Elasticsearch: A Complete Guide

More Information
Learn
  • Install and configure Elasticsearch, Logstash, and Kibana
  • Write CRUDE operations and other search functionalities using the Elasticsearch Python and Java Clients
  • Build analytics using aggregations
  • Set up and scale Elasticsearch clusters using best practices
  • Master document relationships and geospatial data
  • Build your own data pipeline using Elastic Stack
  • Choose the appropriate amount of shards and replicas for your deployment
  • Become familiar with the Elasticsearch APIs
About

Elasticsearch is a modern, fast, distributed, scalable, fault tolerant, open source search and analytics engine. It provides a new level of control over how you can index and search even huge sets of data. This course will take you from the basics of Elasticsearch to using Elasticsearch in the Elastic Stack and in production.

You’ll start with the very basics: Elasticsearch terminology, installation, and configuring Elasticsearch. After this, you’ll take a look at analytics and indexing, search, and querying. You’ll learn how to create maps and visualizations. You’ll also be briefed on cluster scaling, search and bulk operations, backups, and security.

Then you’ll be ready to get into Elasticsearch’s internal functionalities including caches, Apache Lucene library, and its monitoring capabilities. You’ll learn about the practical usage of Elasticsearch configuration parameters and how to use the monitoring API. You’ll discover how to improve the user search experience, index distribution, segment statistics, merging, and more.

Once you have mastered this, you’ll dive into end-to-end visualize-analyze-log techniques with Elastic Stack (also known as the ELK stack). You’ll explore Elasticsearch, Logstash, and Kibana and see how to make them work together to build fresh insights and business metrics out of data. You’ll be able to use Elasticsearch with other de facto components in order to get the most out of Elasticsearch. By the end of this course, you’ll have developed a full-fledged data pipeline.

This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:

  • Elasticsearch Essentials
  • Mastering Elasticsearch, Second Edition
  • Learning ELK Stack
Features
  • Solve your data analytics problems with the Elastic Stack
  • Improve your user search experience with Elasticsearch and develop your own Elasticsearch plugins
  • Design your index, configure it, and distribute it — you’ll also learn how it works
Page Count 801
Course Length 24 hours 1 minutes
ISBN 9781787288546
Date Of Publication 31 Jan 2017
Altering Apache Lucene scoring
Choosing the right directory implementation – the store module
NRT, flush, refresh, and transaction log
Segment merging under control
When it is too much for I/O – throttling explained
Understanding Elasticsearch caching
Summary
Discovery and recovery modules
The human-friendly status API – using the Cat API
Backing up
Federated search
Summary

Authors

Rafał Kuć

Rafał Kuć is a software engineer, trainer, speaker and consultant. He is working as a consultant and software engineer at Sematext Group Inc. where he concentrates on open source technologies such as Apache Lucene, Solr, and Elasticsearch. He has more than 14 years of experience in various software domains—from banking software to e–commerce products. He is mainly focused on Java; however, he is open to every tool and programming language that might help him to achieve his goals easily and quickly. Rafał is also one of the founders of the solr.pl site, where he tries to share his knowledge and help people solve their Solr and Lucene problems. He is also a speaker at various conferences around the world such as Lucene Eurocon, Berlin Buzzwords, ApacheCon, Lucene/Solr Revolution, Velocity, and DevOps Days.

Rafał began his journey with Lucene in 2002; however, it wasn't love at first sight. When he came back to Lucene in late 2003, he revised his thoughts about the framework and saw the potential in search technologies. Then Solr came and that was it. He started working with Elasticsearch in the middle of 2010. At present, Lucene, Solr, Elasticsearch, and information retrieval are his main areas of interest.

Rafał is also the author of the Solr Cookbook series, ElasticSearch Server and its second edition, and the first and second editions of Mastering ElasticSearch, all published by Packt Publishing.

Marek Rogoziński

Marek Rogoziński is a software architect and consultant with more than 10 years of experience. His specialization concerns solutions based on open source search engines, such as Solr and Elasticsearch, and the software stack for big data analytics including Hadoop, Hbase, and Twitter Storm.

He is also a cofounder of the solr.pl site, which publishes information and tutorials about Solr and Lucene libraries. He is the coauthor of ElasticSearch Server and its second edition, and the first and second editions of Mastering ElasticSearch, all published by Packt Publishing.

He is currently the chief technology officer and lead architect at ZenCard, a company that processes and analyzes large quantities of payment transactions in real time, allowing automatic and anonymous identification of retail customers on all retailer channels (m-commerce/e-commerce/brick&mortar) and giving retailers a customer retention and loyalty tool.

Saurabh Chhajed

Saurabh Chhajed is a technologist with vast professional experience in building Enterprise applications that span across product and service industries. He has experience building some of the largest recommender engines using big data analytics and machine learning, and also enjoys acting as an evangelist for big data and NoSQL technologies. With his rich technical experience, Saurabh has helped some of the largest financial and industrial companies in USA build their large product suites and distributed applications from scratch. He shares his personal experiences with technology at http://saurzcode.in.

Saurabh has also reviewed books by Packt Publishing, Apache Camel Essentials and Java EE 7 Development with NetBeans 8, in the past.

Bharvi Dixit

Bharvi Dixit is an IT professional with extensive experience of working on search servers, NoSQL databases, and cloud services. He holds a master's degree in computer science and is currently working with Sentieo, a USA-based financial data and equity research platform, where he leads the overall platform and architecture of the company spanning across hundreds of servers. At Sentieo, he also plays a key role in the search and data team.

He is also the organizer of Delhi's Elasticsearch Meetup Group, where he speaks about Elasticsearch and Lucene and is continuously building the community around these technologies.

Bharvi also works as a freelance Elasticsearch consultant and has helped more than half a dozen organizations adapt Elasticsearch to solve their complex search problems around different use cases, such as creating search solutions for big data-automated intelligence platforms in the area of counter-terrorism and risk management, as well as in other domains, such as recruitment, e-commerce, finance, social search, and log monitoring.

He has a keen interest in creating scalable backend platforms. His other areas of interests are search engineering, data analytics, and distributed computing. Java and Python are the primary languages in which he loves to write code. He has also built a proprietary software for consultancy firms.

In 2013, he started working on Lucene and Elasticsearch, and in 2016, he authored his first book, Elasticsearch Essentials, which was published by Packt. He has also worked as a technical reviewer for the book Learning Kibana 5.0 by Packt.

You can connect with him on LinkedIn at https://in.linkedin.com/in/bharvidixit or can follow him on Twitter @d_bharvi.