🗓️ 04102025 0034

ELASTICSEARCH TEXT SEARCH CHEATSHEET

A quick reference for Elasticsearch search capabilities and when to use each type.

Core Concepts

Full-Text vs Exact Match

Type	Use Case	Example
Full-Text	Natural language search, fuzzy matching	"searching for articles"
Exact Match	IDs, status codes, categories	status: "active"

Key difference: Full-text is analyzed (lowercased, stemmed, tokenized), exact match is not.

Search Types Overview

Search Type	What It Does	Best For
Match	Full-text search with analysis	General search, user queries
Multi-Match	Search across multiple fields	Searching title + description
Match Phrase	Exact phrase in order	"New York", "machine learning"
Term	Exact value match	IDs, enums, keywords
Fuzzy	Typo-tolerant search	Handling misspellings
Prefix	Starts with...	Autocomplete, type-ahead
Wildcard	Pattern matching	user*, *@gmail.com
Regexp	Regex patterns	Complex pattern matching
Range	Numeric/date ranges	Price filters, date ranges
Bool	Combine queries	Complex filtering logic

match vs term

• match: Analyzed (lowercased, stemmed) - "Searching" → "search"
• term: Exact value - "Searching" ≠ "searching"

match vs match_phrase

• match: Words can be in any order
• match_phrase: Words must be in exact order

must vs filter (in bool)

• must: Affects relevance score (use for search)
• filter: Yes/no match, faster (use for filtering)

should vs must

• should: Optional, boosts score if matched (OR logic)
• must: Required (AND logic)

Common Patterns

Search with Filters

Combine search queries (must) with filters (filter) - filters don't affect relevance score and are cached for performance.

Fuzzy Search with Minimum Match

Use fuzziness: "AUTO" to handle typos, and minimum_should_match (e.g., "75%") to require a percentage of search terms to match.

Wildcard Search

Pattern matching with * and ? - useful but can be slow, especially with leading wildcards.

Performance Tips

1. Use filters over queries when you don't need scoring
2. Term queries are faster than match queries
3. Wildcard with * at start is slow - avoid if possible
4. Use prefix/edge_ngram for autocomplete, not wildcard
5. Cache filters - ES automatically caches filter results
6. Limit fields in multi_match - don't search everything

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References

• elasticsearch_scoring_relevance - How results are ranked and scored
• elasticsearch_analyzers - How text is processed and tokenized
• Elasticsearch Query DSL
• Match Query
• Bool Query