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商品描述
In the new era of IoT, big data, and cloud systems, better performance and higher density of storage systems has become crucial. To increase data storage density, new techniques have evolved and hybrid and parallel access techniques―together with specially designed IO scheduling and data migration algorithms―are being deployed to develop high-performance data storage solutions. Among the various storage system performance analysis techniques, IO event trace analysis (block-level trace analysis particularly) is one of the most common approaches for system optimization and design. However, the task of completing a systematic survey is challenging and very few works on this topic exist.
Block Trace Analysis and Storage System Optimization brings together theoretical analysis (such as IO qualitative properties and quantitative metrics) and practical tools (such as trace parsing, analysis, and results reporting perspectives). The book provides content on block-level trace analysis techniques, and includes case studies to illustrate how these techniques and tools can be applied in real applications (such as SSHD, RAID, Hadoop, and Ceph systems).
What You’ll Learn
- Understand the fundamental factors of data storage system performance
- Master an essential analytical skill using block trace via various applications
- Distinguish how the IO pattern differs in the block level from the file level
- Know how the sequential HDFS request becomes “fragmented” in final storage devices
- Perform trace analysis tasks with a tool based on the MATLAB and Python platforms
Who This Book Is For
IT professionals interested in storage system performance optimization: network administrators, data storage managers, data storage engineers, storage network engineers, systems engineers
商品描述(中文翻譯)
了解資料儲存系統性能的基本因素，並掌握使用 MATLAB 和 Python 工具進行區塊追蹤的基本分析技能。您將提高生產力，學習執行特定任務的最佳技術（例如，以定量方式分析 IO 模式、識別儲存系統瓶頸以及設計快取策略）。
在物聯網、大數據和雲端系統的新時代，儲存系統的更佳性能和更高密度變得至關重要。為了提高資料儲存密度，新的技術不斷演進，混合和並行存取技術，以及專門設計的 IO 排程和資料遷移演算法，正在被部署以開發高性能的資料儲存解決方案。在各種儲存系統性能分析技術中，IO 事件追蹤分析（特別是區塊級追蹤分析）是系統優化和設計中最常見的方法之一。然而，完成系統性調查的任務具有挑戰性，且在這個主題上相關的研究作品非常少。
《區塊追蹤分析與儲存系統優化》結合了理論分析（如 IO 定性特性和定量指標）和實用工具（如追蹤解析、分析和結果報告的視角）。本書提供有關區塊級追蹤分析技術的內容，並包括案例研究，以說明這些技術和工具如何應用於實際應用中（如 SSHD、RAID、Hadoop 和 Ceph 系統）。
您將學到的內容：
- 了解資料儲存系統性能的基本因素
- 掌握使用各種應用進行區塊追蹤的基本分析技能
- 辨別區塊級的 IO 模式與檔案級的差異
- 知道順序 HDFS 請求如何在最終儲存設備中變得「碎片化」
- 使用基於 MATLAB 和 Python 平台的工具執行追蹤分析任務
本書適合對儲存系統性能優化感興趣的 IT 專業人士：網路管理員、資料儲存經理、資料儲存工程師、儲存網路工程師、系統工程師。
