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HBase High Performance Cookbook

You're reading from  HBase High Performance Cookbook

Product type Book
Published in Jan 2017
Publisher Packt
ISBN-13 9781783983063
Pages 350 pages
Edition 1st Edition
Languages
Author (1):
Ruchir Choudhry Ruchir Choudhry
Profile icon Ruchir Choudhry
Toc

Table of Contents (19) Chapters close

HBase High Performance Cookbook
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Configuring HBase 2. Loading Data from Various DBs 3. Working with Large Distributed Systems Part I 4. Working with Large Distributed Systems Part II 5. Working with Scalable Structure of tables 6. HBase Clients 7. Large-Scale MapReduce 8. HBase Performance Tuning 9. Performing Advanced Tasks on HBase 10. Optimizing Hbase for Cloud 11. Case Study Index

Using Sqoop


Sqoop provides an excellent way to import data in parallel from existing RDBMs to HDFS. We get an exact set of table structures that are imported. This happens because of parallel processing. These files can have text delimited by ',' '|', and so on. After manipulating imported records by using MapReduce or Hive, the output result set can be exported back to RDBMS. The data imported can be done in real time or in the batch process (using a cron job).

Getting ready

Prerequisites:

HBase and Hadoop cluster must be up and running.

You can do a wget to http://mirrors.gigenet.com/apache/sqoop/1.4.6/sqoop-1.4.6.tar.gz

Untar it to /u/HbaseB using tar –zxvf sqoop-1.4.6.tar.gz

It will create a /u/HbaseB/sqoop-1.4.6 folder.

A Sqoop user is created in the target DB, which has read/write access and is not bound strictly with CPU and memory (RAM, Storage) limitation by the DBAs.

How to do it…

  1. Log in to MySQL by executing the following command:

    Mysql –h yourMySqlHostName –u scoop –p
    mysql> create...
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