Book Image

Hadoop 2.x Administration Cookbook

By : Aman Singh
Book Image

Hadoop 2.x Administration Cookbook

By: Aman Singh

Overview of this book

Hadoop enables the distributed storage and processing of large datasets across clusters of computers. Learning how to administer Hadoop is crucial to exploit its unique features. With this book, you will be able to overcome common problems encountered in Hadoop administration. The book begins with laying the foundation by showing you the steps needed to set up a Hadoop cluster and its various nodes. You will get a better understanding of how to maintain Hadoop cluster, especially on the HDFS layer and using YARN and MapReduce. Further on, you will explore durability and high availability of a Hadoop cluster. You’ll get a better understanding of the schedulers in Hadoop and how to configure and use them for your tasks. You will also get hands-on experience with the backup and recovery options and the performance tuning aspects of Hadoop. Finally, you will get a better understanding of troubleshooting, diagnostics, and best practices in Hadoop administration. By the end of this book, you will have a proper understanding of working with Hadoop clusters and will also be able to secure, encrypt it, and configure auditing for your Hadoop clusters.
Table of Contents (20 chapters)
Hadoop 2.x Administration Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Index

Loading data into Hive


In this recipe, we look at how we can import data into Hive and also how we can point it to existing data using an external table.

The data store formats for Hive can be text, ORC and parquet, as well as a few other formats. Each one has its advantages in terms of compression, performance, space utilization and memory overheads.

Getting ready

To progress through the recipe, you must have completed the recipe Using MySQL for Hive metastore. There are many examples of each type of Hive distribution at $HIVE_HOME/examples.

How to do it...

  1. Connect to the edge node edge1.cyrus.com in the cluster and switch to the hadoop user.

  2. Connect by either using Hive or the beeline client and import the data by creating a table as shown in the following screenshot:

  3. Now take a look at the HDFS warehouse location. You will see a file named kv1.txt copied there, as shown in the following screenshot:

  4. Describe the table pokes and look at the data, as shown in the following screenshot. What if you...