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Elasticsearch 5.x Cookbook

You're reading from Elasticsearch 5.x Cookbook Distributed Search and Analytics

Product type Paperback

Published in Feb 2017

Publisher

ISBN-13 9781786465580

Length 696 pages

Edition 3rd Edition

Languages

Java

Tools

Elasticsearch

Concepts

Enterprise Search

Author (1):

Alberto Paro

View More author details

Table of Contents (25) Chapters

Credits

About the Author

About the Reviewer

www.PacktPub.com

Customer Feedback

Dedication

Preface

1. Getting Started FREE CHAPTER

2. Downloading and Setup

3. Managing Mappings

4. Basic Operations

5. Search

6. Text and Numeric Queries

7. Relationships and Geo Queries

8. Aggregations

9. Scripting

10. Managing Clusters and Nodes

11. Backup and Restore

12. User Interfaces

13. Ingest

14. Java Integration

15. Scala Integration

16. Python Integration

17. Plugin Development

18. Big Data Integration

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:

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 
```
We can write es.pig that contains...

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Authors (1)

Alberto Paro

Alberto Paro

Alberto Paro is an engineer, manager, and software developer. He currently works as technology architecture delivery associate director of the Accenture Cloud First data and AI team in Italy. He loves to study emerging solutions and applications, mainly related to cloud and big data processing, NoSQL, Natural language processing (NLP), software development, and machine learning. In 2000, he graduated in computer science engineering from Politecnico di Milano. Then, he worked with many companies, mainly using Scala/Java and Python on knowledge management solutions and advanced data mining products, using state-of-the-art big data software. A lot of his time is spent teaching how to effectively use big data solutions, NoSQL data stores, and related technologies.

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