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Mastering Hadoop

You're reading from   Mastering Hadoop Go beyond the basics and master the next generation of Hadoop data processing platforms

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Product type Paperback
Published in Dec 2014
Publisher
ISBN-13 9781783983643
Length 374 pages
Edition 1st Edition
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Author (1):
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Sandeep Karanth Sandeep Karanth
Author Profile Icon Sandeep Karanth
Sandeep Karanth
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Table of Contents (15) Chapters Close

Preface 1. Hadoop 2.X FREE CHAPTER 2. Advanced MapReduce 3. Advanced Pig 4. Advanced Hive 5. Serialization and Hadoop I/O 6. YARN – Bringing Other Paradigms to Hadoop 7. Storm on YARN – Low Latency Processing in Hadoop 8. Hadoop on the Cloud 9. HDFS Replacements 10. HDFS Federation 11. Hadoop Security 12. Analytics Using Hadoop A. Hadoop for Microsoft Windows Index

HDFS block placement

Replication is an important feature in HDFS; it ensures data reliability against loss and high availability in the face of failures. The default replication factor is 3, though this parameter can be tuned using the dfs.replication configuration parameter. HDFS does not replicate the file as a whole; rather, it chunks the file into fixed size blocks and stores it across the cluster.

The replication factor can be specified at file creation time. It can be changed as and when desired. The salient feature of HDFS is the smart placement of blocks, and this feature distinguishes it from other distributed filesystems. The placement policy is said to be rack-aware, that is, it is cognizant of the physical location of where the block resides. This not only aids in fault tolerance but can also be instrumental in making network bandwidth utilization efficient. Any computing paradigm running on HDFS can make use of this information to minimize the amount of data that needs to be...

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