Chapter 3: Search Fundamentals

March 2, 2026 · View on GitHub

Welcome to Chapter 3: Search Fundamentals. In this part of MeiliSearch Tutorial: Lightning Fast Search Engine, you will build an intuitive mental model first, then move into concrete implementation details and practical production tradeoffs.

This chapter covers the core search capabilities of Meilisearch, from basic queries to advanced search features.

Simple Text Search

# Basic search
curl 'http://localhost:7700/indexes/movies/search?q=star'

# Search with multiple words
curl 'http://localhost:7700/indexes/movies/search?q=star wars'

# Search for exact phrase
curl 'http://localhost:7700/indexes/movies/search?q="star wars"'

# Note: Meilisearch searches all searchable fields by default
# To search specific fields, use filters
curl 'http://localhost:7700/indexes/movies/search?q=nolan&filter=director=Nolan'

🎯 Search Parameters

Limit and Offset

# Get first 5 results
curl 'http://localhost:7700/indexes/movies/search?q=movie&limit=5'

# Pagination
curl 'http://localhost:7700/indexes/movies/search?q=movie&limit=10&offset=20'

Sorting Results

# Sort by year (ascending)
curl 'http://localhost:7700/indexes/movies/search?q=movie&sort=year:asc'

# Sort by rating (descending)
curl 'http://localhost:7700/indexes/movies/search?q=movie&sort=rating:desc'

# Multiple sort criteria
curl 'http://localhost:7700/indexes/movies/search?q=movie&sort=rating:desc,year:asc'

Matching Strategy

# Last word takes precedence (default)
curl 'http://localhost:7700/indexes/movies/search?q=star wars&matchingStrategy=last'

# All words must match
curl 'http://localhost:7700/indexes/movies/search?q=star wars&matchingStrategy=all'

🔤 Typo Tolerance

Meilisearch automatically handles typos and spelling mistakes:

# Original query
curl 'http://localhost:7700/indexes/movies/search?q=shwshnk'

# Still finds "Shawshank"
# Meilisearch corrects up to 2 typos for words with 5+ characters

Typo Tolerance Configuration

# Configure typo tolerance
curl -X PUT 'http://localhost:7700/indexes/movies/settings/typo-tolerance' \
  -H 'Content-Type: application/json' \
  -H 'Authorization: Bearer your_master_key' \
  --data '{
    "enabled": true,
    "minWordSizeForTypos": {
      "oneTypo": 5,
      "twoTypos": 9
    },
    "disableOnAttributes": ["director"]
  }'

🎨 Highlighting and Snippets

Highlighting Search Terms

# Enable highlighting
curl 'http://localhost:7700/indexes/movies/search?q=star&attributesToHighlight=["title"]'

Response with highlighting:

{
  "hits": [
    {
      "id": 1,
      "title": "Star Wars",
      "_formatted": {
        "title": "<em>Star</em> <em>Wars</em>"
      }
    }
  ]
}

Custom Highlight Tags

curl 'http://localhost:7700/indexes/movies/search?q=star&highlightPreTag=<strong>&highlightPostTag=</strong>'

Snippets

# Generate snippets for long text fields
curl 'http://localhost:7700/indexes/movies/search?q=space&attributesToSnippet=["description:50"]'

🔍 Advanced Search Features

# Search for documents containing the word "space"
curl 'http://localhost:7700/indexes/movies/search?q=space'

# Use underscore for single character wildcard
curl 'http://localhost:7700/indexes/movies/search?q=sp_ce'

Meilisearch supports prefix search automatically:

# Finds "Star Wars", "Star Trek", etc.
curl 'http://localhost:7700/indexes/movies/search?q=star'

Multi-Language Support

# Meilisearch handles different languages automatically
curl 'http://localhost:7700/indexes/movies/search?q=film'  # English
curl 'http://localhost:7700/indexes/movies/search?q=película'  # Spanish

📊 Search Analytics

Searchable Attributes

# Configure which fields are searchable
curl -X PUT 'http://localhost:7700/indexes/movies/settings/searchable-attributes' \
  -H 'Content-Type: application/json' \
  -H 'Authorization: Bearer your_master_key' \
  --data '["title", "director", "genre", "description"]'

Ranking Rules

# Configure ranking rules
curl -X PUT 'http://localhost:7700/indexes/movies/settings/ranking-rules' \
  -H 'Content-Type: application/json' \
  -H 'Authorization: Bearer your_master_key' \
  --data '[
    "words",
    "typo",
    "proximity",
    "attribute",
    "sort",
    "exactness"
  ]'

🔧 Search Performance

Query Optimization

# Use specific queries instead of broad searches
curl 'http://localhost:7700/indexes/movies/search?q="exact phrase"'

# Use filters to narrow down results
curl 'http://localhost:7700/indexes/movies/search?q=movie&filter=year>=2000'

Caching

# Meilisearch automatically caches frequent queries
# Cache can be cleared if needed
curl -X POST 'http://localhost:7700/indexes/movies/cache/clear' \
  -H 'Authorization: Bearer your_master_key'

Basic Facets

# Enable facets
curl 'http://localhost:7700/indexes/movies/search?q=movie&facets=["genre","year"]'

Response:

{
  "hits": [...],
  "facetDistribution": {
    "genre": {
      "Drama": 15,
      "Action": 12,
      "Comedy": 8
    },
    "year": {
      "2020": 5,
      "2019": 8,
      "2018": 10
    }
  }
}

🎯 Search Best Practices

Query Construction

// Good: Specific queries
const searchParams = {
  q: 'star wars',
  limit: 20,
  attributesToRetrieve: ['title', 'year', 'rating']
};

// Avoid: Overly broad queries
const badSearch = {
  q: 'a',  // Too broad
  limit: 1000  // Too many results
};

Result Processing

// Process search results
function processResults(response) {
  const { hits, estimatedTotalHits, processingTimeMs } = response;

  console.log(`Found ${estimatedTotalHits} results in ${processingTimeMs}ms`);

  return hits.map(hit => ({
    id: hit.id,
    title: hit._formatted?.title || hit.title,
    highlights: hit._formatted
  }));
}

🚨 Common Search Issues

No Results Found

# Check if index exists
curl 'http://localhost:7700/indexes'

# Check if documents are indexed
curl 'http://localhost:7700/indexes/movies/documents'

# Check searchable attributes
curl 'http://localhost:7700/indexes/movies/settings/searchable-attributes'

Slow Search Performance

# Check index stats
curl 'http://localhost:7700/indexes/movies/stats'

# Monitor task queue
curl 'http://localhost:7700/tasks?statuses=processing'

📝 Chapter Summary

  • ✅ Performed basic and advanced searches
  • ✅ Configured typo tolerance and highlighting
  • ✅ Used sorting, pagination, and filtering
  • ✅ Implemented faceted search
  • ✅ Optimized search performance
  • ✅ Handled common search issues

Key Takeaways:

  • Meilisearch provides instant, typo-tolerant search
  • Configure searchable attributes for better relevance
  • Use highlighting and snippets for better UX
  • Monitor performance and optimize queries
  • Facets help users refine their searches

What Problem Does This Solve?

Most teams struggle here because the hard part is not writing more code, but deciding clear boundaries for curl, http, localhost so behavior stays predictable as complexity grows.

In practical terms, this chapter helps you avoid three common failures:

  • coupling core logic too tightly to one implementation path
  • missing the handoff boundaries between setup, execution, and validation
  • shipping changes without clear rollback or observability strategy

After working through this chapter, you should be able to reason about Chapter 3: Search Fundamentals as an operating subsystem inside MeiliSearch Tutorial: Lightning Fast Search Engine, with explicit contracts for inputs, state transitions, and outputs.

Use the implementation notes around indexes, movies, search as your checklist when adapting these patterns to your own repository.

How it Works Under the Hood

Under the hood, Chapter 3: Search Fundamentals usually follows a repeatable control path:

  1. Context bootstrap: initialize runtime config and prerequisites for curl.
  2. Input normalization: shape incoming data so http receives stable contracts.
  3. Core execution: run the main logic branch and propagate intermediate state through localhost.
  4. Policy and safety checks: enforce limits, auth scopes, and failure boundaries.
  5. Output composition: return canonical result payloads for downstream consumers.
  6. Operational telemetry: emit logs/metrics needed for debugging and performance tuning.

When debugging, walk this sequence in order and confirm each stage has explicit success/failure conditions.

Source Walkthrough

Use the following upstream sources to verify implementation details while reading this chapter:

  • View Repo Why it matters: authoritative reference on View Repo (github.com).
  • AI Codebase Knowledge Builder Why it matters: authoritative reference on AI Codebase Knowledge Builder (github.com).

Suggested trace strategy:

  • search upstream code for curl and http to map concrete implementation paths
  • compare docs claims against actual runtime/config code before reusing patterns in production

Chapter Connections