This article categorizes Elasticsearch data types into five groups, maps each MySQL type to its ES equivalent with practical notes, explains the critical text vs keyword distinction, covers dynamic mapping traps, and provides interview-ready mnemonics for type selection and concept translation.
This article explains why JSON field mismatches cause backend failures in microservice architectures and presents three robust Spring Boot solutions—using a Map, Jackson's JsonNode, and @JsonAnySetter/@JsonAnyGetter—to flexibly and safely adapt dynamic JSON structures.
This article explains what mapping explosion is in Elasticsearch, why it hurts performance and memory, and presents three practical solutions—strict, false, and runtime dynamic settings—along with code examples and trade‑off discussions.
This article explains Elasticsearch mapping, covering dynamic mapping, field datatypes, meta‑fields, mapping parameters, and dynamic templates, while emphasizing the importance of careful schema design and the need for reindexing when changes are required.
