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Hadoop Real-World Solutions Cookbook- Second Edition

You're reading from   Hadoop Real-World Solutions Cookbook- Second Edition Over 90 hands-on recipes to help you learn and master the intricacies of Apache Hadoop 2.X, YARN, Hive, Pig, Oozie, Flume, Sqoop, Apache Spark, and Mahout

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Product type Paperback
Published in Mar 2016
Publisher
ISBN-13 9781784395506
Length 290 pages
Edition 2nd Edition
Tools
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Author (1):
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Tanmay Deshpande Tanmay Deshpande
Author Profile Icon Tanmay Deshpande
Tanmay Deshpande
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Table of Contents (12) Chapters Close

Preface 1. Getting Started with Hadoop 2.X FREE CHAPTER 2. Exploring HDFS 3. Mastering Map Reduce Programs 4. Data Analysis Using Hive, Pig, and Hbase 5. Advanced Data Analysis Using Hive 6. Data Import/Export Using Sqoop and Flume 7. Automation of Hadoop Tasks Using Oozie 8. Machine Learning and Predictive Analytics Using Mahout and R 9. Integration with Apache Spark 10. Hadoop Use Cases Index

Importing data from RDMBS to HDFS using Sqoop


Most organizations use RDBMS databases as their primary storage for their data. To analyze the data, we need to first import that data on HDFS. Sqoop is a tool that helps us achieve this with ease, and with just a single command, we can import data into HDFS as required. In this recipe, we are going to see how to import data from MySQL to Hadoop using Sqoop.

Getting ready

To perform this recipe, you should have a Hadoop cluster running with you as well as the latest version of Sqoop installed on it. Here I am using Sqoop 1.4.6. We would also need MySQL database to be present in the network. Installing Sqoop is easy by downloading Sqoop tar ball and setting it in the system path. As we are going to import data from MySQL, we would also need to download MySQL connector from https://dev.mysql.com/downloads/connector/. Based on your MySQL version, download the right connector jar and copy it into the lib directory of Sqoop installation.

How to do it...

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