The text explores the creation of Full Text Search (FTS) indexes in Couchbase, focusing on best practices and use cases such as simple search, field-independent search, nearest neighbor search, and dynamic search. Using the Travel Sample dataset, it details the indexing of various fields like hotel descriptions, names, aliases, addresses, reviews, and geolocation coordinates. Each use case involves creating specific indexes with tailored type mappings and field settings to optimize search performance. It highlights the importance of configuring JSON type fields, analyzers, and dynamic mappings, while demonstrating how to execute and test these indexes using both the Couchbase UI and REST API. The document emphasizes the benefits of using the Scorch index type for its improved performance and reduced size, and provides detailed instructions on how to run searches and obtain results, including highlighted matches and geospatial searches.