回答關於數據庫性能的「如果」問題。

如今的數據庫管理員面臨著許多問題，例如：
- 如果我們使用多租戶功能合併數據庫？
- 如果我們將數據庫服務器虛擬化為Docker容器？
- 如果我們部署最新的NVMe快閃磁盤以加快IO訪問速度？
- 壓縮、分區和內存OLTP等功能是否能夠回本？
- 如果我們將數據庫遷移到雲端？

作為一名管理員，您是否知道這些問題的答案，甚至知道如何測試這些假設？

《數據庫基準測試和壓力測試》將向您介紹使用行業標準測試套件（如TCP系列測試）進行數據庫基準測試的方法，這些測試套件是供供應商依賴的相同測試套件。您將學習運行這些行業標準基準測試並收集結果，以回答有關架構變更、技術變更甚至數據庫軟件品牌的性能影響的問題。您將學習如何測量性能並預測環境變更的具體影響。您將了解基準測試的限制以及基準測試和工作負載捕獲/回放之間的重要區別。

本書教您如何創建支持業務和技術決策的實證證據。它關乎在應該測量而不是猜測的情況下進行測試。實證測試是提供可測量結果的科學測試。從對可能的架構或技術變更影響的假設開始。然後運行適當的基準測試來收集數據，並預測您正在探索的變更是否有益，以及益處的程度。停止猜測。開始測量。讓《數據庫基準測試和壓力測試》指引您的方向。

您將學到什麼：
- 了解行業標準的數據庫基準測試，以及何時使用每個測試最為適合
- 為數據庫基準測試做好準備，以獲得可靠的結果
- 為合併、虛擬化和雲項目進行數據庫基準測試
- 辨識並避免在基準測試數據庫性能方面的常見錯誤
- 以合理、簡潔的方式測量和解讀結果，以進行可靠的比較
- 根據優缺點選擇和提供有關基準測試工具的建議

本書適合對數據庫性能產生影響的架構決策（如是否使用基於雲的服務、是否合併和容器化）以及必須對存儲或任何其他影響數據庫性能的技術提出建議的數據庫管理員和專業人士閱讀。

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