Elasticsearch is an open source search server that is built on Apache Lucene. It uses Lucene as the core search engine, but provides many features that are not part of Lucene. For example, usage of Elasticsearch relies on a comprehensive REST API. Like Apache Lucene, Elasticsearch is written in Java and is therefore cross-platform and… read more

In this article, we will see how to add an index to our Elasticsearch cluster. To do this, we will be using the Kibana plugin, Sense, which we installed in a previous article. To create an index in Elasticsearch, simply issue a PUT request like below. PUT /ecommerce { } This command is translated into an HTTP… read more

Now that we have created an index, let’s see how we can delete an index. In fact, we are going to delete the index that we created in the previous article in this series and add it again later. Open the Sense plugin for Kibana and simply issue the below request to delete the index. DELETE /ecommerce Let’s ensure… read more

In this part of the series, we will be talking about mapping in Elasticsearch. I will introduce mapping as well as cover dynamic and explicit mapping. What is Mapping in Elasticsearch? Like I briefly mentioned in the article about Elasticsearch terminology, mapping describes how documents and their fields are indexed and stored. This typically involves defining the… read more

Having introduced mapping, we will now go into a bit of more detail about data types. There are four categories of data types in Elasticsearch, namely core data types, complex data types, geo data types and specialized data types, which we will all take a look at now. Feel free to skip this article and move… read more

Now that we have taken a look at field data types, it is time to talk about meta fields. Introduction to Meta Fields So, just what are meta fields? Each document that is indexed in Elasticsearch has metadata associated with it. The names of these fields are prefixed with an underscore, and some of them… read more