Elasticsearch & Geospatial

This course will cover the geospatial features available in Elasticsearch. Students will learn how to apply geospatial functions within Elasticsearch with examples. We will also cover how to integrate the Elasticsearch stack with the popular Geospatial server 'Geoserver'. Kibana maps use will also be demonstrated.

Elasticsearch as part of the ELK (Elasticsearch, Logstash & Kibana) stack is a very popular open-source distributed document store and analytics platform. It has been widely used by several organizations, individuals and teams to develop powerful search capabilities within their applications. It has also been adopted to solve complex Geospatial problems within map-based web applications. Elasticsearch is built on top of Apache Lucene which itself allows super-fast full-text search, however, the use of Elasticsearch is made easier via a simple Restful API. This means the user does not need to worry about how to learn to work with Lucene but rather uses simple API requests (Query DSL) to interact with Elasticsearch.  Elasticsearch is distributed and usually implemented within a cluster of machines in production. This means it is highly scalable as both vertical and horizontal scaling can be achieved. Elasticsearch itself is a complex system but this complexity is transparent to the end user. This also means very powerful applications can be built using Elasticsearch. Although not covered in this course a cloud-based version of Elasticsearch on AWS is available and makes it very easy to work with Elasticsearch and integrate it within applications and pipelines.