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Further your knowledge of the Elasticsearch server by learning more about its internals, querying, and data handlingAbout This Book
- Understand Apache Lucene and Elasticsearch's design and architecture
- Design your index, configure it, and distribute it, not only with assumptions, but with the underlying knowledge of how it works
- Improve your user search experience with Elasticsearch functionality and learn how to develop your own Elasticsearch plugins
This book is for Elasticsearch users who want to extend their knowledge and develop new skills. Prior knowledge of the Query DSL and data indexing is expected.
What You Will Learn- Understand Apache Lucene and Elasticsearch's design and architecture
- Use and configure different scoring models to alter the default scoring mechanism
- Choose the appropriate amount of shards and replicas for your deployment
- Improve user search experience by utilizing Elasticsearch functionality
- Control segment merging and learn why Elasticsearch uses merging
- Develop custom Elasticsearch plugins and cover detailed examples of how to extend Elasticsearch by writing your own plugins
- Apply your knowledge to create scalable, efficient, and fault tolerant clusters and monitor your cluster by using and understanding the Elasticsearch API
Elasticsearch is a modern, fast, distributed, scalable, fault tolerant, and open source search and analytics engine. Elasticsearch leverages the capabilities of Apache Lucene, providing a new level of control over how you can index and search even huge sets of data.
This book covers intermediate and advanced functionalities of Elasticsearch and walks you through its internals including caches, the Apache Lucene library, and its monitoring capabilities. You'll learn about practical usage of Elasticsearch configuration parameters and how to use the monitoring API.
With this book, you'll delve into Elasticsearch's query rewrite, query template, bulk operation, document grouping, and function score queries. You will also learn how to improve user search experience, index distribution, segment statistics, and merging. By the end of the book, you will be able to enhance Elasticsearch's performance and create your own Elasticsearch plugins.
- Sales Rank: #240723 in eBooks
- Published on: 2015-02-27
- Released on: 2015-02-27
- Format: Kindle eBook
About the Author
Rafal Kuc
Rafal Kuc is a born team leader and software developer. Currently, he is working as a consultant and a software engineer at Sematext Group, Inc., where he concentrates on open source technologies, such as Apache Lucene, Solr, Elasticsearch, and the Hadoop stack. He has more than 13 years of experience in various software branches―from banking software to e-commerce products. He is mainly focused on Java but is open to every tool and programming language that will make the achievement of his goal easier and faster. Rafal is also one of the founders of the solr.pl website, where he tries to share his knowledge and help people with their problems related to Solr and Lucene. He is also a speaker at various conferences around the world, such as Lucene Eurocon, Berlin Buzzwords, ApacheCon, Lucene Revolution, and DevOps Days. He began his journey with Lucene in 2002, but 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 came Solr, and that was it. He started working with Elasticsearch in the middle of 2010. Currently, Lucene, Solr, Elasticsearch, and information retrieval are his main points of interest. Rafal is the author of Solr 3.1 Cookbook, its update―Solr 4.0 Cookbook―and its third release―Solr Cookbook, Third Edition. He is also the author of Elasticsearch Server and its second edition, along with the first edition of Mastering Elasticsearch, all published by Packt Publishing.
Marek Rogozinski
Marek Rogozinski is a software architect and consultant with over 10 years of experience. He specializes in solutions based on open source search engines, such as Solr and Elasticsearch, and software stack for Big Data analytics, including Hadoop, Hbase, and Twitter Storm. He is also a cofounder of the solr.pl website, which publishes information and tutorials about Solr and Lucene libraries. He is the coauthor of Mastering ElasticSearch, ElasticSearch Server, and Elasticsearch Server Second Edition, both published by Packt Publishing. Currently, he holds the position of chief technology officer and lead architect at ZenCard, a company processing and analyzing large amounts of payment transactions in real time, allowing automatic and anonymous identification of retail customers on all retailer channels (m-commerce / e-commerce / brick and mortar) and giving retailers a customer retention and loyalty tool.
Most helpful customer reviews
2 of 2 people found the following review helpful.
the book has good information but is poorly organized and not written in ...
By David Williams
Not written in reference style (for general subject matter experts) nor in introduction style (for those needing paragraphs of explanations). Basically, the book has good information but is poorly organized and not written in a manner conducive to comprehension.
2 of 2 people found the following review helpful.
An indispensable book for professionals who manage and maintain Elasticsearch servers for a living
By adnan baloch
First off, a disclaimer for newbies: This book is meant for intermediate users of the Elasticsearch Server. Still, the book begins with a short but comprehensive introduction to the basic concepts used in document indexing, the various node types in Elasticsearch and the Apache Lucene library that powers Elasticsearch under the hood. The examples in the book are based on the premise that the user is running an online bookstore which is a powerful way to explore the possibilities offered by Elasticsearch. The examples are in JSON document format which should be familiar to any serious developer. The score of a query determines how well the document matches the input query. The scoring formula is explained using a
simple example to demonstrate how it works in practice. Query rewrite methods, filters and types of queries are explained in detail with a special focus on their performance impact. Simple use cases let the readers know when to use which query group. A new sandboxed scripting language called Groovy is introduced that enables on-the-fly calculation of document scores without compromising the security of the search server. Lucene expressions are also given a brief touch. Readers will enjoy the chapter on improving search suggestions which can make a real difference in the search experience of users. Plenty of examples in this chapter help to take the guesswork out of improving query relevance. Filtering garbage results and using term faceting to narrow down search results are discussed to give readers the power to tailor their websites according to their needs for maximum user satisfaction. Scaling to accommodate increasing demands requires the right amount of shards and replicas. Deciding this amount is explored with a practical routing example. The final few chapters deal with low level index control, Elasticsearch administration, performance improving techniques and developing Elasticsearch plugins. whether you have a single node or an entire cluster of nodes in the cloud, the sheer amount of information contained in over 400 pages of this book ensures that readers will find this book a worthy companion in their quest to tame and tune Elasticsearch server for blazing fast query speed and highly relevant search results.
1 of 1 people found the following review helpful.
Very useful book for ElasticSearch users
By R. Somerfield
I've been using ElasticSearch professionally for over 6 months - our first version product using ElasticSearch has shipped this week!
Whilst it is fairly easy to get started with ElasticSearch, there are a lot of fundamental aspects to it (and its underpinnings) which can have a dramatic affect on using it. And, whilst there are some good examples, they tend to be fairly simplistic.
Up until I got this book I'd been (extensively!!) relying on Google. And whilst I've eventually managed to work out the answers, it took a lot of searching and therefore a lot longer than I'd have ideally liked. In addition, finding individual snippets on the web doesn't help with some of the broad knowledge.
I found this book to be an excellent guide to help me understand the underpinnings of ElasticSearch, and also helped me to make many improvements in my Google-aquired knowledge. I would recommend it to anyone how is spending any amount of time with ElasticSearch.
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