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Block Trace Analysis and Storage System Optimization - A Practical Approach with MATLAB/Python Tools (Paperback, 1st ed.)
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Block Trace Analysis and Storage System Optimization - A Practical Approach with MATLAB/Python Tools (Paperback, 1st ed.)
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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
General
Imprint: |
Apress
|
Country of origin: |
United States |
Release date: |
November 2018 |
First published: |
2018 |
Authors: |
Jun Xu
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Dimensions: |
235 x 155 x 20mm (L x W x T) |
Format: |
Paperback
|
Pages: |
271 |
Edition: |
1st ed. |
ISBN-13: |
978-1-4842-3927-8 |
Categories: |
Books >
Computing & IT >
Internet >
Network computers
|
LSN: |
1-4842-3927-X |
Barcode: |
9781484239278 |
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