Elasticsearch Suggesters: Beyond Autocomplete
summary
Shows how Elasticsearch 7.0.4 suggesters are used beyond simple autocomplete with live REST-API demos that build indices, custom analyzers and documents and prove each feature works. Covers completion suggester (prefix-only, finite state transducer, fuzzy and skip_duplicates, _source control), term suggester (edit distance; needs text analyzed fields), phrase suggester (shingles/trigrams, collate/prune/confidence, highlighting) and context suggester (category/geo contexts, weighting, JVM heap and index-size costs). Also demos edge n‑gram for middle-word matching.
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chapters (16)
- 0:00Intro
- 1:00WHY THIS TALK!
- 2:57WHAT IS ELASTICSEARCH
- 3:39ELASTICSEARCH CONCEPTS
- 5:20WHAT DOES AN ANALYZER DO
- 7:31WHAT IS A SUGGESTER
- 8:24COMPLETION SUGGESTER
- 9:29A COUPLE NOTES ON DEMOS
- 18:15TERM SUGGESTER
- 18:29WHAT IS EDIT DISTANCE
- 24:34PHRASE SUGGESTER
- 24:56WHAT IS N-GRAM LANGUAGE MODEL!
- 25:24N-GRAM LANGUAGE FOR WORDS
- 37:34CONTEXT SUGGESTER
- 49:02QUESTIONS
- 49:30THANK YOU
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