Mappings & Text Analysis

Lessons in this group, roughly in build order:

• dynamic-vs-explicit-mapping — The choice between letting Elasticsearch infer field types from the first document it sees (dynamic)…
• core-field-types-text-keyword-numeric-date-boolean — The handful of field types that cover the vast majority of mappings, and the rule that decides between…
• object-nested-fields — How Elasticsearch indexes JSON sub-objects: the default object type flattens them, while the nested type…
• analyzers-standard-language-custom — An analyzer is the pipeline that turns a text value into the index terms stored in the inverted-index —…
• tokenizers — The component inside an analyzer that splits a character stream into individual tokens (terms) — and emits…
• token-filters-character-filters — The two filtering stages of an analyzer: character filters transform the raw text before the tokenizer;…
• normalizers — A normalizer is a stripped-down analyzer for keyword fields: it applies character and token filters but…
• multi-fields — Indexing the same source value several ways under one field via the fields parameter — typically a text…