Elasticsearch is a very popular search and analytics engine which helps you get up and running with search for your site or application in no time. This course covers how to improve search nuances by designing the right schema for your documents.
You can get better search results beyond the basic out-of-the-box search experience with Elasticsearch. In this course, Designing Schema for Elasticsearch, you will learn how to configure indexes to get more nuanced and meaningful search results. First, you will use dynamic and explicit mapping which allows you to specify field types within your document, which in turn determines how they are indexed and searched. Next, you will learn how you can map relationships and hierarchies from the traditional RDBMS world to the flat world of Elasticsearch. Finally, you will see Elasticsearch's special features, working with geospatial data such as GPS, and time-based data such as log files, and also aliasing indices to share them across multiple users for a better search experience. At the end of this course, you will have hands-on experience designing your Elasticsearch indexes and mappings to work well with different kinds of data, such as hierarchical, geospatial, or time-based data.
A problem solver at heart, Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework.