Book Image

Elasticsearch 5.x Cookbook - Third Edition

By : Alberto Paro
Book Image

Elasticsearch 5.x Cookbook - Third Edition

By: Alberto Paro

Overview of this book

Elasticsearch is a Lucene-based distributed search server that allows users to index and search unstructured content with petabytes of data. This book is your one-stop guide to master the complete Elasticsearch ecosystem. We’ll guide you through comprehensive recipes on what’s new in Elasticsearch 5.x, showing you how to create complex queries and analytics, and perform index mapping, aggregation, and scripting. Further on, you will explore the modules of Cluster and Node monitoring and see ways to back up and restore a snapshot of an index. You will understand how to install Kibana to monitor a cluster and also to extend Kibana for plugins. Finally, you will also see how you can integrate your Java, Scala, Python, and Big Data applications such as Apache Spark and Pig with Elasticsearch, and add enhanced functionalities with custom plugins. By the end of this book, you will have an in-depth knowledge of the implementation of the Elasticsearch architecture and will be able to manage data efficiently and effectively with Elasticsearch.
Table of Contents (25 chapters)
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Dedication
Preface

Indexing data with Apache Pig


Apache Pig (https://pig.apache.org/) is a tool frequently used to store/manipulate data in datastores. It can be very handy if you need to import some CSV in Elasticsearch in a very fast way.

Getting ready

You need an up-and-running Elasticsearch installation as we described in Downloading and installing Elasticsearch recipe in Chapter 2, Downloading and Setup.

You need a working Pig installation. Depending on your operating system you should follow the instruction at http://pig.apache.org/docs/r0.16.0/start.html.

If you are using Mac OS X with Homebrew you can install it with brew install pig.

How to do it...

We want read a CSV and write the data in Elasticsearch. We will perform the steps given as follows:

  1. We will download a CSV dataset from geonames site: all the geoname locations of Great Britain. We can fast download them and unzip them via:

            wget http://download.geonames.org/export/dump/GB.zip 
            unzip GB.zip 
    
  2. We can write es.pig that contains...