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

Writing the Map Reduce program in Java to analyze web log data


In this recipe, we are going to take a look at how to write a map reduce program to analyze web logs. Web logs are data that is generated by web servers for requests they receive. There are various web servers such as Apache, Nginx, Tomcat, and so on. Each web server logs data in a specific format. In this recipe, we are going to use data from the Apache Web Server, which is in combined access logs.

Note

To read more on combined access logs, refer to

http://httpd.apache.org/docs/1.3/logs.html#combined.

Getting ready

To perform this recipe, you should already have a running Hadoop cluster as well as an eclipse similar to an IDE.

How to do it...

We can write map reduce programs to analyze various aspects of web log data. In this recipe, we are going to write a map reduce program that reads a web log file, results pages, views, and their counts. Here is some sample web log data we'll consider as input for our program:

106.208.17.105 -...