Book Image

Hadoop Real-World Solutions Cookbook - Second Edition

By : Tanmay Deshpande
Book Image

Hadoop Real-World Solutions Cookbook - Second Edition

By: Tanmay Deshpande

Overview of this book

Big data is the current requirement. Most organizations produce huge amount of data every day. With the arrival of Hadoop-like tools, it has become easier for everyone to solve big data problems with great efficiency and at minimal cost. Grasping Machine Learning techniques will help you greatly in building predictive models and using this data to make the right decisions for your organization. Hadoop Real World Solutions Cookbook gives readers insights into learning and mastering big data via recipes. The book not only clarifies most big data tools in the market but also provides best practices for using them. The book provides recipes that are based on the latest versions of Apache Hadoop 2.X, YARN, Hive, Pig, Sqoop, Flume, Apache Spark, Mahout and many more such ecosystem tools. This real-world-solution cookbook is packed with handy recipes you can apply to your own everyday issues. Each chapter provides in-depth recipes that can be referenced easily. This book provides detailed practices on the latest technologies such as YARN and Apache Spark. Readers will be able to consider themselves as big data experts on completion of this book. This guide is an invaluable tutorial if you are planning to implement a big data warehouse for your business.
Table of Contents (18 chapters)
Hadoop Real-World Solutions Cookbook Second Edition
Credits
About the Author
Acknowledgements
About the Reviewer
www.PacktPub.com
Preface
Index

Running Spark on YARN


In the previous recipe, we took a look at how to use Spark's built-in cluster manager; in this recipe, we are going to explore how to use YARN as a cluster manager to execute the Spark application.

Getting ready

To perform this recipe, you should have a running Hadoop cluster. You should also have performed the previous recipe.

How to do it...

As mentioned in the previous recipe, we can either use Spark's built-in cluster manager, or we can use an external cluster manager such as YARN. In order to execute the Spark application on YARN, we need to edit SPARK_HOME/conf/spark-env.sh, and add the following properties to it:

export HADOOP_CONF_DIR=/usr/local/hadoop/etc/hadoop
export YARN_CONF_DIR=/usr/local/hadoop/etc/Hadoop

Here, /usr/local/hadoop/etc/hadoop is the directory where we have our Hadoop and YARN configuration files.

Now, let's execute the same Spark application on YARN using the following command:

./bin/spark-submit --class org.apache.spark.examples.SparkPi \
    ...