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How to Implement Search Functionality

intermediate12 minSoftware Development

Add fast, relevant search to your application with full-text search, autocomplete, and filtering.

What You'll Learn

This intermediate-level guide walks you through how to implement search functionality step by step. Estimated time: 12 min.

Step 1: Choose your search backend

Select PostgreSQL full-text search for simplicity, Elasticsearch for advanced features, or Typesense/Meilisearch for easy setup.

Step 2: Set up search indexing

Configure your search index with proper field mappings, analyzers, tokenizers, and synonym support.

Step 3: Implement search API

Build a search endpoint with query parsing, filtering, faceting, pagination, and result highlighting.

Step 4: Add autocomplete

Implement type-ahead suggestions using prefix matching, popular queries, and recent search history.

Step 5: Optimize relevance

Tune scoring with field boosting, custom ranking functions, and user behavior signals to improve result quality.

Frequently Asked Questions

Do I need a dedicated search engine?

PostgreSQL full-text search handles most small to medium applications well. Move to Elasticsearch or Typesense when you need faceting, synonyms, or typo tolerance.

How do I handle typos in search?

Meilisearch and Typesense have built-in typo tolerance. For Elasticsearch, use fuzzy matching. For PostgreSQL, use trigram similarity with pg_trgm.

How fast should search be?

Autocomplete should respond in under 100ms, full search results in under 300ms. Use caching and query optimization to hit these targets.

Further Reading

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