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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

The RecordReader class

Unlike InputSplit, the RecordReader class presents a record view of the data to the Map task. RecordReader works within each InputSplit class and generates records from the data in the form of key-value pairs. The InputSplit boundary is a guideline for RecordReader and is not enforced. On one extreme, a custom RecordReader class can be written to read an entire file (though this is not encouraged). Most often, a RecordReader class will have to read from a subsequent InputSplit class to present the complete record to the Map task. This happens when records overlap InputSplit classes.

The reading of bytes from a subsequent InputSplit class happens via the FSDataInputS tream objects. Though this reading does not respect locality in itself, generally, it gathers only a few bytes from the next split and there is not a significant performance overhead. But in some cases where record sizes are huge, this can have a bearing on the performance due to significant byte transfers...

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