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Learning Hadoop 2

You're reading from   Learning Hadoop 2 Design and implement data processing, lifecycle management, and analytic workflows with the cutting-edge toolbox of Hadoop 2

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Product type Paperback
Published in Feb 2015
Publisher Packt
ISBN-13 9781783285518
Length 382 pages
Edition 1st Edition
Tools
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Toc

Table of Contents (13) Chapters Close

Preface 1. Introduction 2. Storage FREE CHAPTER 3. Processing – MapReduce and Beyond 4. Real-time Computation with Samza 5. Iterative Computation with Spark 6. Data Analysis with Apache Pig 7. Hadoop and SQL 8. Data Lifecycle Management 9. Making Development Easier 10. Running a Hadoop Cluster 11. Where to Go Next Index

Prerequisites


Before diving into specific technologies, let's generate some data that we'll use in the examples throughout this chapter. We'll create a modified version of a former Pig script as the main functionality for this. The script in this chapter assumes that the Elephant Bird JARs used previously are available in the /jar directory on HDFS. The full source code is at https://github.com/learninghadoop2/book-examples/blob/master/ch7/extract_for_hive.pig, but the core of extract_for_hive.pig is as follows:

-- load JSON data
tweets = load '$inputDir' using  com.twitter.elephantbird.pig.load.JsonLoader('-nestedLoad');
-- Tweets
tweets_tsv = foreach tweets {
generate 
    (chararray)CustomFormatToISO($0#'created_at', 
'EEE MMMM d HH:mm:ss Z y') as dt, 
    (chararray)$0#'id_str', 
(chararray)$0#'text' as text, 
    (chararray)$0#'in_reply_to', 
(boolean)$0#'retweeted' as is_retweeted, 
(chararray)$0#'user'#'id_str' as user_id, (chararray)$0#'place'#'id' as place_id;
}
store tweets_tsv...
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