Book Image

ElasticSearch Server

Book Image

ElasticSearch Server

Overview of this book

ElasticSearch is an open source search server built on Apache Lucene. It was built to provide a scalable search solution with built-in support for near real-time search and multi-tenancy.Jumping into the world of ElasticSearch by setting up your own custom cluster, this book will show you how to create a fast, scalable, and flexible search solution. By learning the ins-and-outs of data indexing and analysis, "ElasticSearch Server" will start you on your journey to mastering the powerful capabilities of ElasticSearch. With practical chapters covering how to search data, extend your search, and go deep into cluster administration and search analysis, this book is perfect for those new and experienced with search servers.In "ElasticSearch Server" you will learn how to revolutionize your website or application with faster, more accurate, and flexible search functionality. Starting with chapters on setting up your own ElasticSearch cluster and searching and extending your search parameters you will quickly be able to create a fast, scalable, and completely custom search solution.Building on your knowledge further you will learn about ElasticSearch's query API and become confident using powerful filtering and faceting capabilities. You will develop practical knowledge on how to make use of ElasticSearch's near real-time capabilities and support for multi-tenancy.Your journey then concludes with chapters that help you monitor and tune your ElasticSearch cluster as well as advanced topics such as shard allocation, gateway configuration, and the discovery module.
Table of Contents (17 chapters)
ElasticSearch Server
Credits
About the Authors
Acknowledgement
Acknowledgement
About the Reviewers
www.PacktPub.com
Preface
Index

Using nested objects


Nested objects can come in handy in certain situations. Basically, with nested objects, ElasticSearch allows us to connect multiple documents together—one main document and multiple dependent ones. Now, imagine that we have a shop with clothes and we store the size and color of each T-shirt. Our standard, non-nested mappings could look like the following code (stored in cloth.json):

{
 "cloth" : {
  "properties" : {
   "name" : {"type" : "string", "store" : "yes", "index" : "analyzed"},
   "size" : {"type" : "string", "store" : "yes", "index" : "not_analyzed"},
   "color" : {"type" : "string", "store" : "yes", "index" : "not_analyzed"}
  }
 }
}

Now imagine that we have a T-shirt in our shop that we only have in the XXL size in "red" and XL size in "black". So our example document could look like the following code:

{
 "name" : "Test shirt",
 "size" : [ "XXL", "XL" ],
 "color" : [ "red", "black" ]
}

But if one of our clients were to search our shop in order to find the XXL...