How deeply does Elasticsearch in Action, Second Edition cover analyze API?

Shows tokens, lowercase conversion, token types, positions, explicit analyzers, stemming, tokenizers, and filters.

Analyze API

As explained in Elasticsearch in Action, Second Edition

The Elasticsearch analyze API analyzes supplied text and returns the terms and intermediate results produced by an analyzer.

The analyze API lets you inspect how Elasticsearch processes text before indexing. Use it to choose an analyzer, explain unexpected search results, and test analysis before production. section 7.2.4

Inspecting “James Bond 007”

GET _analyze { "text": "James Bond 007" } With no analyzer specified, Elasticsearch uses the standard analyzer. The response produces the lowercase tokens “james”, “bond”, and “007”, along with token types and positions. section 7.2.4

Specify an analyzer to compare alternatives. The simple analyzer returns “james” and “bond” because “007” is truncated at a non-letter character; the english analyzer returns “jame”, “bond”, and “007” through stemming. section 7.2.4

Testing a custom analyzer

GET _analyze { "tokenizer": "path_hierarchy", "filter": ["uppercase"], "text": "/Volumes/FILES/Dev" } The request can provide its tokenizer and token filters directly, making it useful for experimenting with custom analysis modules. section 4.5.1

How Elasticsearch in Action, Second Edition covers it

Cover of Elasticsearch in Action, Second Edition

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Related concepts

text analyzeruses · A text analyzer is a component that transforms text into terms or other linguistic representations for indexing and searching.
html_strip character filterused by · The html_strip character filter removes HTML markup from an input character stream before tokenization, optionally preserving specified tags.
token filterused by · A token filter is a text-analysis component that transforms, removes, or adds tokens after tokenization.
standard tokenizerused by · A standard tokenizer is a built-in Lucene text-analysis component that divides text into tokens according to predefined standard rules.

This explainer was generated by Manning's knowledge graph from the text of Elasticsearch in Action, Second Edition. The section links point to the parts of the book it draws on.