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Hadoop Essentials

You're reading from   Hadoop Essentials Delve into the key concepts of Hadoop and get a thorough understanding of the Hadoop ecosystem

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Product type Paperback
Published in Apr 2015
Publisher Packt
ISBN-13 9781784396688
Length 194 pages
Edition 1st Edition
Languages
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Author (1):
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Shiva Achari Shiva Achari
Author Profile Icon Shiva Achari
Shiva Achari
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Toc

Table of Contents (9) Chapters Close

Preface 1. Introduction to Big Data and Hadoop FREE CHAPTER 2. Hadoop Ecosystem 3. Pillars of Hadoop – HDFS, MapReduce, and YARN 4. Data Access Components – Hive and Pig 5. Storage Component – HBase 6. Data Ingestion in Hadoop – Sqoop and Flume 7. Streaming and Real-time Analysis – Storm and Spark Index

Conventions

In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.

Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "We can include other contexts through the use of the include directive."

A block of code is set as follows:

public static class MyPartitioner extends   org.apache.hadoop.mapreduce.Partitioner<Text,Text>

{
  @Override
  public int getPartition(Text key, Text value, int numPartitions)
  {
   int count =Integer.parseInt(line[1]);
   if(count<=3)
    return 0;
   else
    return 1;
  }
}

And in Driver class
job.setPartitionerClass(MyPartitioner.class);

Any command-line input or output is written as follows:

hadoop fs -put /home/shiva/Samplefile.txt  /user/shiva/dir3/

Note

Warnings or important notes appear in a box like this.

Tip

Tips and tricks appear like this.

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