Many as One – the Distributed Model

Every single server of Elasticsearch is considered a node, and multiple nodes form a cluster. Elasticsearch uses clusters to provide scalability and redundancy. If a search is performed on a cluster, all of the nodes within it will be included in the search. For the most productive environment, it is best to use multiple nodes on different machines, with each one performing a specific task. A less efficient route is to use multiple nodes on the same machine—this is undoubtedly slower and is only really appropriate when testing high-availability features.–

Elasticsearch stores JSON documents and uses Lucene as a backend search engine. It indexes the documents, as well as their contents, so queries can be performed on fields as well. This makes searching very easy. Simple queries can be built using a field name or full text...

API conventions

The Elasticsearch REST module allows Elasticsearch APIs to be exposed over HTTP using JSON. We can perform different operations on Elasticsearch using APIs, such as monitoring the cluster health, checking nodes, indices, and shards, or creating, updating, or deleting the index. So, ideally, we can do everything using the REST-based API, which we can use to interact with Elasticsearch. We will discuss these APIs in detail later in this chapter, but for now, let's learn how to handle multiple indices if we want to interact with them simultaneously.

Handling multiple indices

APIs can be applied to multiple indices using a list of indices, a wildcard index, or all of the indices, by using the _all notation...

Summary

In this chapter, we covered the REST APIs that we can use to interact with Elasticsearch. We looked at how we can handle multiple indices and then moved on to look at the common options for the API response. We also covered the APIs for cluster health, state, and statistics to check the cluster details. After the cluster APIs, we covered the node APIs that we use to check the state and stats of the node. Then, we covered index APIs, learning how to create, delete, and retrieve indices. After looking at index APIs, we learned about document APIs and how we can use them to create, view, update, and delete documents, as well as using them to delete multiple documents using a query.

In the next chapter, we will walk through the details of how full text is analyzed and indexed in Elasticsearch, including a discussion of the various analyzers and filters and how to configure...