Block Trace Analysis and Storage System Optimization: A Practical Approach with MATLAB/Python Tools

Block Trace Analysis and Storage System Optimization: A Practical Approach with MATLAB/Python Tools

by JunXu (Author)

Synopsis

Understand the fundamental factors of data storage system performance and master an essential analytical skill using block trace via applications such as MATLAB and Python tools. You will increase your productivity and learn the best techniques for doing specific tasks (such as analyzing the IO pattern in a quantitative way, identifying the storage system bottleneck, and designing the cache policy).

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

$30.26

Save:$5.34 (15%)

Quantity

20+ in stock

More Information

Format: Paperback
Pages: 292
Edition: 1st ed.
Publisher: Apress
Published: 11 Jan 2019

ISBN 10: 148423927X
ISBN 13: 9781484239278

Author Bio
Jun Xu is a principal engineer at Western Digital. Before joining Western Digital, he was with Data Storage Institute, Nanyang Technological University, and National University of Singapore. He has multi-discipline knowledge and solid experiences in complex system design, management, modeling and simulation, data analytics, data center, cloud storage, and IoT. He has published over 50 international papers, 14 US patents (applications), and one monograph. He was a committee member of several international conferences on control and automation and is an editor of the journal Unmanned Systems. He is a senior member of IEEE and a certificated FRM and obtained his BS degree in Applied Mathematics in 2001 and a PhD in Control and Automation in 2006, from Southeast University (China) and Nanyang Technological University (Singapore), respectively.